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- .dockerignore +3 -0
- Cargo.lock +3402 -0
- Cargo.toml +16 -0
- Dockerfile +179 -99
- LICENSE +201 -0
- Makefile +45 -0
- aml/deployment.yaml +38 -0
- aml/endpoint.yaml +3 -0
- aml/model.yaml +3 -0
- assets/architecture.jpg +0 -0
- assets/benchmark.png +0 -0
- benchmark/Cargo.lock +2884 -0
- benchmark/Cargo.toml +35 -0
- benchmark/rust-toolchain.toml +3 -0
- benchmark/src/app.rs +688 -0
- benchmark/src/event.rs +65 -0
- benchmark/src/generation.rs +226 -0
- benchmark/src/lib.rs +110 -0
- benchmark/src/main.rs +131 -0
- benchmark/src/utils.rs +43 -0
- clients/python/Makefile +6 -0
- clients/python/poetry.lock +0 -0
- clients/python/pyproject.toml +29 -0
- clients/python/tests/conftest.py +51 -0
- clients/python/tests/test_client.py +146 -0
- clients/python/tests/test_errors.py +64 -0
- clients/python/tests/test_inference_api.py +42 -0
- clients/python/tests/test_types.py +84 -0
- clients/python/text_generation/__init__.py +18 -0
- clients/python/text_generation/client.py +481 -0
- clients/python/text_generation/errors.py +106 -0
- clients/python/text_generation/inference_api.py +168 -0
- clients/python/text_generation/types.py +231 -0
- docs/index.html +30 -0
- docs/openapi.json +730 -0
- k6/load_test.js +98 -0
- launcher/Cargo.toml +22 -0
- launcher/build.rs +29 -0
- launcher/src/env_runtime.rs +45 -0
- launcher/src/main.rs +925 -0
- launcher/tests/bloom_560m.json +142 -0
- launcher/tests/integration_tests.rs +172 -0
- launcher/tests/mt0_base.json +137 -0
- proto/generate.proto +181 -0
- router/Cargo.toml +44 -0
- router/build.rs +26 -0
- router/client/Cargo.toml +19 -0
- router/client/build.rs +19 -0
- router/client/src/client.rs +121 -0
- router/client/src/lib.rs +44 -0
.dockerignore
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server/transformers
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Cargo.lock
ADDED
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@@ -0,0 +1,3402 @@
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|
| 1 |
+
# This file is automatically @generated by Cargo.
|
| 2 |
+
# It is not intended for manual editing.
|
| 3 |
+
version = 3
|
| 4 |
+
|
| 5 |
+
[[package]]
|
| 6 |
+
name = "adler"
|
| 7 |
+
version = "1.0.2"
|
| 8 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 9 |
+
checksum = "f26201604c87b1e01bd3d98f8d5d9a8fcbb815e8cedb41ffccbeb4bf593a35fe"
|
| 10 |
+
|
| 11 |
+
[[package]]
|
| 12 |
+
name = "aes"
|
| 13 |
+
version = "0.7.5"
|
| 14 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 15 |
+
checksum = "9e8b47f52ea9bae42228d07ec09eb676433d7c4ed1ebdf0f1d1c29ed446f1ab8"
|
| 16 |
+
dependencies = [
|
| 17 |
+
"cfg-if",
|
| 18 |
+
"cipher",
|
| 19 |
+
"cpufeatures",
|
| 20 |
+
"opaque-debug",
|
| 21 |
+
]
|
| 22 |
+
|
| 23 |
+
[[package]]
|
| 24 |
+
name = "ahash"
|
| 25 |
+
version = "0.7.6"
|
| 26 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 27 |
+
checksum = "fcb51a0695d8f838b1ee009b3fbf66bda078cd64590202a864a8f3e8c4315c47"
|
| 28 |
+
dependencies = [
|
| 29 |
+
"getrandom",
|
| 30 |
+
"once_cell",
|
| 31 |
+
"version_check",
|
| 32 |
+
]
|
| 33 |
+
|
| 34 |
+
[[package]]
|
| 35 |
+
name = "aho-corasick"
|
| 36 |
+
version = "0.7.20"
|
| 37 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 38 |
+
checksum = "cc936419f96fa211c1b9166887b38e5e40b19958e5b895be7c1f93adec7071ac"
|
| 39 |
+
dependencies = [
|
| 40 |
+
"memchr",
|
| 41 |
+
]
|
| 42 |
+
|
| 43 |
+
[[package]]
|
| 44 |
+
name = "anstream"
|
| 45 |
+
version = "0.3.0"
|
| 46 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 47 |
+
checksum = "9e579a7752471abc2a8268df8b20005e3eadd975f585398f17efcfd8d4927371"
|
| 48 |
+
dependencies = [
|
| 49 |
+
"anstyle",
|
| 50 |
+
"anstyle-parse",
|
| 51 |
+
"anstyle-query",
|
| 52 |
+
"anstyle-wincon",
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Cargo.toml
ADDED
|
@@ -0,0 +1,16 @@
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|
|
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|
|
|
|
| 1 |
+
[workspace]
|
| 2 |
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members = [
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| 3 |
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"router",
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| 4 |
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"router/client",
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| 5 |
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"router/grpc-metadata",
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| 6 |
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"launcher"
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| 7 |
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| 8 |
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exclude = [
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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| 13 |
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|
| 15 |
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lto = "off"
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| 16 |
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panic = "abort"
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Dockerfile
CHANGED
|
@@ -1,99 +1,179 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
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|
| 4 |
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|
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|
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| 20 |
-
|
| 21 |
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|
| 22 |
-
|
| 23 |
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|
| 24 |
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|
| 25 |
-
RUN
|
| 26 |
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|
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| 29 |
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| 30 |
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|
| 53 |
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|
| 54 |
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&&
|
| 55 |
-
|
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|
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|
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|
|
|
|
|
|
|
|
|
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|
| 1 |
+
# Rust builder
|
| 2 |
+
FROM lukemathwalker/cargo-chef:latest-rust-1.69 AS chef
|
| 3 |
+
WORKDIR /usr/src
|
| 4 |
+
|
| 5 |
+
FROM chef as planner
|
| 6 |
+
COPY Cargo.toml Cargo.toml
|
| 7 |
+
COPY rust-toolchain.toml rust-toolchain.toml
|
| 8 |
+
COPY proto proto
|
| 9 |
+
COPY router router
|
| 10 |
+
COPY launcher launcher
|
| 11 |
+
RUN cargo chef prepare --recipe-path recipe.json
|
| 12 |
+
|
| 13 |
+
FROM chef AS builder
|
| 14 |
+
|
| 15 |
+
ARG GIT_SHA
|
| 16 |
+
ARG DOCKER_LABEL
|
| 17 |
+
|
| 18 |
+
RUN PROTOC_ZIP=protoc-21.12-linux-x86_64.zip && \
|
| 19 |
+
curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v21.12/$PROTOC_ZIP && \
|
| 20 |
+
unzip -o $PROTOC_ZIP -d /usr/local bin/protoc && \
|
| 21 |
+
unzip -o $PROTOC_ZIP -d /usr/local 'include/*' && \
|
| 22 |
+
rm -f $PROTOC_ZIP
|
| 23 |
+
|
| 24 |
+
COPY --from=planner /usr/src/recipe.json recipe.json
|
| 25 |
+
RUN cargo chef cook --release --recipe-path recipe.json
|
| 26 |
+
|
| 27 |
+
COPY Cargo.toml Cargo.toml
|
| 28 |
+
COPY rust-toolchain.toml rust-toolchain.toml
|
| 29 |
+
COPY proto proto
|
| 30 |
+
COPY router router
|
| 31 |
+
COPY launcher launcher
|
| 32 |
+
RUN cargo build --release
|
| 33 |
+
|
| 34 |
+
# Python builder
|
| 35 |
+
# Adapted from: https://github.com/pytorch/pytorch/blob/master/Dockerfile
|
| 36 |
+
FROM debian:bullseye-slim as pytorch-install
|
| 37 |
+
|
| 38 |
+
ARG PYTORCH_VERSION=2.0.0
|
| 39 |
+
ARG PYTHON_VERSION=3.9
|
| 40 |
+
ARG CUDA_VERSION=11.8
|
| 41 |
+
ARG MAMBA_VERSION=23.1.0-1
|
| 42 |
+
ARG CUDA_CHANNEL=nvidia
|
| 43 |
+
ARG INSTALL_CHANNEL=pytorch
|
| 44 |
+
# Automatically set by buildx
|
| 45 |
+
ARG TARGETPLATFORM
|
| 46 |
+
|
| 47 |
+
ENV PATH /opt/conda/bin:$PATH
|
| 48 |
+
|
| 49 |
+
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
|
| 50 |
+
build-essential \
|
| 51 |
+
ca-certificates \
|
| 52 |
+
ccache \
|
| 53 |
+
curl \
|
| 54 |
+
git && \
|
| 55 |
+
rm -rf /var/lib/apt/lists/*
|
| 56 |
+
|
| 57 |
+
# Install conda
|
| 58 |
+
# translating Docker's TARGETPLATFORM into mamba arches
|
| 59 |
+
RUN case ${TARGETPLATFORM} in \
|
| 60 |
+
"linux/arm64") MAMBA_ARCH=aarch64 ;; \
|
| 61 |
+
*) MAMBA_ARCH=x86_64 ;; \
|
| 62 |
+
esac && \
|
| 63 |
+
curl -fsSL -v -o ~/mambaforge.sh -O "https://github.com/conda-forge/miniforge/releases/download/${MAMBA_VERSION}/Mambaforge-${MAMBA_VERSION}-Linux-${MAMBA_ARCH}.sh"
|
| 64 |
+
RUN chmod +x ~/mambaforge.sh && \
|
| 65 |
+
bash ~/mambaforge.sh -b -p /opt/conda && \
|
| 66 |
+
rm ~/mambaforge.sh
|
| 67 |
+
|
| 68 |
+
# Install pytorch
|
| 69 |
+
# On arm64 we exit with an error code
|
| 70 |
+
RUN case ${TARGETPLATFORM} in \
|
| 71 |
+
"linux/arm64") exit 1 ;; \
|
| 72 |
+
*) /opt/conda/bin/conda update -y conda && \
|
| 73 |
+
/opt/conda/bin/conda install -c "${INSTALL_CHANNEL}" -c "${CUDA_CHANNEL}" -y "python=${PYTHON_VERSION}" pytorch==$PYTORCH_VERSION "pytorch-cuda=$(echo $CUDA_VERSION | cut -d'.' -f 1-2)" ;; \
|
| 74 |
+
esac && \
|
| 75 |
+
/opt/conda/bin/conda clean -ya
|
| 76 |
+
|
| 77 |
+
# CUDA kernels builder image
|
| 78 |
+
FROM pytorch-install as kernel-builder
|
| 79 |
+
|
| 80 |
+
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
|
| 81 |
+
ninja-build \
|
| 82 |
+
&& rm -rf /var/lib/apt/lists/*
|
| 83 |
+
|
| 84 |
+
RUN /opt/conda/bin/conda install -c "nvidia/label/cuda-11.8.0" cuda==11.8 && \
|
| 85 |
+
/opt/conda/bin/conda clean -ya
|
| 86 |
+
|
| 87 |
+
|
| 88 |
+
# Build Flash Attention CUDA kernels
|
| 89 |
+
FROM kernel-builder as flash-att-builder
|
| 90 |
+
|
| 91 |
+
WORKDIR /usr/src
|
| 92 |
+
|
| 93 |
+
COPY server/Makefile-flash-att Makefile
|
| 94 |
+
|
| 95 |
+
# Build specific version of flash attention
|
| 96 |
+
RUN make build-flash-attention
|
| 97 |
+
|
| 98 |
+
# Build Transformers CUDA kernels
|
| 99 |
+
FROM kernel-builder as transformers-builder
|
| 100 |
+
|
| 101 |
+
WORKDIR /usr/src
|
| 102 |
+
|
| 103 |
+
COPY server/Makefile-transformers Makefile
|
| 104 |
+
|
| 105 |
+
# Build specific version of transformers
|
| 106 |
+
RUN BUILD_EXTENSIONS="True" make build-transformers
|
| 107 |
+
|
| 108 |
+
# Text Generation Inference base image
|
| 109 |
+
FROM debian:bullseye-slim as base
|
| 110 |
+
|
| 111 |
+
# Conda env
|
| 112 |
+
ENV PATH=/opt/conda/bin:$PATH \
|
| 113 |
+
CONDA_PREFIX=/opt/conda
|
| 114 |
+
|
| 115 |
+
# Text Generation Inference base env
|
| 116 |
+
ENV HUGGINGFACE_HUB_CACHE=/data \
|
| 117 |
+
HF_HUB_ENABLE_HF_TRANSFER=1 \
|
| 118 |
+
MODEL_ID=bigscience/bloom-560m \
|
| 119 |
+
QUANTIZE=false \
|
| 120 |
+
NUM_SHARD=1 \
|
| 121 |
+
PORT=80
|
| 122 |
+
|
| 123 |
+
LABEL com.nvidia.volumes.needed="nvidia_driver"
|
| 124 |
+
|
| 125 |
+
WORKDIR /usr/src
|
| 126 |
+
|
| 127 |
+
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
|
| 128 |
+
libssl-dev \
|
| 129 |
+
ca-certificates \
|
| 130 |
+
make \
|
| 131 |
+
&& rm -rf /var/lib/apt/lists/*
|
| 132 |
+
|
| 133 |
+
# Copy conda with PyTorch installed
|
| 134 |
+
COPY --from=pytorch-install /opt/conda /opt/conda
|
| 135 |
+
|
| 136 |
+
# Copy build artifacts from flash attention builder
|
| 137 |
+
COPY --from=flash-att-builder /usr/src/flash-attention/build/lib.linux-x86_64-cpython-39 /opt/conda/lib/python3.9/site-packages
|
| 138 |
+
COPY --from=flash-att-builder /usr/src/flash-attention/csrc/layer_norm/build/lib.linux-x86_64-cpython-39 /opt/conda/lib/python3.9/site-packages
|
| 139 |
+
COPY --from=flash-att-builder /usr/src/flash-attention/csrc/rotary/build/lib.linux-x86_64-cpython-39 /opt/conda/lib/python3.9/site-packages
|
| 140 |
+
|
| 141 |
+
# Copy build artifacts from transformers builder
|
| 142 |
+
COPY --from=transformers-builder /usr/src/transformers /usr/src/transformers
|
| 143 |
+
COPY --from=transformers-builder /usr/src/transformers/build/lib.linux-x86_64-cpython-39/transformers /usr/src/transformers/src/transformers
|
| 144 |
+
|
| 145 |
+
# Install transformers dependencies
|
| 146 |
+
RUN cd /usr/src/transformers && pip install -e . --no-cache-dir && pip install einops --no-cache-dir
|
| 147 |
+
|
| 148 |
+
# Install server
|
| 149 |
+
COPY proto proto
|
| 150 |
+
COPY server server
|
| 151 |
+
COPY server/Makefile server/Makefile
|
| 152 |
+
RUN cd server && \
|
| 153 |
+
make gen-server && \
|
| 154 |
+
pip install -r requirements.txt && \
|
| 155 |
+
pip install ".[bnb, accelerate]" --no-cache-dir
|
| 156 |
+
|
| 157 |
+
# Install router
|
| 158 |
+
COPY --from=builder /usr/src/target/release/text-generation-router /usr/local/bin/text-generation-router
|
| 159 |
+
# Install launcher
|
| 160 |
+
COPY --from=builder /usr/src/target/release/text-generation-launcher /usr/local/bin/text-generation-launcher
|
| 161 |
+
|
| 162 |
+
# AWS Sagemaker compatbile image
|
| 163 |
+
FROM base as sagemaker
|
| 164 |
+
|
| 165 |
+
COPY sagemaker-entrypoint.sh entrypoint.sh
|
| 166 |
+
RUN chmod +x entrypoint.sh
|
| 167 |
+
|
| 168 |
+
# NVIDIA env vars
|
| 169 |
+
ENV NVIDIA_VISIBLE_DEVICES all
|
| 170 |
+
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
|
| 171 |
+
ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
|
| 172 |
+
|
| 173 |
+
ENTRYPOINT ["./entrypoint.sh"]
|
| 174 |
+
|
| 175 |
+
# Final image
|
| 176 |
+
FROM base
|
| 177 |
+
|
| 178 |
+
ENTRYPOINT ["text-generation-launcher"]
|
| 179 |
+
CMD ["--json-output"]
|
LICENSE
ADDED
|
@@ -0,0 +1,201 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
|
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|
|
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|
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|
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|
|
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|
|
|
|
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|
|
|
|
|
|
| 1 |
+
Apache License
|
| 2 |
+
Version 2.0, January 2004
|
| 3 |
+
http://www.apache.org/licenses/
|
| 4 |
+
|
| 5 |
+
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
| 6 |
+
|
| 7 |
+
1. Definitions.
|
| 8 |
+
|
| 9 |
+
"License" shall mean the terms and conditions for use, reproduction,
|
| 10 |
+
and distribution as defined by Sections 1 through 9 of this document.
|
| 11 |
+
|
| 12 |
+
"Licensor" shall mean the copyright owner or entity authorized by
|
| 13 |
+
the copyright owner that is granting the License.
|
| 14 |
+
|
| 15 |
+
"Legal Entity" shall mean the union of the acting entity and all
|
| 16 |
+
other entities that control, are controlled by, or are under common
|
| 17 |
+
control with that entity. For the purposes of this definition,
|
| 18 |
+
"control" means (i) the power, direct or indirect, to cause the
|
| 19 |
+
direction or management of such entity, whether by contract or
|
| 20 |
+
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
| 21 |
+
outstanding shares, or (iii) beneficial ownership of such entity.
|
| 22 |
+
|
| 23 |
+
"You" (or "Your") shall mean an individual or Legal Entity
|
| 24 |
+
exercising permissions granted by this License.
|
| 25 |
+
|
| 26 |
+
"Source" form shall mean the preferred form for making modifications,
|
| 27 |
+
including but not limited to software source code, documentation
|
| 28 |
+
source, and configuration files.
|
| 29 |
+
|
| 30 |
+
"Object" form shall mean any form resulting from mechanical
|
| 31 |
+
transformation or translation of a Source form, including but
|
| 32 |
+
not limited to compiled object code, generated documentation,
|
| 33 |
+
and conversions to other media types.
|
| 34 |
+
|
| 35 |
+
"Work" shall mean the work of authorship, whether in Source or
|
| 36 |
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Object form, made available under the License, as indicated by a
|
| 37 |
+
copyright notice that is included in or attached to the work
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| 38 |
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(an example is provided in the Appendix below).
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| 39 |
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| 40 |
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"Derivative Works" shall mean any work, whether in Source or Object
|
| 41 |
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form, that is based on (or derived from) the Work and for which the
|
| 42 |
+
editorial revisions, annotations, elaborations, or other modifications
|
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represent, as a whole, an original work of authorship. For the purposes
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of this License, Derivative Works shall not include works that remain
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separable from, or merely link (or bind by name) to the interfaces of,
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the Work and Derivative Works thereof.
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| 48 |
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"Contribution" shall mean any work of authorship, including
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"Contributor" shall mean Licensor and any individual or Legal Entity
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|
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or a Contribution incorporated within the Work constitutes direct
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|
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|
| 87 |
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| 89 |
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4. Redistribution. You may reproduce and distribute copies of the
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|
Makefile
ADDED
|
@@ -0,0 +1,45 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
install-server:
|
| 2 |
+
cd server && make install
|
| 3 |
+
|
| 4 |
+
install-router:
|
| 5 |
+
cd router && cargo install --path .
|
| 6 |
+
|
| 7 |
+
install-launcher:
|
| 8 |
+
cd launcher && cargo install --path .
|
| 9 |
+
|
| 10 |
+
install-benchmark:
|
| 11 |
+
cd benchmark && cargo install --path .
|
| 12 |
+
|
| 13 |
+
install: install-server install-router install-launcher
|
| 14 |
+
|
| 15 |
+
server-dev:
|
| 16 |
+
cd server && make run-dev
|
| 17 |
+
|
| 18 |
+
router-dev:
|
| 19 |
+
cd router && cargo run -- --port 8080
|
| 20 |
+
|
| 21 |
+
integration-tests: install-router install-launcher
|
| 22 |
+
cargo test
|
| 23 |
+
|
| 24 |
+
python-server-tests:
|
| 25 |
+
HF_HUB_ENABLE_HF_TRANSFER=1 pytest server/tests
|
| 26 |
+
|
| 27 |
+
python-client-tests:
|
| 28 |
+
pytest clients/python/tests
|
| 29 |
+
|
| 30 |
+
python-tests: python-server-tests python-client-tests
|
| 31 |
+
|
| 32 |
+
run-bloom-560m:
|
| 33 |
+
text-generation-launcher --model-id bigscience/bloom-560m --num-shard 2 --port 8080
|
| 34 |
+
|
| 35 |
+
run-bloom-560m-quantize:
|
| 36 |
+
text-generation-launcher --model-id bigscience/bloom-560m --num-shard 2 --quantize --port 8080
|
| 37 |
+
|
| 38 |
+
download-bloom:
|
| 39 |
+
HF_HUB_ENABLE_HF_TRANSFER=1 text-generation-server download-weights bigscience/bloom
|
| 40 |
+
|
| 41 |
+
run-bloom:
|
| 42 |
+
text-generation-launcher --model-id bigscience/bloom --num-shard 8 --port 8080
|
| 43 |
+
|
| 44 |
+
run-bloom-quantize:
|
| 45 |
+
text-generation-launcher --model-id bigscience/bloom --num-shard 8 --quantize --port 8080
|
aml/deployment.yaml
ADDED
|
@@ -0,0 +1,38 @@
|
|
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|
|
|
|
| 1 |
+
$schema: https://azuremlschemas.azureedge.net/latest/managedOnlineDeployment.schema.json
|
| 2 |
+
name: bloom-deployment
|
| 3 |
+
endpoint_name: bloom-inference
|
| 4 |
+
model: azureml:bloom-safetensors:1
|
| 5 |
+
model_mount_path: /var/azureml-model
|
| 6 |
+
environment_variables:
|
| 7 |
+
WEIGHTS_CACHE_OVERRIDE: /var/azureml-model/bloom-safetensors
|
| 8 |
+
MODEL_ID: bigscience/bloom
|
| 9 |
+
NUM_SHARD: 8
|
| 10 |
+
environment:
|
| 11 |
+
image: db4c2190dd824d1f950f5d1555fbadf0.azurecr.io/text-generation-inference:0.2.0
|
| 12 |
+
inference_config:
|
| 13 |
+
liveness_route:
|
| 14 |
+
port: 80
|
| 15 |
+
path: /health
|
| 16 |
+
readiness_route:
|
| 17 |
+
port: 80
|
| 18 |
+
path: /health
|
| 19 |
+
scoring_route:
|
| 20 |
+
port: 80
|
| 21 |
+
path: /generate
|
| 22 |
+
instance_type: Standard_ND96amsr_A100_v4
|
| 23 |
+
request_settings:
|
| 24 |
+
request_timeout_ms: 90000
|
| 25 |
+
max_concurrent_requests_per_instance: 256
|
| 26 |
+
liveness_probe:
|
| 27 |
+
initial_delay: 600
|
| 28 |
+
timeout: 90
|
| 29 |
+
period: 120
|
| 30 |
+
success_threshold: 1
|
| 31 |
+
failure_threshold: 5
|
| 32 |
+
readiness_probe:
|
| 33 |
+
initial_delay: 600
|
| 34 |
+
timeout: 90
|
| 35 |
+
period: 120
|
| 36 |
+
success_threshold: 1
|
| 37 |
+
failure_threshold: 5
|
| 38 |
+
instance_count: 1
|
aml/endpoint.yaml
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
$schema: https://azuremlsdk2.blob.core.windows.net/latest/managedOnlineEndpoint.schema.json
|
| 2 |
+
name: bloom-inference
|
| 3 |
+
auth_mode: key
|
aml/model.yaml
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
$schema: https://azuremlschemas.azureedge.net/latest/model.schema.json
|
| 2 |
+
name: bloom-safetensors
|
| 3 |
+
path: /data/bloom-safetensors
|
assets/architecture.jpg
ADDED
|
assets/benchmark.png
ADDED
|
benchmark/Cargo.lock
ADDED
|
@@ -0,0 +1,2884 @@
|
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|
| 1 |
+
# This file is automatically @generated by Cargo.
|
| 2 |
+
# It is not intended for manual editing.
|
| 3 |
+
version = 3
|
| 4 |
+
|
| 5 |
+
[[package]]
|
| 6 |
+
name = "adler"
|
| 7 |
+
version = "1.0.2"
|
| 8 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 9 |
+
checksum = "f26201604c87b1e01bd3d98f8d5d9a8fcbb815e8cedb41ffccbeb4bf593a35fe"
|
| 10 |
+
|
| 11 |
+
[[package]]
|
| 12 |
+
name = "aes"
|
| 13 |
+
version = "0.7.5"
|
| 14 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 15 |
+
checksum = "9e8b47f52ea9bae42228d07ec09eb676433d7c4ed1ebdf0f1d1c29ed446f1ab8"
|
| 16 |
+
dependencies = [
|
| 17 |
+
"cfg-if",
|
| 18 |
+
"cipher",
|
| 19 |
+
"cpufeatures",
|
| 20 |
+
"opaque-debug",
|
| 21 |
+
]
|
| 22 |
+
|
| 23 |
+
[[package]]
|
| 24 |
+
name = "aho-corasick"
|
| 25 |
+
version = "0.7.20"
|
| 26 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 27 |
+
checksum = "cc936419f96fa211c1b9166887b38e5e40b19958e5b895be7c1f93adec7071ac"
|
| 28 |
+
dependencies = [
|
| 29 |
+
"memchr",
|
| 30 |
+
]
|
| 31 |
+
|
| 32 |
+
[[package]]
|
| 33 |
+
name = "anstream"
|
| 34 |
+
version = "0.2.6"
|
| 35 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 36 |
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checksum = "342258dd14006105c2b75ab1bd7543a03bdf0cfc94383303ac212a04939dff6f"
|
| 37 |
+
dependencies = [
|
| 38 |
+
"anstyle",
|
| 39 |
+
"anstyle-parse",
|
| 40 |
+
"anstyle-wincon",
|
| 41 |
+
"concolor-override",
|
| 42 |
+
"concolor-query",
|
| 43 |
+
"is-terminal",
|
| 44 |
+
"utf8parse",
|
| 45 |
+
]
|
| 46 |
+
|
| 47 |
+
[[package]]
|
| 48 |
+
name = "anstyle"
|
| 49 |
+
version = "0.3.5"
|
| 50 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 51 |
+
checksum = "23ea9e81bd02e310c216d080f6223c179012256e5151c41db88d12c88a1684d2"
|
| 52 |
+
|
| 53 |
+
[[package]]
|
| 54 |
+
name = "anstyle-parse"
|
| 55 |
+
version = "0.1.1"
|
| 56 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 57 |
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checksum = "a7d1bb534e9efed14f3e5f44e7dd1a4f709384023a4165199a4241e18dff0116"
|
| 58 |
+
dependencies = [
|
| 59 |
+
"utf8parse",
|
| 60 |
+
]
|
| 61 |
+
|
| 62 |
+
[[package]]
|
| 63 |
+
name = "anstyle-wincon"
|
| 64 |
+
version = "0.2.0"
|
| 65 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 66 |
+
checksum = "c3127af6145b149f3287bb9a0d10ad9c5692dba8c53ad48285e5bec4063834fa"
|
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name = "xattr"
|
| 2829 |
+
version = "0.2.3"
|
| 2830 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 2831 |
+
checksum = "6d1526bbe5aaeb5eb06885f4d987bcdfa5e23187055de9b83fe00156a821fabc"
|
| 2832 |
+
dependencies = [
|
| 2833 |
+
"libc",
|
| 2834 |
+
]
|
| 2835 |
+
|
| 2836 |
+
[[package]]
|
| 2837 |
+
name = "zip"
|
| 2838 |
+
version = "0.6.4"
|
| 2839 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 2840 |
+
checksum = "0445d0fbc924bb93539b4316c11afb121ea39296f99a3c4c9edad09e3658cdef"
|
| 2841 |
+
dependencies = [
|
| 2842 |
+
"aes",
|
| 2843 |
+
"byteorder",
|
| 2844 |
+
"bzip2",
|
| 2845 |
+
"constant_time_eq",
|
| 2846 |
+
"crc32fast",
|
| 2847 |
+
"crossbeam-utils",
|
| 2848 |
+
"flate2",
|
| 2849 |
+
"hmac",
|
| 2850 |
+
"pbkdf2",
|
| 2851 |
+
"sha1",
|
| 2852 |
+
"time",
|
| 2853 |
+
"zstd",
|
| 2854 |
+
]
|
| 2855 |
+
|
| 2856 |
+
[[package]]
|
| 2857 |
+
name = "zstd"
|
| 2858 |
+
version = "0.11.2+zstd.1.5.2"
|
| 2859 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 2860 |
+
checksum = "20cc960326ece64f010d2d2107537f26dc589a6573a316bd5b1dba685fa5fde4"
|
| 2861 |
+
dependencies = [
|
| 2862 |
+
"zstd-safe",
|
| 2863 |
+
]
|
| 2864 |
+
|
| 2865 |
+
[[package]]
|
| 2866 |
+
name = "zstd-safe"
|
| 2867 |
+
version = "5.0.2+zstd.1.5.2"
|
| 2868 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 2869 |
+
checksum = "1d2a5585e04f9eea4b2a3d1eca508c4dee9592a89ef6f450c11719da0726f4db"
|
| 2870 |
+
dependencies = [
|
| 2871 |
+
"libc",
|
| 2872 |
+
"zstd-sys",
|
| 2873 |
+
]
|
| 2874 |
+
|
| 2875 |
+
[[package]]
|
| 2876 |
+
name = "zstd-sys"
|
| 2877 |
+
version = "2.0.8+zstd.1.5.5"
|
| 2878 |
+
source = "registry+https://github.com/rust-lang/crates.io-index"
|
| 2879 |
+
checksum = "5556e6ee25d32df2586c098bbfa278803692a20d0ab9565e049480d52707ec8c"
|
| 2880 |
+
dependencies = [
|
| 2881 |
+
"cc",
|
| 2882 |
+
"libc",
|
| 2883 |
+
"pkg-config",
|
| 2884 |
+
]
|
benchmark/Cargo.toml
ADDED
|
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[package]
|
| 2 |
+
name = "text-generation-benchmark"
|
| 3 |
+
version = "0.1.0"
|
| 4 |
+
edition = "2021"
|
| 5 |
+
authors = ["Olivier Dehaene"]
|
| 6 |
+
description = "Text Generation Benchmarking tool"
|
| 7 |
+
|
| 8 |
+
[profile.release]
|
| 9 |
+
debug = 1
|
| 10 |
+
incremental = true
|
| 11 |
+
lto = "off"
|
| 12 |
+
panic = "abort"
|
| 13 |
+
|
| 14 |
+
[lib]
|
| 15 |
+
path = "src/lib.rs"
|
| 16 |
+
|
| 17 |
+
[[bin]]
|
| 18 |
+
name = "text-generation-benchmark"
|
| 19 |
+
path = "src/main.rs"
|
| 20 |
+
|
| 21 |
+
[dependencies]
|
| 22 |
+
average = "0.13"
|
| 23 |
+
clap = { version = "4.1.4", features = ["derive", "env"] }
|
| 24 |
+
crossterm = "0.26"
|
| 25 |
+
float-ord = "0.3.2"
|
| 26 |
+
serde = {version = "1.0.142", features = ["derive"]}
|
| 27 |
+
serde_json = "1.0"
|
| 28 |
+
text-generation-client = { path = "../router/client" }
|
| 29 |
+
thiserror = "1.0.38"
|
| 30 |
+
tokenizers = "0.13.3"
|
| 31 |
+
tokio = { version = "1.25.0", features = ["rt", "rt-multi-thread", "parking_lot", "signal", "sync"] }
|
| 32 |
+
tui = {package = "ratatui", version = "0.20", default-features = false, features = ["crossterm"]}
|
| 33 |
+
tracing = "0.1.37"
|
| 34 |
+
tracing-subscriber = { version = "0.3.16", features = ["json", "env-filter"] }
|
| 35 |
+
|
benchmark/rust-toolchain.toml
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[toolchain]
|
| 2 |
+
channel = "1.67.0"
|
| 3 |
+
components = ["rustfmt", "clippy"]
|
benchmark/src/app.rs
ADDED
|
@@ -0,0 +1,688 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
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| 1 |
+
/// Inspired by https://github.com/hatoo/oha/blob/bb989ea3cd77727e7743e7daa60a19894bb5e901/src/monitor.rs
|
| 2 |
+
use crate::generation::{Decode, Message, Prefill};
|
| 3 |
+
use crossterm::event::{KeyCode, KeyEvent, KeyModifiers};
|
| 4 |
+
use text_generation_client::ClientError;
|
| 5 |
+
use tokio::sync::mpsc;
|
| 6 |
+
use tui::backend::Backend;
|
| 7 |
+
use tui::layout::{Alignment, Constraint, Direction, Layout};
|
| 8 |
+
use tui::style::{Color, Modifier, Style};
|
| 9 |
+
use tui::text::{Span, Spans};
|
| 10 |
+
use tui::widgets::{
|
| 11 |
+
Axis, BarChart, Block, Borders, Chart, Dataset, Gauge, GraphType, Paragraph, Tabs,
|
| 12 |
+
};
|
| 13 |
+
use tui::{symbols, Frame};
|
| 14 |
+
|
| 15 |
+
/// TUI powered App
|
| 16 |
+
pub(crate) struct App {
|
| 17 |
+
pub(crate) running: bool,
|
| 18 |
+
completed_runs: Vec<usize>,
|
| 19 |
+
completed_batch: usize,
|
| 20 |
+
current_batch: usize,
|
| 21 |
+
current_tab: usize,
|
| 22 |
+
touched_tab: bool,
|
| 23 |
+
zoom: bool,
|
| 24 |
+
is_error: bool,
|
| 25 |
+
data: Data,
|
| 26 |
+
tokenizer_name: String,
|
| 27 |
+
sequence_length: u32,
|
| 28 |
+
decode_length: u32,
|
| 29 |
+
n_run: usize,
|
| 30 |
+
batch_size: Vec<u32>,
|
| 31 |
+
receiver: mpsc::Receiver<Result<Message, ClientError>>,
|
| 32 |
+
}
|
| 33 |
+
|
| 34 |
+
impl App {
|
| 35 |
+
pub(crate) fn new(
|
| 36 |
+
receiver: mpsc::Receiver<Result<Message, ClientError>>,
|
| 37 |
+
tokenizer_name: String,
|
| 38 |
+
sequence_length: u32,
|
| 39 |
+
decode_length: u32,
|
| 40 |
+
n_run: usize,
|
| 41 |
+
batch_size: Vec<u32>,
|
| 42 |
+
) -> Self {
|
| 43 |
+
let data = Data::new(n_run, batch_size.len());
|
| 44 |
+
let current_tab = 0;
|
| 45 |
+
|
| 46 |
+
let completed_runs: Vec<usize> = (0..batch_size.len()).map(|_| 0).collect();
|
| 47 |
+
let completed_batch = 0;
|
| 48 |
+
let current_batch = 0;
|
| 49 |
+
let is_error = false;
|
| 50 |
+
|
| 51 |
+
Self {
|
| 52 |
+
running: true,
|
| 53 |
+
completed_runs,
|
| 54 |
+
completed_batch,
|
| 55 |
+
current_batch,
|
| 56 |
+
current_tab,
|
| 57 |
+
touched_tab: false,
|
| 58 |
+
zoom: false,
|
| 59 |
+
is_error,
|
| 60 |
+
data,
|
| 61 |
+
tokenizer_name,
|
| 62 |
+
sequence_length,
|
| 63 |
+
decode_length,
|
| 64 |
+
n_run,
|
| 65 |
+
batch_size,
|
| 66 |
+
receiver,
|
| 67 |
+
}
|
| 68 |
+
}
|
| 69 |
+
|
| 70 |
+
/// Handle crossterm key events
|
| 71 |
+
pub(crate) fn handle_key_event(&mut self, key_event: KeyEvent) {
|
| 72 |
+
match key_event {
|
| 73 |
+
// Increase and wrap tab
|
| 74 |
+
KeyEvent {
|
| 75 |
+
code: KeyCode::Right,
|
| 76 |
+
..
|
| 77 |
+
}
|
| 78 |
+
| KeyEvent {
|
| 79 |
+
code: KeyCode::Tab, ..
|
| 80 |
+
} => {
|
| 81 |
+
self.touched_tab = true;
|
| 82 |
+
self.current_tab = (self.current_tab + 1) % self.batch_size.len();
|
| 83 |
+
}
|
| 84 |
+
// Decrease and wrap tab
|
| 85 |
+
KeyEvent {
|
| 86 |
+
code: KeyCode::Left,
|
| 87 |
+
..
|
| 88 |
+
} => {
|
| 89 |
+
self.touched_tab = true;
|
| 90 |
+
if self.current_tab > 0 {
|
| 91 |
+
self.current_tab -= 1;
|
| 92 |
+
} else {
|
| 93 |
+
self.current_tab = self.batch_size.len() - 1;
|
| 94 |
+
}
|
| 95 |
+
}
|
| 96 |
+
// Zoom on throughput/latency fig
|
| 97 |
+
KeyEvent {
|
| 98 |
+
code: KeyCode::Char('+'),
|
| 99 |
+
..
|
| 100 |
+
} => {
|
| 101 |
+
self.zoom = true;
|
| 102 |
+
}
|
| 103 |
+
// Unzoom on throughput/latency fig
|
| 104 |
+
KeyEvent {
|
| 105 |
+
code: KeyCode::Char('-'),
|
| 106 |
+
..
|
| 107 |
+
} => {
|
| 108 |
+
self.zoom = false;
|
| 109 |
+
}
|
| 110 |
+
// Quit
|
| 111 |
+
KeyEvent {
|
| 112 |
+
code: KeyCode::Char('q'),
|
| 113 |
+
..
|
| 114 |
+
}
|
| 115 |
+
| KeyEvent {
|
| 116 |
+
code: KeyCode::Char('c'),
|
| 117 |
+
modifiers: KeyModifiers::CONTROL,
|
| 118 |
+
..
|
| 119 |
+
} => {
|
| 120 |
+
self.running = false;
|
| 121 |
+
}
|
| 122 |
+
_ => (),
|
| 123 |
+
}
|
| 124 |
+
}
|
| 125 |
+
|
| 126 |
+
/// Get all pending messages from generation task
|
| 127 |
+
pub(crate) fn tick(&mut self) {
|
| 128 |
+
while let Ok(message) = self.receiver.try_recv() {
|
| 129 |
+
match message {
|
| 130 |
+
Ok(message) => match message {
|
| 131 |
+
Message::Prefill(step) => self.data.push_prefill(step, self.current_batch),
|
| 132 |
+
Message::Decode(step) => self.data.push_decode(step, self.current_batch),
|
| 133 |
+
Message::EndRun => {
|
| 134 |
+
self.completed_runs[self.current_batch] += 1;
|
| 135 |
+
}
|
| 136 |
+
Message::EndBatch => {
|
| 137 |
+
self.data.end_batch(self.current_batch);
|
| 138 |
+
self.completed_batch += 1;
|
| 139 |
+
|
| 140 |
+
if self.current_batch < self.batch_size.len() - 1 {
|
| 141 |
+
// Only go to next tab if the user never touched the tab keys
|
| 142 |
+
if !self.touched_tab {
|
| 143 |
+
self.current_tab += 1;
|
| 144 |
+
}
|
| 145 |
+
|
| 146 |
+
self.current_batch += 1;
|
| 147 |
+
}
|
| 148 |
+
}
|
| 149 |
+
Message::Warmup => {}
|
| 150 |
+
},
|
| 151 |
+
Err(_) => self.is_error = true,
|
| 152 |
+
}
|
| 153 |
+
}
|
| 154 |
+
}
|
| 155 |
+
|
| 156 |
+
/// Render frame
|
| 157 |
+
pub fn render<B: Backend>(&mut self, f: &mut Frame<'_, B>) {
|
| 158 |
+
let batch_progress =
|
| 159 |
+
(self.completed_batch as f64 / self.batch_size.len() as f64).clamp(0.0, 1.0);
|
| 160 |
+
let run_progress =
|
| 161 |
+
(self.completed_runs[self.current_batch] as f64 / self.n_run as f64).clamp(0.0, 1.0);
|
| 162 |
+
|
| 163 |
+
// Vertical layout
|
| 164 |
+
let row5 = Layout::default()
|
| 165 |
+
.direction(Direction::Vertical)
|
| 166 |
+
.constraints(
|
| 167 |
+
[
|
| 168 |
+
Constraint::Length(1),
|
| 169 |
+
Constraint::Length(3),
|
| 170 |
+
Constraint::Length(3),
|
| 171 |
+
Constraint::Length(13),
|
| 172 |
+
Constraint::Min(10),
|
| 173 |
+
]
|
| 174 |
+
.as_ref(),
|
| 175 |
+
)
|
| 176 |
+
.split(f.size());
|
| 177 |
+
|
| 178 |
+
// Top row horizontal layout
|
| 179 |
+
let top = Layout::default()
|
| 180 |
+
.direction(Direction::Horizontal)
|
| 181 |
+
.constraints([Constraint::Percentage(50), Constraint::Percentage(50)].as_ref())
|
| 182 |
+
.split(row5[2]);
|
| 183 |
+
|
| 184 |
+
// Mid row horizontal layout
|
| 185 |
+
let mid = Layout::default()
|
| 186 |
+
.direction(Direction::Horizontal)
|
| 187 |
+
.constraints(
|
| 188 |
+
[
|
| 189 |
+
Constraint::Percentage(25),
|
| 190 |
+
Constraint::Percentage(25),
|
| 191 |
+
Constraint::Percentage(25),
|
| 192 |
+
Constraint::Percentage(25),
|
| 193 |
+
]
|
| 194 |
+
.as_ref(),
|
| 195 |
+
)
|
| 196 |
+
.split(row5[3]);
|
| 197 |
+
|
| 198 |
+
// Left mid row vertical layout
|
| 199 |
+
let prefill_text = Layout::default()
|
| 200 |
+
.direction(Direction::Vertical)
|
| 201 |
+
.constraints([Constraint::Length(8), Constraint::Length(5)].as_ref())
|
| 202 |
+
.split(mid[0]);
|
| 203 |
+
|
| 204 |
+
// Right mid row vertical layout
|
| 205 |
+
let decode_text = Layout::default()
|
| 206 |
+
.direction(Direction::Vertical)
|
| 207 |
+
.constraints([Constraint::Length(8), Constraint::Length(5)].as_ref())
|
| 208 |
+
.split(mid[2]);
|
| 209 |
+
let decode_text_latency = Layout::default()
|
| 210 |
+
.direction(Direction::Horizontal)
|
| 211 |
+
.constraints([Constraint::Percentage(50), Constraint::Percentage(50)].as_ref())
|
| 212 |
+
.split(decode_text[0]);
|
| 213 |
+
|
| 214 |
+
// Bottom row horizontal layout
|
| 215 |
+
let bottom = Layout::default()
|
| 216 |
+
.direction(Direction::Horizontal)
|
| 217 |
+
.constraints([Constraint::Percentage(50), Constraint::Percentage(50)].as_ref())
|
| 218 |
+
.split(row5[4]);
|
| 219 |
+
|
| 220 |
+
// Title
|
| 221 |
+
let title = Block::default()
|
| 222 |
+
.borders(Borders::NONE)
|
| 223 |
+
.title(format!(
|
| 224 |
+
"Model: {} | Sequence Length: {} | Decode Length: {}",
|
| 225 |
+
self.tokenizer_name, self.sequence_length, self.decode_length
|
| 226 |
+
))
|
| 227 |
+
.style(
|
| 228 |
+
Style::default()
|
| 229 |
+
.add_modifier(Modifier::BOLD)
|
| 230 |
+
.fg(Color::White),
|
| 231 |
+
);
|
| 232 |
+
f.render_widget(title, row5[0]);
|
| 233 |
+
|
| 234 |
+
// Helper
|
| 235 |
+
let helper = Block::default()
|
| 236 |
+
.borders(Borders::NONE)
|
| 237 |
+
.title("<- | tab | ->: change batch tab | q / CTRL + c: quit | +/-: zoom")
|
| 238 |
+
.title_alignment(Alignment::Right)
|
| 239 |
+
.style(Style::default().fg(Color::White));
|
| 240 |
+
f.render_widget(helper, row5[0]);
|
| 241 |
+
|
| 242 |
+
// Batch tabs
|
| 243 |
+
let titles = self
|
| 244 |
+
.batch_size
|
| 245 |
+
.iter()
|
| 246 |
+
.map(|b| {
|
| 247 |
+
Spans::from(vec![Span::styled(
|
| 248 |
+
format!("Batch: {b}"),
|
| 249 |
+
Style::default().fg(Color::White),
|
| 250 |
+
)])
|
| 251 |
+
})
|
| 252 |
+
.collect();
|
| 253 |
+
let tabs = Tabs::new(titles)
|
| 254 |
+
.block(Block::default().borders(Borders::ALL).title("Tabs"))
|
| 255 |
+
.select(self.current_tab)
|
| 256 |
+
.style(Style::default().fg(Color::LightCyan))
|
| 257 |
+
.highlight_style(
|
| 258 |
+
Style::default()
|
| 259 |
+
.add_modifier(Modifier::BOLD)
|
| 260 |
+
.bg(Color::Black),
|
| 261 |
+
);
|
| 262 |
+
f.render_widget(tabs, row5[1]);
|
| 263 |
+
|
| 264 |
+
// Total progress bar
|
| 265 |
+
let color = if self.is_error {
|
| 266 |
+
Color::Red
|
| 267 |
+
} else {
|
| 268 |
+
Color::LightGreen
|
| 269 |
+
};
|
| 270 |
+
let batch_gauge = progress_gauge(
|
| 271 |
+
"Total Progress",
|
| 272 |
+
format!("{} / {}", self.completed_batch, self.batch_size.len()),
|
| 273 |
+
batch_progress,
|
| 274 |
+
color,
|
| 275 |
+
);
|
| 276 |
+
f.render_widget(batch_gauge, top[0]);
|
| 277 |
+
|
| 278 |
+
// Batch progress Bar
|
| 279 |
+
let color = if self.is_error {
|
| 280 |
+
Color::Red
|
| 281 |
+
} else {
|
| 282 |
+
Color::LightBlue
|
| 283 |
+
};
|
| 284 |
+
let run_gauge = progress_gauge(
|
| 285 |
+
"Batch Progress",
|
| 286 |
+
format!(
|
| 287 |
+
"{} / {}",
|
| 288 |
+
self.completed_runs[self.current_batch], self.n_run
|
| 289 |
+
),
|
| 290 |
+
run_progress,
|
| 291 |
+
color,
|
| 292 |
+
);
|
| 293 |
+
f.render_widget(run_gauge, top[1]);
|
| 294 |
+
|
| 295 |
+
// Prefill text infos
|
| 296 |
+
let prefill_latency_block = latency_paragraph(
|
| 297 |
+
&mut self.data.prefill_latencies[self.current_tab],
|
| 298 |
+
"Prefill",
|
| 299 |
+
);
|
| 300 |
+
let prefill_throughput_block =
|
| 301 |
+
throughput_paragraph(&self.data.prefill_throughputs[self.current_tab], "Prefill");
|
| 302 |
+
|
| 303 |
+
f.render_widget(prefill_latency_block, prefill_text[0]);
|
| 304 |
+
f.render_widget(prefill_throughput_block, prefill_text[1]);
|
| 305 |
+
|
| 306 |
+
// Prefill latency histogram
|
| 307 |
+
let histo_width = 7;
|
| 308 |
+
let bins = if mid[1].width < 2 {
|
| 309 |
+
0
|
| 310 |
+
} else {
|
| 311 |
+
(mid[1].width as usize - 2) / (histo_width + 1)
|
| 312 |
+
}
|
| 313 |
+
.max(2);
|
| 314 |
+
|
| 315 |
+
let histo_data =
|
| 316 |
+
latency_histogram_data(&self.data.prefill_latencies[self.current_tab], bins);
|
| 317 |
+
let histo_data_str: Vec<(&str, u64)> =
|
| 318 |
+
histo_data.iter().map(|(l, v)| (l.as_str(), *v)).collect();
|
| 319 |
+
let prefill_histogram =
|
| 320 |
+
latency_histogram(&histo_data_str, "Prefill").bar_width(histo_width as u16);
|
| 321 |
+
f.render_widget(prefill_histogram, mid[1]);
|
| 322 |
+
|
| 323 |
+
// Decode text info
|
| 324 |
+
let decode_latency_block = latency_paragraph(
|
| 325 |
+
&mut self.data.decode_latencies[self.current_tab],
|
| 326 |
+
"Decode Total",
|
| 327 |
+
);
|
| 328 |
+
let decode_token_latency_block = latency_paragraph(
|
| 329 |
+
&mut self.data.decode_token_latencies[self.current_tab],
|
| 330 |
+
"Decode Token",
|
| 331 |
+
);
|
| 332 |
+
let decode_throughput_block =
|
| 333 |
+
throughput_paragraph(&self.data.decode_throughputs[self.current_tab], "Decode");
|
| 334 |
+
f.render_widget(decode_latency_block, decode_text_latency[0]);
|
| 335 |
+
f.render_widget(decode_token_latency_block, decode_text_latency[1]);
|
| 336 |
+
f.render_widget(decode_throughput_block, decode_text[1]);
|
| 337 |
+
|
| 338 |
+
// Decode latency histogram
|
| 339 |
+
let histo_data =
|
| 340 |
+
latency_histogram_data(&self.data.decode_latencies[self.current_tab], bins);
|
| 341 |
+
let histo_data_str: Vec<(&str, u64)> =
|
| 342 |
+
histo_data.iter().map(|(l, v)| (l.as_str(), *v)).collect();
|
| 343 |
+
let decode_histogram =
|
| 344 |
+
latency_histogram(&histo_data_str, "Decode").bar_width(histo_width as u16);
|
| 345 |
+
f.render_widget(decode_histogram, mid[3]);
|
| 346 |
+
|
| 347 |
+
// Prefill latency/throughput chart
|
| 348 |
+
let prefill_latency_throughput_chart = latency_throughput_chart(
|
| 349 |
+
&self.data.prefill_batch_latency_throughput,
|
| 350 |
+
&self.batch_size,
|
| 351 |
+
self.zoom,
|
| 352 |
+
"Prefill",
|
| 353 |
+
);
|
| 354 |
+
f.render_widget(prefill_latency_throughput_chart, bottom[0]);
|
| 355 |
+
|
| 356 |
+
// Decode latency/throughput chart
|
| 357 |
+
let decode_latency_throughput_chart = latency_throughput_chart(
|
| 358 |
+
&self.data.decode_batch_latency_throughput,
|
| 359 |
+
&self.batch_size,
|
| 360 |
+
self.zoom,
|
| 361 |
+
"Decode",
|
| 362 |
+
);
|
| 363 |
+
f.render_widget(decode_latency_throughput_chart, bottom[1]);
|
| 364 |
+
}
|
| 365 |
+
}
|
| 366 |
+
|
| 367 |
+
/// App internal data struct
|
| 368 |
+
struct Data {
|
| 369 |
+
prefill_latencies: Vec<Vec<f64>>,
|
| 370 |
+
prefill_throughputs: Vec<Vec<f64>>,
|
| 371 |
+
decode_latencies: Vec<Vec<f64>>,
|
| 372 |
+
decode_token_latencies: Vec<Vec<f64>>,
|
| 373 |
+
decode_throughputs: Vec<Vec<f64>>,
|
| 374 |
+
prefill_batch_latency_throughput: Vec<(f64, f64)>,
|
| 375 |
+
decode_batch_latency_throughput: Vec<(f64, f64)>,
|
| 376 |
+
}
|
| 377 |
+
|
| 378 |
+
impl Data {
|
| 379 |
+
fn new(n_run: usize, n_batch: usize) -> Self {
|
| 380 |
+
let prefill_latencies: Vec<Vec<f64>> =
|
| 381 |
+
(0..n_batch).map(|_| Vec::with_capacity(n_run)).collect();
|
| 382 |
+
let prefill_throughputs: Vec<Vec<f64>> = prefill_latencies.clone();
|
| 383 |
+
|
| 384 |
+
let decode_latencies: Vec<Vec<f64>> = prefill_latencies.clone();
|
| 385 |
+
let decode_token_latencies: Vec<Vec<f64>> = decode_latencies.clone();
|
| 386 |
+
let decode_throughputs: Vec<Vec<f64>> = prefill_throughputs.clone();
|
| 387 |
+
|
| 388 |
+
let prefill_batch_latency_throughput: Vec<(f64, f64)> = Vec::with_capacity(n_batch);
|
| 389 |
+
let decode_batch_latency_throughput: Vec<(f64, f64)> =
|
| 390 |
+
prefill_batch_latency_throughput.clone();
|
| 391 |
+
|
| 392 |
+
Self {
|
| 393 |
+
prefill_latencies,
|
| 394 |
+
prefill_throughputs,
|
| 395 |
+
decode_latencies,
|
| 396 |
+
decode_token_latencies,
|
| 397 |
+
decode_throughputs,
|
| 398 |
+
prefill_batch_latency_throughput,
|
| 399 |
+
decode_batch_latency_throughput,
|
| 400 |
+
}
|
| 401 |
+
}
|
| 402 |
+
|
| 403 |
+
fn push_prefill(&mut self, prefill: Prefill, batch_idx: usize) {
|
| 404 |
+
let latency = prefill.latency.as_millis() as f64;
|
| 405 |
+
self.prefill_latencies[batch_idx].push(latency);
|
| 406 |
+
self.prefill_throughputs[batch_idx].push(prefill.throughput);
|
| 407 |
+
}
|
| 408 |
+
|
| 409 |
+
fn push_decode(&mut self, decode: Decode, batch_idx: usize) {
|
| 410 |
+
let latency = decode.latency.as_millis() as f64;
|
| 411 |
+
let token_latency = decode.token_latency.as_millis() as f64;
|
| 412 |
+
self.decode_latencies[batch_idx].push(latency);
|
| 413 |
+
self.decode_token_latencies[batch_idx].push(token_latency);
|
| 414 |
+
self.decode_throughputs[batch_idx].push(decode.throughput);
|
| 415 |
+
}
|
| 416 |
+
|
| 417 |
+
fn end_batch(&mut self, batch_idx: usize) {
|
| 418 |
+
self.prefill_batch_latency_throughput.push((
|
| 419 |
+
self.prefill_latencies[batch_idx].iter().sum::<f64>()
|
| 420 |
+
/ self.prefill_latencies[batch_idx].len() as f64,
|
| 421 |
+
self.prefill_throughputs[batch_idx].iter().sum::<f64>()
|
| 422 |
+
/ self.prefill_throughputs[batch_idx].len() as f64,
|
| 423 |
+
));
|
| 424 |
+
self.decode_batch_latency_throughput.push((
|
| 425 |
+
self.decode_latencies[batch_idx].iter().sum::<f64>()
|
| 426 |
+
/ self.decode_latencies[batch_idx].len() as f64,
|
| 427 |
+
self.decode_throughputs[batch_idx].iter().sum::<f64>()
|
| 428 |
+
/ self.decode_throughputs[batch_idx].len() as f64,
|
| 429 |
+
));
|
| 430 |
+
}
|
| 431 |
+
}
|
| 432 |
+
|
| 433 |
+
/// Progress bar
|
| 434 |
+
fn progress_gauge(title: &str, label: String, progress: f64, color: Color) -> Gauge {
|
| 435 |
+
Gauge::default()
|
| 436 |
+
.block(Block::default().title(title).borders(Borders::ALL))
|
| 437 |
+
.gauge_style(Style::default().fg(color))
|
| 438 |
+
.label(Span::raw(label))
|
| 439 |
+
.ratio(progress)
|
| 440 |
+
}
|
| 441 |
+
|
| 442 |
+
/// Throughput paragraph
|
| 443 |
+
fn throughput_paragraph<'a>(throughput: &Vec<f64>, name: &'static str) -> Paragraph<'a> {
|
| 444 |
+
// Throughput average/high/low texts
|
| 445 |
+
let throughput_texts = statis_spans(throughput, "tokens/secs");
|
| 446 |
+
|
| 447 |
+
// Throughput block
|
| 448 |
+
Paragraph::new(throughput_texts).block(
|
| 449 |
+
Block::default()
|
| 450 |
+
.title(Span::raw(format!("{name} Throughput")))
|
| 451 |
+
.borders(Borders::ALL),
|
| 452 |
+
)
|
| 453 |
+
}
|
| 454 |
+
|
| 455 |
+
/// Latency paragraph
|
| 456 |
+
fn latency_paragraph<'a>(latency: &mut Vec<f64>, name: &'static str) -> Paragraph<'a> {
|
| 457 |
+
// Latency average/high/low texts
|
| 458 |
+
let mut latency_texts = statis_spans(latency, "ms");
|
| 459 |
+
|
| 460 |
+
// Sort latency for percentiles
|
| 461 |
+
float_ord::sort(latency);
|
| 462 |
+
let latency_percentiles = crate::utils::percentiles(latency, &[50, 90, 99]);
|
| 463 |
+
|
| 464 |
+
// Latency p50/p90/p99 texts
|
| 465 |
+
let colors = vec![Color::LightGreen, Color::LightYellow, Color::LightRed];
|
| 466 |
+
for (i, (name, value)) in latency_percentiles.iter().enumerate() {
|
| 467 |
+
let span = Spans::from(vec![Span::styled(
|
| 468 |
+
format!("{name}: {value:.2} ms"),
|
| 469 |
+
Style::default().fg(colors[i]),
|
| 470 |
+
)]);
|
| 471 |
+
latency_texts.push(span);
|
| 472 |
+
}
|
| 473 |
+
|
| 474 |
+
Paragraph::new(latency_texts).block(
|
| 475 |
+
Block::default()
|
| 476 |
+
.title(Span::raw(format!("{name} Latency")))
|
| 477 |
+
.borders(Borders::ALL),
|
| 478 |
+
)
|
| 479 |
+
}
|
| 480 |
+
|
| 481 |
+
/// Average/High/Low spans
|
| 482 |
+
fn statis_spans<'a>(data: &Vec<f64>, unit: &'static str) -> Vec<Spans<'a>> {
|
| 483 |
+
vec![
|
| 484 |
+
Spans::from(vec![Span::styled(
|
| 485 |
+
format!(
|
| 486 |
+
"Average: {:.2} {unit}",
|
| 487 |
+
data.iter().sum::<f64>() / data.len() as f64
|
| 488 |
+
),
|
| 489 |
+
Style::default().fg(Color::LightBlue),
|
| 490 |
+
)]),
|
| 491 |
+
Spans::from(vec![Span::styled(
|
| 492 |
+
format!(
|
| 493 |
+
"Lowest: {:.2} {unit}",
|
| 494 |
+
data.iter()
|
| 495 |
+
.min_by(|a, b| a.total_cmp(b))
|
| 496 |
+
.unwrap_or(&std::f64::NAN)
|
| 497 |
+
),
|
| 498 |
+
Style::default().fg(Color::Reset),
|
| 499 |
+
)]),
|
| 500 |
+
Spans::from(vec![Span::styled(
|
| 501 |
+
format!(
|
| 502 |
+
"Highest: {:.2} {unit}",
|
| 503 |
+
data.iter()
|
| 504 |
+
.max_by(|a, b| a.total_cmp(b))
|
| 505 |
+
.unwrap_or(&std::f64::NAN)
|
| 506 |
+
),
|
| 507 |
+
Style::default().fg(Color::Reset),
|
| 508 |
+
)]),
|
| 509 |
+
]
|
| 510 |
+
}
|
| 511 |
+
|
| 512 |
+
/// Latency histogram data
|
| 513 |
+
fn latency_histogram_data(latency: &[f64], bins: usize) -> Vec<(String, u64)> {
|
| 514 |
+
let histo_data: Vec<(String, u64)> = {
|
| 515 |
+
let histo = crate::utils::histogram(latency, bins);
|
| 516 |
+
histo
|
| 517 |
+
.into_iter()
|
| 518 |
+
.map(|(label, v)| (format!("{label:.2}"), v as u64))
|
| 519 |
+
.collect()
|
| 520 |
+
};
|
| 521 |
+
|
| 522 |
+
histo_data
|
| 523 |
+
}
|
| 524 |
+
|
| 525 |
+
/// Latency Histogram
|
| 526 |
+
fn latency_histogram<'a>(
|
| 527 |
+
histo_data_str: &'a Vec<(&'a str, u64)>,
|
| 528 |
+
name: &'static str,
|
| 529 |
+
) -> BarChart<'a> {
|
| 530 |
+
BarChart::default()
|
| 531 |
+
.block(
|
| 532 |
+
Block::default()
|
| 533 |
+
.title(format!("{name} latency histogram"))
|
| 534 |
+
.style(Style::default().fg(Color::LightYellow).bg(Color::Reset))
|
| 535 |
+
.borders(Borders::ALL),
|
| 536 |
+
)
|
| 537 |
+
.data(histo_data_str.as_slice())
|
| 538 |
+
}
|
| 539 |
+
|
| 540 |
+
/// Latency/Throughput chart
|
| 541 |
+
fn latency_throughput_chart<'a>(
|
| 542 |
+
latency_throughput: &'a Vec<(f64, f64)>,
|
| 543 |
+
batch_sizes: &'a [u32],
|
| 544 |
+
zoom: bool,
|
| 545 |
+
name: &'static str,
|
| 546 |
+
) -> Chart<'a> {
|
| 547 |
+
let latency_iter = latency_throughput.iter().map(|(l, _)| l);
|
| 548 |
+
let throughput_iter = latency_throughput.iter().map(|(_, t)| t);
|
| 549 |
+
|
| 550 |
+
// Get extreme values
|
| 551 |
+
let min_latency: f64 = *latency_iter
|
| 552 |
+
.clone()
|
| 553 |
+
.min_by(|a, b| a.total_cmp(b))
|
| 554 |
+
.unwrap_or(&std::f64::NAN);
|
| 555 |
+
let max_latency: f64 = *latency_iter
|
| 556 |
+
.max_by(|a, b| a.total_cmp(b))
|
| 557 |
+
.unwrap_or(&std::f64::NAN);
|
| 558 |
+
let min_throughput: f64 = *throughput_iter
|
| 559 |
+
.clone()
|
| 560 |
+
.min_by(|a, b| a.total_cmp(b))
|
| 561 |
+
.unwrap_or(&std::f64::NAN);
|
| 562 |
+
let max_throughput: f64 = *throughput_iter
|
| 563 |
+
.max_by(|a, b| a.total_cmp(b))
|
| 564 |
+
.unwrap_or(&std::f64::NAN);
|
| 565 |
+
|
| 566 |
+
// Char min max values
|
| 567 |
+
let min_x = if zoom {
|
| 568 |
+
((min_latency - 0.05 * min_latency) / 100.0).floor() * 100.0
|
| 569 |
+
} else {
|
| 570 |
+
0.0
|
| 571 |
+
};
|
| 572 |
+
let max_x = ((max_latency + 0.05 * max_latency) / 100.0).ceil() * 100.0;
|
| 573 |
+
let step_x = (max_x - min_x) / 4.0;
|
| 574 |
+
|
| 575 |
+
// Chart min max values
|
| 576 |
+
let min_y = if zoom {
|
| 577 |
+
((min_throughput - 0.05 * min_throughput) / 100.0).floor() * 100.0
|
| 578 |
+
} else {
|
| 579 |
+
0.0
|
| 580 |
+
};
|
| 581 |
+
let max_y = ((max_throughput + 0.05 * max_throughput) / 100.0).ceil() * 100.0;
|
| 582 |
+
let step_y = (max_y - min_y) / 4.0;
|
| 583 |
+
|
| 584 |
+
// Labels
|
| 585 |
+
let mut x_labels = vec![Span::styled(
|
| 586 |
+
format!("{min_x:.2}"),
|
| 587 |
+
Style::default()
|
| 588 |
+
.add_modifier(Modifier::BOLD)
|
| 589 |
+
.fg(Color::Gray)
|
| 590 |
+
.bg(Color::Reset),
|
| 591 |
+
)];
|
| 592 |
+
for i in 0..3 {
|
| 593 |
+
x_labels.push(Span::styled(
|
| 594 |
+
format!("{:.2}", min_x + ((i + 1) as f64 * step_x)),
|
| 595 |
+
Style::default().fg(Color::Gray).bg(Color::Reset),
|
| 596 |
+
));
|
| 597 |
+
}
|
| 598 |
+
x_labels.push(Span::styled(
|
| 599 |
+
format!("{max_x:.2}"),
|
| 600 |
+
Style::default()
|
| 601 |
+
.add_modifier(Modifier::BOLD)
|
| 602 |
+
.fg(Color::Gray)
|
| 603 |
+
.bg(Color::Reset),
|
| 604 |
+
));
|
| 605 |
+
|
| 606 |
+
// Labels
|
| 607 |
+
let mut y_labels = vec![Span::styled(
|
| 608 |
+
format!("{min_y:.2}"),
|
| 609 |
+
Style::default()
|
| 610 |
+
.add_modifier(Modifier::BOLD)
|
| 611 |
+
.fg(Color::Gray)
|
| 612 |
+
.bg(Color::Reset),
|
| 613 |
+
)];
|
| 614 |
+
for i in 0..3 {
|
| 615 |
+
y_labels.push(Span::styled(
|
| 616 |
+
format!("{:.2}", min_y + ((i + 1) as f64 * step_y)),
|
| 617 |
+
Style::default().fg(Color::Gray).bg(Color::Reset),
|
| 618 |
+
));
|
| 619 |
+
}
|
| 620 |
+
y_labels.push(Span::styled(
|
| 621 |
+
format!("{max_y:.2}"),
|
| 622 |
+
Style::default()
|
| 623 |
+
.add_modifier(Modifier::BOLD)
|
| 624 |
+
.fg(Color::Gray)
|
| 625 |
+
.bg(Color::Reset),
|
| 626 |
+
));
|
| 627 |
+
|
| 628 |
+
// Chart dataset
|
| 629 |
+
let colors = color_vec();
|
| 630 |
+
let datasets: Vec<Dataset> = (0..latency_throughput.len())
|
| 631 |
+
.map(|i| {
|
| 632 |
+
let color_idx = i % colors.len();
|
| 633 |
+
|
| 634 |
+
Dataset::default()
|
| 635 |
+
.name(batch_sizes[i].to_string())
|
| 636 |
+
.marker(symbols::Marker::Block)
|
| 637 |
+
.style(Style::default().fg(colors[color_idx]))
|
| 638 |
+
.graph_type(GraphType::Scatter)
|
| 639 |
+
.data(&latency_throughput[i..(i + 1)])
|
| 640 |
+
})
|
| 641 |
+
.collect();
|
| 642 |
+
|
| 643 |
+
// Chart
|
| 644 |
+
Chart::new(datasets)
|
| 645 |
+
.style(Style::default().fg(Color::Cyan).bg(Color::Reset))
|
| 646 |
+
.block(
|
| 647 |
+
Block::default()
|
| 648 |
+
.title(Span::styled(
|
| 649 |
+
format!("{name} throughput over latency"),
|
| 650 |
+
Style::default().fg(Color::Gray).bg(Color::Reset),
|
| 651 |
+
))
|
| 652 |
+
.borders(Borders::ALL),
|
| 653 |
+
)
|
| 654 |
+
.x_axis(
|
| 655 |
+
Axis::default()
|
| 656 |
+
.title("ms")
|
| 657 |
+
.style(Style::default().fg(Color::Gray).bg(Color::Reset))
|
| 658 |
+
.labels(x_labels)
|
| 659 |
+
.bounds([min_x, max_x]),
|
| 660 |
+
)
|
| 661 |
+
.y_axis(
|
| 662 |
+
Axis::default()
|
| 663 |
+
.title("tokens/secs")
|
| 664 |
+
.style(Style::default().fg(Color::Gray).bg(Color::Reset))
|
| 665 |
+
.labels(y_labels)
|
| 666 |
+
.bounds([min_y, max_y]),
|
| 667 |
+
)
|
| 668 |
+
}
|
| 669 |
+
|
| 670 |
+
// Colors for latency/throughput chart
|
| 671 |
+
fn color_vec() -> Vec<Color> {
|
| 672 |
+
vec![
|
| 673 |
+
Color::Red,
|
| 674 |
+
Color::Green,
|
| 675 |
+
Color::Yellow,
|
| 676 |
+
Color::Blue,
|
| 677 |
+
Color::Magenta,
|
| 678 |
+
Color::Cyan,
|
| 679 |
+
Color::Gray,
|
| 680 |
+
Color::DarkGray,
|
| 681 |
+
Color::LightRed,
|
| 682 |
+
Color::LightGreen,
|
| 683 |
+
Color::LightYellow,
|
| 684 |
+
Color::LightBlue,
|
| 685 |
+
Color::LightMagenta,
|
| 686 |
+
Color::LightCyan,
|
| 687 |
+
]
|
| 688 |
+
}
|
benchmark/src/event.rs
ADDED
|
@@ -0,0 +1,65 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
/// Inspired by https://github.com/orhun/rust-tui-template/blob/472aa515119d4c94903eac12d9784417281dc7f5/src/event.rs
|
| 2 |
+
use crossterm::event;
|
| 3 |
+
use std::time::{Duration, Instant};
|
| 4 |
+
use tokio::sync::{broadcast, mpsc};
|
| 5 |
+
|
| 6 |
+
/// Events
|
| 7 |
+
#[derive(Debug)]
|
| 8 |
+
pub(crate) enum Event {
|
| 9 |
+
/// Terminal tick.
|
| 10 |
+
Tick,
|
| 11 |
+
/// Key press.
|
| 12 |
+
Key(event::KeyEvent),
|
| 13 |
+
/// Terminal resize.
|
| 14 |
+
Resize(u16, u16),
|
| 15 |
+
}
|
| 16 |
+
|
| 17 |
+
pub(crate) async fn terminal_event_task(
|
| 18 |
+
fps: u32,
|
| 19 |
+
event_sender: mpsc::Sender<Event>,
|
| 20 |
+
mut shutdown_receiver: broadcast::Receiver<()>,
|
| 21 |
+
_shutdown_guard_sender: mpsc::Sender<()>,
|
| 22 |
+
) {
|
| 23 |
+
// End task if a message is received on shutdown_receiver
|
| 24 |
+
// _shutdown_guard_sender will be dropped once the task is finished
|
| 25 |
+
tokio::select! {
|
| 26 |
+
_ = event_loop(fps, event_sender) => {
|
| 27 |
+
},
|
| 28 |
+
_ = shutdown_receiver.recv() => {}
|
| 29 |
+
}
|
| 30 |
+
}
|
| 31 |
+
|
| 32 |
+
/// Main event loop
|
| 33 |
+
async fn event_loop(fps: u32, event_sender: mpsc::Sender<Event>) {
|
| 34 |
+
// Frame budget
|
| 35 |
+
let per_frame = Duration::from_secs(1) / fps;
|
| 36 |
+
|
| 37 |
+
// When was last frame executed
|
| 38 |
+
let mut last_frame = Instant::now();
|
| 39 |
+
|
| 40 |
+
loop {
|
| 41 |
+
// Sleep to avoid blocking the thread for too long
|
| 42 |
+
if let Some(sleep) = per_frame.checked_sub(last_frame.elapsed()) {
|
| 43 |
+
tokio::time::sleep(sleep).await;
|
| 44 |
+
}
|
| 45 |
+
|
| 46 |
+
// Get crossterm event and send a new one over the channel
|
| 47 |
+
if event::poll(Duration::from_secs(0)).expect("no events available") {
|
| 48 |
+
match event::read().expect("unable to read event") {
|
| 49 |
+
event::Event::Key(e) => event_sender.send(Event::Key(e)).await.unwrap_or(()),
|
| 50 |
+
event::Event::Resize(w, h) => {
|
| 51 |
+
event_sender.send(Event::Resize(w, h)).await.unwrap_or(())
|
| 52 |
+
}
|
| 53 |
+
_ => (),
|
| 54 |
+
}
|
| 55 |
+
}
|
| 56 |
+
|
| 57 |
+
// Frame budget exceeded
|
| 58 |
+
if last_frame.elapsed() >= per_frame {
|
| 59 |
+
// Send tick
|
| 60 |
+
event_sender.send(Event::Tick).await.unwrap_or(());
|
| 61 |
+
// Rest last_frame time
|
| 62 |
+
last_frame = Instant::now();
|
| 63 |
+
}
|
| 64 |
+
}
|
| 65 |
+
}
|
benchmark/src/generation.rs
ADDED
|
@@ -0,0 +1,226 @@
|
|
|
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|
|
|
|
|
|
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|
|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
use std::time::{Duration, Instant};
|
| 2 |
+
use text_generation_client::{
|
| 3 |
+
Batch, ClientError, NextTokenChooserParameters, Request, ShardedClient,
|
| 4 |
+
StoppingCriteriaParameters,
|
| 5 |
+
};
|
| 6 |
+
use tokenizers::{Tokenizer, TruncationDirection};
|
| 7 |
+
use tokio::sync::{broadcast, mpsc};
|
| 8 |
+
|
| 9 |
+
const LOREM_IPSUM: &str = "Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.";
|
| 10 |
+
|
| 11 |
+
#[derive(Debug, Clone)]
|
| 12 |
+
pub(crate) struct Prefill {
|
| 13 |
+
pub(crate) latency: Duration,
|
| 14 |
+
pub(crate) throughput: f64,
|
| 15 |
+
}
|
| 16 |
+
|
| 17 |
+
#[derive(Debug, Clone)]
|
| 18 |
+
pub(crate) struct Decode {
|
| 19 |
+
pub(crate) latency: Duration,
|
| 20 |
+
pub(crate) token_latency: Duration,
|
| 21 |
+
pub(crate) throughput: f64,
|
| 22 |
+
}
|
| 23 |
+
|
| 24 |
+
#[derive(Debug)]
|
| 25 |
+
pub(crate) enum Message {
|
| 26 |
+
Warmup,
|
| 27 |
+
Prefill(Prefill),
|
| 28 |
+
Decode(Decode),
|
| 29 |
+
EndRun,
|
| 30 |
+
EndBatch,
|
| 31 |
+
}
|
| 32 |
+
|
| 33 |
+
/// Benchmarking task
|
| 34 |
+
#[allow(clippy::too_many_arguments)]
|
| 35 |
+
pub(crate) async fn generation_task(
|
| 36 |
+
tokenizer: Tokenizer,
|
| 37 |
+
batch_size: Vec<u32>,
|
| 38 |
+
sequence_length: u32,
|
| 39 |
+
decode_length: u32,
|
| 40 |
+
n_runs: usize,
|
| 41 |
+
warmups: usize,
|
| 42 |
+
client: ShardedClient,
|
| 43 |
+
run_sender: mpsc::Sender<Result<Message, ClientError>>,
|
| 44 |
+
mut shutdown_receiver: broadcast::Receiver<()>,
|
| 45 |
+
_shutdown_guard_sender: mpsc::Sender<()>,
|
| 46 |
+
) {
|
| 47 |
+
// End task if a message is received on shutdown_receiver
|
| 48 |
+
// _shutdown_guard_sender will be dropped once the task is finished
|
| 49 |
+
tokio::select! {
|
| 50 |
+
res = generate_runs(tokenizer, batch_size, sequence_length, decode_length, n_runs, warmups, client, run_sender.clone()) => {
|
| 51 |
+
if let Err(err) = res {
|
| 52 |
+
run_sender.send(Err(err)).await.unwrap_or(());
|
| 53 |
+
}
|
| 54 |
+
},
|
| 55 |
+
_ = shutdown_receiver.recv() => {}
|
| 56 |
+
}
|
| 57 |
+
}
|
| 58 |
+
|
| 59 |
+
/// Benchmark prefill/decode
|
| 60 |
+
#[allow(clippy::too_many_arguments)]
|
| 61 |
+
async fn generate_runs(
|
| 62 |
+
tokenizer: Tokenizer,
|
| 63 |
+
batch_size: Vec<u32>,
|
| 64 |
+
sequence_length: u32,
|
| 65 |
+
decode_length: u32,
|
| 66 |
+
n_runs: usize,
|
| 67 |
+
warmups: usize,
|
| 68 |
+
mut client: ShardedClient,
|
| 69 |
+
run_sender: mpsc::Sender<Result<Message, ClientError>>,
|
| 70 |
+
) -> Result<(), ClientError> {
|
| 71 |
+
// Create a dummy sequence
|
| 72 |
+
let sequence = create_sequence(sequence_length, tokenizer);
|
| 73 |
+
|
| 74 |
+
for b in batch_size {
|
| 75 |
+
// Warmups on batch size
|
| 76 |
+
for _ in 0..warmups {
|
| 77 |
+
let (_, decode_batch) = prefill(
|
| 78 |
+
sequence.clone(),
|
| 79 |
+
sequence_length,
|
| 80 |
+
b,
|
| 81 |
+
decode_length,
|
| 82 |
+
&mut client,
|
| 83 |
+
)
|
| 84 |
+
.await?;
|
| 85 |
+
let _ = decode(decode_batch, &mut client).await?;
|
| 86 |
+
// Send warmup message
|
| 87 |
+
run_sender.send(Ok(Message::Warmup)).await.unwrap_or(());
|
| 88 |
+
}
|
| 89 |
+
|
| 90 |
+
for _ in 0..n_runs {
|
| 91 |
+
let (prefill, decode_batch) = prefill(
|
| 92 |
+
sequence.clone(),
|
| 93 |
+
sequence_length,
|
| 94 |
+
b,
|
| 95 |
+
decode_length,
|
| 96 |
+
&mut client,
|
| 97 |
+
)
|
| 98 |
+
.await?;
|
| 99 |
+
// Send prefill message
|
| 100 |
+
run_sender
|
| 101 |
+
.send(Ok(Message::Prefill(prefill)))
|
| 102 |
+
.await
|
| 103 |
+
.unwrap_or(());
|
| 104 |
+
|
| 105 |
+
let decode = decode(decode_batch, &mut client).await?;
|
| 106 |
+
|
| 107 |
+
// Send decode message
|
| 108 |
+
run_sender
|
| 109 |
+
.send(Ok(Message::Decode(decode)))
|
| 110 |
+
.await
|
| 111 |
+
.unwrap_or(());
|
| 112 |
+
|
| 113 |
+
// Send run ended message
|
| 114 |
+
run_sender.send(Ok(Message::EndRun)).await.unwrap_or(());
|
| 115 |
+
}
|
| 116 |
+
// Batch ended
|
| 117 |
+
run_sender.send(Ok(Message::EndBatch)).await.unwrap_or(());
|
| 118 |
+
}
|
| 119 |
+
Ok(())
|
| 120 |
+
}
|
| 121 |
+
|
| 122 |
+
// Run a prefill step
|
| 123 |
+
async fn prefill(
|
| 124 |
+
sequence: String,
|
| 125 |
+
sequence_length: u32,
|
| 126 |
+
batch_size: u32,
|
| 127 |
+
decode_length: u32,
|
| 128 |
+
client: &mut ShardedClient,
|
| 129 |
+
) -> Result<(Prefill, Batch), ClientError> {
|
| 130 |
+
// Create requests
|
| 131 |
+
let requests = (0..batch_size)
|
| 132 |
+
.map(|id| Request {
|
| 133 |
+
id: id.into(),
|
| 134 |
+
inputs: sequence.clone(),
|
| 135 |
+
truncate: sequence_length,
|
| 136 |
+
parameters: Some(NextTokenChooserParameters {
|
| 137 |
+
temperature: 1.0,
|
| 138 |
+
top_k: 0,
|
| 139 |
+
top_p: 1.0,
|
| 140 |
+
typical_p: 1.0,
|
| 141 |
+
do_sample: false,
|
| 142 |
+
seed: 0,
|
| 143 |
+
repetition_penalty: 1.0,
|
| 144 |
+
watermark: false,
|
| 145 |
+
}),
|
| 146 |
+
stopping_parameters: Some(StoppingCriteriaParameters {
|
| 147 |
+
max_new_tokens: decode_length,
|
| 148 |
+
stop_sequences: vec![],
|
| 149 |
+
ignore_eos_token: true, // Will not stop even if a eos token is generated
|
| 150 |
+
}),
|
| 151 |
+
})
|
| 152 |
+
.collect();
|
| 153 |
+
|
| 154 |
+
let batch = Batch {
|
| 155 |
+
id: 0,
|
| 156 |
+
requests,
|
| 157 |
+
size: batch_size,
|
| 158 |
+
max_tokens: batch_size * (sequence_length + decode_length),
|
| 159 |
+
};
|
| 160 |
+
|
| 161 |
+
// Run prefill
|
| 162 |
+
let start_time = Instant::now();
|
| 163 |
+
let (_, decode_batch) = client.prefill(batch.clone()).await?;
|
| 164 |
+
|
| 165 |
+
// Get latency
|
| 166 |
+
let latency = start_time.elapsed();
|
| 167 |
+
|
| 168 |
+
// Compute throughput from latency and batch size
|
| 169 |
+
let throughput = batch_size as f64 / latency.as_secs_f64();
|
| 170 |
+
|
| 171 |
+
// Decode batch cannot be empty
|
| 172 |
+
let decode_batch = decode_batch.expect("decode_batch is None. This is a bug.");
|
| 173 |
+
|
| 174 |
+
let step = Prefill {
|
| 175 |
+
latency,
|
| 176 |
+
throughput,
|
| 177 |
+
};
|
| 178 |
+
|
| 179 |
+
Ok((step, decode_batch))
|
| 180 |
+
}
|
| 181 |
+
|
| 182 |
+
/// Run a full decode
|
| 183 |
+
async fn decode(batch: Batch, client: &mut ShardedClient) -> Result<Decode, ClientError> {
|
| 184 |
+
let mut decode_length = 0;
|
| 185 |
+
let batch_size = batch.size;
|
| 186 |
+
|
| 187 |
+
let start_time = Instant::now();
|
| 188 |
+
|
| 189 |
+
// Full decode over decode length
|
| 190 |
+
let mut next_batch = Some(batch);
|
| 191 |
+
while let Some(batch) = next_batch {
|
| 192 |
+
let result = client.decode(vec![batch]).await?;
|
| 193 |
+
next_batch = result.1;
|
| 194 |
+
decode_length += 1;
|
| 195 |
+
}
|
| 196 |
+
|
| 197 |
+
// Get latency
|
| 198 |
+
let latency = start_time.elapsed();
|
| 199 |
+
let token_latency = latency / decode_length;
|
| 200 |
+
|
| 201 |
+
// Compute throughput from latency, batch size and decode length
|
| 202 |
+
let throughput = (batch_size * decode_length) as f64 / latency.as_secs_f64();
|
| 203 |
+
|
| 204 |
+
let step = Decode {
|
| 205 |
+
latency,
|
| 206 |
+
token_latency,
|
| 207 |
+
throughput,
|
| 208 |
+
};
|
| 209 |
+
Ok(step)
|
| 210 |
+
}
|
| 211 |
+
|
| 212 |
+
/// Create a dummy sequence of the correct length
|
| 213 |
+
fn create_sequence(sequence_length: u32, tokenizer: Tokenizer) -> String {
|
| 214 |
+
let lorem_ipsum_length = tokenizer.encode(LOREM_IPSUM, true).unwrap().len();
|
| 215 |
+
// Repeat lorem ipsum to cover sequence length
|
| 216 |
+
let string_sequence =
|
| 217 |
+
LOREM_IPSUM.repeat((0..sequence_length).step_by(lorem_ipsum_length).len());
|
| 218 |
+
// Encode sequence
|
| 219 |
+
let mut encoding = tokenizer.encode(string_sequence, true).unwrap();
|
| 220 |
+
// Truncate to sequence_length
|
| 221 |
+
encoding.truncate(sequence_length as usize, 0, TruncationDirection::Left);
|
| 222 |
+
// Decode
|
| 223 |
+
tokenizer
|
| 224 |
+
.decode(Vec::from(encoding.get_ids()), false)
|
| 225 |
+
.unwrap()
|
| 226 |
+
}
|
benchmark/src/lib.rs
ADDED
|
@@ -0,0 +1,110 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
mod app;
|
| 2 |
+
mod event;
|
| 3 |
+
mod generation;
|
| 4 |
+
mod utils;
|
| 5 |
+
|
| 6 |
+
use crate::app::App;
|
| 7 |
+
use crate::event::Event;
|
| 8 |
+
use crossterm::ExecutableCommand;
|
| 9 |
+
use std::io;
|
| 10 |
+
use text_generation_client::ShardedClient;
|
| 11 |
+
use tokenizers::Tokenizer;
|
| 12 |
+
use tokio::sync::{broadcast, mpsc};
|
| 13 |
+
use tui::backend::CrosstermBackend;
|
| 14 |
+
use tui::Terminal;
|
| 15 |
+
|
| 16 |
+
/// Run benchmarking app
|
| 17 |
+
#[allow(clippy::too_many_arguments)]
|
| 18 |
+
pub async fn run(
|
| 19 |
+
tokenizer_name: String,
|
| 20 |
+
tokenizer: Tokenizer,
|
| 21 |
+
batch_size: Vec<u32>,
|
| 22 |
+
sequence_length: u32,
|
| 23 |
+
decode_length: u32,
|
| 24 |
+
n_runs: usize,
|
| 25 |
+
warmups: usize,
|
| 26 |
+
client: ShardedClient,
|
| 27 |
+
) -> Result<(), crossterm::ErrorKind> {
|
| 28 |
+
// Initialize terminal properties
|
| 29 |
+
crossterm::terminal::enable_raw_mode()?;
|
| 30 |
+
io::stdout().execute(crossterm::terminal::EnterAlternateScreen)?;
|
| 31 |
+
io::stdout().execute(crossterm::cursor::Hide)?;
|
| 32 |
+
|
| 33 |
+
// Initialize terminal
|
| 34 |
+
let mut terminal = {
|
| 35 |
+
let backend = CrosstermBackend::new(io::stdout());
|
| 36 |
+
Terminal::new(backend)?
|
| 37 |
+
};
|
| 38 |
+
|
| 39 |
+
// Create message channel between generation_task and app
|
| 40 |
+
let (run_sender, run_receiver) = mpsc::channel(8);
|
| 41 |
+
// Crossterm event channel
|
| 42 |
+
let (event_sender, mut event_receiver) = mpsc::channel(8);
|
| 43 |
+
// Shutdown channel to terminate tasks
|
| 44 |
+
let (shutdown_sender, _) = broadcast::channel(1);
|
| 45 |
+
// Channel to check if tasks terminated
|
| 46 |
+
let (shutdown_guard_sender, mut shutdown_guard_receiver) = mpsc::channel(1);
|
| 47 |
+
|
| 48 |
+
// Create generation task
|
| 49 |
+
tokio::spawn(generation::generation_task(
|
| 50 |
+
tokenizer,
|
| 51 |
+
batch_size.clone(),
|
| 52 |
+
sequence_length,
|
| 53 |
+
decode_length,
|
| 54 |
+
n_runs,
|
| 55 |
+
warmups,
|
| 56 |
+
client,
|
| 57 |
+
run_sender,
|
| 58 |
+
shutdown_sender.subscribe(),
|
| 59 |
+
shutdown_guard_sender.clone(),
|
| 60 |
+
));
|
| 61 |
+
|
| 62 |
+
// Create event task
|
| 63 |
+
tokio::spawn(event::terminal_event_task(
|
| 64 |
+
250,
|
| 65 |
+
event_sender,
|
| 66 |
+
shutdown_sender.subscribe(),
|
| 67 |
+
shutdown_guard_sender.clone(),
|
| 68 |
+
));
|
| 69 |
+
|
| 70 |
+
// Drop our end of shutdown sender
|
| 71 |
+
drop(shutdown_guard_sender);
|
| 72 |
+
|
| 73 |
+
// Create App
|
| 74 |
+
let mut app = App::new(
|
| 75 |
+
run_receiver,
|
| 76 |
+
tokenizer_name,
|
| 77 |
+
sequence_length,
|
| 78 |
+
decode_length,
|
| 79 |
+
n_runs,
|
| 80 |
+
batch_size,
|
| 81 |
+
);
|
| 82 |
+
|
| 83 |
+
while app.running {
|
| 84 |
+
// Draw frame
|
| 85 |
+
terminal.draw(|frame| app.render(frame))?;
|
| 86 |
+
|
| 87 |
+
// Await a new event from event handling task
|
| 88 |
+
match event_receiver.recv().await {
|
| 89 |
+
None => break,
|
| 90 |
+
// Update app state
|
| 91 |
+
Some(event) => match event {
|
| 92 |
+
Event::Tick => app.tick(),
|
| 93 |
+
Event::Key(key_event) => app.handle_key_event(key_event),
|
| 94 |
+
_ => {}
|
| 95 |
+
},
|
| 96 |
+
}
|
| 97 |
+
}
|
| 98 |
+
|
| 99 |
+
// Ask tasks to shutdown
|
| 100 |
+
let _ = shutdown_sender.send(());
|
| 101 |
+
// Wait for tasks to shutdown
|
| 102 |
+
let _ = shutdown_guard_receiver.recv().await;
|
| 103 |
+
|
| 104 |
+
// Revert terminal to original view
|
| 105 |
+
io::stdout().execute(crossterm::terminal::LeaveAlternateScreen)?;
|
| 106 |
+
crossterm::terminal::disable_raw_mode()?;
|
| 107 |
+
io::stdout().execute(crossterm::cursor::Show)?;
|
| 108 |
+
|
| 109 |
+
Ok(())
|
| 110 |
+
}
|
benchmark/src/main.rs
ADDED
|
@@ -0,0 +1,131 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
/// Text Generation Inference benchmarking tool
|
| 2 |
+
///
|
| 3 |
+
/// Inspired by the great Oha app: https://github.com/hatoo/oha
|
| 4 |
+
/// and: https://github.com/orhun/rust-tui-template
|
| 5 |
+
use clap::Parser;
|
| 6 |
+
use std::path::Path;
|
| 7 |
+
use text_generation_client::ShardedClient;
|
| 8 |
+
use tokenizers::{FromPretrainedParameters, Tokenizer};
|
| 9 |
+
use tracing_subscriber::layer::SubscriberExt;
|
| 10 |
+
use tracing_subscriber::util::SubscriberInitExt;
|
| 11 |
+
use tracing_subscriber::EnvFilter;
|
| 12 |
+
|
| 13 |
+
/// App Configuration
|
| 14 |
+
#[derive(Parser, Debug)]
|
| 15 |
+
#[clap(author, version, about, long_about = None)]
|
| 16 |
+
struct Args {
|
| 17 |
+
#[clap(short, long, env)]
|
| 18 |
+
tokenizer_name: String,
|
| 19 |
+
#[clap(default_value = "main", long, env)]
|
| 20 |
+
revision: String,
|
| 21 |
+
#[clap(short, long)]
|
| 22 |
+
batch_size: Option<Vec<u32>>,
|
| 23 |
+
#[clap(default_value = "10", short, long, env)]
|
| 24 |
+
sequence_length: u32,
|
| 25 |
+
#[clap(default_value = "8", short, long, env)]
|
| 26 |
+
decode_length: u32,
|
| 27 |
+
#[clap(default_value = "10", short, long, env)]
|
| 28 |
+
runs: usize,
|
| 29 |
+
#[clap(default_value = "1", short, long, env)]
|
| 30 |
+
warmups: usize,
|
| 31 |
+
#[clap(default_value = "/tmp/text-generation-server-0", short, long, env)]
|
| 32 |
+
master_shard_uds_path: String,
|
| 33 |
+
}
|
| 34 |
+
|
| 35 |
+
fn main() -> Result<(), Box<dyn std::error::Error>> {
|
| 36 |
+
// Get args
|
| 37 |
+
let args = Args::parse();
|
| 38 |
+
// Pattern match configuration
|
| 39 |
+
let Args {
|
| 40 |
+
tokenizer_name,
|
| 41 |
+
revision,
|
| 42 |
+
batch_size,
|
| 43 |
+
sequence_length,
|
| 44 |
+
decode_length,
|
| 45 |
+
runs,
|
| 46 |
+
warmups,
|
| 47 |
+
master_shard_uds_path,
|
| 48 |
+
} = args;
|
| 49 |
+
|
| 50 |
+
let batch_size = batch_size.unwrap_or(vec![1, 2, 4, 8, 16, 32]);
|
| 51 |
+
|
| 52 |
+
init_logging();
|
| 53 |
+
|
| 54 |
+
// Tokenizer instance
|
| 55 |
+
// This will only be used to validate payloads
|
| 56 |
+
tracing::info!("Loading tokenizer");
|
| 57 |
+
let local_path = Path::new(&tokenizer_name);
|
| 58 |
+
let tokenizer =
|
| 59 |
+
if local_path.exists() && local_path.is_dir() && local_path.join("tokenizer.json").exists()
|
| 60 |
+
{
|
| 61 |
+
// Load local tokenizer
|
| 62 |
+
tracing::info!("Found local tokenizer");
|
| 63 |
+
Tokenizer::from_file(local_path.join("tokenizer.json")).unwrap()
|
| 64 |
+
} else {
|
| 65 |
+
tracing::info!("Downloading tokenizer");
|
| 66 |
+
|
| 67 |
+
// Parse Huggingface hub token
|
| 68 |
+
let auth_token = std::env::var("HUGGING_FACE_HUB_TOKEN").ok();
|
| 69 |
+
|
| 70 |
+
// Download and instantiate tokenizer
|
| 71 |
+
// We need to download it outside of the Tokio runtime
|
| 72 |
+
let params = FromPretrainedParameters {
|
| 73 |
+
revision,
|
| 74 |
+
auth_token,
|
| 75 |
+
..Default::default()
|
| 76 |
+
};
|
| 77 |
+
Tokenizer::from_pretrained(tokenizer_name.clone(), Some(params)).unwrap()
|
| 78 |
+
};
|
| 79 |
+
tracing::info!("Tokenizer loaded");
|
| 80 |
+
|
| 81 |
+
// Launch Tokio runtime
|
| 82 |
+
tokio::runtime::Builder::new_multi_thread()
|
| 83 |
+
.enable_all()
|
| 84 |
+
.build()
|
| 85 |
+
.unwrap()
|
| 86 |
+
.block_on(async {
|
| 87 |
+
// Instantiate sharded client from the master unix socket
|
| 88 |
+
tracing::info!("Connect to model server");
|
| 89 |
+
let mut sharded_client = ShardedClient::connect_uds(master_shard_uds_path)
|
| 90 |
+
.await
|
| 91 |
+
.expect("Could not connect to server");
|
| 92 |
+
// Clear the cache; useful if the webserver rebooted
|
| 93 |
+
sharded_client
|
| 94 |
+
.clear_cache(None)
|
| 95 |
+
.await
|
| 96 |
+
.expect("Unable to clear cache");
|
| 97 |
+
tracing::info!("Connected");
|
| 98 |
+
|
| 99 |
+
// Run app
|
| 100 |
+
text_generation_benchmark::run(
|
| 101 |
+
tokenizer_name,
|
| 102 |
+
tokenizer,
|
| 103 |
+
batch_size,
|
| 104 |
+
sequence_length,
|
| 105 |
+
decode_length,
|
| 106 |
+
runs,
|
| 107 |
+
warmups,
|
| 108 |
+
sharded_client,
|
| 109 |
+
)
|
| 110 |
+
.await
|
| 111 |
+
.unwrap();
|
| 112 |
+
});
|
| 113 |
+
Ok(())
|
| 114 |
+
}
|
| 115 |
+
|
| 116 |
+
/// Init logging using LOG_LEVEL
|
| 117 |
+
fn init_logging() {
|
| 118 |
+
// STDOUT/STDERR layer
|
| 119 |
+
let fmt_layer = tracing_subscriber::fmt::layer()
|
| 120 |
+
.with_file(true)
|
| 121 |
+
.with_line_number(true);
|
| 122 |
+
|
| 123 |
+
// Filter events with LOG_LEVEL
|
| 124 |
+
let env_filter =
|
| 125 |
+
EnvFilter::try_from_env("LOG_LEVEL").unwrap_or_else(|_| EnvFilter::new("info"));
|
| 126 |
+
|
| 127 |
+
tracing_subscriber::registry()
|
| 128 |
+
.with(env_filter)
|
| 129 |
+
.with(fmt_layer)
|
| 130 |
+
.init();
|
| 131 |
+
}
|
benchmark/src/utils.rs
ADDED
|
@@ -0,0 +1,43 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
/// MIT License
|
| 2 |
+
//
|
| 3 |
+
// Copyright (c) 2020 hatoo
|
| 4 |
+
//
|
| 5 |
+
// Permission is hereby granted, free of charge, to any person obtaining a copy
|
| 6 |
+
// of this software and associated documentation files (the "Software"), to deal
|
| 7 |
+
// in the Software without restriction, including without limitation the rights
|
| 8 |
+
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
| 9 |
+
// copies of the Software, and to permit persons to whom the Software is
|
| 10 |
+
// furnished to do so, subject to the following conditions:
|
| 11 |
+
//
|
| 12 |
+
// The above copyright notice and this permission notice shall be included in all
|
| 13 |
+
// copies or substantial portions of the Software.
|
| 14 |
+
use std::collections::BTreeMap;
|
| 15 |
+
|
| 16 |
+
pub(crate) fn histogram(values: &[f64], bins: usize) -> Vec<(f64, usize)> {
|
| 17 |
+
assert!(bins >= 2);
|
| 18 |
+
let mut bucket: Vec<usize> = vec![0; bins];
|
| 19 |
+
let min = values.iter().collect::<average::Min>().min();
|
| 20 |
+
let max = values.iter().collect::<average::Max>().max();
|
| 21 |
+
let step = (max - min) / (bins - 1) as f64;
|
| 22 |
+
|
| 23 |
+
for &v in values {
|
| 24 |
+
let i = std::cmp::min(((v - min) / step).ceil() as usize, bins - 1);
|
| 25 |
+
bucket[i] += 1;
|
| 26 |
+
}
|
| 27 |
+
|
| 28 |
+
bucket
|
| 29 |
+
.into_iter()
|
| 30 |
+
.enumerate()
|
| 31 |
+
.map(|(i, v)| (min + step * i as f64, v))
|
| 32 |
+
.collect()
|
| 33 |
+
}
|
| 34 |
+
|
| 35 |
+
pub(crate) fn percentiles(values: &[f64], pecents: &[i32]) -> BTreeMap<String, f64> {
|
| 36 |
+
pecents
|
| 37 |
+
.iter()
|
| 38 |
+
.map(|&p| {
|
| 39 |
+
let i = (f64::from(p) / 100.0 * values.len() as f64) as usize;
|
| 40 |
+
(format!("p{p}"), *values.get(i).unwrap_or(&std::f64::NAN))
|
| 41 |
+
})
|
| 42 |
+
.collect()
|
| 43 |
+
}
|
clients/python/Makefile
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
unit-tests:
|
| 2 |
+
python -m pytest --cov=text_generation tests
|
| 3 |
+
|
| 4 |
+
install:
|
| 5 |
+
pip install pip --upgrade
|
| 6 |
+
pip install -e .
|
clients/python/poetry.lock
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
clients/python/pyproject.toml
ADDED
|
@@ -0,0 +1,29 @@
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| 1 |
+
[tool.poetry]
|
| 2 |
+
name = "text-generation"
|
| 3 |
+
version = "0.5.1"
|
| 4 |
+
description = "Hugging Face Text Generation Python Client"
|
| 5 |
+
license = "Apache-2.0"
|
| 6 |
+
authors = ["Olivier Dehaene <olivier@huggingface.co>"]
|
| 7 |
+
maintainers = ["Olivier Dehaene <olivier@huggingface.co>"]
|
| 8 |
+
readme = "README.md"
|
| 9 |
+
homepage = "https://github.com/huggingface/text-generation-inference"
|
| 10 |
+
repository = "https://github.com/huggingface/text-generation-inference"
|
| 11 |
+
|
| 12 |
+
|
| 13 |
+
[tool.poetry.dependencies]
|
| 14 |
+
python = "^3.7"
|
| 15 |
+
pydantic = "^1.10"
|
| 16 |
+
aiohttp = "^3.8"
|
| 17 |
+
huggingface-hub = ">= 0.12, < 1.0"
|
| 18 |
+
|
| 19 |
+
[tool.poetry.dev-dependencies]
|
| 20 |
+
pytest = "^6.2.5"
|
| 21 |
+
pytest-asyncio = "^0.17.2"
|
| 22 |
+
pytest-cov = "^3.0.0"
|
| 23 |
+
|
| 24 |
+
[tool.pytest.ini_options]
|
| 25 |
+
asyncio_mode = "auto"
|
| 26 |
+
|
| 27 |
+
[build-system]
|
| 28 |
+
requires = ["poetry-core>=1.0.0"]
|
| 29 |
+
build-backend = "poetry.core.masonry.api"
|
clients/python/tests/conftest.py
ADDED
|
@@ -0,0 +1,51 @@
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|
| 1 |
+
import pytest
|
| 2 |
+
|
| 3 |
+
from text_generation import __version__
|
| 4 |
+
from huggingface_hub.utils import build_hf_headers
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
@pytest.fixture
|
| 8 |
+
def flan_t5_xxl():
|
| 9 |
+
return "google/flan-t5-xxl"
|
| 10 |
+
|
| 11 |
+
|
| 12 |
+
@pytest.fixture
|
| 13 |
+
def fake_model():
|
| 14 |
+
return "fake/model"
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
@pytest.fixture
|
| 18 |
+
def unsupported_model():
|
| 19 |
+
return "gpt2"
|
| 20 |
+
|
| 21 |
+
|
| 22 |
+
@pytest.fixture
|
| 23 |
+
def base_url():
|
| 24 |
+
return "https://api-inference.huggingface.co/models"
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
@pytest.fixture
|
| 28 |
+
def bloom_url(base_url, bloom_model):
|
| 29 |
+
return f"{base_url}/{bloom_model}"
|
| 30 |
+
|
| 31 |
+
|
| 32 |
+
@pytest.fixture
|
| 33 |
+
def flan_t5_xxl_url(base_url, flan_t5_xxl):
|
| 34 |
+
return f"{base_url}/{flan_t5_xxl}"
|
| 35 |
+
|
| 36 |
+
|
| 37 |
+
@pytest.fixture
|
| 38 |
+
def fake_url(base_url, fake_model):
|
| 39 |
+
return f"{base_url}/{fake_model}"
|
| 40 |
+
|
| 41 |
+
|
| 42 |
+
@pytest.fixture
|
| 43 |
+
def unsupported_url(base_url, unsupported_model):
|
| 44 |
+
return f"{base_url}/{unsupported_model}"
|
| 45 |
+
|
| 46 |
+
|
| 47 |
+
@pytest.fixture(scope="session")
|
| 48 |
+
def hf_headers():
|
| 49 |
+
return build_hf_headers(
|
| 50 |
+
library_name="text-generation-tests", library_version=__version__
|
| 51 |
+
)
|
clients/python/tests/test_client.py
ADDED
|
@@ -0,0 +1,146 @@
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|
|
| 1 |
+
import pytest
|
| 2 |
+
|
| 3 |
+
from text_generation import Client, AsyncClient
|
| 4 |
+
from text_generation.errors import NotFoundError, ValidationError
|
| 5 |
+
from text_generation.types import FinishReason, PrefillToken, Token
|
| 6 |
+
|
| 7 |
+
|
| 8 |
+
def test_generate(flan_t5_xxl_url, hf_headers):
|
| 9 |
+
client = Client(flan_t5_xxl_url, hf_headers)
|
| 10 |
+
response = client.generate("test", max_new_tokens=1)
|
| 11 |
+
|
| 12 |
+
assert response.generated_text == ""
|
| 13 |
+
assert response.details.finish_reason == FinishReason.Length
|
| 14 |
+
assert response.details.generated_tokens == 1
|
| 15 |
+
assert response.details.seed is None
|
| 16 |
+
assert len(response.details.prefill) == 1
|
| 17 |
+
assert response.details.prefill[0] == PrefillToken(id=0, text="<pad>", logprob=None)
|
| 18 |
+
assert len(response.details.tokens) == 1
|
| 19 |
+
assert response.details.tokens[0] == Token(
|
| 20 |
+
id=3, text="", logprob=-1.984375, special=False
|
| 21 |
+
)
|
| 22 |
+
|
| 23 |
+
|
| 24 |
+
def test_generate_best_of(flan_t5_xxl_url, hf_headers):
|
| 25 |
+
client = Client(flan_t5_xxl_url, hf_headers)
|
| 26 |
+
response = client.generate("test", max_new_tokens=1, best_of=2, do_sample=True)
|
| 27 |
+
|
| 28 |
+
assert response.details.seed is not None
|
| 29 |
+
assert response.details.best_of_sequences is not None
|
| 30 |
+
assert len(response.details.best_of_sequences) == 1
|
| 31 |
+
assert response.details.best_of_sequences[0].seed is not None
|
| 32 |
+
|
| 33 |
+
|
| 34 |
+
def test_generate_not_found(fake_url, hf_headers):
|
| 35 |
+
client = Client(fake_url, hf_headers)
|
| 36 |
+
with pytest.raises(NotFoundError):
|
| 37 |
+
client.generate("test")
|
| 38 |
+
|
| 39 |
+
|
| 40 |
+
def test_generate_validation_error(flan_t5_xxl_url, hf_headers):
|
| 41 |
+
client = Client(flan_t5_xxl_url, hf_headers)
|
| 42 |
+
with pytest.raises(ValidationError):
|
| 43 |
+
client.generate("test", max_new_tokens=10_000)
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
def test_generate_stream(flan_t5_xxl_url, hf_headers):
|
| 47 |
+
client = Client(flan_t5_xxl_url, hf_headers)
|
| 48 |
+
responses = [
|
| 49 |
+
response for response in client.generate_stream("test", max_new_tokens=1)
|
| 50 |
+
]
|
| 51 |
+
|
| 52 |
+
assert len(responses) == 1
|
| 53 |
+
response = responses[0]
|
| 54 |
+
|
| 55 |
+
assert response.generated_text == ""
|
| 56 |
+
assert response.details.finish_reason == FinishReason.Length
|
| 57 |
+
assert response.details.generated_tokens == 1
|
| 58 |
+
assert response.details.seed is None
|
| 59 |
+
|
| 60 |
+
|
| 61 |
+
def test_generate_stream_not_found(fake_url, hf_headers):
|
| 62 |
+
client = Client(fake_url, hf_headers)
|
| 63 |
+
with pytest.raises(NotFoundError):
|
| 64 |
+
list(client.generate_stream("test"))
|
| 65 |
+
|
| 66 |
+
|
| 67 |
+
def test_generate_stream_validation_error(flan_t5_xxl_url, hf_headers):
|
| 68 |
+
client = Client(flan_t5_xxl_url, hf_headers)
|
| 69 |
+
with pytest.raises(ValidationError):
|
| 70 |
+
list(client.generate_stream("test", max_new_tokens=10_000))
|
| 71 |
+
|
| 72 |
+
|
| 73 |
+
@pytest.mark.asyncio
|
| 74 |
+
async def test_generate_async(flan_t5_xxl_url, hf_headers):
|
| 75 |
+
client = AsyncClient(flan_t5_xxl_url, hf_headers)
|
| 76 |
+
response = await client.generate("test", max_new_tokens=1)
|
| 77 |
+
|
| 78 |
+
assert response.generated_text == ""
|
| 79 |
+
assert response.details.finish_reason == FinishReason.Length
|
| 80 |
+
assert response.details.generated_tokens == 1
|
| 81 |
+
assert response.details.seed is None
|
| 82 |
+
assert len(response.details.prefill) == 1
|
| 83 |
+
assert response.details.prefill[0] == PrefillToken(id=0, text="<pad>", logprob=None)
|
| 84 |
+
assert len(response.details.tokens) == 1
|
| 85 |
+
assert response.details.tokens[0] == Token(
|
| 86 |
+
id=3, text="", logprob=-1.984375, special=False
|
| 87 |
+
)
|
| 88 |
+
|
| 89 |
+
|
| 90 |
+
@pytest.mark.asyncio
|
| 91 |
+
async def test_generate_async_best_of(flan_t5_xxl_url, hf_headers):
|
| 92 |
+
client = AsyncClient(flan_t5_xxl_url, hf_headers)
|
| 93 |
+
response = await client.generate(
|
| 94 |
+
"test", max_new_tokens=1, best_of=2, do_sample=True
|
| 95 |
+
)
|
| 96 |
+
|
| 97 |
+
assert response.details.seed is not None
|
| 98 |
+
assert response.details.best_of_sequences is not None
|
| 99 |
+
assert len(response.details.best_of_sequences) == 1
|
| 100 |
+
assert response.details.best_of_sequences[0].seed is not None
|
| 101 |
+
|
| 102 |
+
|
| 103 |
+
@pytest.mark.asyncio
|
| 104 |
+
async def test_generate_async_not_found(fake_url, hf_headers):
|
| 105 |
+
client = AsyncClient(fake_url, hf_headers)
|
| 106 |
+
with pytest.raises(NotFoundError):
|
| 107 |
+
await client.generate("test")
|
| 108 |
+
|
| 109 |
+
|
| 110 |
+
@pytest.mark.asyncio
|
| 111 |
+
async def test_generate_async_validation_error(flan_t5_xxl_url, hf_headers):
|
| 112 |
+
client = AsyncClient(flan_t5_xxl_url, hf_headers)
|
| 113 |
+
with pytest.raises(ValidationError):
|
| 114 |
+
await client.generate("test", max_new_tokens=10_000)
|
| 115 |
+
|
| 116 |
+
|
| 117 |
+
@pytest.mark.asyncio
|
| 118 |
+
async def test_generate_stream_async(flan_t5_xxl_url, hf_headers):
|
| 119 |
+
client = AsyncClient(flan_t5_xxl_url, hf_headers)
|
| 120 |
+
responses = [
|
| 121 |
+
response async for response in client.generate_stream("test", max_new_tokens=1)
|
| 122 |
+
]
|
| 123 |
+
|
| 124 |
+
assert len(responses) == 1
|
| 125 |
+
response = responses[0]
|
| 126 |
+
|
| 127 |
+
assert response.generated_text == ""
|
| 128 |
+
assert response.details.finish_reason == FinishReason.Length
|
| 129 |
+
assert response.details.generated_tokens == 1
|
| 130 |
+
assert response.details.seed is None
|
| 131 |
+
|
| 132 |
+
|
| 133 |
+
@pytest.mark.asyncio
|
| 134 |
+
async def test_generate_stream_async_not_found(fake_url, hf_headers):
|
| 135 |
+
client = AsyncClient(fake_url, hf_headers)
|
| 136 |
+
with pytest.raises(NotFoundError):
|
| 137 |
+
async for _ in client.generate_stream("test"):
|
| 138 |
+
pass
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
@pytest.mark.asyncio
|
| 142 |
+
async def test_generate_stream_async_validation_error(flan_t5_xxl_url, hf_headers):
|
| 143 |
+
client = AsyncClient(flan_t5_xxl_url, hf_headers)
|
| 144 |
+
with pytest.raises(ValidationError):
|
| 145 |
+
async for _ in client.generate_stream("test", max_new_tokens=10_000):
|
| 146 |
+
pass
|
clients/python/tests/test_errors.py
ADDED
|
@@ -0,0 +1,64 @@
|
|
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|
|
|
|
| 1 |
+
from text_generation.errors import (
|
| 2 |
+
parse_error,
|
| 3 |
+
GenerationError,
|
| 4 |
+
IncompleteGenerationError,
|
| 5 |
+
OverloadedError,
|
| 6 |
+
ValidationError,
|
| 7 |
+
BadRequestError,
|
| 8 |
+
ShardNotReadyError,
|
| 9 |
+
ShardTimeoutError,
|
| 10 |
+
NotFoundError,
|
| 11 |
+
RateLimitExceededError,
|
| 12 |
+
UnknownError,
|
| 13 |
+
)
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
def test_generation_error():
|
| 17 |
+
payload = {"error_type": "generation", "error": "test"}
|
| 18 |
+
assert isinstance(parse_error(400, payload), GenerationError)
|
| 19 |
+
|
| 20 |
+
|
| 21 |
+
def test_incomplete_generation_error():
|
| 22 |
+
payload = {"error_type": "incomplete_generation", "error": "test"}
|
| 23 |
+
assert isinstance(parse_error(400, payload), IncompleteGenerationError)
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
def test_overloaded_error():
|
| 27 |
+
payload = {"error_type": "overloaded", "error": "test"}
|
| 28 |
+
assert isinstance(parse_error(400, payload), OverloadedError)
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
def test_validation_error():
|
| 32 |
+
payload = {"error_type": "validation", "error": "test"}
|
| 33 |
+
assert isinstance(parse_error(400, payload), ValidationError)
|
| 34 |
+
|
| 35 |
+
|
| 36 |
+
def test_bad_request_error():
|
| 37 |
+
payload = {"error": "test"}
|
| 38 |
+
assert isinstance(parse_error(400, payload), BadRequestError)
|
| 39 |
+
|
| 40 |
+
|
| 41 |
+
def test_shard_not_ready_error():
|
| 42 |
+
payload = {"error": "test"}
|
| 43 |
+
assert isinstance(parse_error(403, payload), ShardNotReadyError)
|
| 44 |
+
assert isinstance(parse_error(424, payload), ShardNotReadyError)
|
| 45 |
+
|
| 46 |
+
|
| 47 |
+
def test_shard_timeout_error():
|
| 48 |
+
payload = {"error": "test"}
|
| 49 |
+
assert isinstance(parse_error(504, payload), ShardTimeoutError)
|
| 50 |
+
|
| 51 |
+
|
| 52 |
+
def test_not_found_error():
|
| 53 |
+
payload = {"error": "test"}
|
| 54 |
+
assert isinstance(parse_error(404, payload), NotFoundError)
|
| 55 |
+
|
| 56 |
+
|
| 57 |
+
def test_rate_limit_exceeded_error():
|
| 58 |
+
payload = {"error": "test"}
|
| 59 |
+
assert isinstance(parse_error(429, payload), RateLimitExceededError)
|
| 60 |
+
|
| 61 |
+
|
| 62 |
+
def test_unknown_error():
|
| 63 |
+
payload = {"error": "test"}
|
| 64 |
+
assert isinstance(parse_error(500, payload), UnknownError)
|
clients/python/tests/test_inference_api.py
ADDED
|
@@ -0,0 +1,42 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import pytest
|
| 2 |
+
|
| 3 |
+
from text_generation import (
|
| 4 |
+
InferenceAPIClient,
|
| 5 |
+
InferenceAPIAsyncClient,
|
| 6 |
+
Client,
|
| 7 |
+
AsyncClient,
|
| 8 |
+
)
|
| 9 |
+
from text_generation.errors import NotSupportedError, NotFoundError
|
| 10 |
+
from text_generation.inference_api import check_model_support, deployed_models
|
| 11 |
+
|
| 12 |
+
|
| 13 |
+
def test_check_model_support(flan_t5_xxl, unsupported_model, fake_model):
|
| 14 |
+
assert check_model_support(flan_t5_xxl)
|
| 15 |
+
assert not check_model_support(unsupported_model)
|
| 16 |
+
|
| 17 |
+
with pytest.raises(NotFoundError):
|
| 18 |
+
check_model_support(fake_model)
|
| 19 |
+
|
| 20 |
+
|
| 21 |
+
def test_deployed_models():
|
| 22 |
+
deployed_models()
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
def test_client(flan_t5_xxl):
|
| 26 |
+
client = InferenceAPIClient(flan_t5_xxl)
|
| 27 |
+
assert isinstance(client, Client)
|
| 28 |
+
|
| 29 |
+
|
| 30 |
+
def test_client_unsupported_model(unsupported_model):
|
| 31 |
+
with pytest.raises(NotSupportedError):
|
| 32 |
+
InferenceAPIClient(unsupported_model)
|
| 33 |
+
|
| 34 |
+
|
| 35 |
+
def test_async_client(flan_t5_xxl):
|
| 36 |
+
client = InferenceAPIAsyncClient(flan_t5_xxl)
|
| 37 |
+
assert isinstance(client, AsyncClient)
|
| 38 |
+
|
| 39 |
+
|
| 40 |
+
def test_async_client_unsupported_model(unsupported_model):
|
| 41 |
+
with pytest.raises(NotSupportedError):
|
| 42 |
+
InferenceAPIAsyncClient(unsupported_model)
|
clients/python/tests/test_types.py
ADDED
|
@@ -0,0 +1,84 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import pytest
|
| 2 |
+
|
| 3 |
+
from text_generation.types import Parameters, Request
|
| 4 |
+
from text_generation.errors import ValidationError
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
def test_parameters_validation():
|
| 8 |
+
# Test best_of
|
| 9 |
+
Parameters(best_of=1)
|
| 10 |
+
with pytest.raises(ValidationError):
|
| 11 |
+
Parameters(best_of=0)
|
| 12 |
+
with pytest.raises(ValidationError):
|
| 13 |
+
Parameters(best_of=-1)
|
| 14 |
+
Parameters(best_of=2, do_sample=True)
|
| 15 |
+
with pytest.raises(ValidationError):
|
| 16 |
+
Parameters(best_of=2)
|
| 17 |
+
with pytest.raises(ValidationError):
|
| 18 |
+
Parameters(best_of=2, seed=1)
|
| 19 |
+
|
| 20 |
+
# Test repetition_penalty
|
| 21 |
+
Parameters(repetition_penalty=1)
|
| 22 |
+
with pytest.raises(ValidationError):
|
| 23 |
+
Parameters(repetition_penalty=0)
|
| 24 |
+
with pytest.raises(ValidationError):
|
| 25 |
+
Parameters(repetition_penalty=-1)
|
| 26 |
+
|
| 27 |
+
# Test seed
|
| 28 |
+
Parameters(seed=1)
|
| 29 |
+
with pytest.raises(ValidationError):
|
| 30 |
+
Parameters(seed=-1)
|
| 31 |
+
|
| 32 |
+
# Test temperature
|
| 33 |
+
Parameters(temperature=1)
|
| 34 |
+
with pytest.raises(ValidationError):
|
| 35 |
+
Parameters(temperature=0)
|
| 36 |
+
with pytest.raises(ValidationError):
|
| 37 |
+
Parameters(temperature=-1)
|
| 38 |
+
|
| 39 |
+
# Test top_k
|
| 40 |
+
Parameters(top_k=1)
|
| 41 |
+
with pytest.raises(ValidationError):
|
| 42 |
+
Parameters(top_k=0)
|
| 43 |
+
with pytest.raises(ValidationError):
|
| 44 |
+
Parameters(top_k=-1)
|
| 45 |
+
|
| 46 |
+
# Test top_p
|
| 47 |
+
Parameters(top_p=0.5)
|
| 48 |
+
with pytest.raises(ValidationError):
|
| 49 |
+
Parameters(top_p=0)
|
| 50 |
+
with pytest.raises(ValidationError):
|
| 51 |
+
Parameters(top_p=-1)
|
| 52 |
+
with pytest.raises(ValidationError):
|
| 53 |
+
Parameters(top_p=1)
|
| 54 |
+
|
| 55 |
+
# Test truncate
|
| 56 |
+
Parameters(truncate=1)
|
| 57 |
+
with pytest.raises(ValidationError):
|
| 58 |
+
Parameters(truncate=0)
|
| 59 |
+
with pytest.raises(ValidationError):
|
| 60 |
+
Parameters(truncate=-1)
|
| 61 |
+
|
| 62 |
+
# Test typical_p
|
| 63 |
+
Parameters(typical_p=0.5)
|
| 64 |
+
with pytest.raises(ValidationError):
|
| 65 |
+
Parameters(typical_p=0)
|
| 66 |
+
with pytest.raises(ValidationError):
|
| 67 |
+
Parameters(typical_p=-1)
|
| 68 |
+
with pytest.raises(ValidationError):
|
| 69 |
+
Parameters(typical_p=1)
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
def test_request_validation():
|
| 73 |
+
Request(inputs="test")
|
| 74 |
+
|
| 75 |
+
with pytest.raises(ValidationError):
|
| 76 |
+
Request(inputs="")
|
| 77 |
+
|
| 78 |
+
Request(inputs="test", stream=True)
|
| 79 |
+
Request(inputs="test", parameters=Parameters(best_of=2, do_sample=True))
|
| 80 |
+
|
| 81 |
+
with pytest.raises(ValidationError):
|
| 82 |
+
Request(
|
| 83 |
+
inputs="test", parameters=Parameters(best_of=2, do_sample=True), stream=True
|
| 84 |
+
)
|
clients/python/text_generation/__init__.py
ADDED
|
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright 2023 The HuggingFace Team. All rights reserved.
|
| 2 |
+
#
|
| 3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
| 4 |
+
# you may not use this file except in compliance with the License.
|
| 5 |
+
# You may obtain a copy of the License at
|
| 6 |
+
#
|
| 7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
| 8 |
+
#
|
| 9 |
+
# Unless required by applicable law or agreed to in writing, software
|
| 10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
| 11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
| 12 |
+
# See the License for the specific language governing permissions and
|
| 13 |
+
# limitations under the License.
|
| 14 |
+
|
| 15 |
+
__version__ = "0.3.0"
|
| 16 |
+
|
| 17 |
+
from text_generation.client import Client, AsyncClient
|
| 18 |
+
from text_generation.inference_api import InferenceAPIClient, InferenceAPIAsyncClient
|
clients/python/text_generation/client.py
ADDED
|
@@ -0,0 +1,481 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
|
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|
| 1 |
+
import json
|
| 2 |
+
import requests
|
| 3 |
+
|
| 4 |
+
from aiohttp import ClientSession, ClientTimeout
|
| 5 |
+
from pydantic import ValidationError
|
| 6 |
+
from typing import Dict, Optional, List, AsyncIterator, Iterator
|
| 7 |
+
|
| 8 |
+
from text_generation.types import (
|
| 9 |
+
StreamResponse,
|
| 10 |
+
Response,
|
| 11 |
+
Request,
|
| 12 |
+
Parameters,
|
| 13 |
+
)
|
| 14 |
+
from text_generation.errors import parse_error
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
class Client:
|
| 18 |
+
"""Client to make calls to a text-generation-inference instance
|
| 19 |
+
|
| 20 |
+
Example:
|
| 21 |
+
|
| 22 |
+
```python
|
| 23 |
+
>>> from text_generation import Client
|
| 24 |
+
|
| 25 |
+
>>> client = Client("https://api-inference.huggingface.co/models/bigscience/bloomz")
|
| 26 |
+
>>> client.generate("Why is the sky blue?").generated_text
|
| 27 |
+
' Rayleigh scattering'
|
| 28 |
+
|
| 29 |
+
>>> result = ""
|
| 30 |
+
>>> for response in client.generate_stream("Why is the sky blue?"):
|
| 31 |
+
>>> if not response.token.special:
|
| 32 |
+
>>> result += response.token.text
|
| 33 |
+
>>> result
|
| 34 |
+
' Rayleigh scattering'
|
| 35 |
+
```
|
| 36 |
+
"""
|
| 37 |
+
|
| 38 |
+
def __init__(
|
| 39 |
+
self,
|
| 40 |
+
base_url: str,
|
| 41 |
+
headers: Optional[Dict[str, str]] = None,
|
| 42 |
+
cookies: Optional[Dict[str, str]] = None,
|
| 43 |
+
timeout: int = 10,
|
| 44 |
+
):
|
| 45 |
+
"""
|
| 46 |
+
Args:
|
| 47 |
+
base_url (`str`):
|
| 48 |
+
text-generation-inference instance base url
|
| 49 |
+
headers (`Optional[Dict[str, str]]`):
|
| 50 |
+
Additional headers
|
| 51 |
+
cookies (`Optional[Dict[str, str]]`):
|
| 52 |
+
Cookies to include in the requests
|
| 53 |
+
timeout (`int`):
|
| 54 |
+
Timeout in seconds
|
| 55 |
+
"""
|
| 56 |
+
self.base_url = base_url
|
| 57 |
+
self.headers = headers
|
| 58 |
+
self.cookies = cookies
|
| 59 |
+
self.timeout = timeout
|
| 60 |
+
|
| 61 |
+
def generate(
|
| 62 |
+
self,
|
| 63 |
+
prompt: str,
|
| 64 |
+
do_sample: bool = False,
|
| 65 |
+
max_new_tokens: int = 20,
|
| 66 |
+
best_of: Optional[int] = None,
|
| 67 |
+
repetition_penalty: Optional[float] = None,
|
| 68 |
+
return_full_text: bool = False,
|
| 69 |
+
seed: Optional[int] = None,
|
| 70 |
+
stop_sequences: Optional[List[str]] = None,
|
| 71 |
+
temperature: Optional[float] = None,
|
| 72 |
+
top_k: Optional[int] = None,
|
| 73 |
+
top_p: Optional[float] = None,
|
| 74 |
+
truncate: Optional[int] = None,
|
| 75 |
+
typical_p: Optional[float] = None,
|
| 76 |
+
watermark: bool = False,
|
| 77 |
+
) -> Response:
|
| 78 |
+
"""
|
| 79 |
+
Given a prompt, generate the following text
|
| 80 |
+
|
| 81 |
+
Args:
|
| 82 |
+
prompt (`str`):
|
| 83 |
+
Input text
|
| 84 |
+
do_sample (`bool`):
|
| 85 |
+
Activate logits sampling
|
| 86 |
+
max_new_tokens (`int`):
|
| 87 |
+
Maximum number of generated tokens
|
| 88 |
+
best_of (`int`):
|
| 89 |
+
Generate best_of sequences and return the one if the highest token logprobs
|
| 90 |
+
repetition_penalty (`float`):
|
| 91 |
+
The parameter for repetition penalty. 1.0 means no penalty. See [this
|
| 92 |
+
paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
| 93 |
+
return_full_text (`bool`):
|
| 94 |
+
Whether to prepend the prompt to the generated text
|
| 95 |
+
seed (`int`):
|
| 96 |
+
Random sampling seed
|
| 97 |
+
stop_sequences (`List[str]`):
|
| 98 |
+
Stop generating tokens if a member of `stop_sequences` is generated
|
| 99 |
+
temperature (`float`):
|
| 100 |
+
The value used to module the logits distribution.
|
| 101 |
+
top_k (`int`):
|
| 102 |
+
The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
| 103 |
+
top_p (`float`):
|
| 104 |
+
If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
| 105 |
+
higher are kept for generation.
|
| 106 |
+
truncate (`int`):
|
| 107 |
+
Truncate inputs tokens to the given size
|
| 108 |
+
typical_p (`float`):
|
| 109 |
+
Typical Decoding mass
|
| 110 |
+
See [Typical Decoding for Natural Language Generation](https://arxiv.org/abs/2202.00666) for more information
|
| 111 |
+
watermark (`bool`):
|
| 112 |
+
Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
| 113 |
+
|
| 114 |
+
Returns:
|
| 115 |
+
Response: generated response
|
| 116 |
+
"""
|
| 117 |
+
# Validate parameters
|
| 118 |
+
parameters = Parameters(
|
| 119 |
+
best_of=best_of,
|
| 120 |
+
details=True,
|
| 121 |
+
do_sample=do_sample,
|
| 122 |
+
max_new_tokens=max_new_tokens,
|
| 123 |
+
repetition_penalty=repetition_penalty,
|
| 124 |
+
return_full_text=return_full_text,
|
| 125 |
+
seed=seed,
|
| 126 |
+
stop=stop_sequences if stop_sequences is not None else [],
|
| 127 |
+
temperature=temperature,
|
| 128 |
+
top_k=top_k,
|
| 129 |
+
top_p=top_p,
|
| 130 |
+
truncate=truncate,
|
| 131 |
+
typical_p=typical_p,
|
| 132 |
+
watermark=watermark,
|
| 133 |
+
)
|
| 134 |
+
request = Request(inputs=prompt, stream=False, parameters=parameters)
|
| 135 |
+
|
| 136 |
+
resp = requests.post(
|
| 137 |
+
self.base_url,
|
| 138 |
+
json=request.dict(),
|
| 139 |
+
headers=self.headers,
|
| 140 |
+
cookies=self.cookies,
|
| 141 |
+
timeout=self.timeout,
|
| 142 |
+
)
|
| 143 |
+
payload = resp.json()
|
| 144 |
+
if resp.status_code != 200:
|
| 145 |
+
raise parse_error(resp.status_code, payload)
|
| 146 |
+
return Response(**payload[0])
|
| 147 |
+
|
| 148 |
+
def generate_stream(
|
| 149 |
+
self,
|
| 150 |
+
prompt: str,
|
| 151 |
+
do_sample: bool = False,
|
| 152 |
+
max_new_tokens: int = 20,
|
| 153 |
+
repetition_penalty: Optional[float] = None,
|
| 154 |
+
return_full_text: bool = False,
|
| 155 |
+
seed: Optional[int] = None,
|
| 156 |
+
stop_sequences: Optional[List[str]] = None,
|
| 157 |
+
temperature: Optional[float] = None,
|
| 158 |
+
top_k: Optional[int] = None,
|
| 159 |
+
top_p: Optional[float] = None,
|
| 160 |
+
truncate: Optional[int] = None,
|
| 161 |
+
typical_p: Optional[float] = None,
|
| 162 |
+
watermark: bool = False,
|
| 163 |
+
) -> Iterator[StreamResponse]:
|
| 164 |
+
"""
|
| 165 |
+
Given a prompt, generate the following stream of tokens
|
| 166 |
+
|
| 167 |
+
Args:
|
| 168 |
+
prompt (`str`):
|
| 169 |
+
Input text
|
| 170 |
+
do_sample (`bool`):
|
| 171 |
+
Activate logits sampling
|
| 172 |
+
max_new_tokens (`int`):
|
| 173 |
+
Maximum number of generated tokens
|
| 174 |
+
repetition_penalty (`float`):
|
| 175 |
+
The parameter for repetition penalty. 1.0 means no penalty. See [this
|
| 176 |
+
paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
| 177 |
+
return_full_text (`bool`):
|
| 178 |
+
Whether to prepend the prompt to the generated text
|
| 179 |
+
seed (`int`):
|
| 180 |
+
Random sampling seed
|
| 181 |
+
stop_sequences (`List[str]`):
|
| 182 |
+
Stop generating tokens if a member of `stop_sequences` is generated
|
| 183 |
+
temperature (`float`):
|
| 184 |
+
The value used to module the logits distribution.
|
| 185 |
+
top_k (`int`):
|
| 186 |
+
The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
| 187 |
+
top_p (`float`):
|
| 188 |
+
If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
| 189 |
+
higher are kept for generation.
|
| 190 |
+
truncate (`int`):
|
| 191 |
+
Truncate inputs tokens to the given size
|
| 192 |
+
typical_p (`float`):
|
| 193 |
+
Typical Decoding mass
|
| 194 |
+
See [Typical Decoding for Natural Language Generation](https://arxiv.org/abs/2202.00666) for more information
|
| 195 |
+
watermark (`bool`):
|
| 196 |
+
Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
| 197 |
+
|
| 198 |
+
Returns:
|
| 199 |
+
Iterator[StreamResponse]: stream of generated tokens
|
| 200 |
+
"""
|
| 201 |
+
# Validate parameters
|
| 202 |
+
parameters = Parameters(
|
| 203 |
+
best_of=None,
|
| 204 |
+
details=True,
|
| 205 |
+
do_sample=do_sample,
|
| 206 |
+
max_new_tokens=max_new_tokens,
|
| 207 |
+
repetition_penalty=repetition_penalty,
|
| 208 |
+
return_full_text=return_full_text,
|
| 209 |
+
seed=seed,
|
| 210 |
+
stop=stop_sequences if stop_sequences is not None else [],
|
| 211 |
+
temperature=temperature,
|
| 212 |
+
top_k=top_k,
|
| 213 |
+
top_p=top_p,
|
| 214 |
+
truncate=truncate,
|
| 215 |
+
typical_p=typical_p,
|
| 216 |
+
watermark=watermark,
|
| 217 |
+
)
|
| 218 |
+
request = Request(inputs=prompt, stream=True, parameters=parameters)
|
| 219 |
+
|
| 220 |
+
resp = requests.post(
|
| 221 |
+
self.base_url,
|
| 222 |
+
json=request.dict(),
|
| 223 |
+
headers=self.headers,
|
| 224 |
+
cookies=self.cookies,
|
| 225 |
+
timeout=self.timeout,
|
| 226 |
+
stream=True,
|
| 227 |
+
)
|
| 228 |
+
|
| 229 |
+
if resp.status_code != 200:
|
| 230 |
+
raise parse_error(resp.status_code, resp.json())
|
| 231 |
+
|
| 232 |
+
# Parse ServerSentEvents
|
| 233 |
+
for byte_payload in resp.iter_lines():
|
| 234 |
+
# Skip line
|
| 235 |
+
if byte_payload == b"\n":
|
| 236 |
+
continue
|
| 237 |
+
|
| 238 |
+
payload = byte_payload.decode("utf-8")
|
| 239 |
+
|
| 240 |
+
# Event data
|
| 241 |
+
if payload.startswith("data:"):
|
| 242 |
+
# Decode payload
|
| 243 |
+
json_payload = json.loads(payload.lstrip("data:").rstrip("/n"))
|
| 244 |
+
# Parse payload
|
| 245 |
+
try:
|
| 246 |
+
response = StreamResponse(**json_payload)
|
| 247 |
+
except ValidationError:
|
| 248 |
+
# If we failed to parse the payload, then it is an error payload
|
| 249 |
+
raise parse_error(resp.status_code, json_payload)
|
| 250 |
+
yield response
|
| 251 |
+
|
| 252 |
+
|
| 253 |
+
class AsyncClient:
|
| 254 |
+
"""Asynchronous Client to make calls to a text-generation-inference instance
|
| 255 |
+
|
| 256 |
+
Example:
|
| 257 |
+
|
| 258 |
+
```python
|
| 259 |
+
>>> from text_generation import AsyncClient
|
| 260 |
+
|
| 261 |
+
>>> client = AsyncClient("https://api-inference.huggingface.co/models/bigscience/bloomz")
|
| 262 |
+
>>> response = await client.generate("Why is the sky blue?")
|
| 263 |
+
>>> response.generated_text
|
| 264 |
+
' Rayleigh scattering'
|
| 265 |
+
|
| 266 |
+
>>> result = ""
|
| 267 |
+
>>> async for response in client.generate_stream("Why is the sky blue?"):
|
| 268 |
+
>>> if not response.token.special:
|
| 269 |
+
>>> result += response.token.text
|
| 270 |
+
>>> result
|
| 271 |
+
' Rayleigh scattering'
|
| 272 |
+
```
|
| 273 |
+
"""
|
| 274 |
+
|
| 275 |
+
def __init__(
|
| 276 |
+
self,
|
| 277 |
+
base_url: str,
|
| 278 |
+
headers: Optional[Dict[str, str]] = None,
|
| 279 |
+
cookies: Optional[Dict[str, str]] = None,
|
| 280 |
+
timeout: int = 10,
|
| 281 |
+
):
|
| 282 |
+
"""
|
| 283 |
+
Args:
|
| 284 |
+
base_url (`str`):
|
| 285 |
+
text-generation-inference instance base url
|
| 286 |
+
headers (`Optional[Dict[str, str]]`):
|
| 287 |
+
Additional headers
|
| 288 |
+
cookies (`Optional[Dict[str, str]]`):
|
| 289 |
+
Cookies to include in the requests
|
| 290 |
+
timeout (`int`):
|
| 291 |
+
Timeout in seconds
|
| 292 |
+
"""
|
| 293 |
+
self.base_url = base_url
|
| 294 |
+
self.headers = headers
|
| 295 |
+
self.cookies = cookies
|
| 296 |
+
self.timeout = ClientTimeout(timeout * 60)
|
| 297 |
+
|
| 298 |
+
async def generate(
|
| 299 |
+
self,
|
| 300 |
+
prompt: str,
|
| 301 |
+
do_sample: bool = False,
|
| 302 |
+
max_new_tokens: int = 20,
|
| 303 |
+
best_of: Optional[int] = None,
|
| 304 |
+
repetition_penalty: Optional[float] = None,
|
| 305 |
+
return_full_text: bool = False,
|
| 306 |
+
seed: Optional[int] = None,
|
| 307 |
+
stop_sequences: Optional[List[str]] = None,
|
| 308 |
+
temperature: Optional[float] = None,
|
| 309 |
+
top_k: Optional[int] = None,
|
| 310 |
+
top_p: Optional[float] = None,
|
| 311 |
+
truncate: Optional[int] = None,
|
| 312 |
+
typical_p: Optional[float] = None,
|
| 313 |
+
watermark: bool = False,
|
| 314 |
+
) -> Response:
|
| 315 |
+
"""
|
| 316 |
+
Given a prompt, generate the following text asynchronously
|
| 317 |
+
|
| 318 |
+
Args:
|
| 319 |
+
prompt (`str`):
|
| 320 |
+
Input text
|
| 321 |
+
do_sample (`bool`):
|
| 322 |
+
Activate logits sampling
|
| 323 |
+
max_new_tokens (`int`):
|
| 324 |
+
Maximum number of generated tokens
|
| 325 |
+
best_of (`int`):
|
| 326 |
+
Generate best_of sequences and return the one if the highest token logprobs
|
| 327 |
+
repetition_penalty (`float`):
|
| 328 |
+
The parameter for repetition penalty. 1.0 means no penalty. See [this
|
| 329 |
+
paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
| 330 |
+
return_full_text (`bool`):
|
| 331 |
+
Whether to prepend the prompt to the generated text
|
| 332 |
+
seed (`int`):
|
| 333 |
+
Random sampling seed
|
| 334 |
+
stop_sequences (`List[str]`):
|
| 335 |
+
Stop generating tokens if a member of `stop_sequences` is generated
|
| 336 |
+
temperature (`float`):
|
| 337 |
+
The value used to module the logits distribution.
|
| 338 |
+
top_k (`int`):
|
| 339 |
+
The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
| 340 |
+
top_p (`float`):
|
| 341 |
+
If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
| 342 |
+
higher are kept for generation.
|
| 343 |
+
truncate (`int`):
|
| 344 |
+
Truncate inputs tokens to the given size
|
| 345 |
+
typical_p (`float`):
|
| 346 |
+
Typical Decoding mass
|
| 347 |
+
See [Typical Decoding for Natural Language Generation](https://arxiv.org/abs/2202.00666) for more information
|
| 348 |
+
watermark (`bool`):
|
| 349 |
+
Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
| 350 |
+
|
| 351 |
+
Returns:
|
| 352 |
+
Response: generated response
|
| 353 |
+
"""
|
| 354 |
+
# Validate parameters
|
| 355 |
+
parameters = Parameters(
|
| 356 |
+
best_of=best_of,
|
| 357 |
+
details=True,
|
| 358 |
+
do_sample=do_sample,
|
| 359 |
+
max_new_tokens=max_new_tokens,
|
| 360 |
+
repetition_penalty=repetition_penalty,
|
| 361 |
+
return_full_text=return_full_text,
|
| 362 |
+
seed=seed,
|
| 363 |
+
stop=stop_sequences if stop_sequences is not None else [],
|
| 364 |
+
temperature=temperature,
|
| 365 |
+
top_k=top_k,
|
| 366 |
+
top_p=top_p,
|
| 367 |
+
truncate=truncate,
|
| 368 |
+
typical_p=typical_p,
|
| 369 |
+
watermark=watermark,
|
| 370 |
+
)
|
| 371 |
+
request = Request(inputs=prompt, stream=False, parameters=parameters)
|
| 372 |
+
|
| 373 |
+
async with ClientSession(
|
| 374 |
+
headers=self.headers, cookies=self.cookies, timeout=self.timeout
|
| 375 |
+
) as session:
|
| 376 |
+
async with session.post(self.base_url, json=request.dict()) as resp:
|
| 377 |
+
payload = await resp.json()
|
| 378 |
+
|
| 379 |
+
if resp.status != 200:
|
| 380 |
+
raise parse_error(resp.status, payload)
|
| 381 |
+
return Response(**payload[0])
|
| 382 |
+
|
| 383 |
+
async def generate_stream(
|
| 384 |
+
self,
|
| 385 |
+
prompt: str,
|
| 386 |
+
do_sample: bool = False,
|
| 387 |
+
max_new_tokens: int = 20,
|
| 388 |
+
repetition_penalty: Optional[float] = None,
|
| 389 |
+
return_full_text: bool = False,
|
| 390 |
+
seed: Optional[int] = None,
|
| 391 |
+
stop_sequences: Optional[List[str]] = None,
|
| 392 |
+
temperature: Optional[float] = None,
|
| 393 |
+
top_k: Optional[int] = None,
|
| 394 |
+
top_p: Optional[float] = None,
|
| 395 |
+
truncate: Optional[int] = None,
|
| 396 |
+
typical_p: Optional[float] = None,
|
| 397 |
+
watermark: bool = False,
|
| 398 |
+
) -> AsyncIterator[StreamResponse]:
|
| 399 |
+
"""
|
| 400 |
+
Given a prompt, generate the following stream of tokens asynchronously
|
| 401 |
+
|
| 402 |
+
Args:
|
| 403 |
+
prompt (`str`):
|
| 404 |
+
Input text
|
| 405 |
+
do_sample (`bool`):
|
| 406 |
+
Activate logits sampling
|
| 407 |
+
max_new_tokens (`int`):
|
| 408 |
+
Maximum number of generated tokens
|
| 409 |
+
repetition_penalty (`float`):
|
| 410 |
+
The parameter for repetition penalty. 1.0 means no penalty. See [this
|
| 411 |
+
paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
| 412 |
+
return_full_text (`bool`):
|
| 413 |
+
Whether to prepend the prompt to the generated text
|
| 414 |
+
seed (`int`):
|
| 415 |
+
Random sampling seed
|
| 416 |
+
stop_sequences (`List[str]`):
|
| 417 |
+
Stop generating tokens if a member of `stop_sequences` is generated
|
| 418 |
+
temperature (`float`):
|
| 419 |
+
The value used to module the logits distribution.
|
| 420 |
+
top_k (`int`):
|
| 421 |
+
The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
| 422 |
+
top_p (`float`):
|
| 423 |
+
If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
| 424 |
+
higher are kept for generation.
|
| 425 |
+
truncate (`int`):
|
| 426 |
+
Truncate inputs tokens to the given size
|
| 427 |
+
typical_p (`float`):
|
| 428 |
+
Typical Decoding mass
|
| 429 |
+
See [Typical Decoding for Natural Language Generation](https://arxiv.org/abs/2202.00666) for more information
|
| 430 |
+
watermark (`bool`):
|
| 431 |
+
Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
| 432 |
+
|
| 433 |
+
Returns:
|
| 434 |
+
AsyncIterator[StreamResponse]: stream of generated tokens
|
| 435 |
+
"""
|
| 436 |
+
# Validate parameters
|
| 437 |
+
parameters = Parameters(
|
| 438 |
+
best_of=None,
|
| 439 |
+
details=True,
|
| 440 |
+
do_sample=do_sample,
|
| 441 |
+
max_new_tokens=max_new_tokens,
|
| 442 |
+
repetition_penalty=repetition_penalty,
|
| 443 |
+
return_full_text=return_full_text,
|
| 444 |
+
seed=seed,
|
| 445 |
+
stop=stop_sequences if stop_sequences is not None else [],
|
| 446 |
+
temperature=temperature,
|
| 447 |
+
top_k=top_k,
|
| 448 |
+
top_p=top_p,
|
| 449 |
+
truncate=truncate,
|
| 450 |
+
typical_p=typical_p,
|
| 451 |
+
watermark=watermark,
|
| 452 |
+
)
|
| 453 |
+
request = Request(inputs=prompt, stream=True, parameters=parameters)
|
| 454 |
+
|
| 455 |
+
async with ClientSession(
|
| 456 |
+
headers=self.headers, cookies=self.cookies, timeout=self.timeout
|
| 457 |
+
) as session:
|
| 458 |
+
async with session.post(self.base_url, json=request.dict()) as resp:
|
| 459 |
+
|
| 460 |
+
if resp.status != 200:
|
| 461 |
+
raise parse_error(resp.status, await resp.json())
|
| 462 |
+
|
| 463 |
+
# Parse ServerSentEvents
|
| 464 |
+
async for byte_payload in resp.content:
|
| 465 |
+
# Skip line
|
| 466 |
+
if byte_payload == b"\n":
|
| 467 |
+
continue
|
| 468 |
+
|
| 469 |
+
payload = byte_payload.decode("utf-8")
|
| 470 |
+
|
| 471 |
+
# Event data
|
| 472 |
+
if payload.startswith("data:"):
|
| 473 |
+
# Decode payload
|
| 474 |
+
json_payload = json.loads(payload.lstrip("data:").rstrip("/n"))
|
| 475 |
+
# Parse payload
|
| 476 |
+
try:
|
| 477 |
+
response = StreamResponse(**json_payload)
|
| 478 |
+
except ValidationError:
|
| 479 |
+
# If we failed to parse the payload, then it is an error payload
|
| 480 |
+
raise parse_error(resp.status, json_payload)
|
| 481 |
+
yield response
|
clients/python/text_generation/errors.py
ADDED
|
@@ -0,0 +1,106 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from typing import Dict
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
# Text Generation Inference Errors
|
| 5 |
+
class ValidationError(Exception):
|
| 6 |
+
def __init__(self, message: str):
|
| 7 |
+
super().__init__(message)
|
| 8 |
+
|
| 9 |
+
|
| 10 |
+
class GenerationError(Exception):
|
| 11 |
+
def __init__(self, message: str):
|
| 12 |
+
super().__init__(message)
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
class OverloadedError(Exception):
|
| 16 |
+
def __init__(self, message: str):
|
| 17 |
+
super().__init__(message)
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
class IncompleteGenerationError(Exception):
|
| 21 |
+
def __init__(self, message: str):
|
| 22 |
+
super().__init__(message)
|
| 23 |
+
|
| 24 |
+
|
| 25 |
+
# API Inference Errors
|
| 26 |
+
class BadRequestError(Exception):
|
| 27 |
+
def __init__(self, message: str):
|
| 28 |
+
super().__init__(message)
|
| 29 |
+
|
| 30 |
+
|
| 31 |
+
class ShardNotReadyError(Exception):
|
| 32 |
+
def __init__(self, message: str):
|
| 33 |
+
super().__init__(message)
|
| 34 |
+
|
| 35 |
+
|
| 36 |
+
class ShardTimeoutError(Exception):
|
| 37 |
+
def __init__(self, message: str):
|
| 38 |
+
super().__init__(message)
|
| 39 |
+
|
| 40 |
+
|
| 41 |
+
class NotFoundError(Exception):
|
| 42 |
+
def __init__(self, message: str):
|
| 43 |
+
super().__init__(message)
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
class RateLimitExceededError(Exception):
|
| 47 |
+
def __init__(self, message: str):
|
| 48 |
+
super().__init__(message)
|
| 49 |
+
|
| 50 |
+
|
| 51 |
+
class NotSupportedError(Exception):
|
| 52 |
+
def __init__(self, model_id: str):
|
| 53 |
+
message = (
|
| 54 |
+
f"Model `{model_id}` is not available for inference with this client. \n"
|
| 55 |
+
"Use `huggingface_hub.inference_api.InferenceApi` instead."
|
| 56 |
+
)
|
| 57 |
+
super(NotSupportedError, self).__init__(message)
|
| 58 |
+
|
| 59 |
+
|
| 60 |
+
# Unknown error
|
| 61 |
+
class UnknownError(Exception):
|
| 62 |
+
def __init__(self, message: str):
|
| 63 |
+
super().__init__(message)
|
| 64 |
+
|
| 65 |
+
|
| 66 |
+
def parse_error(status_code: int, payload: Dict[str, str]) -> Exception:
|
| 67 |
+
"""
|
| 68 |
+
Parse error given an HTTP status code and a json payload
|
| 69 |
+
|
| 70 |
+
Args:
|
| 71 |
+
status_code (`int`):
|
| 72 |
+
HTTP status code
|
| 73 |
+
payload (`Dict[str, str]`):
|
| 74 |
+
Json payload
|
| 75 |
+
|
| 76 |
+
Returns:
|
| 77 |
+
Exception: parsed exception
|
| 78 |
+
|
| 79 |
+
"""
|
| 80 |
+
# Try to parse a Text Generation Inference error
|
| 81 |
+
message = payload["error"]
|
| 82 |
+
if "error_type" in payload:
|
| 83 |
+
error_type = payload["error_type"]
|
| 84 |
+
if error_type == "generation":
|
| 85 |
+
return GenerationError(message)
|
| 86 |
+
if error_type == "incomplete_generation":
|
| 87 |
+
return IncompleteGenerationError(message)
|
| 88 |
+
if error_type == "overloaded":
|
| 89 |
+
return OverloadedError(message)
|
| 90 |
+
if error_type == "validation":
|
| 91 |
+
return ValidationError(message)
|
| 92 |
+
|
| 93 |
+
# Try to parse a APIInference error
|
| 94 |
+
if status_code == 400:
|
| 95 |
+
return BadRequestError(message)
|
| 96 |
+
if status_code == 403 or status_code == 424:
|
| 97 |
+
return ShardNotReadyError(message)
|
| 98 |
+
if status_code == 504:
|
| 99 |
+
return ShardTimeoutError(message)
|
| 100 |
+
if status_code == 404:
|
| 101 |
+
return NotFoundError(message)
|
| 102 |
+
if status_code == 429:
|
| 103 |
+
return RateLimitExceededError(message)
|
| 104 |
+
|
| 105 |
+
# Fallback to an unknown error
|
| 106 |
+
return UnknownError(message)
|
clients/python/text_generation/inference_api.py
ADDED
|
@@ -0,0 +1,168 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
import requests
|
| 3 |
+
|
| 4 |
+
from typing import Dict, Optional, List
|
| 5 |
+
from huggingface_hub.utils import build_hf_headers
|
| 6 |
+
|
| 7 |
+
from text_generation import Client, AsyncClient, __version__
|
| 8 |
+
from text_generation.types import DeployedModel
|
| 9 |
+
from text_generation.errors import NotSupportedError, parse_error
|
| 10 |
+
|
| 11 |
+
INFERENCE_ENDPOINT = os.environ.get(
|
| 12 |
+
"HF_INFERENCE_ENDPOINT", "https://api-inference.huggingface.co"
|
| 13 |
+
)
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
def deployed_models(headers: Optional[Dict] = None) -> List[DeployedModel]:
|
| 17 |
+
"""
|
| 18 |
+
Get all currently deployed models with text-generation-inference-support
|
| 19 |
+
|
| 20 |
+
Returns:
|
| 21 |
+
List[DeployedModel]: list of all currently deployed models
|
| 22 |
+
"""
|
| 23 |
+
resp = requests.get(
|
| 24 |
+
f"https://api-inference.huggingface.co/framework/text-generation-inference",
|
| 25 |
+
headers=headers,
|
| 26 |
+
timeout=5,
|
| 27 |
+
)
|
| 28 |
+
|
| 29 |
+
payload = resp.json()
|
| 30 |
+
if resp.status_code != 200:
|
| 31 |
+
raise parse_error(resp.status_code, payload)
|
| 32 |
+
|
| 33 |
+
models = [DeployedModel(**raw_deployed_model) for raw_deployed_model in payload]
|
| 34 |
+
return models
|
| 35 |
+
|
| 36 |
+
|
| 37 |
+
def check_model_support(repo_id: str, headers: Optional[Dict] = None) -> bool:
|
| 38 |
+
"""
|
| 39 |
+
Check if a given model is supported by text-generation-inference
|
| 40 |
+
|
| 41 |
+
Returns:
|
| 42 |
+
bool: whether the model is supported by this client
|
| 43 |
+
"""
|
| 44 |
+
resp = requests.get(
|
| 45 |
+
f"https://api-inference.huggingface.co/status/{repo_id}",
|
| 46 |
+
headers=headers,
|
| 47 |
+
timeout=5,
|
| 48 |
+
)
|
| 49 |
+
|
| 50 |
+
payload = resp.json()
|
| 51 |
+
if resp.status_code != 200:
|
| 52 |
+
raise parse_error(resp.status_code, payload)
|
| 53 |
+
|
| 54 |
+
framework = payload["framework"]
|
| 55 |
+
supported = framework == "text-generation-inference"
|
| 56 |
+
return supported
|
| 57 |
+
|
| 58 |
+
|
| 59 |
+
class InferenceAPIClient(Client):
|
| 60 |
+
"""Client to make calls to the HuggingFace Inference API.
|
| 61 |
+
|
| 62 |
+
Only supports a subset of the available text-generation or text2text-generation models that are served using
|
| 63 |
+
text-generation-inference
|
| 64 |
+
|
| 65 |
+
Example:
|
| 66 |
+
|
| 67 |
+
```python
|
| 68 |
+
>>> from text_generation import InferenceAPIClient
|
| 69 |
+
|
| 70 |
+
>>> client = InferenceAPIClient("bigscience/bloomz")
|
| 71 |
+
>>> client.generate("Why is the sky blue?").generated_text
|
| 72 |
+
' Rayleigh scattering'
|
| 73 |
+
|
| 74 |
+
>>> result = ""
|
| 75 |
+
>>> for response in client.generate_stream("Why is the sky blue?"):
|
| 76 |
+
>>> if not response.token.special:
|
| 77 |
+
>>> result += response.token.text
|
| 78 |
+
>>> result
|
| 79 |
+
' Rayleigh scattering'
|
| 80 |
+
```
|
| 81 |
+
"""
|
| 82 |
+
|
| 83 |
+
def __init__(self, repo_id: str, token: Optional[str] = None, timeout: int = 10):
|
| 84 |
+
"""
|
| 85 |
+
Init headers and API information
|
| 86 |
+
|
| 87 |
+
Args:
|
| 88 |
+
repo_id (`str`):
|
| 89 |
+
Id of repository (e.g. `bigscience/bloom`).
|
| 90 |
+
token (`str`, `optional`):
|
| 91 |
+
The API token to use as HTTP bearer authorization. This is not
|
| 92 |
+
the authentication token. You can find the token in
|
| 93 |
+
https://huggingface.co/settings/token. Alternatively, you can
|
| 94 |
+
find both your organizations and personal API tokens using
|
| 95 |
+
`HfApi().whoami(token)`.
|
| 96 |
+
timeout (`int`):
|
| 97 |
+
Timeout in seconds
|
| 98 |
+
"""
|
| 99 |
+
|
| 100 |
+
headers = build_hf_headers(
|
| 101 |
+
token=token, library_name="text-generation", library_version=__version__
|
| 102 |
+
)
|
| 103 |
+
|
| 104 |
+
# Text Generation Inference client only supports a subset of the available hub models
|
| 105 |
+
if not check_model_support(repo_id, headers):
|
| 106 |
+
raise NotSupportedError(repo_id)
|
| 107 |
+
|
| 108 |
+
base_url = f"{INFERENCE_ENDPOINT}/models/{repo_id}"
|
| 109 |
+
|
| 110 |
+
super(InferenceAPIClient, self).__init__(
|
| 111 |
+
base_url, headers=headers, timeout=timeout
|
| 112 |
+
)
|
| 113 |
+
|
| 114 |
+
|
| 115 |
+
class InferenceAPIAsyncClient(AsyncClient):
|
| 116 |
+
"""Aynschronous Client to make calls to the HuggingFace Inference API.
|
| 117 |
+
|
| 118 |
+
Only supports a subset of the available text-generation or text2text-generation models that are served using
|
| 119 |
+
text-generation-inference
|
| 120 |
+
|
| 121 |
+
Example:
|
| 122 |
+
|
| 123 |
+
```python
|
| 124 |
+
>>> from text_generation import InferenceAPIAsyncClient
|
| 125 |
+
|
| 126 |
+
>>> client = InferenceAPIAsyncClient("bigscience/bloomz")
|
| 127 |
+
>>> response = await client.generate("Why is the sky blue?")
|
| 128 |
+
>>> response.generated_text
|
| 129 |
+
' Rayleigh scattering'
|
| 130 |
+
|
| 131 |
+
>>> result = ""
|
| 132 |
+
>>> async for response in client.generate_stream("Why is the sky blue?"):
|
| 133 |
+
>>> if not response.token.special:
|
| 134 |
+
>>> result += response.token.text
|
| 135 |
+
>>> result
|
| 136 |
+
' Rayleigh scattering'
|
| 137 |
+
```
|
| 138 |
+
"""
|
| 139 |
+
|
| 140 |
+
def __init__(self, repo_id: str, token: Optional[str] = None, timeout: int = 10):
|
| 141 |
+
"""
|
| 142 |
+
Init headers and API information
|
| 143 |
+
|
| 144 |
+
Args:
|
| 145 |
+
repo_id (`str`):
|
| 146 |
+
Id of repository (e.g. `bigscience/bloom`).
|
| 147 |
+
token (`str`, `optional`):
|
| 148 |
+
The API token to use as HTTP bearer authorization. This is not
|
| 149 |
+
the authentication token. You can find the token in
|
| 150 |
+
https://huggingface.co/settings/token. Alternatively, you can
|
| 151 |
+
find both your organizations and personal API tokens using
|
| 152 |
+
`HfApi().whoami(token)`.
|
| 153 |
+
timeout (`int`):
|
| 154 |
+
Timeout in seconds
|
| 155 |
+
"""
|
| 156 |
+
headers = build_hf_headers(
|
| 157 |
+
token=token, library_name="text-generation", library_version=__version__
|
| 158 |
+
)
|
| 159 |
+
|
| 160 |
+
# Text Generation Inference client only supports a subset of the available hub models
|
| 161 |
+
if not check_model_support(repo_id, headers):
|
| 162 |
+
raise NotSupportedError(repo_id)
|
| 163 |
+
|
| 164 |
+
base_url = f"{INFERENCE_ENDPOINT}/models/{repo_id}"
|
| 165 |
+
|
| 166 |
+
super(InferenceAPIAsyncClient, self).__init__(
|
| 167 |
+
base_url, headers=headers, timeout=timeout
|
| 168 |
+
)
|
clients/python/text_generation/types.py
ADDED
|
@@ -0,0 +1,231 @@
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from enum import Enum
|
| 2 |
+
from pydantic import BaseModel, validator
|
| 3 |
+
from typing import Optional, List
|
| 4 |
+
|
| 5 |
+
from text_generation.errors import ValidationError
|
| 6 |
+
|
| 7 |
+
|
| 8 |
+
class Parameters(BaseModel):
|
| 9 |
+
# Activate logits sampling
|
| 10 |
+
do_sample: bool = False
|
| 11 |
+
# Maximum number of generated tokens
|
| 12 |
+
max_new_tokens: int = 20
|
| 13 |
+
# The parameter for repetition penalty. 1.0 means no penalty.
|
| 14 |
+
# See [this paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.
|
| 15 |
+
repetition_penalty: Optional[float] = None
|
| 16 |
+
# Whether to prepend the prompt to the generated text
|
| 17 |
+
return_full_text: bool = False
|
| 18 |
+
# Stop generating tokens if a member of `stop_sequences` is generated
|
| 19 |
+
stop: List[str] = []
|
| 20 |
+
# Random sampling seed
|
| 21 |
+
seed: Optional[int]
|
| 22 |
+
# The value used to module the logits distribution.
|
| 23 |
+
temperature: Optional[float]
|
| 24 |
+
# The number of highest probability vocabulary tokens to keep for top-k-filtering.
|
| 25 |
+
top_k: Optional[int]
|
| 26 |
+
# If set to < 1, only the smallest set of most probable tokens with probabilities that add up to `top_p` or
|
| 27 |
+
# higher are kept for generation.
|
| 28 |
+
top_p: Optional[float]
|
| 29 |
+
# truncate inputs tokens to the given size
|
| 30 |
+
truncate: Optional[int]
|
| 31 |
+
# Typical Decoding mass
|
| 32 |
+
# See [Typical Decoding for Natural Language Generation](https://arxiv.org/abs/2202.00666) for more information
|
| 33 |
+
typical_p: Optional[float]
|
| 34 |
+
# Generate best_of sequences and return the one if the highest token logprobs
|
| 35 |
+
best_of: Optional[int]
|
| 36 |
+
# Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226)
|
| 37 |
+
watermark: bool = False
|
| 38 |
+
# Get generation details
|
| 39 |
+
details: bool = False
|
| 40 |
+
|
| 41 |
+
@validator("best_of")
|
| 42 |
+
def valid_best_of(cls, field_value, values):
|
| 43 |
+
if field_value is not None:
|
| 44 |
+
if field_value <= 0:
|
| 45 |
+
raise ValidationError("`best_of` must be strictly positive")
|
| 46 |
+
if field_value > 1 and values["seed"] is not None:
|
| 47 |
+
raise ValidationError("`seed` must not be set when `best_of` is > 1")
|
| 48 |
+
sampling = (
|
| 49 |
+
values["do_sample"]
|
| 50 |
+
| (values["temperature"] is not None)
|
| 51 |
+
| (values["top_k"] is not None)
|
| 52 |
+
| (values["top_p"] is not None)
|
| 53 |
+
| (values["typical_p"] is not None)
|
| 54 |
+
)
|
| 55 |
+
if field_value > 1 and not sampling:
|
| 56 |
+
raise ValidationError("you must use sampling when `best_of` is > 1")
|
| 57 |
+
|
| 58 |
+
return field_value
|
| 59 |
+
|
| 60 |
+
@validator("repetition_penalty")
|
| 61 |
+
def valid_repetition_penalty(cls, v):
|
| 62 |
+
if v is not None and v <= 0:
|
| 63 |
+
raise ValidationError("`repetition_penalty` must be strictly positive")
|
| 64 |
+
return v
|
| 65 |
+
|
| 66 |
+
@validator("seed")
|
| 67 |
+
def valid_seed(cls, v):
|
| 68 |
+
if v is not None and v < 0:
|
| 69 |
+
raise ValidationError("`seed` must be positive")
|
| 70 |
+
return v
|
| 71 |
+
|
| 72 |
+
@validator("temperature")
|
| 73 |
+
def valid_temp(cls, v):
|
| 74 |
+
if v is not None and v <= 0:
|
| 75 |
+
raise ValidationError("`temperature` must be strictly positive")
|
| 76 |
+
return v
|
| 77 |
+
|
| 78 |
+
@validator("top_k")
|
| 79 |
+
def valid_top_k(cls, v):
|
| 80 |
+
if v is not None and v <= 0:
|
| 81 |
+
raise ValidationError("`top_k` must be strictly positive")
|
| 82 |
+
return v
|
| 83 |
+
|
| 84 |
+
@validator("top_p")
|
| 85 |
+
def valid_top_p(cls, v):
|
| 86 |
+
if v is not None and (v <= 0 or v >= 1.0):
|
| 87 |
+
raise ValidationError("`top_p` must be > 0.0 and < 1.0")
|
| 88 |
+
return v
|
| 89 |
+
|
| 90 |
+
@validator("truncate")
|
| 91 |
+
def valid_truncate(cls, v):
|
| 92 |
+
if v is not None and v <= 0:
|
| 93 |
+
raise ValidationError("`truncate` must be strictly positive")
|
| 94 |
+
return v
|
| 95 |
+
|
| 96 |
+
@validator("typical_p")
|
| 97 |
+
def valid_typical_p(cls, v):
|
| 98 |
+
if v is not None and (v <= 0 or v >= 1.0):
|
| 99 |
+
raise ValidationError("`typical_p` must be > 0.0 and < 1.0")
|
| 100 |
+
return v
|
| 101 |
+
|
| 102 |
+
|
| 103 |
+
class Request(BaseModel):
|
| 104 |
+
# Prompt
|
| 105 |
+
inputs: str
|
| 106 |
+
# Generation parameters
|
| 107 |
+
parameters: Optional[Parameters]
|
| 108 |
+
# Whether to stream output tokens
|
| 109 |
+
stream: bool = False
|
| 110 |
+
|
| 111 |
+
@validator("inputs")
|
| 112 |
+
def valid_input(cls, v):
|
| 113 |
+
if not v:
|
| 114 |
+
raise ValidationError("`inputs` cannot be empty")
|
| 115 |
+
return v
|
| 116 |
+
|
| 117 |
+
@validator("stream")
|
| 118 |
+
def valid_best_of_stream(cls, field_value, values):
|
| 119 |
+
parameters = values["parameters"]
|
| 120 |
+
if (
|
| 121 |
+
parameters is not None
|
| 122 |
+
and parameters.best_of is not None
|
| 123 |
+
and parameters.best_of > 1
|
| 124 |
+
and field_value
|
| 125 |
+
):
|
| 126 |
+
raise ValidationError(
|
| 127 |
+
"`best_of` != 1 is not supported when `stream` == True"
|
| 128 |
+
)
|
| 129 |
+
return field_value
|
| 130 |
+
|
| 131 |
+
|
| 132 |
+
# Prompt tokens
|
| 133 |
+
class PrefillToken(BaseModel):
|
| 134 |
+
# Token ID from the model tokenizer
|
| 135 |
+
id: int
|
| 136 |
+
# Token text
|
| 137 |
+
text: str
|
| 138 |
+
# Logprob
|
| 139 |
+
# Optional since the logprob of the first token cannot be computed
|
| 140 |
+
logprob: Optional[float]
|
| 141 |
+
|
| 142 |
+
|
| 143 |
+
# Generated tokens
|
| 144 |
+
class Token(BaseModel):
|
| 145 |
+
# Token ID from the model tokenizer
|
| 146 |
+
id: int
|
| 147 |
+
# Token text
|
| 148 |
+
text: str
|
| 149 |
+
# Logprob
|
| 150 |
+
logprob: float
|
| 151 |
+
# Is the token a special token
|
| 152 |
+
# Can be used to ignore tokens when concatenating
|
| 153 |
+
special: bool
|
| 154 |
+
|
| 155 |
+
|
| 156 |
+
# Generation finish reason
|
| 157 |
+
class FinishReason(Enum):
|
| 158 |
+
# number of generated tokens == `max_new_tokens`
|
| 159 |
+
Length = "length"
|
| 160 |
+
# the model generated its end of sequence token
|
| 161 |
+
EndOfSequenceToken = "eos_token"
|
| 162 |
+
# the model generated a text included in `stop_sequences`
|
| 163 |
+
StopSequence = "stop_sequence"
|
| 164 |
+
|
| 165 |
+
|
| 166 |
+
# Additional sequences when using the `best_of` parameter
|
| 167 |
+
class BestOfSequence(BaseModel):
|
| 168 |
+
# Generated text
|
| 169 |
+
generated_text: str
|
| 170 |
+
# Generation finish reason
|
| 171 |
+
finish_reason: FinishReason
|
| 172 |
+
# Number of generated tokens
|
| 173 |
+
generated_tokens: int
|
| 174 |
+
# Sampling seed if sampling was activated
|
| 175 |
+
seed: Optional[int]
|
| 176 |
+
# Prompt tokens
|
| 177 |
+
prefill: List[PrefillToken]
|
| 178 |
+
# Generated tokens
|
| 179 |
+
tokens: List[Token]
|
| 180 |
+
|
| 181 |
+
|
| 182 |
+
# `generate` details
|
| 183 |
+
class Details(BaseModel):
|
| 184 |
+
# Generation finish reason
|
| 185 |
+
finish_reason: FinishReason
|
| 186 |
+
# Number of generated tokens
|
| 187 |
+
generated_tokens: int
|
| 188 |
+
# Sampling seed if sampling was activated
|
| 189 |
+
seed: Optional[int]
|
| 190 |
+
# Prompt tokens
|
| 191 |
+
prefill: List[PrefillToken]
|
| 192 |
+
# Generated tokens
|
| 193 |
+
tokens: List[Token]
|
| 194 |
+
# Additional sequences when using the `best_of` parameter
|
| 195 |
+
best_of_sequences: Optional[List[BestOfSequence]]
|
| 196 |
+
|
| 197 |
+
|
| 198 |
+
# `generate` return value
|
| 199 |
+
class Response(BaseModel):
|
| 200 |
+
# Generated text
|
| 201 |
+
generated_text: str
|
| 202 |
+
# Generation details
|
| 203 |
+
details: Details
|
| 204 |
+
|
| 205 |
+
|
| 206 |
+
# `generate_stream` details
|
| 207 |
+
class StreamDetails(BaseModel):
|
| 208 |
+
# Generation finish reason
|
| 209 |
+
finish_reason: FinishReason
|
| 210 |
+
# Number of generated tokens
|
| 211 |
+
generated_tokens: int
|
| 212 |
+
# Sampling seed if sampling was activated
|
| 213 |
+
seed: Optional[int]
|
| 214 |
+
|
| 215 |
+
|
| 216 |
+
# `generate_stream` return value
|
| 217 |
+
class StreamResponse(BaseModel):
|
| 218 |
+
# Generated token
|
| 219 |
+
token: Token
|
| 220 |
+
# Complete generated text
|
| 221 |
+
# Only available when the generation is finished
|
| 222 |
+
generated_text: Optional[str]
|
| 223 |
+
# Generation details
|
| 224 |
+
# Only available when the generation is finished
|
| 225 |
+
details: Optional[StreamDetails]
|
| 226 |
+
|
| 227 |
+
|
| 228 |
+
# Inference API currently deployed model
|
| 229 |
+
class DeployedModel(BaseModel):
|
| 230 |
+
model_id: str
|
| 231 |
+
sha: str
|
docs/index.html
ADDED
|
@@ -0,0 +1,30 @@
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
<html>
|
| 2 |
+
<head>
|
| 3 |
+
<!-- Load the latest Swagger UI code and style from npm using unpkg.com -->
|
| 4 |
+
<script src="https://unpkg.com/swagger-ui-dist@3/swagger-ui-bundle.js"></script>
|
| 5 |
+
<link rel="stylesheet" type="text/css" href="https://unpkg.com/swagger-ui-dist@3/swagger-ui.css"/>
|
| 6 |
+
<title>Text Generation Inference API</title>
|
| 7 |
+
</head>
|
| 8 |
+
<body>
|
| 9 |
+
<div id="swagger-ui"></div> <!-- Div to hold the UI component -->
|
| 10 |
+
<script>
|
| 11 |
+
window.onload = function () {
|
| 12 |
+
// Begin Swagger UI call region
|
| 13 |
+
const ui = SwaggerUIBundle({
|
| 14 |
+
url: "openapi.json", //Location of Open API spec in the repo
|
| 15 |
+
dom_id: '#swagger-ui',
|
| 16 |
+
deepLinking: true,
|
| 17 |
+
supportedSubmitMethods: [],
|
| 18 |
+
presets: [
|
| 19 |
+
SwaggerUIBundle.presets.apis,
|
| 20 |
+
SwaggerUIBundle.SwaggerUIStandalonePreset
|
| 21 |
+
],
|
| 22 |
+
plugins: [
|
| 23 |
+
SwaggerUIBundle.plugins.DownloadUrl
|
| 24 |
+
],
|
| 25 |
+
})
|
| 26 |
+
window.ui = ui
|
| 27 |
+
}
|
| 28 |
+
</script>
|
| 29 |
+
</body>
|
| 30 |
+
</html>
|
docs/openapi.json
ADDED
|
@@ -0,0 +1,730 @@
|
|
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
{
|
| 2 |
+
"openapi": "3.0.3",
|
| 3 |
+
"info": {
|
| 4 |
+
"title": "Text Generation Inference",
|
| 5 |
+
"description": "Text Generation Webserver",
|
| 6 |
+
"contact": {
|
| 7 |
+
"name": "Olivier Dehaene"
|
| 8 |
+
},
|
| 9 |
+
"license": {
|
| 10 |
+
"name": "Apache 2.0",
|
| 11 |
+
"url": "https://www.apache.org/licenses/LICENSE-2.0"
|
| 12 |
+
},
|
| 13 |
+
"version": "0.6.0"
|
| 14 |
+
},
|
| 15 |
+
"paths": {
|
| 16 |
+
"/": {
|
| 17 |
+
"post": {
|
| 18 |
+
"tags": [
|
| 19 |
+
"Text Generation Inference"
|
| 20 |
+
],
|
| 21 |
+
"summary": "Generate tokens if `stream == false` or a stream of token if `stream == true`",
|
| 22 |
+
"description": "Generate tokens if `stream == false` or a stream of token if `stream == true`",
|
| 23 |
+
"operationId": "compat_generate",
|
| 24 |
+
"requestBody": {
|
| 25 |
+
"content": {
|
| 26 |
+
"application/json": {
|
| 27 |
+
"schema": {
|
| 28 |
+
"$ref": "#/components/schemas/CompatGenerateRequest"
|
| 29 |
+
}
|
| 30 |
+
}
|
| 31 |
+
},
|
| 32 |
+
"required": true
|
| 33 |
+
},
|
| 34 |
+
"responses": {
|
| 35 |
+
"200": {
|
| 36 |
+
"description": "See /generate or /generate_stream"
|
| 37 |
+
},
|
| 38 |
+
"422": {
|
| 39 |
+
"description": "Input validation error",
|
| 40 |
+
"content": {
|
| 41 |
+
"application/json": {
|
| 42 |
+
"schema": {
|
| 43 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 44 |
+
},
|
| 45 |
+
"example": {
|
| 46 |
+
"error": "Input validation error"
|
| 47 |
+
}
|
| 48 |
+
}
|
| 49 |
+
}
|
| 50 |
+
},
|
| 51 |
+
"424": {
|
| 52 |
+
"description": "Generation Error",
|
| 53 |
+
"content": {
|
| 54 |
+
"application/json": {
|
| 55 |
+
"schema": {
|
| 56 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 57 |
+
},
|
| 58 |
+
"example": {
|
| 59 |
+
"error": "Request failed during generation"
|
| 60 |
+
}
|
| 61 |
+
}
|
| 62 |
+
}
|
| 63 |
+
},
|
| 64 |
+
"429": {
|
| 65 |
+
"description": "Model is overloaded",
|
| 66 |
+
"content": {
|
| 67 |
+
"application/json": {
|
| 68 |
+
"schema": {
|
| 69 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 70 |
+
},
|
| 71 |
+
"example": {
|
| 72 |
+
"error": "Model is overloaded"
|
| 73 |
+
}
|
| 74 |
+
}
|
| 75 |
+
}
|
| 76 |
+
},
|
| 77 |
+
"500": {
|
| 78 |
+
"description": "Incomplete generation",
|
| 79 |
+
"content": {
|
| 80 |
+
"application/json": {
|
| 81 |
+
"schema": {
|
| 82 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 83 |
+
},
|
| 84 |
+
"example": {
|
| 85 |
+
"error": "Incomplete generation"
|
| 86 |
+
}
|
| 87 |
+
}
|
| 88 |
+
}
|
| 89 |
+
}
|
| 90 |
+
}
|
| 91 |
+
}
|
| 92 |
+
},
|
| 93 |
+
"/generate": {
|
| 94 |
+
"post": {
|
| 95 |
+
"tags": [
|
| 96 |
+
"Text Generation Inference"
|
| 97 |
+
],
|
| 98 |
+
"summary": "Generate tokens",
|
| 99 |
+
"description": "Generate tokens",
|
| 100 |
+
"operationId": "generate",
|
| 101 |
+
"requestBody": {
|
| 102 |
+
"content": {
|
| 103 |
+
"application/json": {
|
| 104 |
+
"schema": {
|
| 105 |
+
"$ref": "#/components/schemas/GenerateRequest"
|
| 106 |
+
}
|
| 107 |
+
}
|
| 108 |
+
},
|
| 109 |
+
"required": true
|
| 110 |
+
},
|
| 111 |
+
"responses": {
|
| 112 |
+
"200": {
|
| 113 |
+
"description": "Generated Text",
|
| 114 |
+
"content": {
|
| 115 |
+
"application/json": {
|
| 116 |
+
"schema": {
|
| 117 |
+
"$ref": "#/components/schemas/GenerateResponse"
|
| 118 |
+
}
|
| 119 |
+
}
|
| 120 |
+
}
|
| 121 |
+
},
|
| 122 |
+
"422": {
|
| 123 |
+
"description": "Input validation error",
|
| 124 |
+
"content": {
|
| 125 |
+
"application/json": {
|
| 126 |
+
"schema": {
|
| 127 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 128 |
+
},
|
| 129 |
+
"example": {
|
| 130 |
+
"error": "Input validation error"
|
| 131 |
+
}
|
| 132 |
+
}
|
| 133 |
+
}
|
| 134 |
+
},
|
| 135 |
+
"424": {
|
| 136 |
+
"description": "Generation Error",
|
| 137 |
+
"content": {
|
| 138 |
+
"application/json": {
|
| 139 |
+
"schema": {
|
| 140 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 141 |
+
},
|
| 142 |
+
"example": {
|
| 143 |
+
"error": "Request failed during generation"
|
| 144 |
+
}
|
| 145 |
+
}
|
| 146 |
+
}
|
| 147 |
+
},
|
| 148 |
+
"429": {
|
| 149 |
+
"description": "Model is overloaded",
|
| 150 |
+
"content": {
|
| 151 |
+
"application/json": {
|
| 152 |
+
"schema": {
|
| 153 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 154 |
+
},
|
| 155 |
+
"example": {
|
| 156 |
+
"error": "Model is overloaded"
|
| 157 |
+
}
|
| 158 |
+
}
|
| 159 |
+
}
|
| 160 |
+
},
|
| 161 |
+
"500": {
|
| 162 |
+
"description": "Incomplete generation",
|
| 163 |
+
"content": {
|
| 164 |
+
"application/json": {
|
| 165 |
+
"schema": {
|
| 166 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 167 |
+
},
|
| 168 |
+
"example": {
|
| 169 |
+
"error": "Incomplete generation"
|
| 170 |
+
}
|
| 171 |
+
}
|
| 172 |
+
}
|
| 173 |
+
}
|
| 174 |
+
}
|
| 175 |
+
}
|
| 176 |
+
},
|
| 177 |
+
"/generate_stream": {
|
| 178 |
+
"post": {
|
| 179 |
+
"tags": [
|
| 180 |
+
"Text Generation Inference"
|
| 181 |
+
],
|
| 182 |
+
"summary": "Generate a stream of token using Server-Sent Events",
|
| 183 |
+
"description": "Generate a stream of token using Server-Sent Events",
|
| 184 |
+
"operationId": "generate_stream",
|
| 185 |
+
"requestBody": {
|
| 186 |
+
"content": {
|
| 187 |
+
"application/json": {
|
| 188 |
+
"schema": {
|
| 189 |
+
"$ref": "#/components/schemas/GenerateRequest"
|
| 190 |
+
}
|
| 191 |
+
}
|
| 192 |
+
},
|
| 193 |
+
"required": true
|
| 194 |
+
},
|
| 195 |
+
"responses": {
|
| 196 |
+
"200": {
|
| 197 |
+
"description": "Generated Text",
|
| 198 |
+
"content": {
|
| 199 |
+
"text/event-stream": {
|
| 200 |
+
"schema": {
|
| 201 |
+
"$ref": "#/components/schemas/StreamResponse"
|
| 202 |
+
}
|
| 203 |
+
}
|
| 204 |
+
}
|
| 205 |
+
},
|
| 206 |
+
"422": {
|
| 207 |
+
"description": "Input validation error",
|
| 208 |
+
"content": {
|
| 209 |
+
"text/event-stream": {
|
| 210 |
+
"schema": {
|
| 211 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 212 |
+
},
|
| 213 |
+
"example": {
|
| 214 |
+
"error": "Input validation error"
|
| 215 |
+
}
|
| 216 |
+
}
|
| 217 |
+
}
|
| 218 |
+
},
|
| 219 |
+
"424": {
|
| 220 |
+
"description": "Generation Error",
|
| 221 |
+
"content": {
|
| 222 |
+
"text/event-stream": {
|
| 223 |
+
"schema": {
|
| 224 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 225 |
+
},
|
| 226 |
+
"example": {
|
| 227 |
+
"error": "Request failed during generation"
|
| 228 |
+
}
|
| 229 |
+
}
|
| 230 |
+
}
|
| 231 |
+
},
|
| 232 |
+
"429": {
|
| 233 |
+
"description": "Model is overloaded",
|
| 234 |
+
"content": {
|
| 235 |
+
"text/event-stream": {
|
| 236 |
+
"schema": {
|
| 237 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 238 |
+
},
|
| 239 |
+
"example": {
|
| 240 |
+
"error": "Model is overloaded"
|
| 241 |
+
}
|
| 242 |
+
}
|
| 243 |
+
}
|
| 244 |
+
},
|
| 245 |
+
"500": {
|
| 246 |
+
"description": "Incomplete generation",
|
| 247 |
+
"content": {
|
| 248 |
+
"text/event-stream": {
|
| 249 |
+
"schema": {
|
| 250 |
+
"$ref": "#/components/schemas/ErrorResponse"
|
| 251 |
+
},
|
| 252 |
+
"example": {
|
| 253 |
+
"error": "Incomplete generation"
|
| 254 |
+
}
|
| 255 |
+
}
|
| 256 |
+
}
|
| 257 |
+
}
|
| 258 |
+
}
|
| 259 |
+
}
|
| 260 |
+
},
|
| 261 |
+
"/info": {
|
| 262 |
+
"get": {
|
| 263 |
+
"tags": [
|
| 264 |
+
"Text Generation Inference"
|
| 265 |
+
],
|
| 266 |
+
"summary": "Text Generation Inference endpoint info",
|
| 267 |
+
"description": "Text Generation Inference endpoint info",
|
| 268 |
+
"operationId": "get_model_info",
|
| 269 |
+
"responses": {
|
| 270 |
+
"200": {
|
| 271 |
+
"description": "Served model info",
|
| 272 |
+
"content": {
|
| 273 |
+
"application/json": {
|
| 274 |
+
"schema": {
|
| 275 |
+
"$ref": "#/components/schemas/Info"
|
| 276 |
+
}
|
| 277 |
+
}
|
| 278 |
+
}
|
| 279 |
+
}
|
| 280 |
+
}
|
| 281 |
+
}
|
| 282 |
+
},
|
| 283 |
+
"/metrics": {
|
| 284 |
+
"get": {
|
| 285 |
+
"tags": [
|
| 286 |
+
"Text Generation Inference"
|
| 287 |
+
],
|
| 288 |
+
"summary": "Prometheus metrics scrape endpoint",
|
| 289 |
+
"description": "Prometheus metrics scrape endpoint",
|
| 290 |
+
"operationId": "metrics",
|
| 291 |
+
"responses": {
|
| 292 |
+
"200": {
|
| 293 |
+
"description": "Prometheus Metrics",
|
| 294 |
+
"content": {
|
| 295 |
+
"text/plain": {
|
| 296 |
+
"schema": {
|
| 297 |
+
"type": "string"
|
| 298 |
+
}
|
| 299 |
+
}
|
| 300 |
+
}
|
| 301 |
+
}
|
| 302 |
+
}
|
| 303 |
+
}
|
| 304 |
+
}
|
| 305 |
+
},
|
| 306 |
+
"components": {
|
| 307 |
+
"schemas": {
|
| 308 |
+
"BestOfSequence": {
|
| 309 |
+
"type": "object",
|
| 310 |
+
"required": [
|
| 311 |
+
"generated_text",
|
| 312 |
+
"finish_reason",
|
| 313 |
+
"generated_tokens",
|
| 314 |
+
"prefill",
|
| 315 |
+
"tokens"
|
| 316 |
+
],
|
| 317 |
+
"properties": {
|
| 318 |
+
"finish_reason": {
|
| 319 |
+
"$ref": "#/components/schemas/FinishReason"
|
| 320 |
+
},
|
| 321 |
+
"generated_text": {
|
| 322 |
+
"type": "string",
|
| 323 |
+
"example": "test"
|
| 324 |
+
},
|
| 325 |
+
"generated_tokens": {
|
| 326 |
+
"type": "integer",
|
| 327 |
+
"format": "int32",
|
| 328 |
+
"example": 1,
|
| 329 |
+
"minimum": 0.0
|
| 330 |
+
},
|
| 331 |
+
"prefill": {
|
| 332 |
+
"type": "array",
|
| 333 |
+
"items": {
|
| 334 |
+
"$ref": "#/components/schemas/PrefillToken"
|
| 335 |
+
}
|
| 336 |
+
},
|
| 337 |
+
"seed": {
|
| 338 |
+
"type": "integer",
|
| 339 |
+
"format": "int64",
|
| 340 |
+
"example": 42,
|
| 341 |
+
"nullable": true,
|
| 342 |
+
"minimum": 0.0
|
| 343 |
+
},
|
| 344 |
+
"tokens": {
|
| 345 |
+
"type": "array",
|
| 346 |
+
"items": {
|
| 347 |
+
"$ref": "#/components/schemas/Token"
|
| 348 |
+
}
|
| 349 |
+
}
|
| 350 |
+
}
|
| 351 |
+
},
|
| 352 |
+
"CompatGenerateRequest": {
|
| 353 |
+
"type": "object",
|
| 354 |
+
"required": [
|
| 355 |
+
"inputs"
|
| 356 |
+
],
|
| 357 |
+
"properties": {
|
| 358 |
+
"inputs": {
|
| 359 |
+
"type": "string",
|
| 360 |
+
"example": "My name is Olivier and I"
|
| 361 |
+
},
|
| 362 |
+
"parameters": {
|
| 363 |
+
"$ref": "#/components/schemas/GenerateParameters"
|
| 364 |
+
},
|
| 365 |
+
"stream": {
|
| 366 |
+
"type": "boolean"
|
| 367 |
+
}
|
| 368 |
+
}
|
| 369 |
+
},
|
| 370 |
+
"Details": {
|
| 371 |
+
"type": "object",
|
| 372 |
+
"required": [
|
| 373 |
+
"finish_reason",
|
| 374 |
+
"generated_tokens",
|
| 375 |
+
"prefill",
|
| 376 |
+
"tokens"
|
| 377 |
+
],
|
| 378 |
+
"properties": {
|
| 379 |
+
"best_of_sequences": {
|
| 380 |
+
"type": "array",
|
| 381 |
+
"items": {
|
| 382 |
+
"$ref": "#/components/schemas/BestOfSequence"
|
| 383 |
+
},
|
| 384 |
+
"nullable": true
|
| 385 |
+
},
|
| 386 |
+
"finish_reason": {
|
| 387 |
+
"$ref": "#/components/schemas/FinishReason"
|
| 388 |
+
},
|
| 389 |
+
"generated_tokens": {
|
| 390 |
+
"type": "integer",
|
| 391 |
+
"format": "int32",
|
| 392 |
+
"example": 1,
|
| 393 |
+
"minimum": 0.0
|
| 394 |
+
},
|
| 395 |
+
"prefill": {
|
| 396 |
+
"type": "array",
|
| 397 |
+
"items": {
|
| 398 |
+
"$ref": "#/components/schemas/PrefillToken"
|
| 399 |
+
}
|
| 400 |
+
},
|
| 401 |
+
"seed": {
|
| 402 |
+
"type": "integer",
|
| 403 |
+
"format": "int64",
|
| 404 |
+
"example": 42,
|
| 405 |
+
"nullable": true,
|
| 406 |
+
"minimum": 0.0
|
| 407 |
+
},
|
| 408 |
+
"tokens": {
|
| 409 |
+
"type": "array",
|
| 410 |
+
"items": {
|
| 411 |
+
"$ref": "#/components/schemas/Token"
|
| 412 |
+
}
|
| 413 |
+
}
|
| 414 |
+
}
|
| 415 |
+
},
|
| 416 |
+
"ErrorResponse": {
|
| 417 |
+
"type": "object",
|
| 418 |
+
"required": [
|
| 419 |
+
"error",
|
| 420 |
+
"error_type"
|
| 421 |
+
],
|
| 422 |
+
"properties": {
|
| 423 |
+
"error": {
|
| 424 |
+
"type": "string"
|
| 425 |
+
},
|
| 426 |
+
"error_type": {
|
| 427 |
+
"type": "string"
|
| 428 |
+
}
|
| 429 |
+
}
|
| 430 |
+
},
|
| 431 |
+
"FinishReason": {
|
| 432 |
+
"type": "string",
|
| 433 |
+
"enum": [
|
| 434 |
+
"length",
|
| 435 |
+
"eos_token",
|
| 436 |
+
"stop_sequence"
|
| 437 |
+
]
|
| 438 |
+
},
|
| 439 |
+
"GenerateParameters": {
|
| 440 |
+
"type": "object",
|
| 441 |
+
"properties": {
|
| 442 |
+
"best_of": {
|
| 443 |
+
"type": "integer",
|
| 444 |
+
"default": "null",
|
| 445 |
+
"example": 1,
|
| 446 |
+
"nullable": true,
|
| 447 |
+
"minimum": 0.0,
|
| 448 |
+
"exclusiveMinimum": 0.0
|
| 449 |
+
},
|
| 450 |
+
"details": {
|
| 451 |
+
"type": "boolean",
|
| 452 |
+
"default": "true"
|
| 453 |
+
},
|
| 454 |
+
"do_sample": {
|
| 455 |
+
"type": "boolean",
|
| 456 |
+
"default": "false",
|
| 457 |
+
"example": true
|
| 458 |
+
},
|
| 459 |
+
"max_new_tokens": {
|
| 460 |
+
"type": "integer",
|
| 461 |
+
"format": "int32",
|
| 462 |
+
"default": "20",
|
| 463 |
+
"minimum": 0.0,
|
| 464 |
+
"exclusiveMaximum": 512.0,
|
| 465 |
+
"exclusiveMinimum": 0.0
|
| 466 |
+
},
|
| 467 |
+
"repetition_penalty": {
|
| 468 |
+
"type": "number",
|
| 469 |
+
"format": "float",
|
| 470 |
+
"default": "null",
|
| 471 |
+
"example": 1.03,
|
| 472 |
+
"nullable": true,
|
| 473 |
+
"exclusiveMinimum": 0.0
|
| 474 |
+
},
|
| 475 |
+
"return_full_text": {
|
| 476 |
+
"type": "boolean",
|
| 477 |
+
"default": "null",
|
| 478 |
+
"example": false,
|
| 479 |
+
"nullable": true
|
| 480 |
+
},
|
| 481 |
+
"seed": {
|
| 482 |
+
"type": "integer",
|
| 483 |
+
"format": "int64",
|
| 484 |
+
"default": "null",
|
| 485 |
+
"example": "null",
|
| 486 |
+
"nullable": true,
|
| 487 |
+
"minimum": 0.0,
|
| 488 |
+
"exclusiveMinimum": 0.0
|
| 489 |
+
},
|
| 490 |
+
"stop": {
|
| 491 |
+
"type": "array",
|
| 492 |
+
"items": {
|
| 493 |
+
"type": "string"
|
| 494 |
+
},
|
| 495 |
+
"example": [
|
| 496 |
+
"photographer"
|
| 497 |
+
],
|
| 498 |
+
"maxItems": 4
|
| 499 |
+
},
|
| 500 |
+
"temperature": {
|
| 501 |
+
"type": "number",
|
| 502 |
+
"format": "float",
|
| 503 |
+
"default": "null",
|
| 504 |
+
"example": 0.5,
|
| 505 |
+
"nullable": true,
|
| 506 |
+
"exclusiveMinimum": 0.0
|
| 507 |
+
},
|
| 508 |
+
"top_k": {
|
| 509 |
+
"type": "integer",
|
| 510 |
+
"format": "int32",
|
| 511 |
+
"default": "null",
|
| 512 |
+
"example": 10,
|
| 513 |
+
"nullable": true,
|
| 514 |
+
"exclusiveMinimum": 0.0
|
| 515 |
+
},
|
| 516 |
+
"top_p": {
|
| 517 |
+
"type": "number",
|
| 518 |
+
"format": "float",
|
| 519 |
+
"default": "null",
|
| 520 |
+
"example": 0.95,
|
| 521 |
+
"nullable": true,
|
| 522 |
+
"maximum": 1.0,
|
| 523 |
+
"exclusiveMinimum": 0.0
|
| 524 |
+
},
|
| 525 |
+
"truncate": {
|
| 526 |
+
"type": "integer",
|
| 527 |
+
"default": "null",
|
| 528 |
+
"example": "null",
|
| 529 |
+
"nullable": true,
|
| 530 |
+
"minimum": 0.0
|
| 531 |
+
},
|
| 532 |
+
"typical_p": {
|
| 533 |
+
"type": "number",
|
| 534 |
+
"format": "float",
|
| 535 |
+
"default": "null",
|
| 536 |
+
"example": 0.95,
|
| 537 |
+
"nullable": true,
|
| 538 |
+
"maximum": 1.0,
|
| 539 |
+
"exclusiveMinimum": 0.0
|
| 540 |
+
},
|
| 541 |
+
"watermark": {
|
| 542 |
+
"type": "boolean",
|
| 543 |
+
"default": "false",
|
| 544 |
+
"example": true
|
| 545 |
+
}
|
| 546 |
+
}
|
| 547 |
+
},
|
| 548 |
+
"GenerateRequest": {
|
| 549 |
+
"type": "object",
|
| 550 |
+
"required": [
|
| 551 |
+
"inputs"
|
| 552 |
+
],
|
| 553 |
+
"properties": {
|
| 554 |
+
"inputs": {
|
| 555 |
+
"type": "string",
|
| 556 |
+
"example": "My name is Olivier and I"
|
| 557 |
+
},
|
| 558 |
+
"parameters": {
|
| 559 |
+
"$ref": "#/components/schemas/GenerateParameters"
|
| 560 |
+
}
|
| 561 |
+
}
|
| 562 |
+
},
|
| 563 |
+
"GenerateResponse": {
|
| 564 |
+
"type": "object",
|
| 565 |
+
"required": [
|
| 566 |
+
"generated_text"
|
| 567 |
+
],
|
| 568 |
+
"properties": {
|
| 569 |
+
"details": {
|
| 570 |
+
"allOf": [
|
| 571 |
+
{
|
| 572 |
+
"$ref": "#/components/schemas/Details"
|
| 573 |
+
}
|
| 574 |
+
],
|
| 575 |
+
"nullable": true
|
| 576 |
+
},
|
| 577 |
+
"generated_text": {
|
| 578 |
+
"type": "string",
|
| 579 |
+
"example": "test"
|
| 580 |
+
}
|
| 581 |
+
}
|
| 582 |
+
},
|
| 583 |
+
"Info": {
|
| 584 |
+
"type": "object",
|
| 585 |
+
"required": [
|
| 586 |
+
"model_id",
|
| 587 |
+
"version"
|
| 588 |
+
],
|
| 589 |
+
"properties": {
|
| 590 |
+
"model_id": {
|
| 591 |
+
"type": "string",
|
| 592 |
+
"example": "bigscience/blomm-560m"
|
| 593 |
+
},
|
| 594 |
+
"model_pipeline_tag": {
|
| 595 |
+
"type": "string",
|
| 596 |
+
"example": "text-generation",
|
| 597 |
+
"nullable": true
|
| 598 |
+
},
|
| 599 |
+
"model_sha": {
|
| 600 |
+
"type": "string",
|
| 601 |
+
"example": "e985a63cdc139290c5f700ff1929f0b5942cced2",
|
| 602 |
+
"nullable": true
|
| 603 |
+
},
|
| 604 |
+
"sha": {
|
| 605 |
+
"type": "string",
|
| 606 |
+
"example": "null",
|
| 607 |
+
"nullable": true
|
| 608 |
+
},
|
| 609 |
+
"version": {
|
| 610 |
+
"type": "string",
|
| 611 |
+
"example": "0.5.0"
|
| 612 |
+
}
|
| 613 |
+
}
|
| 614 |
+
},
|
| 615 |
+
"PrefillToken": {
|
| 616 |
+
"type": "object",
|
| 617 |
+
"required": [
|
| 618 |
+
"id",
|
| 619 |
+
"text",
|
| 620 |
+
"logprob"
|
| 621 |
+
],
|
| 622 |
+
"properties": {
|
| 623 |
+
"id": {
|
| 624 |
+
"type": "integer",
|
| 625 |
+
"format": "int32",
|
| 626 |
+
"example": 0,
|
| 627 |
+
"minimum": 0.0
|
| 628 |
+
},
|
| 629 |
+
"logprob": {
|
| 630 |
+
"type": "number",
|
| 631 |
+
"format": "float",
|
| 632 |
+
"example": -0.34,
|
| 633 |
+
"nullable": true
|
| 634 |
+
},
|
| 635 |
+
"text": {
|
| 636 |
+
"type": "string",
|
| 637 |
+
"example": "test"
|
| 638 |
+
}
|
| 639 |
+
}
|
| 640 |
+
},
|
| 641 |
+
"StreamDetails": {
|
| 642 |
+
"type": "object",
|
| 643 |
+
"required": [
|
| 644 |
+
"finish_reason",
|
| 645 |
+
"generated_tokens"
|
| 646 |
+
],
|
| 647 |
+
"properties": {
|
| 648 |
+
"finish_reason": {
|
| 649 |
+
"$ref": "#/components/schemas/FinishReason"
|
| 650 |
+
},
|
| 651 |
+
"generated_tokens": {
|
| 652 |
+
"type": "integer",
|
| 653 |
+
"format": "int32",
|
| 654 |
+
"example": 1,
|
| 655 |
+
"minimum": 0.0
|
| 656 |
+
},
|
| 657 |
+
"seed": {
|
| 658 |
+
"type": "integer",
|
| 659 |
+
"format": "int64",
|
| 660 |
+
"example": 42,
|
| 661 |
+
"nullable": true,
|
| 662 |
+
"minimum": 0.0
|
| 663 |
+
}
|
| 664 |
+
}
|
| 665 |
+
},
|
| 666 |
+
"StreamResponse": {
|
| 667 |
+
"type": "object",
|
| 668 |
+
"required": [
|
| 669 |
+
"token"
|
| 670 |
+
],
|
| 671 |
+
"properties": {
|
| 672 |
+
"details": {
|
| 673 |
+
"allOf": [
|
| 674 |
+
{
|
| 675 |
+
"$ref": "#/components/schemas/StreamDetails"
|
| 676 |
+
}
|
| 677 |
+
],
|
| 678 |
+
"nullable": true
|
| 679 |
+
},
|
| 680 |
+
"generated_text": {
|
| 681 |
+
"type": "string",
|
| 682 |
+
"default": "null",
|
| 683 |
+
"example": "test",
|
| 684 |
+
"nullable": true
|
| 685 |
+
},
|
| 686 |
+
"token": {
|
| 687 |
+
"$ref": "#/components/schemas/Token"
|
| 688 |
+
}
|
| 689 |
+
}
|
| 690 |
+
},
|
| 691 |
+
"Token": {
|
| 692 |
+
"type": "object",
|
| 693 |
+
"required": [
|
| 694 |
+
"id",
|
| 695 |
+
"text",
|
| 696 |
+
"logprob",
|
| 697 |
+
"special"
|
| 698 |
+
],
|
| 699 |
+
"properties": {
|
| 700 |
+
"id": {
|
| 701 |
+
"type": "integer",
|
| 702 |
+
"format": "int32",
|
| 703 |
+
"example": 0,
|
| 704 |
+
"minimum": 0.0
|
| 705 |
+
},
|
| 706 |
+
"logprob": {
|
| 707 |
+
"type": "number",
|
| 708 |
+
"format": "float",
|
| 709 |
+
"example": -0.34,
|
| 710 |
+
"nullable": true
|
| 711 |
+
},
|
| 712 |
+
"special": {
|
| 713 |
+
"type": "boolean",
|
| 714 |
+
"example": "false"
|
| 715 |
+
},
|
| 716 |
+
"text": {
|
| 717 |
+
"type": "string",
|
| 718 |
+
"example": "test"
|
| 719 |
+
}
|
| 720 |
+
}
|
| 721 |
+
}
|
| 722 |
+
}
|
| 723 |
+
},
|
| 724 |
+
"tags": [
|
| 725 |
+
{
|
| 726 |
+
"name": "Text Generation Inference",
|
| 727 |
+
"description": "Hugging Face Text Generation Inference API"
|
| 728 |
+
}
|
| 729 |
+
]
|
| 730 |
+
}
|
k6/load_test.js
ADDED
|
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import http from 'k6/http';
|
| 2 |
+
import {check, sleep} from 'k6';
|
| 3 |
+
|
| 4 |
+
export const options = {
|
| 5 |
+
stages: [
|
| 6 |
+
{duration: '1m', target: 50},
|
| 7 |
+
{duration: '2m', target: 100},
|
| 8 |
+
{duration: '1m', target: 0},
|
| 9 |
+
],
|
| 10 |
+
hosts: {
|
| 11 |
+
'text-generation-inference.huggingface.co': '127.0.0.1:3000',
|
| 12 |
+
},
|
| 13 |
+
};
|
| 14 |
+
const SLEEP_DURATION = 1;
|
| 15 |
+
|
| 16 |
+
function greedy_example(inputs, max_new_tokens, name) {
|
| 17 |
+
let body = JSON.stringify({
|
| 18 |
+
inputs: inputs,
|
| 19 |
+
parameters: {
|
| 20 |
+
max_new_tokens: max_new_tokens,
|
| 21 |
+
do_sample: false,
|
| 22 |
+
}
|
| 23 |
+
});
|
| 24 |
+
let params = {
|
| 25 |
+
headers: {
|
| 26 |
+
'Content-Type': 'application/json',
|
| 27 |
+
},
|
| 28 |
+
tags: {
|
| 29 |
+
name: name
|
| 30 |
+
}
|
| 31 |
+
};
|
| 32 |
+
return http.post('http://text-generation-inference.huggingface.co/generate', body, params);
|
| 33 |
+
}
|
| 34 |
+
|
| 35 |
+
function sample_example(inputs, max_new_tokens, name) {
|
| 36 |
+
let body = JSON.stringify({
|
| 37 |
+
inputs: inputs,
|
| 38 |
+
parameters: {
|
| 39 |
+
max_new_tokens: max_new_tokens,
|
| 40 |
+
do_sample: true,
|
| 41 |
+
top_p: 0.9,
|
| 42 |
+
seed: 0
|
| 43 |
+
}
|
| 44 |
+
});
|
| 45 |
+
let params = {
|
| 46 |
+
headers: {
|
| 47 |
+
'Content-Type': 'application/json',
|
| 48 |
+
},
|
| 49 |
+
tags: {
|
| 50 |
+
name: name
|
| 51 |
+
}
|
| 52 |
+
};
|
| 53 |
+
return http.post('http://text-generation-inference.huggingface.co/generate', body, params);
|
| 54 |
+
}
|
| 55 |
+
|
| 56 |
+
export default function () {
|
| 57 |
+
const response_1 = sample_example('A "whatpu" is a small, furry animal native to Tanzania. An example of a sentence that uses the word whatpu is: We were traveling in Africa and we saw these very cute whatpus. To do a "farduddle" means to jump up and down really fast. An example of a sentence that uses the word farduddle is:', 32, 'example-1');
|
| 58 |
+
check(response_1, {
|
| 59 |
+
'is status 200': (r) => r.status === 200,
|
| 60 |
+
});
|
| 61 |
+
sleep(SLEEP_DURATION);
|
| 62 |
+
|
| 63 |
+
const response_2 = sample_example("A poem about the beauty of science by Alfred Edgar Brittle\\nTitle: The Magic Craft\\nIn the old times", 50, "example-2");
|
| 64 |
+
check(response_2, {
|
| 65 |
+
'is status 200': (r) => r.status === 200,
|
| 66 |
+
});
|
| 67 |
+
sleep(SLEEP_DURATION);
|
| 68 |
+
|
| 69 |
+
const response_3 = greedy_example("استخراج العدد العاملي في لغة بايثون: ", 30, "example-3");
|
| 70 |
+
check(response_3, {
|
| 71 |
+
'is status 200': (r) => r.status === 200,
|
| 72 |
+
});
|
| 73 |
+
sleep(SLEEP_DURATION);
|
| 74 |
+
|
| 75 |
+
const response_4 = sample_example("Pour déguster un ortolan, il faut tout d'abord", 32, "example-4");
|
| 76 |
+
check(response_4, {
|
| 77 |
+
'is status 200': (r) => r.status === 200,
|
| 78 |
+
});
|
| 79 |
+
sleep(SLEEP_DURATION);
|
| 80 |
+
|
| 81 |
+
const response_5 = sample_example("Traduce español de España a español de Argentina\nEl coche es rojo - el auto es rojo\nEl ordenador es nuevo - la computadora es nueva\nel boligrafo es negro -", 16, "example-5");
|
| 82 |
+
check(response_5, {
|
| 83 |
+
'is status 200': (r) => r.status === 200,
|
| 84 |
+
});
|
| 85 |
+
sleep(SLEEP_DURATION);
|
| 86 |
+
|
| 87 |
+
const response_6 = sample_example("Question: If I put cheese into the fridge, will it melt?\nAnswer:", 32, "example-6");
|
| 88 |
+
check(response_6, {
|
| 89 |
+
'is status 200': (r) => r.status === 200,
|
| 90 |
+
});
|
| 91 |
+
sleep(SLEEP_DURATION);
|
| 92 |
+
|
| 93 |
+
const response_7 = greedy_example("Question: Where does the Greek Goddess Persephone spend half of the year when she is not with her mother?\nAnswer:", 24, "example-7");
|
| 94 |
+
check(response_7, {
|
| 95 |
+
'is status 200': (r) => r.status === 200,
|
| 96 |
+
});
|
| 97 |
+
sleep(SLEEP_DURATION);
|
| 98 |
+
}
|
launcher/Cargo.toml
ADDED
|
@@ -0,0 +1,22 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[package]
|
| 2 |
+
name = "text-generation-launcher"
|
| 3 |
+
version = "0.6.0"
|
| 4 |
+
edition = "2021"
|
| 5 |
+
authors = ["Olivier Dehaene"]
|
| 6 |
+
description = "Text Generation Launcher"
|
| 7 |
+
|
| 8 |
+
[dependencies]
|
| 9 |
+
clap = { version = "4.1.4", features = ["derive", "env"] }
|
| 10 |
+
ctrlc = { version = "3.2.5", features = ["termination"] }
|
| 11 |
+
serde = { version = "1.0.152", features = ["derive"] }
|
| 12 |
+
serde_json = "1.0.93"
|
| 13 |
+
subprocess = "0.2.9"
|
| 14 |
+
tracing = "0.1.37"
|
| 15 |
+
tracing-subscriber = { version = "0.3.16", features = ["json"] }
|
| 16 |
+
|
| 17 |
+
[dev-dependencies]
|
| 18 |
+
float_eq = "1.0.1"
|
| 19 |
+
reqwest = { version = "0.11.14", features = ["blocking", "json"] }
|
| 20 |
+
|
| 21 |
+
[build-dependencies]
|
| 22 |
+
vergen = { version = "8.0.0", features = ["build", "cargo", "git", "gitcl", "rustc", "si"] }
|
launcher/build.rs
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
use std::error::Error;
|
| 2 |
+
use vergen::EmitBuilder;
|
| 3 |
+
|
| 4 |
+
fn main() -> Result<(), Box<dyn Error>> {
|
| 5 |
+
// Emit cargo and rustc compile time values
|
| 6 |
+
EmitBuilder::builder().all_cargo().all_rustc().emit()?;
|
| 7 |
+
|
| 8 |
+
// Try to get the git sha from the local git repository
|
| 9 |
+
if EmitBuilder::builder()
|
| 10 |
+
.fail_on_error()
|
| 11 |
+
.git_sha(false)
|
| 12 |
+
.emit()
|
| 13 |
+
.is_err()
|
| 14 |
+
{
|
| 15 |
+
// Unable to get the git sha
|
| 16 |
+
if let Ok(sha) = std::env::var("GIT_SHA") {
|
| 17 |
+
// Set it from an env var
|
| 18 |
+
println!("cargo:rustc-env=VERGEN_GIT_SHA={sha}");
|
| 19 |
+
}
|
| 20 |
+
}
|
| 21 |
+
|
| 22 |
+
// Set docker label if present
|
| 23 |
+
if let Ok(label) = std::env::var("DOCKER_LABEL") {
|
| 24 |
+
// Set it from an env var
|
| 25 |
+
println!("cargo:rustc-env=DOCKER_LABEL={label}");
|
| 26 |
+
}
|
| 27 |
+
|
| 28 |
+
Ok(())
|
| 29 |
+
}
|
launcher/src/env_runtime.rs
ADDED
|
@@ -0,0 +1,45 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
use std::fmt;
|
| 2 |
+
use std::process::Command;
|
| 3 |
+
|
| 4 |
+
pub(crate) struct Env {
|
| 5 |
+
cargo_target: &'static str,
|
| 6 |
+
cargo_version: &'static str,
|
| 7 |
+
git_sha: &'static str,
|
| 8 |
+
docker_label: &'static str,
|
| 9 |
+
nvidia_env: String,
|
| 10 |
+
}
|
| 11 |
+
|
| 12 |
+
impl Env {
|
| 13 |
+
pub fn new() -> Self {
|
| 14 |
+
let nvidia_env = nvidia_smi();
|
| 15 |
+
|
| 16 |
+
Self {
|
| 17 |
+
nvidia_env: nvidia_env.unwrap_or("N/A".to_string()),
|
| 18 |
+
cargo_target: env!("VERGEN_CARGO_TARGET_TRIPLE"),
|
| 19 |
+
cargo_version: env!("VERGEN_RUSTC_SEMVER"),
|
| 20 |
+
git_sha: option_env!("VERGEN_GIT_SHA").unwrap_or("N/A"),
|
| 21 |
+
docker_label: option_env!("DOCKER_LABEL").unwrap_or("N/A"),
|
| 22 |
+
}
|
| 23 |
+
}
|
| 24 |
+
}
|
| 25 |
+
|
| 26 |
+
impl fmt::Display for Env {
|
| 27 |
+
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
| 28 |
+
writeln!(f, "Runtime environment:")?;
|
| 29 |
+
|
| 30 |
+
writeln!(f, "Target: {}", self.cargo_target)?;
|
| 31 |
+
writeln!(f, "Cargo version: {}", self.cargo_version)?;
|
| 32 |
+
writeln!(f, "Commit sha: {}", self.git_sha)?;
|
| 33 |
+
writeln!(f, "Docker label: {}", self.docker_label)?;
|
| 34 |
+
write!(f, "nvidia-smi:\n{}", self.nvidia_env)?;
|
| 35 |
+
|
| 36 |
+
Ok(())
|
| 37 |
+
}
|
| 38 |
+
}
|
| 39 |
+
|
| 40 |
+
fn nvidia_smi() -> Option<String> {
|
| 41 |
+
let output = Command::new("nvidia-smi").output().ok()?;
|
| 42 |
+
let nvidia_smi = String::from_utf8(output.stdout).ok()?;
|
| 43 |
+
let output = nvidia_smi.replace('\n', "\n ");
|
| 44 |
+
Some(output.trim().to_string())
|
| 45 |
+
}
|
launcher/src/main.rs
ADDED
|
@@ -0,0 +1,925 @@
|
|
|
|
|
|
|
|
|
|
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|
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|
| 1 |
+
use clap::Parser;
|
| 2 |
+
use serde::Deserialize;
|
| 3 |
+
use std::env;
|
| 4 |
+
use std::ffi::OsString;
|
| 5 |
+
use std::io::{BufRead, BufReader, Read};
|
| 6 |
+
use std::path::Path;
|
| 7 |
+
use std::sync::atomic::{AtomicBool, Ordering};
|
| 8 |
+
use std::sync::mpsc::TryRecvError;
|
| 9 |
+
use std::sync::Arc;
|
| 10 |
+
use std::sync::{mpsc, Mutex};
|
| 11 |
+
use std::thread;
|
| 12 |
+
use std::thread::sleep;
|
| 13 |
+
use std::time::{Duration, Instant};
|
| 14 |
+
use std::{fs, io};
|
| 15 |
+
use subprocess::{ExitStatus, Popen, PopenConfig, PopenError, Redirection};
|
| 16 |
+
|
| 17 |
+
mod env_runtime;
|
| 18 |
+
|
| 19 |
+
/// App Configuration
|
| 20 |
+
#[derive(Parser, Debug)]
|
| 21 |
+
#[clap(author, version, about, long_about = None)]
|
| 22 |
+
struct Args {
|
| 23 |
+
/// The name of the model to load.
|
| 24 |
+
/// Can be a MODEL_ID as listed on <https://hf.co/models> like
|
| 25 |
+
/// `gpt2` or `OpenAssistant/oasst-sft-1-pythia-12b`.
|
| 26 |
+
/// Or it can be a local directory containing the necessary files
|
| 27 |
+
/// as saved by `save_pretrained(...)` methods of transformers
|
| 28 |
+
#[clap(default_value = "bigscience/bloom-560m", long, env)]
|
| 29 |
+
model_id: String,
|
| 30 |
+
|
| 31 |
+
/// The actual revision of the model if you're referring to a model
|
| 32 |
+
/// on the hub. You can use a specific commit id or a branch like `refs/pr/2`.
|
| 33 |
+
#[clap(long, env)]
|
| 34 |
+
revision: Option<String>,
|
| 35 |
+
|
| 36 |
+
/// Wether to shard or not the model across multiple GPUs
|
| 37 |
+
/// By default text-generation-inference will use all available GPUs to run
|
| 38 |
+
/// the model. Setting it to `false` deactivates `num_shard`.
|
| 39 |
+
#[clap(long, env)]
|
| 40 |
+
sharded: Option<bool>,
|
| 41 |
+
|
| 42 |
+
/// The number of shards to use if you don't want to use all GPUs on a given machine.
|
| 43 |
+
/// You can use `CUDA_VISIBLE_DEVICE=0,1 text-generation-launcher... --num_shard 2`
|
| 44 |
+
/// and `CUDA_VISIBLE_DEVICE=2,3 text-generation-launcher... --num_shard 2` to
|
| 45 |
+
/// launch 2 copies with 2 shard each on a given machine with 4 GPUs for instance.
|
| 46 |
+
#[clap(long, env)]
|
| 47 |
+
num_shard: Option<usize>,
|
| 48 |
+
|
| 49 |
+
/// Wether you want the model to be quantized or not. This will use bitsandbytes for
|
| 50 |
+
/// quantization on the fly.
|
| 51 |
+
#[clap(long, env)]
|
| 52 |
+
quantize: bool,
|
| 53 |
+
|
| 54 |
+
/// The maximum amount of concurrent requests for this particular deployment.
|
| 55 |
+
/// Having a low limit will refuse clients requests instead of having them
|
| 56 |
+
/// wait for too long and is usually good to handle backpressure correctly.
|
| 57 |
+
#[clap(default_value = "128", long, env)]
|
| 58 |
+
max_concurrent_requests: usize,
|
| 59 |
+
|
| 60 |
+
/// This is the maximum allowed value for clients to set `best_of`.
|
| 61 |
+
/// Best of makes `n` generations at the same time, and return the best
|
| 62 |
+
/// in terms of overall log probability over the entire generated sequence
|
| 63 |
+
#[clap(default_value = "2", long, env)]
|
| 64 |
+
max_best_of: usize,
|
| 65 |
+
|
| 66 |
+
/// This is the maximum allowed value for clients to set `stop_sequences`.
|
| 67 |
+
/// Stop sequences are used to allow the model to stop on more than just
|
| 68 |
+
/// the EOS token, and enable more complex "prompting" where users can preprompt
|
| 69 |
+
/// the model in a specific way and define their "own" stop token aligned with
|
| 70 |
+
/// their prompt.
|
| 71 |
+
#[clap(default_value = "4", long, env)]
|
| 72 |
+
max_stop_sequences: usize,
|
| 73 |
+
|
| 74 |
+
/// This is the maximum allowed input length (expressed in number of tokens)
|
| 75 |
+
/// for users. The larger this value, the longer prompt users can send which
|
| 76 |
+
/// can impact the overall memory required to handle the load.
|
| 77 |
+
/// Please note that some models have a finite range of sequence they can handle.
|
| 78 |
+
#[clap(default_value = "1000", long, env)]
|
| 79 |
+
max_input_length: usize,
|
| 80 |
+
|
| 81 |
+
/// This is the most important value to set as it defines the "memory budget"
|
| 82 |
+
/// of running clients requests.
|
| 83 |
+
/// Clients will send input sequences and ask to generate `max_new_tokens`
|
| 84 |
+
/// on top. with a value of `1512` users can send either a prompt of
|
| 85 |
+
/// `1000` and ask for `512` new tokens, or send a prompt of `1` and ask for
|
| 86 |
+
/// `1511` max_new_tokens.
|
| 87 |
+
/// The larger this value, the larger amount each request will be in your RAM
|
| 88 |
+
/// and the less effective batching can be.
|
| 89 |
+
#[clap(default_value = "1512", long, env)]
|
| 90 |
+
max_total_tokens: usize,
|
| 91 |
+
|
| 92 |
+
/// The maximum allowed batch size during dynamic batching.
|
| 93 |
+
/// Using `max_batch_total_tokens` should be favored in general
|
| 94 |
+
/// as it's a finer way to control RAM usage.
|
| 95 |
+
#[clap(long, env)]
|
| 96 |
+
max_batch_size: Option<usize>,
|
| 97 |
+
|
| 98 |
+
/// This represents the ratio of waiting queries vs running queries where
|
| 99 |
+
/// you want to start considering pausing the running queries to include the waiting
|
| 100 |
+
/// ones into the same batch.
|
| 101 |
+
/// `waiting_served_ratio=1.2` Means when 12 queries are waiting and there's
|
| 102 |
+
/// only 10 queries left in the current batch we check if we can fit those 12
|
| 103 |
+
/// waiting queries into the batching strategy, and if yes, then batching happens
|
| 104 |
+
/// delaying the 10 running queries by a `prefill` run.
|
| 105 |
+
///
|
| 106 |
+
/// This setting is only applied if there is room in the batch
|
| 107 |
+
/// as defined by `max_batch_total_tokens`.
|
| 108 |
+
#[clap(default_value = "1.2", long, env)]
|
| 109 |
+
waiting_served_ratio: f32,
|
| 110 |
+
|
| 111 |
+
/// **IMPORTANT** This is one critical control to allow maximum usage
|
| 112 |
+
/// of the available hardware.
|
| 113 |
+
///
|
| 114 |
+
/// This represents the total amount of potential tokens within a batch.
|
| 115 |
+
/// When using padding (not recommended) this would be equivalent of
|
| 116 |
+
/// `batch_size` * `max_total_tokens`.
|
| 117 |
+
///
|
| 118 |
+
/// However in the non-padded (flash attention) version this can be much finer.
|
| 119 |
+
///
|
| 120 |
+
/// For `max_batch_total_tokens=1000`, you could fit `10` queries of `total_tokens=100`
|
| 121 |
+
/// or a single query of `1000` tokens.
|
| 122 |
+
///
|
| 123 |
+
/// So you don't have to control that finely
|
| 124 |
+
/// `max_batch_size` or `max_total_tokens`. In fact you could mostly relax them if you
|
| 125 |
+
/// want maximum flexibility. However, for your users if they are asking for the full amount of
|
| 126 |
+
/// total tokens, they are likely to wait for a very long time to get a spot
|
| 127 |
+
/// in the batch (since they are going to be alone) so setting `max_batch_size`
|
| 128 |
+
/// and `max_total_tokens` can still be useful to prevent those long waiting times.
|
| 129 |
+
///
|
| 130 |
+
/// Overall this number should be the largest possible amount that fits the
|
| 131 |
+
/// remaining memory (after the model is loaded). Since the actual memory overhead
|
| 132 |
+
/// depends on other parameters like if you're using quantization, flash attention
|
| 133 |
+
/// or the model implementation, text-generation-inference cannot infer this number
|
| 134 |
+
/// automatically.
|
| 135 |
+
#[clap(default_value = "32000", long, env)]
|
| 136 |
+
max_batch_total_tokens: u32,
|
| 137 |
+
|
| 138 |
+
/// This setting defines how many tokens can be passed before forcing the waiting
|
| 139 |
+
/// queries to be put on the batch (if the size of the batch allows for it).
|
| 140 |
+
/// New queries require 1 `prefill` forward, which is different from `decode`
|
| 141 |
+
/// and therefore you need to pause the running batch in order to run `prefill`
|
| 142 |
+
/// to create the correct values for the waiting queries to be able to join the batch.
|
| 143 |
+
///
|
| 144 |
+
/// With a value too small, queries will always "steal" the compute to run `prefill`
|
| 145 |
+
/// and running queries will be delayed by a lot.
|
| 146 |
+
///
|
| 147 |
+
/// With a value too big, waiting queries could wait for a very long time
|
| 148 |
+
/// before being allowed a slot in the running batch. If your server is busy
|
| 149 |
+
/// that means that requests that could run in ~2s on an empty server could
|
| 150 |
+
/// end up running in ~20s because the query had to wait for 18s.
|
| 151 |
+
///
|
| 152 |
+
/// This number is expressed in number of tokens to make it a bit more
|
| 153 |
+
/// "model" agnostic, but what should really matter is the overall latency
|
| 154 |
+
/// for end users.
|
| 155 |
+
#[clap(default_value = "20", long, env)]
|
| 156 |
+
max_waiting_tokens: usize,
|
| 157 |
+
#[clap(default_value = "3000", long, short, env)]
|
| 158 |
+
|
| 159 |
+
/// The port to listen on.
|
| 160 |
+
port: u16,
|
| 161 |
+
|
| 162 |
+
/// The name of the socket for gRPC communication between the webserver
|
| 163 |
+
/// and the shards.
|
| 164 |
+
#[clap(default_value = "/tmp/text-generation-server", long, env)]
|
| 165 |
+
shard_uds_path: String,
|
| 166 |
+
|
| 167 |
+
/// The address the master shard will listen on. (setting used by torch distributed)
|
| 168 |
+
#[clap(default_value = "localhost", long, env)]
|
| 169 |
+
master_addr: String,
|
| 170 |
+
|
| 171 |
+
/// The address the master port will listen on. (setting used by torch distributed)
|
| 172 |
+
#[clap(default_value = "29500", long, env)]
|
| 173 |
+
master_port: usize,
|
| 174 |
+
|
| 175 |
+
/// The location of the huggingface hub cache.
|
| 176 |
+
/// Used to override the location if you want to provide a mounted disk for instance
|
| 177 |
+
#[clap(long, env)]
|
| 178 |
+
huggingface_hub_cache: Option<String>,
|
| 179 |
+
|
| 180 |
+
/// The location of the huggingface hub cache.
|
| 181 |
+
/// Used to override the location if you want to provide a mounted disk for instance
|
| 182 |
+
#[clap(long, env)]
|
| 183 |
+
weights_cache_override: Option<String>,
|
| 184 |
+
|
| 185 |
+
/// For some models (like bloom), text-generation-inference implemented custom
|
| 186 |
+
/// cuda kernels to speed up inference. Those kernels were only tested on A100.
|
| 187 |
+
/// Use this flag to disable them if you're running on different hardware and
|
| 188 |
+
/// encounter issues.
|
| 189 |
+
#[clap(long, env)]
|
| 190 |
+
disable_custom_kernels: bool,
|
| 191 |
+
|
| 192 |
+
/// Outputs the logs in JSON format (useful for telemetry)
|
| 193 |
+
#[clap(long, env)]
|
| 194 |
+
json_output: bool,
|
| 195 |
+
|
| 196 |
+
#[clap(long, env)]
|
| 197 |
+
otlp_endpoint: Option<String>,
|
| 198 |
+
|
| 199 |
+
#[clap(long, env)]
|
| 200 |
+
cors_allow_origin: Vec<String>,
|
| 201 |
+
#[clap(long, env)]
|
| 202 |
+
watermark_gamma: Option<f32>,
|
| 203 |
+
#[clap(long, env)]
|
| 204 |
+
watermark_delta: Option<f32>,
|
| 205 |
+
|
| 206 |
+
/// Display a lot of information about your runtime environment
|
| 207 |
+
#[clap(long, short, action)]
|
| 208 |
+
env: bool,
|
| 209 |
+
}
|
| 210 |
+
|
| 211 |
+
#[derive(Debug)]
|
| 212 |
+
enum ShardStatus {
|
| 213 |
+
Ready,
|
| 214 |
+
Failed((usize, String)),
|
| 215 |
+
}
|
| 216 |
+
|
| 217 |
+
#[allow(clippy::too_many_arguments)]
|
| 218 |
+
fn shard_manager(
|
| 219 |
+
model_id: String,
|
| 220 |
+
revision: Option<String>,
|
| 221 |
+
quantize: bool,
|
| 222 |
+
uds_path: String,
|
| 223 |
+
rank: usize,
|
| 224 |
+
world_size: usize,
|
| 225 |
+
master_addr: String,
|
| 226 |
+
master_port: usize,
|
| 227 |
+
huggingface_hub_cache: Option<String>,
|
| 228 |
+
weights_cache_override: Option<String>,
|
| 229 |
+
disable_custom_kernels: bool,
|
| 230 |
+
watermark_gamma: Option<f32>,
|
| 231 |
+
watermark_delta: Option<f32>,
|
| 232 |
+
otlp_endpoint: Option<String>,
|
| 233 |
+
status_sender: mpsc::Sender<ShardStatus>,
|
| 234 |
+
shutdown: Arc<Mutex<bool>>,
|
| 235 |
+
_shutdown_sender: mpsc::Sender<()>,
|
| 236 |
+
) {
|
| 237 |
+
// Get UDS path
|
| 238 |
+
let uds_string = format!("{uds_path}-{rank}");
|
| 239 |
+
let uds = Path::new(&uds_string);
|
| 240 |
+
// Clean previous runs
|
| 241 |
+
fs::remove_file(uds).unwrap_or_default();
|
| 242 |
+
|
| 243 |
+
// Process args
|
| 244 |
+
let mut shard_argv = vec![
|
| 245 |
+
"text-generation-server".to_string(),
|
| 246 |
+
"serve".to_string(),
|
| 247 |
+
model_id,
|
| 248 |
+
"--uds-path".to_string(),
|
| 249 |
+
uds_path,
|
| 250 |
+
"--logger-level".to_string(),
|
| 251 |
+
"INFO".to_string(),
|
| 252 |
+
"--json-output".to_string(),
|
| 253 |
+
];
|
| 254 |
+
|
| 255 |
+
// Activate tensor parallelism
|
| 256 |
+
if world_size > 1 {
|
| 257 |
+
shard_argv.push("--sharded".to_string());
|
| 258 |
+
}
|
| 259 |
+
|
| 260 |
+
if quantize {
|
| 261 |
+
shard_argv.push("--quantize".to_string())
|
| 262 |
+
}
|
| 263 |
+
|
| 264 |
+
// Model optional revision
|
| 265 |
+
if let Some(revision) = revision {
|
| 266 |
+
shard_argv.push("--revision".to_string());
|
| 267 |
+
shard_argv.push(revision)
|
| 268 |
+
}
|
| 269 |
+
|
| 270 |
+
// OpenTelemetry
|
| 271 |
+
if let Some(otlp_endpoint) = otlp_endpoint {
|
| 272 |
+
shard_argv.push("--otlp-endpoint".to_string());
|
| 273 |
+
shard_argv.push(otlp_endpoint);
|
| 274 |
+
}
|
| 275 |
+
|
| 276 |
+
// Copy current process env
|
| 277 |
+
let mut env: Vec<(OsString, OsString)> = env::vars_os().collect();
|
| 278 |
+
|
| 279 |
+
// Torch Distributed Env vars
|
| 280 |
+
env.push(("RANK".into(), rank.to_string().into()));
|
| 281 |
+
env.push(("WORLD_SIZE".into(), world_size.to_string().into()));
|
| 282 |
+
env.push(("MASTER_ADDR".into(), master_addr.into()));
|
| 283 |
+
env.push(("MASTER_PORT".into(), master_port.to_string().into()));
|
| 284 |
+
env.push(("NCCL_ASYNC_ERROR_HANDLING".into(), "1".into()));
|
| 285 |
+
|
| 286 |
+
// Safetensors load fast
|
| 287 |
+
env.push(("SAFETENSORS_FAST_GPU".into(), "1".into()));
|
| 288 |
+
|
| 289 |
+
// Enable hf transfer for insane download speeds
|
| 290 |
+
let enable_hf_transfer = env::var("HF_HUB_ENABLE_HF_TRANSFER").unwrap_or("1".to_string());
|
| 291 |
+
env.push((
|
| 292 |
+
"HF_HUB_ENABLE_HF_TRANSFER".into(),
|
| 293 |
+
enable_hf_transfer.into(),
|
| 294 |
+
));
|
| 295 |
+
|
| 296 |
+
// Parse Inference API token
|
| 297 |
+
if let Ok(api_token) = env::var("HF_API_TOKEN") {
|
| 298 |
+
env.push(("HUGGING_FACE_HUB_TOKEN".into(), api_token.into()))
|
| 299 |
+
};
|
| 300 |
+
|
| 301 |
+
// If huggingface_hub_cache is some, pass it to the shard
|
| 302 |
+
// Useful when running inside a docker container
|
| 303 |
+
if let Some(huggingface_hub_cache) = huggingface_hub_cache {
|
| 304 |
+
env.push(("HUGGINGFACE_HUB_CACHE".into(), huggingface_hub_cache.into()));
|
| 305 |
+
};
|
| 306 |
+
|
| 307 |
+
// If weights_cache_override is some, pass it to the shard
|
| 308 |
+
// Useful when running inside a HuggingFace Inference Endpoint
|
| 309 |
+
if let Some(weights_cache_override) = weights_cache_override {
|
| 310 |
+
env.push((
|
| 311 |
+
"WEIGHTS_CACHE_OVERRIDE".into(),
|
| 312 |
+
weights_cache_override.into(),
|
| 313 |
+
));
|
| 314 |
+
};
|
| 315 |
+
|
| 316 |
+
// If disable_custom_kernels is true, pass it to the shard as an env var
|
| 317 |
+
if disable_custom_kernels {
|
| 318 |
+
env.push(("DISABLE_CUSTOM_KERNELS".into(), "True".into()))
|
| 319 |
+
}
|
| 320 |
+
|
| 321 |
+
// Watermark Gamma
|
| 322 |
+
if let Some(watermark_gamma) = watermark_gamma {
|
| 323 |
+
env.push(("WATERMARK_GAMMA".into(), watermark_gamma.to_string().into()))
|
| 324 |
+
}
|
| 325 |
+
|
| 326 |
+
// Watermark Delta
|
| 327 |
+
if let Some(watermark_delta) = watermark_delta {
|
| 328 |
+
env.push(("WATERMARK_DELTA".into(), watermark_delta.to_string().into()))
|
| 329 |
+
}
|
| 330 |
+
|
| 331 |
+
// Start process
|
| 332 |
+
tracing::info!("Starting shard {rank}");
|
| 333 |
+
let mut p = match Popen::create(
|
| 334 |
+
&shard_argv,
|
| 335 |
+
PopenConfig {
|
| 336 |
+
stdout: Redirection::Pipe,
|
| 337 |
+
stderr: Redirection::Pipe,
|
| 338 |
+
// Needed for the shutdown procedure
|
| 339 |
+
setpgid: true,
|
| 340 |
+
// NCCL env vars
|
| 341 |
+
env: Some(env),
|
| 342 |
+
..Default::default()
|
| 343 |
+
},
|
| 344 |
+
) {
|
| 345 |
+
Ok(p) => p,
|
| 346 |
+
Err(err) => {
|
| 347 |
+
if let PopenError::IoError(ref err) = err {
|
| 348 |
+
if err.kind() == io::ErrorKind::NotFound {
|
| 349 |
+
tracing::error!("text-generation-server not found in PATH");
|
| 350 |
+
tracing::error!("Please install it with `make install-server`")
|
| 351 |
+
}
|
| 352 |
+
}
|
| 353 |
+
status_sender
|
| 354 |
+
.send(ShardStatus::Failed((rank, err.to_string())))
|
| 355 |
+
.unwrap();
|
| 356 |
+
return;
|
| 357 |
+
}
|
| 358 |
+
};
|
| 359 |
+
|
| 360 |
+
// Redirect STDOUT to the console
|
| 361 |
+
let shard_stdout = p.stdout.take().unwrap();
|
| 362 |
+
|
| 363 |
+
thread::spawn(move || {
|
| 364 |
+
// Enter shard-manager tracing span
|
| 365 |
+
let stdout = BufReader::new(shard_stdout);
|
| 366 |
+
let _span = tracing::span!(tracing::Level::INFO, "shard-manager", rank = rank).entered();
|
| 367 |
+
for line in stdout.lines() {
|
| 368 |
+
// Parse loguru logs
|
| 369 |
+
if let Ok(log) = serde_json::from_str::<PythonLogMessage>(&line.unwrap()) {
|
| 370 |
+
log.trace();
|
| 371 |
+
}
|
| 372 |
+
}
|
| 373 |
+
});
|
| 374 |
+
|
| 375 |
+
let mut ready = false;
|
| 376 |
+
let start_time = Instant::now();
|
| 377 |
+
let mut wait_time = Instant::now();
|
| 378 |
+
loop {
|
| 379 |
+
// Process exited
|
| 380 |
+
if p.poll().is_some() {
|
| 381 |
+
let mut err = String::new();
|
| 382 |
+
p.stderr.take().unwrap().read_to_string(&mut err).unwrap();
|
| 383 |
+
status_sender
|
| 384 |
+
.send(ShardStatus::Failed((rank, err)))
|
| 385 |
+
.unwrap();
|
| 386 |
+
return;
|
| 387 |
+
}
|
| 388 |
+
|
| 389 |
+
// We received a shutdown signal
|
| 390 |
+
if *shutdown.lock().unwrap() {
|
| 391 |
+
p.terminate().unwrap();
|
| 392 |
+
let _ = p.wait_timeout(Duration::from_secs(90));
|
| 393 |
+
tracing::info!("Shard {rank} terminated");
|
| 394 |
+
return;
|
| 395 |
+
}
|
| 396 |
+
|
| 397 |
+
// Shard is ready
|
| 398 |
+
if uds.exists() && !ready {
|
| 399 |
+
tracing::info!("Shard {rank} ready in {:?}", start_time.elapsed());
|
| 400 |
+
status_sender.send(ShardStatus::Ready).unwrap();
|
| 401 |
+
ready = true;
|
| 402 |
+
} else if !ready && wait_time.elapsed() > Duration::from_secs(10) {
|
| 403 |
+
tracing::info!("Waiting for shard {rank} to be ready...");
|
| 404 |
+
wait_time = Instant::now();
|
| 405 |
+
}
|
| 406 |
+
sleep(Duration::from_millis(100));
|
| 407 |
+
}
|
| 408 |
+
}
|
| 409 |
+
|
| 410 |
+
fn shutdown_shards(shutdown: Arc<Mutex<bool>>, shutdown_receiver: &mpsc::Receiver<()>) {
|
| 411 |
+
tracing::info!("Shutting down shards");
|
| 412 |
+
// Update shutdown value to true
|
| 413 |
+
// This will be picked up by the shard manager
|
| 414 |
+
{
|
| 415 |
+
let mut shutdown = shutdown.lock().unwrap();
|
| 416 |
+
*shutdown = true;
|
| 417 |
+
}
|
| 418 |
+
|
| 419 |
+
// Wait for shards to shutdown
|
| 420 |
+
// This will block till all shutdown_sender are dropped
|
| 421 |
+
let _ = shutdown_receiver.recv();
|
| 422 |
+
}
|
| 423 |
+
|
| 424 |
+
fn num_cuda_devices() -> Option<usize> {
|
| 425 |
+
if let Ok(cuda_visible_devices) = env::var("CUDA_VISIBLE_DEVICES") {
|
| 426 |
+
let n_devices = cuda_visible_devices.split(',').count();
|
| 427 |
+
return Some(n_devices);
|
| 428 |
+
}
|
| 429 |
+
None
|
| 430 |
+
}
|
| 431 |
+
|
| 432 |
+
#[derive(Deserialize)]
|
| 433 |
+
#[serde(rename_all = "UPPERCASE")]
|
| 434 |
+
enum PythonLogLevelEnum {
|
| 435 |
+
Trace,
|
| 436 |
+
Debug,
|
| 437 |
+
Info,
|
| 438 |
+
Success,
|
| 439 |
+
Warning,
|
| 440 |
+
Error,
|
| 441 |
+
Critical,
|
| 442 |
+
}
|
| 443 |
+
|
| 444 |
+
#[derive(Deserialize)]
|
| 445 |
+
struct PythonLogLevel {
|
| 446 |
+
name: PythonLogLevelEnum,
|
| 447 |
+
}
|
| 448 |
+
|
| 449 |
+
#[derive(Deserialize)]
|
| 450 |
+
struct PythonLogRecord {
|
| 451 |
+
level: PythonLogLevel,
|
| 452 |
+
}
|
| 453 |
+
|
| 454 |
+
#[derive(Deserialize)]
|
| 455 |
+
struct PythonLogMessage {
|
| 456 |
+
text: String,
|
| 457 |
+
record: PythonLogRecord,
|
| 458 |
+
}
|
| 459 |
+
|
| 460 |
+
impl PythonLogMessage {
|
| 461 |
+
fn trace(&self) {
|
| 462 |
+
match self.record.level.name {
|
| 463 |
+
PythonLogLevelEnum::Trace => tracing::trace!("{}", self.text),
|
| 464 |
+
PythonLogLevelEnum::Debug => tracing::debug!("{}", self.text),
|
| 465 |
+
PythonLogLevelEnum::Info => tracing::info!("{}", self.text),
|
| 466 |
+
PythonLogLevelEnum::Success => tracing::info!("{}", self.text),
|
| 467 |
+
PythonLogLevelEnum::Warning => tracing::warn!("{}", self.text),
|
| 468 |
+
PythonLogLevelEnum::Error => tracing::error!("{}", self.text),
|
| 469 |
+
PythonLogLevelEnum::Critical => tracing::error!("{}", self.text),
|
| 470 |
+
}
|
| 471 |
+
}
|
| 472 |
+
}
|
| 473 |
+
|
| 474 |
+
fn find_num_shards(sharded: Option<bool>, num_shard: Option<usize>) -> usize {
|
| 475 |
+
// get the number of shards given `sharded` and `num_shard`
|
| 476 |
+
let num_shard = match (sharded, num_shard) {
|
| 477 |
+
(Some(true), None) => {
|
| 478 |
+
// try to default to the number of available GPUs
|
| 479 |
+
tracing::info!("Parsing num_shard from CUDA_VISIBLE_DEVICES");
|
| 480 |
+
let n_devices =
|
| 481 |
+
num_cuda_devices().expect("--num-shard and CUDA_VISIBLE_DEVICES are not set");
|
| 482 |
+
if n_devices <= 1 {
|
| 483 |
+
panic!("`sharded` is true but only found {n_devices} CUDA devices");
|
| 484 |
+
}
|
| 485 |
+
n_devices
|
| 486 |
+
}
|
| 487 |
+
(Some(true), Some(num_shard)) => {
|
| 488 |
+
// we can't have only one shard while sharded
|
| 489 |
+
if num_shard <= 1 {
|
| 490 |
+
panic!("`sharded` is true but `num_shard` <= 1");
|
| 491 |
+
}
|
| 492 |
+
num_shard
|
| 493 |
+
}
|
| 494 |
+
(Some(false), Some(num_shard)) => num_shard,
|
| 495 |
+
(Some(false), None) => 1,
|
| 496 |
+
(None, None) => num_cuda_devices().unwrap_or(1),
|
| 497 |
+
(None, Some(num_shard)) => num_shard,
|
| 498 |
+
};
|
| 499 |
+
if num_shard < 1 {
|
| 500 |
+
panic!("`num_shard` cannot be < 1");
|
| 501 |
+
}
|
| 502 |
+
num_shard
|
| 503 |
+
}
|
| 504 |
+
|
| 505 |
+
#[derive(Debug)]
|
| 506 |
+
enum LauncherError {
|
| 507 |
+
DownloadError,
|
| 508 |
+
ShardCannotStart,
|
| 509 |
+
ShardDisconnected,
|
| 510 |
+
ShardFailed,
|
| 511 |
+
WebserverFailed,
|
| 512 |
+
WebserverCannotStart,
|
| 513 |
+
}
|
| 514 |
+
|
| 515 |
+
fn download_model(args: &Args, running: Arc<AtomicBool>) -> Result<(), LauncherError> {
|
| 516 |
+
let mut download_argv = vec![
|
| 517 |
+
"text-generation-server".to_string(),
|
| 518 |
+
"download-weights".to_string(),
|
| 519 |
+
args.model_id.to_string(),
|
| 520 |
+
"--extension".to_string(),
|
| 521 |
+
".safetensors".to_string(),
|
| 522 |
+
"--logger-level".to_string(),
|
| 523 |
+
"INFO".to_string(),
|
| 524 |
+
"--json-output".to_string(),
|
| 525 |
+
];
|
| 526 |
+
|
| 527 |
+
// Model optional revision
|
| 528 |
+
if let Some(revision) = &args.revision {
|
| 529 |
+
download_argv.push("--revision".to_string());
|
| 530 |
+
download_argv.push(revision.to_string())
|
| 531 |
+
}
|
| 532 |
+
|
| 533 |
+
// Copy current process env
|
| 534 |
+
let mut env: Vec<(OsString, OsString)> = env::vars_os().collect();
|
| 535 |
+
|
| 536 |
+
// If huggingface_hub_cache is set, pass it to the shard
|
| 537 |
+
// Useful when running inside a docker container
|
| 538 |
+
if let Some(ref huggingface_hub_cache) = args.huggingface_hub_cache {
|
| 539 |
+
env.push(("HUGGINGFACE_HUB_CACHE".into(), huggingface_hub_cache.into()));
|
| 540 |
+
};
|
| 541 |
+
|
| 542 |
+
// Enable hf transfer for insane download speeds
|
| 543 |
+
let enable_hf_transfer = env::var("HF_HUB_ENABLE_HF_TRANSFER").unwrap_or("1".to_string());
|
| 544 |
+
env.push((
|
| 545 |
+
"HF_HUB_ENABLE_HF_TRANSFER".into(),
|
| 546 |
+
enable_hf_transfer.into(),
|
| 547 |
+
));
|
| 548 |
+
|
| 549 |
+
// Parse Inference API token
|
| 550 |
+
if let Ok(api_token) = env::var("HF_API_TOKEN") {
|
| 551 |
+
env.push(("HUGGING_FACE_HUB_TOKEN".into(), api_token.into()))
|
| 552 |
+
};
|
| 553 |
+
|
| 554 |
+
// Start process
|
| 555 |
+
tracing::info!("Starting download process.");
|
| 556 |
+
let mut download_process = match Popen::create(
|
| 557 |
+
&download_argv,
|
| 558 |
+
PopenConfig {
|
| 559 |
+
stdout: Redirection::Pipe,
|
| 560 |
+
stderr: Redirection::Pipe,
|
| 561 |
+
// Needed for the shutdown procedure
|
| 562 |
+
setpgid: true,
|
| 563 |
+
env: Some(env),
|
| 564 |
+
..Default::default()
|
| 565 |
+
},
|
| 566 |
+
) {
|
| 567 |
+
Ok(p) => p,
|
| 568 |
+
Err(err) => {
|
| 569 |
+
if let PopenError::IoError(ref err) = err {
|
| 570 |
+
if err.kind() == io::ErrorKind::NotFound {
|
| 571 |
+
tracing::error!("text-generation-server not found in PATH");
|
| 572 |
+
tracing::error!("Please install it with `make install-server`")
|
| 573 |
+
}
|
| 574 |
+
}
|
| 575 |
+
return Err(LauncherError::DownloadError);
|
| 576 |
+
}
|
| 577 |
+
};
|
| 578 |
+
|
| 579 |
+
// Redirect STDOUT to the console
|
| 580 |
+
let download_stdout = download_process.stdout.take().unwrap();
|
| 581 |
+
thread::spawn(move || {
|
| 582 |
+
// Enter download tracing span
|
| 583 |
+
let stdout = BufReader::new(download_stdout);
|
| 584 |
+
let _span = tracing::span!(tracing::Level::INFO, "download").entered();
|
| 585 |
+
for line in stdout.lines() {
|
| 586 |
+
// Parse loguru logs
|
| 587 |
+
if let Ok(log) = serde_json::from_str::<PythonLogMessage>(&line.unwrap()) {
|
| 588 |
+
log.trace();
|
| 589 |
+
}
|
| 590 |
+
}
|
| 591 |
+
});
|
| 592 |
+
|
| 593 |
+
loop {
|
| 594 |
+
if let Some(status) = download_process.poll() {
|
| 595 |
+
match status {
|
| 596 |
+
ExitStatus::Exited(exit_code) => {
|
| 597 |
+
if exit_code == 0 {
|
| 598 |
+
tracing::info!("Successfully downloaded weights.");
|
| 599 |
+
break;
|
| 600 |
+
} else {
|
| 601 |
+
let mut err = String::new();
|
| 602 |
+
download_process
|
| 603 |
+
.stderr
|
| 604 |
+
.take()
|
| 605 |
+
.unwrap()
|
| 606 |
+
.read_to_string(&mut err)
|
| 607 |
+
.unwrap();
|
| 608 |
+
tracing::error!("Download encountered an error: {err}");
|
| 609 |
+
return Err(LauncherError::DownloadError);
|
| 610 |
+
}
|
| 611 |
+
}
|
| 612 |
+
_ => {
|
| 613 |
+
tracing::error!("Download process exited with an unknown status.");
|
| 614 |
+
return Err(LauncherError::DownloadError);
|
| 615 |
+
}
|
| 616 |
+
}
|
| 617 |
+
}
|
| 618 |
+
if !running.load(Ordering::SeqCst) {
|
| 619 |
+
download_process.terminate().unwrap();
|
| 620 |
+
tracing::info!("Waiting for download process to gracefully shutdown");
|
| 621 |
+
download_process
|
| 622 |
+
.wait_timeout(Duration::from_secs(90))
|
| 623 |
+
.unwrap();
|
| 624 |
+
tracing::info!("Download process terminated");
|
| 625 |
+
return Ok(());
|
| 626 |
+
}
|
| 627 |
+
sleep(Duration::from_millis(100));
|
| 628 |
+
}
|
| 629 |
+
Ok(())
|
| 630 |
+
}
|
| 631 |
+
|
| 632 |
+
#[allow(clippy::too_many_arguments)]
|
| 633 |
+
fn spawn_shards(
|
| 634 |
+
num_shard: usize,
|
| 635 |
+
args: &Args,
|
| 636 |
+
shutdown: Arc<Mutex<bool>>,
|
| 637 |
+
shutdown_receiver: &mpsc::Receiver<()>,
|
| 638 |
+
shutdown_sender: mpsc::Sender<()>,
|
| 639 |
+
status_receiver: &mpsc::Receiver<ShardStatus>,
|
| 640 |
+
status_sender: mpsc::Sender<ShardStatus>,
|
| 641 |
+
running: Arc<AtomicBool>,
|
| 642 |
+
) -> Result<(), LauncherError> {
|
| 643 |
+
// Start shard processes
|
| 644 |
+
for rank in 0..num_shard {
|
| 645 |
+
let model_id = args.model_id.clone();
|
| 646 |
+
let revision = args.revision.clone();
|
| 647 |
+
let uds_path = args.shard_uds_path.clone();
|
| 648 |
+
let master_addr = args.master_addr.clone();
|
| 649 |
+
let huggingface_hub_cache = args.huggingface_hub_cache.clone();
|
| 650 |
+
let weights_cache_override = args.weights_cache_override.clone();
|
| 651 |
+
let status_sender = status_sender.clone();
|
| 652 |
+
let shutdown = shutdown.clone();
|
| 653 |
+
let shutdown_sender = shutdown_sender.clone();
|
| 654 |
+
let otlp_endpoint = args.otlp_endpoint.clone();
|
| 655 |
+
let quantize = args.quantize;
|
| 656 |
+
let master_port = args.master_port;
|
| 657 |
+
let disable_custom_kernels = args.disable_custom_kernels;
|
| 658 |
+
let watermark_gamma = args.watermark_gamma;
|
| 659 |
+
let watermark_delta = args.watermark_delta;
|
| 660 |
+
thread::spawn(move || {
|
| 661 |
+
shard_manager(
|
| 662 |
+
model_id,
|
| 663 |
+
revision,
|
| 664 |
+
quantize,
|
| 665 |
+
uds_path,
|
| 666 |
+
rank,
|
| 667 |
+
num_shard,
|
| 668 |
+
master_addr,
|
| 669 |
+
master_port,
|
| 670 |
+
huggingface_hub_cache,
|
| 671 |
+
weights_cache_override,
|
| 672 |
+
disable_custom_kernels,
|
| 673 |
+
watermark_gamma,
|
| 674 |
+
watermark_delta,
|
| 675 |
+
otlp_endpoint,
|
| 676 |
+
status_sender,
|
| 677 |
+
shutdown,
|
| 678 |
+
shutdown_sender,
|
| 679 |
+
)
|
| 680 |
+
});
|
| 681 |
+
}
|
| 682 |
+
drop(shutdown_sender);
|
| 683 |
+
|
| 684 |
+
// Wait for shard to start
|
| 685 |
+
let mut shard_ready = 0;
|
| 686 |
+
while running.load(Ordering::SeqCst) {
|
| 687 |
+
match status_receiver.try_recv() {
|
| 688 |
+
Ok(ShardStatus::Ready) => {
|
| 689 |
+
shard_ready += 1;
|
| 690 |
+
if shard_ready == num_shard {
|
| 691 |
+
break;
|
| 692 |
+
}
|
| 693 |
+
}
|
| 694 |
+
Err(TryRecvError::Empty) => {
|
| 695 |
+
sleep(Duration::from_millis(100));
|
| 696 |
+
}
|
| 697 |
+
Ok(ShardStatus::Failed((rank, err))) => {
|
| 698 |
+
tracing::error!("Shard {} failed to start:\n{}", rank, err);
|
| 699 |
+
shutdown_shards(shutdown, shutdown_receiver);
|
| 700 |
+
return Err(LauncherError::ShardCannotStart);
|
| 701 |
+
}
|
| 702 |
+
Err(TryRecvError::Disconnected) => {
|
| 703 |
+
tracing::error!("Shard status channel disconnected");
|
| 704 |
+
shutdown_shards(shutdown, shutdown_receiver);
|
| 705 |
+
return Err(LauncherError::ShardDisconnected);
|
| 706 |
+
}
|
| 707 |
+
}
|
| 708 |
+
}
|
| 709 |
+
Ok(())
|
| 710 |
+
}
|
| 711 |
+
|
| 712 |
+
fn spawn_webserver(
|
| 713 |
+
args: Args,
|
| 714 |
+
shutdown: Arc<Mutex<bool>>,
|
| 715 |
+
shutdown_receiver: &mpsc::Receiver<()>,
|
| 716 |
+
) -> Result<Popen, LauncherError> {
|
| 717 |
+
// All shard started
|
| 718 |
+
// Start webserver
|
| 719 |
+
tracing::info!("Starting Webserver");
|
| 720 |
+
let mut argv = vec![
|
| 721 |
+
"text-generation-router".to_string(),
|
| 722 |
+
"--max-concurrent-requests".to_string(),
|
| 723 |
+
args.max_concurrent_requests.to_string(),
|
| 724 |
+
"--max-best-of".to_string(),
|
| 725 |
+
args.max_best_of.to_string(),
|
| 726 |
+
"--max-stop-sequences".to_string(),
|
| 727 |
+
args.max_stop_sequences.to_string(),
|
| 728 |
+
"--max-input-length".to_string(),
|
| 729 |
+
args.max_input_length.to_string(),
|
| 730 |
+
"--max-total-tokens".to_string(),
|
| 731 |
+
args.max_total_tokens.to_string(),
|
| 732 |
+
"--waiting-served-ratio".to_string(),
|
| 733 |
+
args.waiting_served_ratio.to_string(),
|
| 734 |
+
"--max-waiting-tokens".to_string(),
|
| 735 |
+
args.max_waiting_tokens.to_string(),
|
| 736 |
+
"--port".to_string(),
|
| 737 |
+
args.port.to_string(),
|
| 738 |
+
"--master-shard-uds-path".to_string(),
|
| 739 |
+
format!("{}-0", args.shard_uds_path),
|
| 740 |
+
"--tokenizer-name".to_string(),
|
| 741 |
+
args.model_id,
|
| 742 |
+
];
|
| 743 |
+
|
| 744 |
+
// Deprecate max_batch_size
|
| 745 |
+
if let Some(max_batch_size) = args.max_batch_size {
|
| 746 |
+
argv.push("--max-batch-size".to_string());
|
| 747 |
+
argv.push(max_batch_size.to_string())
|
| 748 |
+
} else {
|
| 749 |
+
argv.push("--max-batch-total-tokens".to_string());
|
| 750 |
+
argv.push(args.max_batch_total_tokens.to_string())
|
| 751 |
+
}
|
| 752 |
+
|
| 753 |
+
// Model optional revision
|
| 754 |
+
if let Some(ref revision) = args.revision {
|
| 755 |
+
argv.push("--revision".to_string());
|
| 756 |
+
argv.push(revision.to_string())
|
| 757 |
+
}
|
| 758 |
+
|
| 759 |
+
if args.json_output {
|
| 760 |
+
argv.push("--json-output".to_string());
|
| 761 |
+
}
|
| 762 |
+
|
| 763 |
+
// OpenTelemetry
|
| 764 |
+
if let Some(otlp_endpoint) = args.otlp_endpoint {
|
| 765 |
+
argv.push("--otlp-endpoint".to_string());
|
| 766 |
+
argv.push(otlp_endpoint);
|
| 767 |
+
}
|
| 768 |
+
|
| 769 |
+
// CORS origins
|
| 770 |
+
for origin in args.cors_allow_origin.into_iter() {
|
| 771 |
+
argv.push("--cors-allow-origin".to_string());
|
| 772 |
+
argv.push(origin);
|
| 773 |
+
}
|
| 774 |
+
|
| 775 |
+
// Copy current process env
|
| 776 |
+
let mut env: Vec<(OsString, OsString)> = env::vars_os().collect();
|
| 777 |
+
|
| 778 |
+
// Parse Inference API token
|
| 779 |
+
if let Ok(api_token) = env::var("HF_API_TOKEN") {
|
| 780 |
+
env.push(("HUGGING_FACE_HUB_TOKEN".into(), api_token.into()))
|
| 781 |
+
};
|
| 782 |
+
|
| 783 |
+
let mut webserver = match Popen::create(
|
| 784 |
+
&argv,
|
| 785 |
+
PopenConfig {
|
| 786 |
+
stdout: Redirection::Pipe,
|
| 787 |
+
stderr: Redirection::Pipe,
|
| 788 |
+
// Needed for the shutdown procedure
|
| 789 |
+
setpgid: true,
|
| 790 |
+
env: Some(env),
|
| 791 |
+
..Default::default()
|
| 792 |
+
},
|
| 793 |
+
) {
|
| 794 |
+
Ok(p) => p,
|
| 795 |
+
Err(err) => {
|
| 796 |
+
tracing::error!("Failed to start webserver: {}", err);
|
| 797 |
+
if let PopenError::IoError(err) = err {
|
| 798 |
+
if err.kind() == io::ErrorKind::NotFound {
|
| 799 |
+
tracing::error!("text-generation-router not found in PATH");
|
| 800 |
+
tracing::error!("Please install it with `make install-router`")
|
| 801 |
+
}
|
| 802 |
+
} else {
|
| 803 |
+
tracing::error!("{}", err);
|
| 804 |
+
}
|
| 805 |
+
|
| 806 |
+
shutdown_shards(shutdown, shutdown_receiver);
|
| 807 |
+
return Err(LauncherError::WebserverCannotStart);
|
| 808 |
+
}
|
| 809 |
+
};
|
| 810 |
+
|
| 811 |
+
// Redirect STDOUT and STDERR to the console
|
| 812 |
+
let webserver_stdout = webserver.stdout.take().unwrap();
|
| 813 |
+
let webserver_stderr = webserver.stderr.take().unwrap();
|
| 814 |
+
|
| 815 |
+
thread::spawn(move || {
|
| 816 |
+
let stdout = BufReader::new(webserver_stdout);
|
| 817 |
+
let stderr = BufReader::new(webserver_stderr);
|
| 818 |
+
for line in stdout.lines() {
|
| 819 |
+
println!("{}", line.unwrap());
|
| 820 |
+
}
|
| 821 |
+
for line in stderr.lines() {
|
| 822 |
+
println!("{}", line.unwrap());
|
| 823 |
+
}
|
| 824 |
+
});
|
| 825 |
+
Ok(webserver)
|
| 826 |
+
}
|
| 827 |
+
|
| 828 |
+
fn main() -> Result<(), LauncherError> {
|
| 829 |
+
// Pattern match configuration
|
| 830 |
+
let args = Args::parse();
|
| 831 |
+
|
| 832 |
+
if args.json_output {
|
| 833 |
+
tracing_subscriber::fmt().json().init();
|
| 834 |
+
} else {
|
| 835 |
+
tracing_subscriber::fmt().compact().init();
|
| 836 |
+
}
|
| 837 |
+
|
| 838 |
+
if args.env {
|
| 839 |
+
let env_runtime = env_runtime::Env::new();
|
| 840 |
+
tracing::info!("{}", env_runtime);
|
| 841 |
+
}
|
| 842 |
+
|
| 843 |
+
tracing::info!("{:?}", args);
|
| 844 |
+
|
| 845 |
+
let num_shard = find_num_shards(args.sharded, args.num_shard);
|
| 846 |
+
if num_shard > 1 {
|
| 847 |
+
tracing::info!("Sharding model on {num_shard} processes");
|
| 848 |
+
}
|
| 849 |
+
|
| 850 |
+
// Signal handler
|
| 851 |
+
let running = Arc::new(AtomicBool::new(true));
|
| 852 |
+
let r = running.clone();
|
| 853 |
+
ctrlc::set_handler(move || {
|
| 854 |
+
r.store(false, Ordering::SeqCst);
|
| 855 |
+
})
|
| 856 |
+
.expect("Error setting Ctrl-C handler");
|
| 857 |
+
|
| 858 |
+
// Check if model_id is a local model
|
| 859 |
+
let local_path = Path::new(&args.model_id);
|
| 860 |
+
let is_local_model = local_path.exists() && local_path.is_dir();
|
| 861 |
+
|
| 862 |
+
// Download weights for sharded models
|
| 863 |
+
if !is_local_model && args.weights_cache_override.is_none() && num_shard > 1 {
|
| 864 |
+
download_model(&args, running.clone())?;
|
| 865 |
+
}
|
| 866 |
+
|
| 867 |
+
// Shared shutdown bool
|
| 868 |
+
let shutdown = Arc::new(Mutex::new(false));
|
| 869 |
+
// Shared shutdown channel
|
| 870 |
+
// When shutting down, the main thread will wait for all senders to be dropped
|
| 871 |
+
let (shutdown_sender, shutdown_receiver) = mpsc::channel();
|
| 872 |
+
|
| 873 |
+
// Shared channel to track shard status
|
| 874 |
+
let (status_sender, status_receiver) = mpsc::channel();
|
| 875 |
+
|
| 876 |
+
spawn_shards(
|
| 877 |
+
num_shard,
|
| 878 |
+
&args,
|
| 879 |
+
shutdown.clone(),
|
| 880 |
+
&shutdown_receiver,
|
| 881 |
+
shutdown_sender,
|
| 882 |
+
&status_receiver,
|
| 883 |
+
status_sender,
|
| 884 |
+
running.clone(),
|
| 885 |
+
)?;
|
| 886 |
+
|
| 887 |
+
// We might have received a termination signal
|
| 888 |
+
if !running.load(Ordering::SeqCst) {
|
| 889 |
+
shutdown_shards(shutdown, &shutdown_receiver);
|
| 890 |
+
return Ok(());
|
| 891 |
+
}
|
| 892 |
+
|
| 893 |
+
let mut webserver = spawn_webserver(args, shutdown.clone(), &shutdown_receiver)?;
|
| 894 |
+
|
| 895 |
+
// Default exit code
|
| 896 |
+
let mut exit_code = Ok(());
|
| 897 |
+
|
| 898 |
+
while running.load(Ordering::SeqCst) {
|
| 899 |
+
if let Ok(ShardStatus::Failed((rank, err))) = status_receiver.try_recv() {
|
| 900 |
+
tracing::error!("Shard {rank} failed:\n{err}");
|
| 901 |
+
exit_code = Err(LauncherError::ShardFailed);
|
| 902 |
+
break;
|
| 903 |
+
};
|
| 904 |
+
|
| 905 |
+
match webserver.poll() {
|
| 906 |
+
Some(_) => {
|
| 907 |
+
tracing::error!("Webserver Crashed");
|
| 908 |
+
shutdown_shards(shutdown, &shutdown_receiver);
|
| 909 |
+
return Err(LauncherError::WebserverFailed);
|
| 910 |
+
}
|
| 911 |
+
None => {
|
| 912 |
+
sleep(Duration::from_millis(100));
|
| 913 |
+
}
|
| 914 |
+
};
|
| 915 |
+
}
|
| 916 |
+
|
| 917 |
+
// Graceful termination
|
| 918 |
+
webserver.terminate().unwrap();
|
| 919 |
+
tracing::info!("Waiting for webserver to gracefully shutdown");
|
| 920 |
+
webserver.wait_timeout(Duration::from_secs(90)).unwrap();
|
| 921 |
+
tracing::info!("Webserver terminated");
|
| 922 |
+
shutdown_shards(shutdown, &shutdown_receiver);
|
| 923 |
+
|
| 924 |
+
exit_code
|
| 925 |
+
}
|
launcher/tests/bloom_560m.json
ADDED
|
@@ -0,0 +1,142 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"generated_text": ".get(\"action\");\n if (action == null) {\n throw new RuntimeException",
|
| 3 |
+
"details": {
|
| 4 |
+
"finish_reason": "length",
|
| 5 |
+
"generated_tokens": 20,
|
| 6 |
+
"seed": null,
|
| 7 |
+
"prefill": [
|
| 8 |
+
{
|
| 9 |
+
"id": 10264,
|
| 10 |
+
"text": "Test",
|
| 11 |
+
"logprob": null
|
| 12 |
+
},
|
| 13 |
+
{
|
| 14 |
+
"id": 8821,
|
| 15 |
+
"text": " request",
|
| 16 |
+
"logprob": -11.894989
|
| 17 |
+
}
|
| 18 |
+
],
|
| 19 |
+
"tokens": [
|
| 20 |
+
{
|
| 21 |
+
"id": 17,
|
| 22 |
+
"text": ".",
|
| 23 |
+
"logprob": -1.8267672,
|
| 24 |
+
"special": false
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
"id": 1587,
|
| 28 |
+
"text": "get",
|
| 29 |
+
"logprob": -2.4674969,
|
| 30 |
+
"special": false
|
| 31 |
+
},
|
| 32 |
+
{
|
| 33 |
+
"id": 11,
|
| 34 |
+
"text": "(",
|
| 35 |
+
"logprob": -1.906001,
|
| 36 |
+
"special": false
|
| 37 |
+
},
|
| 38 |
+
{
|
| 39 |
+
"id": 5,
|
| 40 |
+
"text": "\"",
|
| 41 |
+
"logprob": -1.2279545,
|
| 42 |
+
"special": false
|
| 43 |
+
},
|
| 44 |
+
{
|
| 45 |
+
"id": 4899,
|
| 46 |
+
"text": "action",
|
| 47 |
+
"logprob": -4.170299,
|
| 48 |
+
"special": false
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"id": 5,
|
| 52 |
+
"text": "\"",
|
| 53 |
+
"logprob": -0.32478866,
|
| 54 |
+
"special": false
|
| 55 |
+
},
|
| 56 |
+
{
|
| 57 |
+
"id": 12,
|
| 58 |
+
"text": ")",
|
| 59 |
+
"logprob": -1.0773665,
|
| 60 |
+
"special": false
|
| 61 |
+
},
|
| 62 |
+
{
|
| 63 |
+
"id": 30,
|
| 64 |
+
"text": ";",
|
| 65 |
+
"logprob": -0.27640742,
|
| 66 |
+
"special": false
|
| 67 |
+
},
|
| 68 |
+
{
|
| 69 |
+
"id": 837,
|
| 70 |
+
"text": "\n ",
|
| 71 |
+
"logprob": -1.6970354,
|
| 72 |
+
"special": false
|
| 73 |
+
},
|
| 74 |
+
{
|
| 75 |
+
"id": 1320,
|
| 76 |
+
"text": " if",
|
| 77 |
+
"logprob": -1.4495516,
|
| 78 |
+
"special": false
|
| 79 |
+
},
|
| 80 |
+
{
|
| 81 |
+
"id": 375,
|
| 82 |
+
"text": " (",
|
| 83 |
+
"logprob": -0.23609057,
|
| 84 |
+
"special": false
|
| 85 |
+
},
|
| 86 |
+
{
|
| 87 |
+
"id": 4899,
|
| 88 |
+
"text": "action",
|
| 89 |
+
"logprob": -1.1916996,
|
| 90 |
+
"special": false
|
| 91 |
+
},
|
| 92 |
+
{
|
| 93 |
+
"id": 3535,
|
| 94 |
+
"text": " ==",
|
| 95 |
+
"logprob": -0.8918753,
|
| 96 |
+
"special": false
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"id": 5109,
|
| 100 |
+
"text": " null",
|
| 101 |
+
"logprob": -0.3933342,
|
| 102 |
+
"special": false
|
| 103 |
+
},
|
| 104 |
+
{
|
| 105 |
+
"id": 12,
|
| 106 |
+
"text": ")",
|
| 107 |
+
"logprob": -0.43212673,
|
| 108 |
+
"special": false
|
| 109 |
+
},
|
| 110 |
+
{
|
| 111 |
+
"id": 731,
|
| 112 |
+
"text": " {",
|
| 113 |
+
"logprob": -0.17702064,
|
| 114 |
+
"special": false
|
| 115 |
+
},
|
| 116 |
+
{
|
| 117 |
+
"id": 1260,
|
| 118 |
+
"text": "\n ",
|
| 119 |
+
"logprob": -0.07027565,
|
| 120 |
+
"special": false
|
| 121 |
+
},
|
| 122 |
+
{
|
| 123 |
+
"id": 10519,
|
| 124 |
+
"text": " throw",
|
| 125 |
+
"logprob": -1.3915029,
|
| 126 |
+
"special": false
|
| 127 |
+
},
|
| 128 |
+
{
|
| 129 |
+
"id": 2084,
|
| 130 |
+
"text": " new",
|
| 131 |
+
"logprob": -0.04201372,
|
| 132 |
+
"special": false
|
| 133 |
+
},
|
| 134 |
+
{
|
| 135 |
+
"id": 150858,
|
| 136 |
+
"text": " RuntimeException",
|
| 137 |
+
"logprob": -1.7329919,
|
| 138 |
+
"special": false
|
| 139 |
+
}
|
| 140 |
+
]
|
| 141 |
+
}
|
| 142 |
+
}
|
launcher/tests/integration_tests.rs
ADDED
|
@@ -0,0 +1,172 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
use float_eq::assert_float_eq;
|
| 2 |
+
use serde::Deserialize;
|
| 3 |
+
use serde_json::Value;
|
| 4 |
+
use std::fs::File;
|
| 5 |
+
use std::io::{BufRead, BufReader};
|
| 6 |
+
use std::path::PathBuf;
|
| 7 |
+
use std::thread;
|
| 8 |
+
use std::thread::sleep;
|
| 9 |
+
use std::time::Duration;
|
| 10 |
+
use subprocess::{Popen, PopenConfig, Redirection};
|
| 11 |
+
|
| 12 |
+
#[derive(Deserialize)]
|
| 13 |
+
pub struct Token {
|
| 14 |
+
id: u32,
|
| 15 |
+
text: String,
|
| 16 |
+
logprob: Option<f32>,
|
| 17 |
+
special: bool,
|
| 18 |
+
}
|
| 19 |
+
|
| 20 |
+
#[derive(Deserialize)]
|
| 21 |
+
struct Details {
|
| 22 |
+
finish_reason: String,
|
| 23 |
+
generated_tokens: u32,
|
| 24 |
+
tokens: Vec<Token>,
|
| 25 |
+
}
|
| 26 |
+
|
| 27 |
+
#[derive(Deserialize)]
|
| 28 |
+
struct GeneratedText {
|
| 29 |
+
generated_text: String,
|
| 30 |
+
details: Details,
|
| 31 |
+
}
|
| 32 |
+
|
| 33 |
+
fn start_launcher(model_id: String, num_shard: usize, port: usize, master_port: usize) -> Popen {
|
| 34 |
+
let argv = vec![
|
| 35 |
+
"text-generation-launcher".to_string(),
|
| 36 |
+
"--model-id".to_string(),
|
| 37 |
+
model_id.clone(),
|
| 38 |
+
"--num-shard".to_string(),
|
| 39 |
+
num_shard.to_string(),
|
| 40 |
+
"--port".to_string(),
|
| 41 |
+
port.to_string(),
|
| 42 |
+
"--master-port".to_string(),
|
| 43 |
+
master_port.to_string(),
|
| 44 |
+
"--shard-uds-path".to_string(),
|
| 45 |
+
format!("/tmp/test-{}-{}-{}", num_shard, port, master_port),
|
| 46 |
+
];
|
| 47 |
+
|
| 48 |
+
let mut launcher = Popen::create(
|
| 49 |
+
&argv,
|
| 50 |
+
PopenConfig {
|
| 51 |
+
stdout: Redirection::Pipe,
|
| 52 |
+
stderr: Redirection::Merge,
|
| 53 |
+
..Default::default()
|
| 54 |
+
},
|
| 55 |
+
)
|
| 56 |
+
.expect("Could not start launcher");
|
| 57 |
+
|
| 58 |
+
// Redirect STDOUT and STDERR to the console
|
| 59 |
+
// (STDERR is merged into STDOUT)
|
| 60 |
+
let launcher_stdout = launcher.stdout.take().unwrap();
|
| 61 |
+
|
| 62 |
+
thread::spawn(move || {
|
| 63 |
+
let stdout = BufReader::new(launcher_stdout);
|
| 64 |
+
for line in stdout.lines() {
|
| 65 |
+
println!("{}", line.unwrap());
|
| 66 |
+
}
|
| 67 |
+
});
|
| 68 |
+
|
| 69 |
+
for _ in 0..60 {
|
| 70 |
+
let health = reqwest::blocking::get(format!("http://localhost:{}/health", port));
|
| 71 |
+
if health.is_ok() {
|
| 72 |
+
return launcher;
|
| 73 |
+
}
|
| 74 |
+
sleep(Duration::from_secs(2));
|
| 75 |
+
}
|
| 76 |
+
|
| 77 |
+
launcher.terminate().unwrap();
|
| 78 |
+
launcher.wait().unwrap();
|
| 79 |
+
panic!("failed to launch {}", model_id)
|
| 80 |
+
}
|
| 81 |
+
|
| 82 |
+
fn test_model(
|
| 83 |
+
model_id: String,
|
| 84 |
+
num_shard: usize,
|
| 85 |
+
port: usize,
|
| 86 |
+
master_port: usize,
|
| 87 |
+
) -> GeneratedText {
|
| 88 |
+
let mut launcher = start_launcher(model_id, num_shard, port, master_port);
|
| 89 |
+
|
| 90 |
+
let data = r#"
|
| 91 |
+
{
|
| 92 |
+
"inputs": "Test request",
|
| 93 |
+
"parameters": {
|
| 94 |
+
"details": true
|
| 95 |
+
}
|
| 96 |
+
}"#;
|
| 97 |
+
let req: Value = serde_json::from_str(data).unwrap();
|
| 98 |
+
|
| 99 |
+
let client = reqwest::blocking::Client::new();
|
| 100 |
+
let res = client
|
| 101 |
+
.post(format!("http://localhost:{}/generate", port))
|
| 102 |
+
.json(&req)
|
| 103 |
+
.send();
|
| 104 |
+
|
| 105 |
+
launcher.terminate().unwrap();
|
| 106 |
+
launcher.wait().unwrap();
|
| 107 |
+
|
| 108 |
+
let result: GeneratedText = res.unwrap().json().unwrap();
|
| 109 |
+
result
|
| 110 |
+
}
|
| 111 |
+
|
| 112 |
+
fn read_json(name: &str) -> GeneratedText {
|
| 113 |
+
let mut d = PathBuf::from(env!("CARGO_MANIFEST_DIR"));
|
| 114 |
+
d.push("tests/");
|
| 115 |
+
d.push(name);
|
| 116 |
+
|
| 117 |
+
let file = File::open(d).unwrap();
|
| 118 |
+
let reader = BufReader::new(file);
|
| 119 |
+
|
| 120 |
+
let result: GeneratedText = serde_json::from_reader(reader).unwrap();
|
| 121 |
+
result
|
| 122 |
+
}
|
| 123 |
+
|
| 124 |
+
fn compare_results(result: GeneratedText, expected: GeneratedText) {
|
| 125 |
+
assert_eq!(result.generated_text, expected.generated_text);
|
| 126 |
+
assert_eq!(result.details.finish_reason, expected.details.finish_reason);
|
| 127 |
+
assert_eq!(
|
| 128 |
+
result.details.generated_tokens,
|
| 129 |
+
expected.details.generated_tokens
|
| 130 |
+
);
|
| 131 |
+
|
| 132 |
+
for (token, expected_token) in result
|
| 133 |
+
.details
|
| 134 |
+
.tokens
|
| 135 |
+
.into_iter()
|
| 136 |
+
.zip(expected.details.tokens.into_iter())
|
| 137 |
+
{
|
| 138 |
+
assert_eq!(token.id, expected_token.id);
|
| 139 |
+
assert_eq!(token.text, expected_token.text);
|
| 140 |
+
assert_eq!(token.special, expected_token.special);
|
| 141 |
+
if let Some(logprob) = token.logprob {
|
| 142 |
+
let expected_logprob = expected_token.logprob.unwrap();
|
| 143 |
+
assert_float_eq!(logprob, expected_logprob, abs <= 0.001);
|
| 144 |
+
} else {
|
| 145 |
+
assert_eq!(token.logprob, expected_token.logprob);
|
| 146 |
+
}
|
| 147 |
+
}
|
| 148 |
+
}
|
| 149 |
+
|
| 150 |
+
#[test]
|
| 151 |
+
fn test_bloom_560m() {
|
| 152 |
+
let expected = read_json("bloom_560m.json");
|
| 153 |
+
|
| 154 |
+
let result = test_model("bigscience/bloom-560m".to_string(), 1, 3000, 29500);
|
| 155 |
+
compare_results(result, expected);
|
| 156 |
+
}
|
| 157 |
+
|
| 158 |
+
#[test]
|
| 159 |
+
fn test_bloom_560m_distributed() {
|
| 160 |
+
let expected = read_json("bloom_560m.json");
|
| 161 |
+
|
| 162 |
+
let result = test_model("bigscience/bloom-560m".to_string(), 2, 3001, 29501);
|
| 163 |
+
compare_results(result, expected);
|
| 164 |
+
}
|
| 165 |
+
|
| 166 |
+
#[test]
|
| 167 |
+
fn test_mt0_base() {
|
| 168 |
+
let expected = read_json("mt0_base.json");
|
| 169 |
+
|
| 170 |
+
let result = test_model("bigscience/mt0-base".to_string(), 1, 3002, 29502);
|
| 171 |
+
compare_results(result, expected);
|
| 172 |
+
}
|
launcher/tests/mt0_base.json
ADDED
|
@@ -0,0 +1,137 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"generated_text": "\"\"\"Test the contents of the contents of the contents. \"\"\" test_test",
|
| 3 |
+
"details": {
|
| 4 |
+
"finish_reason": "length",
|
| 5 |
+
"generated_tokens": 20,
|
| 6 |
+
"seed": null,
|
| 7 |
+
"prefill": [
|
| 8 |
+
{
|
| 9 |
+
"id": 0,
|
| 10 |
+
"text": "<pad>",
|
| 11 |
+
"logprob": null
|
| 12 |
+
}
|
| 13 |
+
],
|
| 14 |
+
"tokens": [
|
| 15 |
+
{
|
| 16 |
+
"id": 259,
|
| 17 |
+
"text": "",
|
| 18 |
+
"logprob": -1.3656927,
|
| 19 |
+
"special": false
|
| 20 |
+
},
|
| 21 |
+
{
|
| 22 |
+
"id": 215100,
|
| 23 |
+
"text": "\"\"\"",
|
| 24 |
+
"logprob": -2.6551573,
|
| 25 |
+
"special": false
|
| 26 |
+
},
|
| 27 |
+
{
|
| 28 |
+
"id": 46138,
|
| 29 |
+
"text": "Test",
|
| 30 |
+
"logprob": -1.8059857,
|
| 31 |
+
"special": false
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"id": 287,
|
| 35 |
+
"text": " the",
|
| 36 |
+
"logprob": -1.2102449,
|
| 37 |
+
"special": false
|
| 38 |
+
},
|
| 39 |
+
{
|
| 40 |
+
"id": 259,
|
| 41 |
+
"text": " ",
|
| 42 |
+
"logprob": -1.6057279,
|
| 43 |
+
"special": false
|
| 44 |
+
},
|
| 45 |
+
{
|
| 46 |
+
"id": 49076,
|
| 47 |
+
"text": "contents",
|
| 48 |
+
"logprob": -3.6060903,
|
| 49 |
+
"special": false
|
| 50 |
+
},
|
| 51 |
+
{
|
| 52 |
+
"id": 304,
|
| 53 |
+
"text": " of",
|
| 54 |
+
"logprob": -0.5270343,
|
| 55 |
+
"special": false
|
| 56 |
+
},
|
| 57 |
+
{
|
| 58 |
+
"id": 287,
|
| 59 |
+
"text": " the",
|
| 60 |
+
"logprob": -0.62522805,
|
| 61 |
+
"special": false
|
| 62 |
+
},
|
| 63 |
+
{
|
| 64 |
+
"id": 259,
|
| 65 |
+
"text": " ",
|
| 66 |
+
"logprob": -1.4069618,
|
| 67 |
+
"special": false
|
| 68 |
+
},
|
| 69 |
+
{
|
| 70 |
+
"id": 49076,
|
| 71 |
+
"text": "contents",
|
| 72 |
+
"logprob": -2.621994,
|
| 73 |
+
"special": false
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"id": 304,
|
| 77 |
+
"text": " of",
|
| 78 |
+
"logprob": -1.3172221,
|
| 79 |
+
"special": false
|
| 80 |
+
},
|
| 81 |
+
{
|
| 82 |
+
"id": 287,
|
| 83 |
+
"text": " the",
|
| 84 |
+
"logprob": -0.3501925,
|
| 85 |
+
"special": false
|
| 86 |
+
},
|
| 87 |
+
{
|
| 88 |
+
"id": 259,
|
| 89 |
+
"text": " ",
|
| 90 |
+
"logprob": -0.7219573,
|
| 91 |
+
"special": false
|
| 92 |
+
},
|
| 93 |
+
{
|
| 94 |
+
"id": 49076,
|
| 95 |
+
"text": "contents",
|
| 96 |
+
"logprob": -1.0494149,
|
| 97 |
+
"special": false
|
| 98 |
+
},
|
| 99 |
+
{
|
| 100 |
+
"id": 260,
|
| 101 |
+
"text": ".",
|
| 102 |
+
"logprob": -1.0803378,
|
| 103 |
+
"special": false
|
| 104 |
+
},
|
| 105 |
+
{
|
| 106 |
+
"id": 259,
|
| 107 |
+
"text": " ",
|
| 108 |
+
"logprob": -0.32933083,
|
| 109 |
+
"special": false
|
| 110 |
+
},
|
| 111 |
+
{
|
| 112 |
+
"id": 215100,
|
| 113 |
+
"text": "\"\"\"",
|
| 114 |
+
"logprob": -0.11268901,
|
| 115 |
+
"special": false
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"id": 2978,
|
| 119 |
+
"text": " test",
|
| 120 |
+
"logprob": -1.5846587,
|
| 121 |
+
"special": false
|
| 122 |
+
},
|
| 123 |
+
{
|
| 124 |
+
"id": 290,
|
| 125 |
+
"text": "_",
|
| 126 |
+
"logprob": -0.49796978,
|
| 127 |
+
"special": false
|
| 128 |
+
},
|
| 129 |
+
{
|
| 130 |
+
"id": 4125,
|
| 131 |
+
"text": "test",
|
| 132 |
+
"logprob": -2.0026445,
|
| 133 |
+
"special": false
|
| 134 |
+
}
|
| 135 |
+
]
|
| 136 |
+
}
|
| 137 |
+
}
|
proto/generate.proto
ADDED
|
@@ -0,0 +1,181 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
syntax = "proto3";
|
| 2 |
+
|
| 3 |
+
package generate.v1;
|
| 4 |
+
|
| 5 |
+
service TextGenerationService {
|
| 6 |
+
/// Model Info
|
| 7 |
+
rpc Info (InfoRequest) returns (InfoResponse) {}
|
| 8 |
+
/// Service discovery
|
| 9 |
+
rpc ServiceDiscovery (ServiceDiscoveryRequest) returns (ServiceDiscoveryResponse) {}
|
| 10 |
+
/// Empties batch cache
|
| 11 |
+
rpc ClearCache (ClearCacheRequest) returns (ClearCacheResponse);
|
| 12 |
+
/// Remove requests from a cached batch
|
| 13 |
+
rpc FilterBatch (FilterBatchRequest) returns (FilterBatchResponse);
|
| 14 |
+
/// Prefill batch and decode first token
|
| 15 |
+
rpc Prefill (PrefillRequest) returns (PrefillResponse);
|
| 16 |
+
/// Decode token for a list of prefilled batches
|
| 17 |
+
rpc Decode (DecodeRequest) returns (DecodeResponse);
|
| 18 |
+
/// Health check
|
| 19 |
+
rpc Health (HealthRequest) returns (HealthResponse);
|
| 20 |
+
}
|
| 21 |
+
|
| 22 |
+
message HealthRequest {}
|
| 23 |
+
message HealthResponse {}
|
| 24 |
+
|
| 25 |
+
/// Empty request
|
| 26 |
+
message InfoRequest {}
|
| 27 |
+
|
| 28 |
+
message InfoResponse {
|
| 29 |
+
bool requires_padding = 1;
|
| 30 |
+
string dtype = 2;
|
| 31 |
+
string device_type = 3;
|
| 32 |
+
}
|
| 33 |
+
|
| 34 |
+
/// Empty request
|
| 35 |
+
message ServiceDiscoveryRequest {}
|
| 36 |
+
|
| 37 |
+
message ServiceDiscoveryResponse {
|
| 38 |
+
/// Other shards urls
|
| 39 |
+
repeated string urls = 1;
|
| 40 |
+
}
|
| 41 |
+
|
| 42 |
+
message ClearCacheRequest {
|
| 43 |
+
/// Optional batch id
|
| 44 |
+
optional uint64 id = 1;
|
| 45 |
+
}
|
| 46 |
+
|
| 47 |
+
/// Empty response
|
| 48 |
+
message ClearCacheResponse {}
|
| 49 |
+
|
| 50 |
+
message NextTokenChooserParameters {
|
| 51 |
+
/// exponential scaling output probability distribution
|
| 52 |
+
float temperature = 1;
|
| 53 |
+
/// restricting to the k highest probability elements
|
| 54 |
+
uint32 top_k = 2;
|
| 55 |
+
/// restricting to top tokens summing to prob_cut_off <= prob_cut_off
|
| 56 |
+
float top_p = 3;
|
| 57 |
+
/// restricting to top tokens summing to prob_cut_off <= prob_cut_off
|
| 58 |
+
float typical_p = 4;
|
| 59 |
+
/// apply sampling on the logits
|
| 60 |
+
bool do_sample = 5;
|
| 61 |
+
/// random seed for sampling
|
| 62 |
+
uint64 seed = 6;
|
| 63 |
+
/// repetition penalty
|
| 64 |
+
float repetition_penalty = 7;
|
| 65 |
+
/// token watermarking using "A Watermark for Large Language Models"
|
| 66 |
+
bool watermark = 8;
|
| 67 |
+
}
|
| 68 |
+
|
| 69 |
+
message StoppingCriteriaParameters {
|
| 70 |
+
/// Maximum number of generated tokens
|
| 71 |
+
uint32 max_new_tokens = 1;
|
| 72 |
+
/// Optional stopping sequences
|
| 73 |
+
repeated string stop_sequences = 2;
|
| 74 |
+
/// Ignore end of sequence token
|
| 75 |
+
/// used for benchmarking
|
| 76 |
+
bool ignore_eos_token = 3;
|
| 77 |
+
}
|
| 78 |
+
|
| 79 |
+
message Request {
|
| 80 |
+
/// Request ID
|
| 81 |
+
uint64 id = 1;
|
| 82 |
+
/// The generation context
|
| 83 |
+
string inputs = 2;
|
| 84 |
+
/// Context truncation
|
| 85 |
+
uint32 truncate = 3;
|
| 86 |
+
/// Next Token Chooser Parameters
|
| 87 |
+
NextTokenChooserParameters parameters = 4;
|
| 88 |
+
/// Stopping Criteria Parameters
|
| 89 |
+
StoppingCriteriaParameters stopping_parameters = 5;
|
| 90 |
+
}
|
| 91 |
+
|
| 92 |
+
message Batch {
|
| 93 |
+
/// Batch ID
|
| 94 |
+
uint64 id = 1;
|
| 95 |
+
/// Individual requests
|
| 96 |
+
repeated Request requests = 2;
|
| 97 |
+
/// Batch size (==len(requests))
|
| 98 |
+
uint32 size = 3;
|
| 99 |
+
/// Maximum number of tokens this batch will grow to
|
| 100 |
+
uint32 max_tokens = 4;
|
| 101 |
+
}
|
| 102 |
+
|
| 103 |
+
enum FinishReason {
|
| 104 |
+
FINISH_REASON_LENGTH = 0;
|
| 105 |
+
FINISH_REASON_EOS_TOKEN = 1;
|
| 106 |
+
FINISH_REASON_STOP_SEQUENCE = 2;
|
| 107 |
+
}
|
| 108 |
+
|
| 109 |
+
message GeneratedText {
|
| 110 |
+
/// Output
|
| 111 |
+
string text = 1;
|
| 112 |
+
/// Number of generated tokens
|
| 113 |
+
uint32 generated_tokens = 2;
|
| 114 |
+
/// Finish reason
|
| 115 |
+
FinishReason finish_reason = 3;
|
| 116 |
+
/// Seed
|
| 117 |
+
optional uint64 seed = 4;
|
| 118 |
+
}
|
| 119 |
+
|
| 120 |
+
message PrefillTokens {
|
| 121 |
+
/// Prefill Token IDs
|
| 122 |
+
repeated uint32 ids = 1;
|
| 123 |
+
/// Prefill Logprobs
|
| 124 |
+
repeated float logprobs = 2;
|
| 125 |
+
/// Prefill tokens
|
| 126 |
+
repeated string texts = 3;
|
| 127 |
+
}
|
| 128 |
+
|
| 129 |
+
message Generation {
|
| 130 |
+
/// Request ID
|
| 131 |
+
uint64 request_id = 1;
|
| 132 |
+
/// Prefill tokens (optional)
|
| 133 |
+
PrefillTokens prefill_tokens = 2;
|
| 134 |
+
/// Token ID
|
| 135 |
+
uint32 token_id = 3;
|
| 136 |
+
/// Logprob
|
| 137 |
+
float token_logprob = 4;
|
| 138 |
+
/// Text
|
| 139 |
+
string token_text = 5;
|
| 140 |
+
/// Is it a special token
|
| 141 |
+
bool token_is_special = 6;
|
| 142 |
+
/// Complete generated text
|
| 143 |
+
GeneratedText generated_text = 7;
|
| 144 |
+
}
|
| 145 |
+
|
| 146 |
+
message FilterBatchRequest {
|
| 147 |
+
/// Batch ID
|
| 148 |
+
uint64 batch_id = 1;
|
| 149 |
+
/// Requests to keep
|
| 150 |
+
repeated Request keep_requests = 2;
|
| 151 |
+
}
|
| 152 |
+
|
| 153 |
+
message FilterBatchResponse {
|
| 154 |
+
/// Filtered Batch (cached)
|
| 155 |
+
Batch batch = 1;
|
| 156 |
+
}
|
| 157 |
+
|
| 158 |
+
|
| 159 |
+
message PrefillRequest {
|
| 160 |
+
/// Batch
|
| 161 |
+
Batch batch = 1;
|
| 162 |
+
}
|
| 163 |
+
|
| 164 |
+
message PrefillResponse {
|
| 165 |
+
/// Generation
|
| 166 |
+
repeated Generation generations = 1;
|
| 167 |
+
/// Next batch (cached)
|
| 168 |
+
optional Batch batch = 2;
|
| 169 |
+
}
|
| 170 |
+
|
| 171 |
+
message DecodeRequest {
|
| 172 |
+
/// Cached batches
|
| 173 |
+
repeated Batch batches = 1;
|
| 174 |
+
}
|
| 175 |
+
|
| 176 |
+
message DecodeResponse {
|
| 177 |
+
/// Decodes
|
| 178 |
+
repeated Generation generations = 1;
|
| 179 |
+
/// Next batch (cached)
|
| 180 |
+
optional Batch batch = 2;
|
| 181 |
+
}
|
router/Cargo.toml
ADDED
|
@@ -0,0 +1,44 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[package]
|
| 2 |
+
name = "text-generation-router"
|
| 3 |
+
version = "0.6.0"
|
| 4 |
+
edition = "2021"
|
| 5 |
+
authors = ["Olivier Dehaene"]
|
| 6 |
+
description = "Text Generation Webserver"
|
| 7 |
+
build = "build.rs"
|
| 8 |
+
|
| 9 |
+
[lib]
|
| 10 |
+
path = "src/lib.rs"
|
| 11 |
+
|
| 12 |
+
[[bin]]
|
| 13 |
+
name = "text-generation-router"
|
| 14 |
+
path = "src/main.rs"
|
| 15 |
+
|
| 16 |
+
[dependencies]
|
| 17 |
+
async-stream = "0.3.3"
|
| 18 |
+
axum = { version = "0.6.4", features = ["json"] }
|
| 19 |
+
axum-tracing-opentelemetry = "0.10.0"
|
| 20 |
+
text-generation-client = { path = "client" }
|
| 21 |
+
clap = { version = "4.1.4", features = ["derive", "env"] }
|
| 22 |
+
flume = "0.10.14"
|
| 23 |
+
futures = "0.3.26"
|
| 24 |
+
metrics = "0.20.1"
|
| 25 |
+
metrics-exporter-prometheus = { version = "0.11.0", features = [] }
|
| 26 |
+
nohash-hasher = "0.2.0"
|
| 27 |
+
opentelemetry = { version = "0.18.0", features = ["rt-tokio"] }
|
| 28 |
+
opentelemetry-otlp = "0.11.0"
|
| 29 |
+
rand = "0.8.5"
|
| 30 |
+
reqwest = { version = "0.11.14", features = [] }
|
| 31 |
+
serde = "1.0.152"
|
| 32 |
+
serde_json = "1.0.93"
|
| 33 |
+
thiserror = "1.0.38"
|
| 34 |
+
tokenizers = "0.13.3"
|
| 35 |
+
tokio = { version = "1.25.0", features = ["rt", "rt-multi-thread", "parking_lot", "signal", "sync"] }
|
| 36 |
+
tower-http = { version = "0.4.0", features = ["cors"] }
|
| 37 |
+
tracing = "0.1.37"
|
| 38 |
+
tracing-opentelemetry = "0.18.0"
|
| 39 |
+
tracing-subscriber = { version = "0.3.16", features = ["json", "env-filter"] }
|
| 40 |
+
utoipa = { version = "3.0.1", features = ["axum_extras"] }
|
| 41 |
+
utoipa-swagger-ui = { version = "3.0.2", features = ["axum"] }
|
| 42 |
+
|
| 43 |
+
[build-dependencies]
|
| 44 |
+
vergen = { version = "8.0.0", features = ["build", "git", "gitcl"] }
|
router/build.rs
ADDED
|
@@ -0,0 +1,26 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
use std::error::Error;
|
| 2 |
+
use vergen::EmitBuilder;
|
| 3 |
+
|
| 4 |
+
fn main() -> Result<(), Box<dyn Error>> {
|
| 5 |
+
// Try to get the git sha from the local git repository
|
| 6 |
+
if EmitBuilder::builder()
|
| 7 |
+
.fail_on_error()
|
| 8 |
+
.git_sha(false)
|
| 9 |
+
.emit()
|
| 10 |
+
.is_err()
|
| 11 |
+
{
|
| 12 |
+
// Unable to get the git sha
|
| 13 |
+
if let Ok(sha) = std::env::var("GIT_SHA") {
|
| 14 |
+
// Set it from an env var
|
| 15 |
+
println!("cargo:rustc-env=VERGEN_GIT_SHA={sha}");
|
| 16 |
+
}
|
| 17 |
+
}
|
| 18 |
+
|
| 19 |
+
// Set docker label if present
|
| 20 |
+
if let Ok(label) = std::env::var("DOCKER_LABEL") {
|
| 21 |
+
// Set it from an env var
|
| 22 |
+
println!("cargo:rustc-env=DOCKER_LABEL={label}");
|
| 23 |
+
}
|
| 24 |
+
|
| 25 |
+
Ok(())
|
| 26 |
+
}
|
router/client/Cargo.toml
ADDED
|
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[package]
|
| 2 |
+
name = "text-generation-client"
|
| 3 |
+
version = "0.6.0"
|
| 4 |
+
edition = "2021"
|
| 5 |
+
|
| 6 |
+
[dependencies]
|
| 7 |
+
futures = "^0.3"
|
| 8 |
+
grpc-metadata = { path = "../grpc-metadata" }
|
| 9 |
+
prost = "^0.11"
|
| 10 |
+
thiserror = "^1.0"
|
| 11 |
+
tokio = { version = "^1.25", features = ["sync"] }
|
| 12 |
+
tonic = "^0.8"
|
| 13 |
+
tower = "^0.4"
|
| 14 |
+
tracing = "^0.1"
|
| 15 |
+
tracing-error = "^0.2"
|
| 16 |
+
|
| 17 |
+
[build-dependencies]
|
| 18 |
+
tonic-build = "0.8.4"
|
| 19 |
+
prost-build = "0.11.6"
|
router/client/build.rs
ADDED
|
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
use std::fs;
|
| 2 |
+
|
| 3 |
+
fn main() -> Result<(), Box<dyn std::error::Error>> {
|
| 4 |
+
println!("cargo:rerun-if-changed=../../proto/generate.proto");
|
| 5 |
+
fs::create_dir("src/pb").unwrap_or(());
|
| 6 |
+
|
| 7 |
+
let mut config = prost_build::Config::new();
|
| 8 |
+
config.protoc_arg("--experimental_allow_proto3_optional");
|
| 9 |
+
|
| 10 |
+
tonic_build::configure()
|
| 11 |
+
.build_client(true)
|
| 12 |
+
.build_server(false)
|
| 13 |
+
.out_dir("src/pb")
|
| 14 |
+
.include_file("mod.rs")
|
| 15 |
+
.compile_with_config(config, &["../../proto/generate.proto"], &["../../proto"])
|
| 16 |
+
.unwrap_or_else(|e| panic!("protobuf compilation failed: {e}"));
|
| 17 |
+
|
| 18 |
+
Ok(())
|
| 19 |
+
}
|
router/client/src/client.rs
ADDED
|
@@ -0,0 +1,121 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
/// Single shard Client
|
| 2 |
+
use crate::pb::generate::v1::text_generation_service_client::TextGenerationServiceClient;
|
| 3 |
+
use crate::pb::generate::v1::*;
|
| 4 |
+
use crate::Result;
|
| 5 |
+
use grpc_metadata::InjectTelemetryContext;
|
| 6 |
+
use tonic::transport::{Channel, Uri};
|
| 7 |
+
use tracing::instrument;
|
| 8 |
+
|
| 9 |
+
/// Text Generation Inference gRPC client
|
| 10 |
+
#[derive(Debug, Clone)]
|
| 11 |
+
pub struct Client {
|
| 12 |
+
stub: TextGenerationServiceClient<Channel>,
|
| 13 |
+
}
|
| 14 |
+
|
| 15 |
+
impl Client {
|
| 16 |
+
/// Returns a client connected to the given url
|
| 17 |
+
pub async fn connect(uri: Uri) -> Result<Self> {
|
| 18 |
+
let channel = Channel::builder(uri).connect().await?;
|
| 19 |
+
|
| 20 |
+
Ok(Self {
|
| 21 |
+
stub: TextGenerationServiceClient::new(channel),
|
| 22 |
+
})
|
| 23 |
+
}
|
| 24 |
+
|
| 25 |
+
/// Returns a client connected to the given unix socket
|
| 26 |
+
pub async fn connect_uds(path: String) -> Result<Self> {
|
| 27 |
+
let channel = Channel::from_shared("http://[::]:50051".to_string())
|
| 28 |
+
.unwrap()
|
| 29 |
+
.connect_with_connector(tower::service_fn(move |_: Uri| {
|
| 30 |
+
tokio::net::UnixStream::connect(path.clone())
|
| 31 |
+
}))
|
| 32 |
+
.await?;
|
| 33 |
+
|
| 34 |
+
Ok(Self {
|
| 35 |
+
stub: TextGenerationServiceClient::new(channel),
|
| 36 |
+
})
|
| 37 |
+
}
|
| 38 |
+
|
| 39 |
+
/// Returns a list of uris or unix sockets of all shards
|
| 40 |
+
#[instrument(skip(self))]
|
| 41 |
+
pub async fn service_discovery(&mut self) -> Result<Vec<String>> {
|
| 42 |
+
let request = tonic::Request::new(ServiceDiscoveryRequest {}).inject_context();
|
| 43 |
+
let response = self.stub.service_discovery(request).await?;
|
| 44 |
+
let urls = response
|
| 45 |
+
.into_inner()
|
| 46 |
+
.urls
|
| 47 |
+
.into_iter()
|
| 48 |
+
// Remove unix socket prefix
|
| 49 |
+
.map(|url| match url.strip_prefix("unix://") {
|
| 50 |
+
None => url,
|
| 51 |
+
Some(stripped_url) => stripped_url.to_string(),
|
| 52 |
+
})
|
| 53 |
+
.collect();
|
| 54 |
+
Ok(urls)
|
| 55 |
+
}
|
| 56 |
+
|
| 57 |
+
/// Get model info
|
| 58 |
+
#[instrument(skip(self))]
|
| 59 |
+
pub async fn info(&mut self) -> Result<InfoResponse> {
|
| 60 |
+
let request = tonic::Request::new(InfoRequest {}).inject_context();
|
| 61 |
+
let response = self.stub.info(request).await?.into_inner();
|
| 62 |
+
Ok(response)
|
| 63 |
+
}
|
| 64 |
+
|
| 65 |
+
/// Get model health
|
| 66 |
+
#[instrument(skip(self))]
|
| 67 |
+
pub async fn health(&mut self) -> Result<HealthResponse> {
|
| 68 |
+
let request = tonic::Request::new(HealthRequest {}).inject_context();
|
| 69 |
+
let response = self.stub.health(request).await?.into_inner();
|
| 70 |
+
Ok(response)
|
| 71 |
+
}
|
| 72 |
+
|
| 73 |
+
/// Clear the past generations cache
|
| 74 |
+
#[instrument(skip(self))]
|
| 75 |
+
pub async fn clear_cache(&mut self, batch_id: Option<u64>) -> Result<()> {
|
| 76 |
+
let request = tonic::Request::new(ClearCacheRequest { id: batch_id }).inject_context();
|
| 77 |
+
self.stub.clear_cache(request).await?;
|
| 78 |
+
Ok(())
|
| 79 |
+
}
|
| 80 |
+
|
| 81 |
+
/// Filter a cached batch
|
| 82 |
+
#[instrument(skip(self))]
|
| 83 |
+
pub async fn filter_batch(
|
| 84 |
+
&mut self,
|
| 85 |
+
batch_id: u64,
|
| 86 |
+
keep_requests: Vec<Request>,
|
| 87 |
+
) -> Result<Option<Batch>> {
|
| 88 |
+
let request = tonic::Request::new(FilterBatchRequest {
|
| 89 |
+
batch_id,
|
| 90 |
+
keep_requests,
|
| 91 |
+
})
|
| 92 |
+
.inject_context();
|
| 93 |
+
let filtered_batch = self.stub.filter_batch(request).await?.into_inner();
|
| 94 |
+
Ok(filtered_batch.batch)
|
| 95 |
+
}
|
| 96 |
+
|
| 97 |
+
/// Generate one token for each request in the given batch
|
| 98 |
+
///
|
| 99 |
+
/// Returns Generation for each request in batch
|
| 100 |
+
/// and the next cached batch
|
| 101 |
+
#[instrument(skip_all, fields(id = &batch.id, size = &batch.size))]
|
| 102 |
+
pub async fn prefill(&mut self, batch: Batch) -> Result<(Vec<Generation>, Option<Batch>)> {
|
| 103 |
+
let request = tonic::Request::new(PrefillRequest { batch: Some(batch) }).inject_context();
|
| 104 |
+
let response = self.stub.prefill(request).await?.into_inner();
|
| 105 |
+
Ok((response.generations, response.batch))
|
| 106 |
+
}
|
| 107 |
+
|
| 108 |
+
/// Generate one token for each request in the given cached batches
|
| 109 |
+
///
|
| 110 |
+
/// Returns Generation for each request in batches
|
| 111 |
+
/// and the next cached batch
|
| 112 |
+
#[instrument(skip_all, fields(size = batches.iter().map(|batch|{batch.size}).sum::<u32>()))]
|
| 113 |
+
pub async fn decode(
|
| 114 |
+
&mut self,
|
| 115 |
+
batches: Vec<Batch>,
|
| 116 |
+
) -> Result<(Vec<Generation>, Option<Batch>)> {
|
| 117 |
+
let request = tonic::Request::new(DecodeRequest { batches }).inject_context();
|
| 118 |
+
let response = self.stub.decode(request).await?.into_inner();
|
| 119 |
+
Ok((response.generations, response.batch))
|
| 120 |
+
}
|
| 121 |
+
}
|
router/client/src/lib.rs
ADDED
|
@@ -0,0 +1,44 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
//! Text Generation gRPC client library
|
| 2 |
+
|
| 3 |
+
mod client;
|
| 4 |
+
#[allow(clippy::derive_partial_eq_without_eq)]
|
| 5 |
+
mod pb;
|
| 6 |
+
mod sharded_client;
|
| 7 |
+
|
| 8 |
+
pub use client::Client;
|
| 9 |
+
pub use pb::generate::v1::HealthResponse;
|
| 10 |
+
pub use pb::generate::v1::InfoResponse as ShardInfo;
|
| 11 |
+
pub use pb::generate::v1::{
|
| 12 |
+
Batch, FinishReason, GeneratedText, Generation, NextTokenChooserParameters, PrefillTokens,
|
| 13 |
+
Request, StoppingCriteriaParameters,
|
| 14 |
+
};
|
| 15 |
+
pub use sharded_client::ShardedClient;
|
| 16 |
+
use thiserror::Error;
|
| 17 |
+
use tonic::transport;
|
| 18 |
+
use tonic::Status;
|
| 19 |
+
|
| 20 |
+
#[derive(Error, Debug, Clone)]
|
| 21 |
+
pub enum ClientError {
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| 22 |
+
#[error("Could not connect to Text Generation server: {0}")]
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| 23 |
+
Connection(String),
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| 24 |
+
#[error("Server error: {0}")]
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| 25 |
+
Generation(String),
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| 26 |
+
}
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| 27 |
+
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| 28 |
+
impl From<Status> for ClientError {
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| 29 |
+
fn from(err: Status) -> Self {
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| 30 |
+
let err = Self::Generation(err.message().to_string());
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| 31 |
+
tracing::error!("{err}");
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| 32 |
+
err
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| 33 |
+
}
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| 34 |
+
}
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| 35 |
+
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| 36 |
+
impl From<transport::Error> for ClientError {
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| 37 |
+
fn from(err: transport::Error) -> Self {
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| 38 |
+
let err = Self::Connection(err.to_string());
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| 39 |
+
tracing::error!("{err}");
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| 40 |
+
err
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| 41 |
+
}
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| 42 |
+
}
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| 43 |
+
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| 44 |
+
pub type Result<T> = std::result::Result<T, ClientError>;
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