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# Use the specified base image |
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FROM nvcr.io/nvidia/pytorch:23.12-py3 |
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# Set the working directory to your project directory |
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WORKDIR ./ |
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# Copy the contents of your project into the Docker image |
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COPY . . |
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# Create and activate Conda environment |
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# RUN conda create --name plm python=3.10 |
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# SHELL ["conda", "run", "-n", "plm", "/bin/bash", "-c"] |
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# RUN conda activate plm |
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# Install Miniconda |
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# RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh && \ |
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# ENV PATH="/opt/conda/bin:${PATH}" |
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# Install dependencies |
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# RUN cd protein_lm/modeling/models/libs/ && pip install -e causal-conv1d && pip install -e mamba && cd ../../../../ |
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# RUN pip install transformers datasets accelerate evaluate pytest fair-esm biopython deepspeed |
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# RUN pip install -e . |
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# RUN pip install hydra-core --upgrade |
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# RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh |
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# source "$HOME/.cargo/env" |
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# RUN pip install -e protein_lm/tokenizer/rust_trie |
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