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#!/bin/bash
#export TPU_IP_ADDRESS=10.8.195.90;
#export XRT_TPU_CONFIG="tpu_worker;0;$TPU_IP_ADDRESS:8470"
#export TPU_NAME="grpc://$TPU_IP_ADDRESS:8470"
export XRT_WORKERS="localservice:0;grpc://localhost:40934"
export XRT_DEVICE_MAP="CPU:0;/job:localservice/replica:0/task:0/device:XLA_CPU:0|GPU:0;/job:localservice/replica:0/task:0/device:XLA_GPU:0"
py=python3
#py=python
#py='python3 -m torch_xla.distributed.xla_dist --tpu='${TPU_NAME}' --conda-env=torch-xla-nightly -- python'
dataset=multimodal
model=residualflower
#exp=aistpp_big
exp=aistpp_residual
#$py training/train.py --data_dir=data/scaled_features --dataset_name=$dataset --model=$model --batch_size=32 --num_windows=1 --max_epochs=20000\
$py training/train.py --data_dir=data/scaled_features --dataset_name=$dataset --model=$model --batch_size=64 --max_epochs=20000\
--fix_lengths \
--do_testing \
--skip_training \
--experiment_name=$exp\
--lr_policy="multistep" \
--lr_decay_milestones="[25,50]" \
--learning_rate=0 \
--dins="72,103" \
--douts="72" \
--input_modalities="expmap_scaled,mel_ddcpca_scaled" \
--output_modalities="expmap_scaled" \
--input_lengths="60,120" \
--output_lengths="10" \
--output_time_offset="60" \
--predicted_inputs="0,0" \
--nlayers=6 \
--nhead=10 \
--scales="[[4,0], [4,0]]" \
--num_glow_coupling_blocks=2 \
--glow_use_attn \
--use_transformer_nn \
--use_pos_emb_coupling \
--use_pos_emb_output \
--dhid=800 \
--cond_concat_dims \
--glow_norm_layer="batchnorm" \
--glow_bn_momentum=0.1 \
--dropout=0 \
--workers=$(nproc) \
--gpus=1 \
--gradient_clip_val=0.5 \
--continue_train \
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