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add lock file
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trainer:
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output_dir: exp/middle-model__partition-0-32-128-256__grouping-8-32-64__deep-filtering-5-3-1__synops-1e-8
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do_train: True
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resume_from_checkpoint: "no"
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per_device_train_batch_size: 128
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eval_batch_size: 8
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dataloader_num_workers: 8
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num_train_epochs: 200
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max_grad_norm: 10
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save_epoch_interval: 1
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eval_epoch_interval: 1
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early_stopping_patience: 100
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save_total_limit: 100
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model:
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n_fft: 512
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hop_length: 128
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win_length: 512
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fdrc: 0.5
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fb_input_size: 64
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fb_hidden_size: 320
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fb_num_layers: 2
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fb_proj_size: 64
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fb_output_activate_function: null
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sb_hidden_size: 224
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sb_num_layers: 2
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freq_cutoffs: [0, 32, 128, 256]
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df_orders: [5, 3, 1]
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center_freq_sizes: [8, 32, 64]
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neighbor_freq_sizes: [15, 15, 15]
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use_pre_layer_norm_fb: True
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use_pre_layer_norm_sb: True
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bn: True
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shared_weights: True
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sequence_model: "GSN"
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num_spks: 1
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train_dataset:
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root: /data/xhao/datasets_fullband/training_set/
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limit: -1
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offset: 0
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eval_dataset:
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root: /home/xhao/proj/spiking-fullsubnet-27-Jan-26/data/validation_set/
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train: False
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limit: -1
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offset: 0
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# eval_dataset:
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# root: /data/xhao/datasets_fullband/test_set_1/
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# train: False
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# limit: -1
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# offset: 0
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#!/usr/bin/env bash
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# For multi-GPU evaluation using Hugging Face Accelerate
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accelerate launch --multi_gpu \
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--num_processes=4 \
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--gpu_ids 0,1,2,3 \
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--main_process_port 46601 \
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run.py \
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--config_path conf/middle-model__partition-0-32-128-256__grouping-8-32-64__deep-filtering-5-3-1__synops-1e-8.yaml \
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--eval_batch_size 4 \
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--resume_from_checkpoint /home/xhao/proj/spiking-fullsubnet/recipes/intel_ndns/spiking_fullsubnet_v2/exp/middle-model__partition-0-32-128-256__grouping-8-32-64__deep-filtering-5-3-1__synops-1e-8/checkpoints/epoch_0188 \
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--do_eval true
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# For training, please comment out the above command and use the following command:
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accelerate launch --multi_gpu \
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--num_processes=4 \
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--gpu_ids 0,1,2,3 \
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--main_process_port 46601 \
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run.py \
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--config_path conf/middle-model__partition-0-32-128-256__grouping-8-32-64__deep-filtering-5-3-1__synops-1e-8.yaml \
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--eval_batch_size 4

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