Update hyperparams.yaml

hyperparams.yaml

@@ -10,89 +10,6 @@
 # Basic parameters
 # Seed needs to be set at top of yaml, before objects with parameters are made
 #
-seed: 1234
-__set_seed: !apply:torch.manual_seed [1234]
-
-# Data params
-
-# the data folder for the wham dataset
-# data_folder needs to follow the format:  /yourpath/whamr.
-# make sure to use the name whamr at your top folder for the dataset!
-data_folder: /network/tmp1/subakany/whamr
-task: enhancement
-dereverberate: false
-
-# the path for wsj0/si_tr_s/ folder -- only needed if dynamic mixing is used
-# e.g. /yourpath/wsj0-processed/si_tr_s/
-# you need to convert the original wsj0 to 8k
-# you can do this conversion with the script ../meta/preprocess_dynamic_mixing.py
-base_folder_dm: /network/tmp1/subakany/wsj0-processed/si_tr_s/
-
-experiment_name: sepformer-whamr-enhancement-DM
-output_folder: results/sepformer-whamr-enhancement-DM/1234
-train_log: results/sepformer-whamr-enhancement-DM/1234/train_log.txt
-save_folder: results/sepformer-whamr-enhancement-DM/1234/save
-
-# the file names should start with whamr instead of whamorg
-train_data: results/sepformer-whamr-enhancement-DM/1234/save/whamr_tr.csv
-valid_data: results/sepformer-whamr-enhancement-DM/1234/save/whamr_cv.csv
-test_data: results/sepformer-whamr-enhancement-DM/1234/save/whamr_tt.csv
-skip_prep: false
-
-# Experiment params
-auto_mix_prec: true # Set it to True for mixed precision
-test_only: false
-num_spks: 1 # set to 3 for wsj0-3mix
-progressbar: true
-save_audio: true # Save estimated sources on disk
-sample_rate: 8000
-n_audio_to_save: 20
-
-# Training parameters
-N_epochs: 200
-batch_size: 1
-lr: 0.00015
-clip_grad_norm: 5
-loss_upper_lim: 999999  # this is the upper limit for an acceptable loss
-# if True, the training sequences are cut to a specified length
-limit_training_signal_len: false
-# this is the length of sequences if we choose to limit
-# the signal length of training sequences
-training_signal_len: 32000000
-
-# Set it to True to dynamically create mixtures at training time
-dynamic_mixing: true
-
-# Parameters for data augmentation
-
-# rir_path variable points to the directory of the room impulse responses
-# e.g. /miniscratch/subakany/rir_wavs
-# If the path does not exist, it is created automatically.
-rir_path: /network/scratch/s/subakany/whamr_rirs_wavs_8k/
-
-use_wavedrop: false
-use_speedperturb: true
-use_speedperturb_sameforeachsource: false
-use_rand_shift: false
-min_shift: -8000
-max_shift: 8000
-
-speedperturb: !new:speechbrain.lobes.augment.TimeDomainSpecAugment
-  perturb_prob: 1.0
-  drop_freq_prob: 0.0
-  drop_chunk_prob: 0.0
-  sample_rate: 8000
-  speeds: [95, 100, 105]
-
-wavedrop: !new:speechbrain.lobes.augment.TimeDomainSpecAugment
-  perturb_prob: 0.0
-  drop_freq_prob: 1.0
-  drop_chunk_prob: 1.0
-  sample_rate: 8000
-
-# loss thresholding -- this thresholds the training loss
-threshold_byloss: true
-threshold: -30
 
 # Encoder parameters
 N_encoder_out: 256
@@ -100,11 +17,6 @@ out_channels: 256
 kernel_size: 16
 kernel_stride: 8
 
-# Dataloader options
-dataloader_opts:
-  batch_size: 1
-  num_workers: 3
-
 # Specifying the network
 Encoder: &id003 !new:speechbrain.lobes.models.dual_path.Encoder
   kernel_size: 16
@@ -149,20 +61,6 @@ Decoder: &id004 !new:speechbrain.lobes.models.dual_path.Decoder
   stride: 8
   bias: false
 
-optimizer: !name:torch.optim.Adam
-  lr: 0.00015
-  weight_decay: 0
-
-loss: !name:speechbrain.nnet.losses.get_si_snr_with_pitwrapper
-
-lr_scheduler: &id007 !new:speechbrain.nnet.schedulers.ReduceLROnPlateau
-
-  factor: 0.5
-  patience: 2
-  dont_halve_until_epoch: 85
-
-epoch_counter: &id006 !new:speechbrain.utils.epoch_loop.EpochCounter
-  limit: 200
 
 modules:
   encoder: *id003
@@ -175,10 +73,6 @@ checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
     encoder: *id003
     decoder: *id004
     masknet: *id005
-    counter: *id006
-    lr_scheduler: *id007
-train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
-  save_file: results/sepformer-whamr-enhancement-DM/1234/train_log.txt
 
 pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
     loadables: