added SSL benchmark and tests

benchmarks/SSL_benchmark/Buckeye/LSTM/hparams/ssl.yaml

@@ -0,0 +1,140 @@
+# ################################
+# ################################
+
+# Seed needs to be set at top of yaml, before objects with parameters are made
+seed: 1986
+__set_seed: !apply:torch.manual_seed [!ref <seed>]
+output_folder: !ref results/<seed>
+wer_file: !ref <output_folder>/wer.txt
+save_folder: !ref <output_folder>/save
+train_log: !ref <output_folder>/train_log.txt
+
+
+# Data files
+skip_prep: False
+csv_folder: !PLACEHOLDER # Path to the folder containing Buckeye training files
+ckpt_interval_minutes: 25 # save checkpoint every N min
+train_csv: !ref <csv_folder>/train.csv
+valid_csv: !ref <csv_folder>/dev.csv
+test_csv:
+   - !ref <csv_folder>/test.csv
+
+num_layers_ssl: 13  #Number of layers in the SSL model (should be 25 for large)
+ssl_hub: facebook/wav2vec2-base
+encoder_dim: 768
+
+# Training parameters
+number_of_epochs: 20
+lr: 0.0002
+lr_weights: 0.01
+sorting: ascending
+auto_mix_prec: False
+sample_rate: 16000
+language_modelling: False
+ngram_lm_path: !PLACEHOLDER # Path to the librispeech .arpa mù file
+
+# With data_parallel batch_size is split into N jobs
+# With DDP batch_size is multiplied by N jobs
+# Must be 3 per GPU to fit 32GB of VRAM
+batch_size: 4
+test_batch_size: 4
+
+# Dataloader options
+train_dataloader_opts:
+   batch_size: !ref <batch_size>
+
+valid_dataloader_opts:
+   batch_size: !ref <batch_size>
+
+test_dataloader_opts:
+   batch_size: !ref <test_batch_size>
+
+# Model parameters
+activation: !name:torch.nn.Sigmoid
+dnn_layers: 1
+dnn_neurons: 768
+freeze_encoder: True
+
+# Outputs
+output_neurons: 30  # BPE size, index(blank/eos/bos) = 0
+
+
+# Functions and classes
+#
+epoch_counter: !new:speechbrain.utils.epoch_loop.EpochCounter
+   limit: !ref <number_of_epochs>
+
+augmentation: !new:speechbrain.lobes.augment.TimeDomainSpecAugment
+   sample_rate: !ref <sample_rate>
+   speeds: [95, 100, 105]
+
+weighted_ssl_model: !new:speechbrain.lobes.models.huggingface_wav2vec.WeightedSSLModel # yamllint disable-line rule:line-length
+   hub: !ref <ssl_hub>
+   num_layers: !ref <num_layers_ssl>
+
+enc: !new:speechbrain.nnet.RNN.LSTM
+   input_shape: [Null, Null, !ref <encoder_dim>]
+   num_layers: 2
+   bidirectional: True
+   dropout: 0.2
+   hidden_size: 1024
+
+ctc_lin: !new:speechbrain.nnet.linear.Linear
+   input_size: 2048
+   n_neurons: !ref <output_neurons>
+
+log_softmax: !new:speechbrain.nnet.activations.Softmax
+   apply_log: True
+
+ctc_cost: !name:speechbrain.nnet.losses.ctc_loss
+   blank_index: !ref <blank_index>
+
+modules:
+   enc: !ref <enc>
+   ctc_lin: !ref <ctc_lin>
+   weighted_ssl_model: !ref <weighted_ssl_model>
+
+model: !new:torch.nn.ModuleList
+   - [!ref <enc>, !ref <ctc_lin>]
+
+model_opt_class: !name:torch.optim.Adam
+   lr: !ref <lr>
+
+weights_opt_class: !name:torch.optim.Adam
+   lr: !ref <lr_weights>
+
+lr_annealing_model: !new:speechbrain.nnet.schedulers.NewBobScheduler
+   initial_value: !ref <lr>
+   improvement_threshold: 0.0025
+   annealing_factor: 0.8
+   patient: 0
+
+lr_annealing_weights: !new:speechbrain.nnet.schedulers.NewBobScheduler
+   initial_value: !ref <lr_weights>
+   improvement_threshold: 0.0025
+   annealing_factor: 0.9
+   patient: 0
+
+label_encoder: !new:speechbrain.dataio.encoder.CTCTextEncoder
+
+checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
+   checkpoints_dir: !ref <save_folder>
+   recoverables:
+      model: !ref <model>
+      ssl_model: !ref <weighted_ssl_model>
+      scheduler_model: !ref <lr_annealing_model>
+      scheduler_encoder: !ref <lr_annealing_weights>
+      counter: !ref <epoch_counter>
+      tokenizer: !ref <label_encoder>
+
+blank_index: 0
+unk_index: 1
+
+
+train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
+   save_file: !ref <train_log>
+
+error_rate_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats
+
+cer_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats
+   split_tokens: True