remove more training stuff

hyperparams.yaml

@@ -8,8 +8,6 @@
 # Authors:  Loren Lugosch, Mirco Ravanelli 2020
 # ############################################################################
 
-token_type: unigram # ["unigram", "bpe", "char"]
-
 # Model parameters
 sample_rate: 16000
 emb_size: 128
@@ -75,11 +73,8 @@ model: !new:torch.nn.ModuleList
 tokenizer: !new:sentencepiece.SentencePieceProcessor
 
 pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
-    collect_in: !ref <save_folder>/TAS_tokenizer
     loadables:
         tokenizer: !ref <tokenizer>
-    paths:
-        tokenizer: !ref <tokenizer_file>
 
 beam_searcher: !new:speechbrain.decoders.S2SRNNBeamSearcher
     embedding: !ref <output_emb>
@@ -96,36 +91,7 @@ beam_searcher: !new:speechbrain.decoders.S2SRNNBeamSearcher
     max_attn_shift: 30
     coverage_penalty: 0.
 
-opt_class: !name:torch.optim.Adam
-    lr: !ref <lr>
-
-lr_annealing: !new:speechbrain.nnet.schedulers.NewBobScheduler
-    initial_value: !ref <lr>
-    improvement_threshold: 0.0025
-    annealing_factor: 0.8
-    patient: 0
-
-checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
-    checkpoints_dir: !ref <save_folder>
-    recoverables:
-        model: !ref <model>
-        scheduler: !ref <lr_annealing>
-        counter: !ref <epoch_counter>
-
-augmentation: !new:speechbrain.lobes.augment.TimeDomainSpecAugment
-    sample_rate: !ref <sample_rate>
-    speeds: [95, 100, 105]
-
 log_softmax: !new:speechbrain.nnet.activations.Softmax
     apply_log: True
 
-seq_cost: !name:speechbrain.nnet.losses.nll_loss
-    label_smoothing: 0.1
-
-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