Delete hyperparams_develop.yaml

hyperparams_develop.yaml

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-# ############################################################################
-# Model: E2E ASR with Transformer
-# Encoder: Transformer Encoder
-# Decoder: Transformer Decoder + (CTC/ATT joint) beamsearch
-# Tokens: BPE with unigram
-# losses: CTC + KLdiv (Label Smoothing loss)
-# Training: AISHELL-1
-# Authors:  Jianyuan Zhong, Titouan Parcollet
-# ############################################################################
-
-# Feature parameters
-sample_rate: 16000
-n_fft: 400
-n_mels: 80
-
-####################### Model parameters ###########################
-# Transformer
-d_model: 256
-nhead: 4
-num_encoder_layers: 12
-num_decoder_layers: 6
-d_ffn: 2048
-transformer_dropout: 0.1
-activation: !name:torch.nn.GELU
-output_neurons: 5000
-vocab_size: 5000
-
-# Outputs
-blank_index: 0
-label_smoothing: 0.1
-pad_index: 0
-bos_index: 1
-eos_index: 2
-unk_index: 0
-
-# Decoding parameters
-min_decode_ratio: 0.0
-max_decode_ratio: 1.0 # 1.0
-valid_search_interval: 10
-valid_beam_size: 10
-test_beam_size: 10
-ctc_weight_decode: 0.40
-
-############################## models ################################
-
-compute_features: !new:speechbrain.lobes.features.Fbank
-    sample_rate: !ref <sample_rate>
-    n_fft: !ref <n_fft>
-    n_mels: !ref <n_mels>
-
-normalizer: !new:speechbrain.processing.features.InputNormalization
-    norm_type: global
-
-
-CNN: !new:speechbrain.lobes.models.convolution.ConvolutionFrontEnd
-    input_shape: (8, 10, 80)
-    num_blocks: 2
-    num_layers_per_block: 1
-    out_channels: (256, 256)
-    kernel_sizes: (3, 3)
-    strides: (2, 2)
-    residuals: (False, False)
-    norm: !name:speechbrain.nnet.normalization.BatchNorm2d
-
-Transformer: !new:speechbrain.lobes.models.transformer.TransformerASR.TransformerASR # yamllint disable-line rule:line-length
-    input_size: 5120
-    tgt_vocab: !ref <output_neurons>
-    d_model: !ref <d_model>
-    nhead: !ref <nhead>
-    num_encoder_layers: !ref <num_encoder_layers>
-    num_decoder_layers: !ref <num_decoder_layers>
-    d_ffn: !ref <d_ffn>
-    dropout: !ref <transformer_dropout>
-    activation: !ref <activation>
-    normalize_before: True
-
-ctc_lin: !new:speechbrain.nnet.linear.Linear
-    input_size: !ref <d_model>
-    n_neurons: !ref <output_neurons>
-
-seq_lin: !new:speechbrain.nnet.linear.Linear
-    input_size: !ref <d_model>
-    n_neurons: !ref <output_neurons>
-
-tokenizer: !new:sentencepiece.SentencePieceProcessor
-
-asr_model: !new:torch.nn.ModuleList
-    - [!ref <CNN>, !ref <Transformer>, !ref <seq_lin>, !ref <ctc_lin>]
-
-# Here, we extract the encoder from the Transformer model
-Tencoder: !new:speechbrain.lobes.models.transformer.TransformerASR.EncoderWrapper
-    transformer: !ref <Transformer>
-
-# We compose the inference (encoder) pipeline.
-encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential
-    input_shape: [null, null, !ref <n_mels>]
-    compute_features: !ref <compute_features>
-    normalize: !ref <normalizer>
-    cnn: !ref <CNN>
-    transformer_encoder: !ref <Tencoder>
-
-ctc_scorer: !new:speechbrain.decoders.scorer.CTCScorer
-    eos_index: !ref <eos_index>
-    blank_index: !ref <blank_index>
-    ctc_fc: !ref <ctc_lin>
-    
-scorer: !new:speechbrain.decoders.scorer.ScorerBuilder
-    full_scorers: [!ref <ctc_scorer>]
-    weights:
-        ctc: !ref <ctc_weight_decode>
-        
-decoder: !new:speechbrain.decoders.S2STransformerBeamSearcher
-    modules: [!ref <Transformer>, !ref <seq_lin>]
-    bos_index: !ref <bos_index>
-    eos_index: !ref <eos_index>
-    min_decode_ratio: !ref <min_decode_ratio>
-    max_decode_ratio: !ref <max_decode_ratio>
-    beam_size: !ref <test_beam_size>
-    using_eos_threshold: False
-    length_normalization: True
-    scorer: !ref <scorer>
-
-modules:
-    normalizer: !ref <normalizer>
-    encoder: !ref <encoder>
-    decoder: !ref <decoder>
-
-log_softmax: !new:torch.nn.LogSoftmax
-    dim: -1
-
-pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
-    loadables:
-        normalizer: !ref <normalizer>
-        asr: !ref <asr_model>
-        tokenizer: !ref <tokenizer>