Introduce code from Rust monorepo. This is a mess

tts/NeMo/examples/asr/experimental/contextnet_rnnt/config_rnnt.yaml

@@ -0,0 +1,237 @@
+name: &name "ConvRNNT5x1"
+
+model:
+  sample_rate: 16000
+  compute_eval_loss: true
+
+  labels: [ " ", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m",
+            "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z", "'" ]
+
+  train_ds:
+    manifest_filepath: ???
+    sample_rate: ${model.sample_rate}
+    batch_size: 32
+    trim_silence: true
+    max_duration: 16.7
+    labels: ${model.labels}
+    shuffle: true
+    is_tarred: false
+    tarred_audio_filepaths: null
+    tarred_shard_strategy: "scatter"
+
+  validation_ds:
+    manifest_filepath: ???
+    sample_rate: ${model.sample_rate}
+    batch_size: 32
+    shuffle: false
+    labels: ${model.labels}
+
+  test_ds:
+    manifest_filepath: null
+    sample_rate: ${model.sample_rate}
+    batch_size: 32
+    shuffle: false
+    labels: ${model.labels}
+
+  model_defaults:
+    repeat: 5
+    dropout: 0.0
+    separable: true
+    se: true
+    se_context_size: -1
+    # encoder / decoder / joint values
+    enc_hidden: 1024
+    pred_hidden: 320
+    joint_hidden: 320
+
+  preprocessor:
+    _target_: nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor
+    normalize: "per_feature"
+    window_size: 0.02
+    sample_rate: ${model.sample_rate}
+    window_stride: 0.01
+    window: "hann"
+    features: &n_mels 80
+    n_fft: 512
+    frame_splicing: 1
+    dither: 0.00001
+
+  spec_augment:
+    _target_: nemo.collections.asr.modules.SpectrogramAugmentation
+    rect_freq: 50
+    rect_masks: 5
+    rect_time: 120
+
+  encoder:
+    _target_: nemo.collections.asr.modules.ConvASREncoder
+    feat_in: *n_mels
+    activation: relu
+    conv_mask: true
+
+    jasper:
+      - filters: 128
+        repeat: 1
+        kernel: [11]
+        stride: [1]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+
+      - filters: 256
+        repeat: ${model.model_defaults.repeat}
+        kernel: [13]
+        stride: [2]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+        stride_last: true
+        residual_mode: "stride_add"
+
+      - filters: 256
+        repeat: ${model.model_defaults.repeat}
+        kernel: [15]
+        stride: [1]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+
+      - filters: 256
+        repeat: ${model.model_defaults.repeat}
+        kernel: [17]
+        stride: [2]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+        stride_last: true
+        residual_mode: "stride_add"
+
+      - filters: 256
+        repeat: ${model.model_defaults.repeat}
+        kernel: [19]
+        stride: [1]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+
+      - filters: 256
+        repeat: 1
+        kernel: [21]
+        stride: [2]
+        dilation: [1]
+        dropout: 0.0
+        residual: false
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+        stride_last: true
+        residual_mode: "stride_add"
+
+      - filters: ${model.model_defaults.enc_hidden}
+        repeat: 1
+        kernel: [1]
+        stride: [1]
+        dilation: [1]
+        dropout: 0.0
+        residual: false
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+
+  decoder:
+    _target_: nemo.collections.asr.modules.RNNTDecoder
+    normalization_mode: null
+    random_state_sampling: false
+    blank_as_pad: true
+
+    prednet:
+      pred_hidden: ${model.model_defaults.pred_hidden}
+      pred_rnn_layers: 1
+      t_max: null
+      dropout: 0.0
+
+  joint:
+    _target_: nemo.collections.asr.modules.RNNTJoint
+    log_softmax: null  # sets it according to cpu/gpu device
+
+    # fused mode
+    experimental_fuse_loss_wer: false
+    fused_batch_size: 1
+
+    jointnet:
+      joint_hidden: ${model.model_defaults.joint_hidden}
+      activation: "relu"
+      dropout: 0.0
+
+  decoding:
+    strategy: "greedy_batch"
+
+    # greedy strategy config
+    greedy:
+      max_symbols: 30
+
+    # beam strategy config
+    beam:
+      beam_size: 2
+      score_norm: true
+      tsd_max_sym_exp: 50  # for Time Synchronous Decoding
+      alsd_max_target_len: 2.0  # for Alignment-Length Synchronous Decoding
+
+  optim:
+    name: adam
+    # _target_: nemo.core.optim.optimizers.Adam
+    lr: .1
+
+    # optimizer arguments
+    betas: [0.9, 0.999]
+    weight_decay: 0.0001
+
+    # scheduler setup
+    sched:
+      name: CosineAnnealing
+
+      # scheduler config override
+      warmup_steps: null
+      warmup_ratio: 0.05
+      min_lr: 1e-6
+      last_epoch: -1
+
+trainer:
+  gpus: 0 # number of gpus
+  max_epochs: 5
+  max_steps: null # computed at runtime if not set
+  num_nodes: 1
+  accelerator: ddp
+  precision: 32
+  accumulate_grad_batches: 1
+  checkpoint_callback: False  # Provided by exp_manager
+  logger: False  # Provided by exp_manager
+  log_every_n_steps: 1  # Interval of logging.
+  val_check_interval: 1.0 # Set to 0.25 to check 4 times per epoch, or an int for number of iterations
+
+exp_manager:
+  exp_dir: null
+  name: *name
+  create_tensorboard_logger: True
+  create_checkpoint_callback: True
+  checkpoint_callback_params:
+    monitor: "val_wer"
+    mode: "min"
+  create_wandb_logger: False
+  wandb_logger_kwargs:
+    name: null
+    project: null

tts/NeMo/examples/asr/experimental/contextnet_rnnt/config_rnnt_bpe.yaml

@@ -0,0 +1,238 @@
+name: &name "ConvRNNTBPE5x1"
+
+model:
+  sample_rate: 16000
+  compute_eval_loss: true
+
+  tokenizer:
+    dir: ???  # path to directory which contains either tokenizer.model (bpe) or vocab.txt (for wpe)
+    type: ???  # Can be either bpe or wpe
+
+  train_ds:
+    manifest_filepath: ???
+    sample_rate: ${model.sample_rate}
+    batch_size: 32
+    trim_silence: true
+    max_duration: 16.7
+    labels: []
+    shuffle: true
+    is_tarred: false
+    tarred_audio_filepaths: null
+    tarred_shard_strategy: "scatter"
+
+  validation_ds:
+    manifest_filepath: ???
+    sample_rate: ${model.sample_rate}
+    batch_size: 32
+    shuffle: false
+    labels: []
+
+  test_ds:
+    manifest_filepath: null
+    sample_rate: ${model.sample_rate}
+    batch_size: 32
+    shuffle: false
+    labels: []
+
+  model_defaults:
+    repeat: 5
+    dropout: 0.0
+    separable: true
+    se: true
+    se_context_size: -1
+    # encoder / decoder / joint values
+    enc_hidden: 1024
+    pred_hidden: 320
+    joint_hidden: 320
+
+  preprocessor:
+    _target_: nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor
+    normalize: "per_feature"
+    window_size: 0.02
+    sample_rate: ${model.sample_rate}
+    window_stride: 0.01
+    window: "hann"
+    features: &n_mels 80
+    n_fft: 512
+    frame_splicing: 1
+    dither: 0.00001
+
+  spec_augment:
+    _target_: nemo.collections.asr.modules.SpectrogramAugmentation
+    rect_freq: 50
+    rect_masks: 5
+    rect_time: 120
+
+  encoder:
+    _target_: nemo.collections.asr.modules.ConvASREncoder
+    feat_in: *n_mels
+    activation: relu
+    conv_mask: true
+
+    jasper:
+      - filters: 128
+        repeat: 1
+        kernel: [11]
+        stride: [1]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+
+      - filters: 256
+        repeat: ${model.model_defaults.repeat}
+        kernel: [13]
+        stride: [2]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+        stride_last: true
+        residual_mode: "stride_add"
+
+      - filters: 256
+        repeat: ${model.model_defaults.repeat}
+        kernel: [15]
+        stride: [1]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+
+      - filters: 256
+        repeat: ${model.model_defaults.repeat}
+        kernel: [17]
+        stride: [2]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+        stride_last: true
+        residual_mode: "stride_add"
+
+      - filters: 256
+        repeat: ${model.model_defaults.repeat}
+        kernel: [19]
+        stride: [1]
+        dilation: [1]
+        dropout: ${model.model_defaults.dropout}
+        residual: true
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+
+      - filters: 256
+        repeat: 1
+        kernel: [21]
+        stride: [2]
+        dilation: [1]
+        dropout: 0.0
+        residual: false
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+        stride_last: true
+        residual_mode: "stride_add"
+
+      - filters: ${model.model_defaults.enc_hidden}
+        repeat: 1
+        kernel: [1]
+        stride: [1]
+        dilation: [1]
+        dropout: 0.0
+        residual: false
+        separable: ${model.model_defaults.separable}
+        se: ${model.model_defaults.se}
+        se_context_size: ${model.model_defaults.se_context_size}
+
+  decoder:
+    _target_: nemo.collections.asr.modules.RNNTDecoder
+    normalization_mode: null
+    random_state_sampling: false
+    blank_as_pad: true
+
+    prednet:
+      pred_hidden: ${model.model_defaults.pred_hidden}
+      pred_rnn_layers: 1
+      t_max: null
+      dropout: 0.0
+
+  joint:
+    _target_: nemo.collections.asr.modules.RNNTJoint
+    log_softmax: null  # sets it according to cpu/gpu device
+
+    # fused mode
+    experimental_fuse_loss_wer: false
+    fused_batch_size: 1
+
+    jointnet:
+      joint_hidden: ${model.model_defaults.joint_hidden}
+      activation: "relu"
+      dropout: 0.0
+
+  decoding:
+    strategy: "greedy_batch"
+
+    # greedy strategy config
+    greedy:
+      max_symbols: 30
+
+    # beam strategy config
+    beam:
+      beam_size: 2
+      score_norm: true
+      tsd_max_sym_exp: 50  # for Time Synchronous Decoding
+      alsd_max_target_len: 2.0  # for Alignment-Length Synchronous Decoding
+
+  optim:
+    name: adam
+    # _target_: nemo.core.optim.optimizers.Adam
+    lr: .1
+
+    # optimizer arguments
+    betas: [0.9, 0.999]
+    weight_decay: 0.0001
+
+    # scheduler setup
+    sched:
+      name: CosineAnnealing
+
+      # scheduler config override
+      warmup_steps: null
+      warmup_ratio: 0.05
+      min_lr: 1e-6
+      last_epoch: -1
+
+trainer:
+  gpus: 0 # number of gpus
+  max_epochs: 5
+  max_steps: null # computed at runtime if not set
+  num_nodes: 1
+  accelerator: ddp
+  precision: 32
+  accumulate_grad_batches: 1
+  checkpoint_callback: False  # Provided by exp_manager
+  logger: False  # Provided by exp_manager
+  log_every_n_steps: 1  # Interval of logging.
+  val_check_interval: 1.0 # Set to 0.25 to check 4 times per epoch, or an int for number of iterations
+
+exp_manager:
+  exp_dir: null
+  name: *name
+  create_tensorboard_logger: True
+  create_checkpoint_callback: True
+  checkpoint_callback_params:
+    monitor: "val_wer"
+    mode: "min"
+  create_wandb_logger: False
+  wandb_logger_kwargs:
+    name: null
+    project: null