Introduce code from Rust monorepo. This is a mess

This commit is contained in:
Brandon Thomas
2022-02-28 05:43:54 -05:00
parent 921fb49f9a
commit ba326bfcfd
1058 changed files with 192192 additions and 0 deletions
@@ -0,0 +1,180 @@
name: &name "MarbleNet-3x2x64"
model:
sample_rate: 16000
repeat: 2
dropout: 0.0
kernel_size_factor: 1.0
labels: ['background', 'speech']
train_ds:
manifest_filepath: ???
sample_rate: ${model.sample_rate}
labels: ${model.labels}
batch_size: 128
shuffle: True
is_tarred: False
tarred_audio_filepaths: null
tarred_shard_strategy: "scatter"
augmentor:
shift:
prob: 1.0
min_shift_ms: -5.0
max_shift_ms: 5.0
white_noise:
prob: 1.0
min_level: -90
max_level: -46
validation_ds:
manifest_filepath: ???
sample_rate: ${model.sample_rate}
labels: ${model.labels}
batch_size: 128
shuffle: False
val_loss_idx: 0
test_ds:
manifest_filepath: null
sample_rate: ${model.sample_rate}
labels: ${model.labels}
batch_size: 128
shuffle: False
test_loss_idx: 0
preprocessor:
_target_: nemo.collections.asr.modules.AudioToMFCCPreprocessor
window_size: 0.025
window_stride: 0.01
window: "hann"
n_mels: &n_mels 64
n_mfcc: *n_mels
n_fft: 512
spec_augment:
_target_: nemo.collections.asr.modules.SpectrogramAugmentation
freq_masks: 2
time_masks: 2
freq_width: 15
time_width: 25
rect_masks: 5
rect_time: 25
rect_freq: 15
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.dropout}
residual: false
separable: true
kernel_size_factor: ${model.kernel_size_factor}
- filters: 64
repeat: ${model.repeat}
kernel: [13]
stride: [1]
dilation: [1]
dropout: ${model.dropout}
residual: true
separable: true
kernel_size_factor: ${model.kernel_size_factor}
- filters: 64
repeat: ${model.repeat}
kernel: [15]
stride: [1]
dilation: [1]
dropout: ${model.dropout}
residual: true
separable: true
kernel_size_factor: ${model.kernel_size_factor}
- filters: 64
repeat: ${model.repeat}
kernel: [17]
stride: [1]
dilation: [1]
dropout: ${model.dropout}
residual: true
separable: true
kernel_size_factor: ${model.kernel_size_factor}
- filters: 128
repeat: 1
kernel: [29]
stride: [1]
dilation: [2]
dropout: ${model.dropout}
residual: false
separable: true
kernel_size_factor: ${model.kernel_size_factor}
- filters: &enc_final_filters 128
repeat: 1
kernel: [1]
stride: [1]
dilation: [1]
dropout: ${model.dropout}
residual: false
decoder:
_target_: nemo.collections.asr.modules.ConvASRDecoderClassification
feat_in: *enc_final_filters
return_logits: true
pooling_type: 'avg'
optim:
name: sgd
lr: 0.01
# optimizer arguments
weight_decay: 0.001
momentum: 0.9
# scheduler setup
sched:
name: PolynomialHoldDecayAnnealing
# Scheduler params
power: 2.0
warmup_ratio: 0.05
hold_ratio: 0.45
min_lr: 0.001
last_epoch: -1
trainer:
gpus: 0 # number of gpus
max_epochs: 150
max_steps: null # computed at runtime if not set
num_nodes: 1
accelerator: ddp
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
create_wandb_logger: False
wandb_logger_kwargs:
name: null
project: null
hydra:
run:
dir: .
job_logging:
root:
handlers: null