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class AVHubertConfig(PretrainedConfig):
model_type = "avhubert"
def __init__(
self,
odim=5049,
adim=1024,
aheads=12,
eunits=3072,
elayers=12,
transformer_input_layer="conv3d",
dropout_rate=0.1,
transformer_attn_dropout_rate=0.1,
transformer_encoder_attn_layer_type="rel_mha",
macaron_style=True,
use_cnn_module=True,
cnn_module_kernel=31,
zero_triu=False,
a_upsample_ratio=1,
relu_type="swish",
ddim=1024,
dheads=16,
dunits=3072,
dlayers=6,
lsm_weight=0.1,
transformer_length_normalized_loss=False,
mtlalpha=0.1,
ctc_type="builtin",
rel_pos_type="latest",
fusion_hdim=8192,
fusion_norm="batchnorm",
hidden_size=1024,
num_attention_heads=16,
activation_dropout=0.0,
activation_function="relu",
adapter_attn_dim=None,
adapter_kernel_size=3,
adapter_stride=2,
add_adapter=False,
apply_spec_augment=True,
attention_dropout=0.1,
audio_dropout=0.5,
audio_feat_dim=104,
bos_token_id=1,
classifier_proj_size=256,
codevector_dim=256,
contrastive_logits_temperature=0.1,
conv_bias=False,
conv_channels=1024,
conv_dim=[512, 512, 512, 512, 512, 512, 512],
conv_kernel=[10, 3, 3, 3, 3, 2, 2],
conv_kernel_sizes=[5, 5],
conv_stride=[5, 2, 2, 2, 2, 2, 2],
ctc_loss_reduction="sum",
ctc_zero_infinity=False,
d_model=1024,
decoder_attention_heads=8,
decoder_ffn_dim=4096,
decoder_layerdrop=0.0,
decoder_layers=9,
decoder_start_token_id=2,
diversity_loss_weight=0.1,
do_stable_layer_norm=False,
dropout=0.1,
dropout_features=0.1,
dropout_input=0.1,
encoder_attention_heads=16,
encoder_embed_dim=1024,
encoder_ffn_dim=2048,
encoder_layerdrop=0.0,
encoder_layers=12,
eos_token_id=2,
feat_extract_activation="gelu",
feat_extract_norm="group",
feat_proj_dropout=0.1,
feat_quantizer_dropout=0.0,
feature_grad_mult=0.1,
final_dim=256,
final_dropout=0.0,
freeze_feat_extract_train=True,
hidden_act="gelu",
hidden_dropout=0.1,
init_std=0.02,
initializer_range=0.02,
input_channels=1,
input_feat_per_channel=80,
intermediate_size=4096,
is_encoder_decoder=True,
label_rate=25,
layer_norm_eps=1e-05,
layerdrop=0.0,
logit_temp=0.1,
mask_channel_length=10,
mask_channel_min_space=1,
mask_channel_other=0.0,
mask_channel_prob=0.0,
mask_channel_selection="static",
mask_feature_length=10,
mask_feature_min_masks=0,
mask_feature_prob=0.0,
mask_length_audio=10,
mask_length_image=5,
mask_min_space=1,
mask_other=0.0,
mask_prob_audio=0.8,
mask_prob_image=0.3,
mask_selection="static",
mask_time_length=10,
mask_time_min_masks=2,
mask_time_min_space=1,
mask_time_other=0.0,
mask_time_prob=0.0,
mask_time_selection="static",
masking_type="input",
max_source_positions=6000,
max_target_positions=2048,
modality_dropout=0.5,
modality_fuse="concat",
modality="av",
model_type="speech_to_text",
no_mask_channel_overlap=False,
no_mask_overlap=False,
no_mask_time_overlap=False,
num_adapter_layers=3,
num_classes=2004,
num_codevector_groups=2,
num_codevectors_per_group=320,
num_conv_layers=2,
num_conv_pos_embedding_groups=16,
num_conv_pos_embeddings=128,
num_dictionaries=1,
num_feat_extract_layers=7,
num_hidden_layers=24,
num_negatives=100,
output_hidden_size=1024,
pad_token_id=1,
proj_codevector_dim=256,
resnet_relu_type="prelu",
resnet_weights=None,
sample_rate=25,
scale_embedding=None,
selection_type="same_seq",
sim_type="cosine",
skip_masked=False,
skip_nomask=False,
sub_encoder_layers=0,
target_glu=False,
tdnn_dilation=[1, 2, 3, 1, 1],
tdnn_dim=[512, 512, 512, 512, 1500],
tdnn_kernel=[5, 3, 3, 1, 1],
untie_final_proj=True,
use_cache=True,
use_weighted_layer_sum=False,
vocab_size=1000,
xvector_output_dim=512,
**kwargs,
):
super().__init__(**kwargs)
self.odim = odim
self.adim = adim
self.aheads = aheads
self.eunits = eunits
self.elayers = elayers
self.transformer_input_layer = transformer_input_layer
self.dropout_rate = dropout_rate
self.transformer_attn_dropout_rate = transformer_attn_dropout_rate
self.transformer_encoder_attn_layer_type = transformer_encoder_attn_layer_type
self.macaron_style = macaron_style
self.use_cnn_module = use_cnn_module
self.cnn_module_kernel = cnn_module_kernel
self.zero_triu = zero_triu
self.a_upsample_ratio = a_upsample_ratio
self.relu_type = relu_type
self.ddim = ddim
self.dheads = dheads
self.dunits = dunits
self.dlayers = dlayers
self.lsm_weight = lsm_weight
self.transformer_length_normalized_loss = transformer_length_normalized_loss
self.mtlalpha = mtlalpha
self.ctc_type = ctc_type
self.rel_pos_type = rel_pos_type
self.fusion_hdim = fusion_hdim
self.fusion_norm = fusion_norm
self.hidden_size = hidden_size
self.num_attention_heads = num_attention_heads
self.activation_dropout = activation_dropout
self.activation_function = activation_function
self.adapter_attn_dim = adapter_attn_dim
self.adapter_kernel_size = adapter_kernel_size
self.adapter_stride = adapter_stride
self.add_adapter = add_adapter
self.apply_spec_augment = apply_spec_augment
self.attention_dropout = attention_dropout
self.audio_dropout = audio_dropout
self.audio_feat_dim = audio_feat_dim
self.bos_token_id = bos_token_id
self.classifier_proj_size = classifier_proj_size
self.codevector_dim = codevector_dim
self.contrastive_logits_temperature = contrastive_logits_temperature
self.conv_bias = conv_bias
self.conv_channels = conv_channels
self.conv_dim = conv_dim
self.conv_kernel = conv_kernel
self.conv_kernel_sizes = conv_kernel_sizes
self.conv_stride = conv_stride
self.ctc_loss_reduction = ctc_loss_reduction
self.ctc_zero_infinity = ctc_zero_infinity
self.d_model = d_model
self.decoder_attention_heads = decoder_attention_heads
self.decoder_ffn_dim = decoder_ffn_dim
self.decoder_layerdrop = decoder_layerdrop
self.decoder_layers = decoder_layers
self.decoder_start_token_id = decoder_start_token_id
self.diversity_loss_weight = diversity_loss_weight
self.do_stable_layer_norm = do_stable_layer_norm
self.dropout = dropout
self.dropout_features = dropout_features
self.dropout_input = dropout_input
self.encoder_attention_heads = encoder_attention_heads
self.encoder_embed_dim = encoder_embed_dim
self.encoder_ffn_dim = encoder_ffn_dim
self.encoder_layerdrop = encoder_layerdrop
self.encoder_layers = encoder_layers
self.eos_token_id = eos_token_id
self.feat_extract_activation = feat_extract_activation
self.feat_extract_norm = feat_extract_norm
self.feat_proj_dropout = feat_proj_dropout
self.feat_quantizer_dropout = feat_quantizer_dropout
self.feature_grad_mult = feature_grad_mult
self.final_dim = final_dim
self.final_dropout = final_dropout
self.freeze_feat_extract_train = freeze_feat_extract_train
self.hidden_act = hidden_act
self.hidden_dropout = hidden_dropout
self.init_std = init_std
self.initializer_range = initializer_range
self.input_channels = input_channels
self.input_feat_per_channel = input_feat_per_channel
self.intermediate_size = intermediate_size
self.is_encoder_decoder = is_encoder_decoder
self.label_rate = label_rate
self.layer_norm_eps = layer_norm_eps
self.layerdrop = layerdrop
self.logit_temp = logit_temp
self.mask_channel_length = mask_channel_length
self.mask_channel_min_space = mask_channel_min_space
self.mask_channel_other = mask_channel_other
self.mask_channel_prob = mask_channel_prob
self.mask_channel_selection = mask_channel_selection
self.mask_feature_length = mask_feature_length
self.mask_feature_min_masks = mask_feature_min_masks
self.mask_feature_prob = mask_feature_prob
self.mask_length_audio = mask_length_audio
self.mask_length_image = mask_length_image
self.mask_min_space = mask_min_space
self.mask_other = mask_other
self.mask_prob_audio = mask_prob_audio
self.mask_prob_image = mask_prob_image
self.mask_selection = mask_selection
self.mask_time_length = mask_time_length
self.mask_time_min_masks = mask_time_min_masks
self.mask_time_min_space = mask_time_min_space
self.mask_time_other = mask_time_other
self.mask_time_prob = mask_time_prob
self.mask_time_selection = mask_time_selection
self.masking_type = masking_type
self.max_source_positions = max_source_positions
self.max_target_positions = max_target_positions
self.modality_dropout = modality_dropout
self.modality_fuse = modality_fuse
self.modality = modality
self.model_type = model_type
self.no_mask_channel_overlap = no_mask_channel_overlap
self.no_mask_overlap = no_mask_overlap
self.no_mask_time_overlap = no_mask_time_overlap
self.num_adapter_layers = num_adapter_layers
self.num_classes = num_classes
self.num_codevector_groups = num_codevector_groups
self.num_codevectors_per_group = num_codevectors_per_group
self.num_conv_layers = num_conv_layers
self.num_conv_pos_embedding_groups = num_conv_pos_embedding_groups
self.num_conv_pos_embeddings = num_conv_pos_embeddings
self.num_dictionaries = num_dictionaries
self.num_feat_extract_layers = num_feat_extract_layers
self.num_hidden_layers = num_hidden_layers
self.num_negatives = num_negatives
self.output_hidden_size = output_hidden_size
self.pad_token_id = pad_token_id
self.proj_codevector_dim = proj_codevector_dim
self.resnet_relu_type = resnet_relu_type
self.resnet_weights = resnet_weights
self.sample_rate = sample_rate
self.scale_embedding = scale_embedding
self.selection_type = selection_type
self.sim_type = sim_type
self.skip_masked = skip_masked
self.skip_nomask = skip_nomask
self.sub_encoder_layers = sub_encoder_layers
self.target_glu = target_glu
self.tdnn_dilation = tdnn_dilation
self.tdnn_dim = tdnn_dim
self.tdnn_kernel = tdnn_kernel
self.untie_final_proj = untie_final_proj
self.use_cache = use_cache
self.use_weighted_layer_sum = use_weighted_layer_sum
self.vocab_size = vocab_size
self.xvector_output_dim = xvector_output_dim
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