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encoder: chunkformer
is_json_cmvn: true
cmvn_file: chunkformer-large-en/global_cmvn
input_dim: 80
output_dim: 4990
encoder_conf:
output_size: 512 # dimension of attention
attention_heads: 8
linear_units: 2048 # the number of units of position-wise feed forward
num_blocks: 17 # the number of encoder blocks
dropout_rate: 0.1
positional_dropout_rate: 0.1
attention_dropout_rate: 0.1
input_layer: 'depthwise' # encoder input type, you can chose conv2d, conv2d6 and conv2d8
normalize_before: true
cnn_module_kernel: 15
use_cnn_module: true
activation_type: 'swish'
pos_enc_layer_type: 'stream_rel_pos'
selfattention_layer_type: 'stream_rel_selfattn'
causal: false
use_dynamic_chunk: false
use_limited_chunk: false
use_context_hint_chunk: false
right_context_probs: [0.75]
right_context_sizes: [128, 128, 128]
limited_decoding_chunk_sizes: [64, 128, 256]
limited_left_chunk_sizes: [128, 256, 128]
cnn_module_norm: 'layer_norm' # using nn.LayerNorm makes model converge faster
use_dynamic_left_chunk: false
use_dynamic_conv: true
freeze_subsampling_layer: false
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