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Have 6 different encoder stacks, U-shaped network.

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This commit is contained in:
Daniel Povey 2022-10-28 20:36:45 +08:00
parent 7b57a34227
commit 96ea4cf1be
1 changed files with 8 additions and 8 deletions
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16
egs/librispeech/ASR/pruned_transducer_stateless7/train.py
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@ -93,35 +93,35 @@ def add_model_arguments(parser: argparse.ArgumentParser):
parser.add_argument(
"--num-encoder-layers",
type=str,
default="2,4,4,4",
default="2,3,3,3,3,3",
help="Number of zipformer encoder layers, comma separated.",
)
parser.add_argument(
"--feedforward-dims",
type=str,
default="1024,1536,1536,1536",
default="1024,1024,1536,1536,1536,1024",
help="Feedforward dimension of the zipformer encoder layers, comma separated.",
)
parser.add_argument(
"--nhead",
type=str,
default="8,8,8,8",
default="8,8,8,8,8,8",
help="Number of attention heads in the zipformer encoder layers.",
)
parser.add_argument(
"--encoder-dims",
type=str,
default="384,384,384,512",
default="384,384,384,384,384,384",
help="Embedding dimension in the 2 blocks of zipformer encoder layers, comma separated"
)
parser.add_argument(
"--attention-dims",
type=str,
default="192,192,192,256",
default="192,192,192,192,192,192",
help="""Attention dimension in the 2 blocks of zipformer encoder layers, comma separated;
not the same as embedding dimension."""
)
@ -129,7 +129,7 @@ def add_model_arguments(parser: argparse.ArgumentParser):
parser.add_argument(
"--encoder-unmasked-dims",
type=str,
default="256,256,256,256",
default="256,256,256,256,256,256",
help="Unmasked dimensions in the encoders, relates to augmentation during training. "
"Must be <= each of encoder_dims. Empirically, less than 256 seems to make performance "
" worse."
@ -138,14 +138,14 @@ def add_model_arguments(parser: argparse.ArgumentParser):
parser.add_argument(
"--zipformer-downsampling-factors",
type=str,
default="1,2,4,8",
default="1,2,4,8,4,2",
help="Downsampling factor for each stack of encoder layers.",
)
parser.add_argument(
"--cnn-module-kernels",
type=str,
default="31,31,31,31",
default="31,31,31,31,31,31",
help="Sizes of kernels in convolution modules",
)