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"""Transducer model arguments."""
import ast
from distutils.util import strtobool
def add_encoder_general_arguments(group):
"""Define general arguments for encoder."""
group.add_argument(
"--etype",
default="blstmp",
type=str,
choices=[
"custom",
"lstm",
"blstm",
"lstmp",
"blstmp",
"vgglstmp",
"vggblstmp",
"vgglstm",
"vggblstm",
"gru",
"bgru",
"grup",
"bgrup",
"vgggrup",
"vggbgrup",
"vgggru",
"vggbgru",
],
help="Type of encoder network architecture",
)
group.add_argument(
"--dropout-rate",
default=0.0,
type=float,
help="Dropout rate for the encoder",
)
return group
def add_rnn_encoder_arguments(group):
"""Define arguments for RNN encoder."""
group.add_argument(
"--elayers",
default=4,
type=int,
help="Number of encoder layers (for shared recognition part "
"in multi-speaker asr mode)",
)
group.add_argument(
"--eunits",
"-u",
default=300,
type=int,
help="Number of encoder hidden units",
)
group.add_argument(
"--eprojs", default=320, type=int, help="Number of encoder projection units"
)
group.add_argument(
"--subsample",
default="1",
type=str,
help="Subsample input frames x_y_z means subsample every x frame "
"at 1st layer, every y frame at 2nd layer etc.",
)
return group
def add_custom_encoder_arguments(group):
"""Define arguments for Custom encoder."""
group.add_argument(
"--enc-block-arch",
type=eval,
action="append",
default=None,
help="Encoder architecture definition by blocks",
)
group.add_argument(
"--enc-block-repeat",
default=0,
type=int,
help="Repeat N times the provided encoder blocks if N > 1",
)
group.add_argument(
"--custom-enc-input-layer",
type=str,
default="conv2d",
choices=["conv2d", "vgg2l", "linear", "embed"],
help="Custom encoder input layer type",
)
group.add_argument(
"--custom-enc-positional-encoding-type",
type=str,
default="abs_pos",
choices=["abs_pos", "scaled_abs_pos", "rel_pos"],
help="Custom encoder positional encoding layer type",
)
group.add_argument(
"--custom-enc-self-attn-type",
type=str,
default="self_attn",
choices=["self_attn", "rel_self_attn"],
help="Custom encoder self-attention type",
)
group.add_argument(
"--custom-enc-pw-activation-type",
type=str,
default="relu",
choices=["relu", "hardtanh", "selu", "swish"],
help="Custom encoder pointwise activation type",
)
group.add_argument(
"--custom-enc-conv-mod-activation-type",
type=str,
default="swish",
choices=["relu", "hardtanh", "selu", "swish"],
help="Custom encoder convolutional module activation type",
)
return group
def add_decoder_general_arguments(group):
"""Define general arguments for encoder."""
group.add_argument(
"--dtype",
default="lstm",
type=str,
choices=["lstm", "gru", "custom"],
help="Type of decoder to use",
)
group.add_argument(
"--dropout-rate-decoder",
default=0.0,
type=float,
help="Dropout rate for the decoder",
)
group.add_argument(
"--dropout-rate-embed-decoder",
default=0.0,
type=float,
help="Dropout rate for the decoder embedding layer",
)
return group
def add_rnn_decoder_arguments(group):
"""Define arguments for RNN decoder."""
group.add_argument(
"--dec-embed-dim",
default=320,
type=int,
help="Number of decoder embeddings dimensions",
)
group.add_argument(
"--dlayers", default=1, type=int, help="Number of decoder layers"
)
group.add_argument(
"--dunits", default=320, type=int, help="Number of decoder hidden units"
)
return group
def add_custom_decoder_arguments(group):
"""Define arguments for Custom decoder."""
group.add_argument(
"--dec-block-arch",
type=eval,
action="append",
default=None,
help="Custom decoder blocks definition",
)
group.add_argument(
"--dec-block-repeat",
default=1,
type=int,
help="Repeat N times the provided decoder blocks if N > 1",
)
group.add_argument(
"--custom-dec-input-layer",
type=str,
default="embed",
choices=["linear", "embed"],
help="Custom decoder input layer type",
)
group.add_argument(
"--custom-dec-pw-activation-type",
type=str,
default="relu",
choices=["relu", "hardtanh", "selu", "swish"],
help="Custom decoder pointwise activation type",
)
return group
def add_custom_training_arguments(group):
"""Define arguments for training with Custom architecture."""
group.add_argument(
"--transformer-warmup-steps",
default=25000,
type=int,
help="Optimizer warmup steps",
)
group.add_argument(
"--transformer-lr",
default=10.0,
type=float,
help="Initial value of learning rate",
)
return group
def add_transducer_arguments(group):
"""Define general arguments for transducer model."""
group.add_argument(
"--trans-type",
default="warp-transducer",
type=str,
choices=["warp-transducer", "warp-rnnt"],
help="Type of transducer implementation to calculate loss.",
)
group.add_argument(
"--transducer-weight",
default=1.0,
type=float,
help="Weight of transducer loss when auxiliary task is used.",
)
group.add_argument(
"--joint-dim",
default=320,
type=int,
help="Number of dimensions in joint space",
)
group.add_argument(
"--joint-activation-type",
type=str,
default="tanh",
choices=["relu", "tanh", "swish"],
help="Joint network activation type",
)
group.add_argument(
"--score-norm",
type=strtobool,
nargs="?",
default=True,
help="Normalize transducer scores by length",
)
return group
def add_auxiliary_task_arguments(group):
"""Add arguments for auxiliary task."""
group.add_argument(
"--aux-task-type",
nargs="?",
default=None,
choices=["default", "symm_kl_div", "both"],
help="Type of auxiliary task.",
)
group.add_argument(
"--aux-task-layer-list",
default=None,
type=ast.literal_eval,
help="List of layers to use for auxiliary task.",
)
group.add_argument(
"--aux-task-weight",
default=0.3,
type=float,
help="Weight of auxiliary task loss.",
)
group.add_argument(
"--aux-ctc",
type=strtobool,
nargs="?",
default=False,
help="Whether to use CTC as auxiliary task.",
)
group.add_argument(
"--aux-ctc-weight",
default=1.0,
type=float,
help="Weight of auxiliary task loss",
)
group.add_argument(
"--aux-ctc-dropout-rate",
default=0.0,
type=float,
help="Dropout rate for auxiliary CTC",
)
group.add_argument(
"--aux-cross-entropy",
type=strtobool,
nargs="?",
default=False,
help="Whether to use CE as auxiliary task for the prediction network.",
)
group.add_argument(
"--aux-cross-entropy-smoothing",
default=0.0,
type=float,
help="Smoothing rate for cross-entropy. If > 0, enables label smoothing loss.",
)
group.add_argument(
"--aux-cross-entropy-weight",
default=0.5,
type=float,
help="Weight of auxiliary task loss",
)
return group
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