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flake8
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@ -38,11 +38,11 @@ from torch.utils.tensorboard import SummaryWriter
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from transformer import Noam
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from transformer import Noam
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from icefall.bpe_graph_compiler import BpeCtcTrainingGraphCompiler
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from icefall.bpe_graph_compiler import BpeCtcTrainingGraphCompiler
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from icefall.graph_compiler import CtcTrainingGraphCompiler
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from icefall.checkpoint import load_checkpoint
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from icefall.checkpoint import load_checkpoint
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from icefall.checkpoint import save_checkpoint as save_checkpoint_impl
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from icefall.checkpoint import save_checkpoint as save_checkpoint_impl
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from icefall.dist import cleanup_dist, setup_dist
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from icefall.dist import cleanup_dist, setup_dist
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from icefall.env import get_env_info
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from icefall.env import get_env_info
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from icefall.graph_compiler import CtcTrainingGraphCompiler
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from icefall.lexicon import Lexicon
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from icefall.lexicon import Lexicon
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from icefall.utils import (
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from icefall.utils import (
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AttributeDict,
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AttributeDict,
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@ -595,8 +595,9 @@ def run(rank, world_size, args):
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)
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)
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elif "lang_phone" in params.lang_dir:
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elif "lang_phone" in params.lang_dir:
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assert params.att_rate == 0, (
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assert params.att_rate == 0, (
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"Attention decoder training does not support phone lang dirs at this time due to a missing "
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"Attention decoder training does not support phone lang dirs "
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"<sos/eos> symbol. Set --att-rate=0 for pure CTC training when using a phone-based lang dir."
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"at this time due to a missing <sos/eos> symbol. Set --att-rate=0 "
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"for pure CTC training when using a phone-based lang dir."
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)
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)
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graph_compiler = CtcTrainingGraphCompiler(
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graph_compiler = CtcTrainingGraphCompiler(
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lexicon,
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lexicon,
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@ -608,8 +609,8 @@ def run(rank, world_size, args):
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graph_compiler.eos_id = 1
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graph_compiler.eos_id = 1
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else:
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else:
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raise ValueError(
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raise ValueError(
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f"Unsupported type of lang dir (we expected it to have 'lang_bpe' or 'lang_phone' "
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f"Unsupported type of lang dir (we expected it to have "
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f"in its name): {params.lang_dir}"
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f"'lang_bpe' or 'lang_phone' in its name): {params.lang_dir}"
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)
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)
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logging.info("About to create model")
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logging.info("About to create model")
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