Load alphabet alongside checkpoint if present, some config fixes/cleanup
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87f0a371b1
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@ -688,9 +688,6 @@ def early_training_checks():
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"for loading and saving."
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)
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if not Config.alphabet_config_path and not Config.bytes_output_mode:
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raise RuntimeError("Missing --alphabet_config_path flag, can't continue")
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def main():
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initialize_globals_from_cli()
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@ -118,6 +118,12 @@ class _SttConfig(Coqpit):
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if not self.available_devices:
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self.available_devices = [self.cpu_device]
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# If neither `--alphabet_config_path` nor `--bytes_output_mode` were specified,
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# look for alphabet file alongside loaded checkpoint.
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checkpoint_alphabet_file = os.path.join(
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self.load_checkpoint_dir, "alphabet.txt"
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)
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if self.bytes_output_mode and self.alphabet_config_path:
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raise RuntimeError(
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"You cannot set --alphabet_config_path *and* --bytes_output_mode"
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@ -126,6 +132,15 @@ class _SttConfig(Coqpit):
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self.alphabet = UTF8Alphabet()
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elif self.alphabet_config_path:
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self.alphabet = Alphabet(os.path.abspath(self.alphabet_config_path))
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elif os.path.exists(checkpoint_alphabet_file):
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print(
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"I --alphabet_config_path not specified, but found an alphabet file "
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f"alongside specified checkpoint ({checkpoint_alphabet_file}).\n"
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"I Will use this alphabet file for this run."
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)
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self.alphabet = Alphabet(checkpoint_alphabet_file)
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else:
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raise RuntimeError("Missing --alphabet_config_path flag, can't continue")
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# Geometric Constants
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# ===================
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@ -157,15 +172,12 @@ class _SttConfig(Coqpit):
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self.n_hidden_3 = self.n_cell_dim
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# Dims in last layer = number of characters in alphabet plus one
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try:
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# +1 for CTC blank label
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self.n_hidden_6 = self.alphabet.GetSize() + 1
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except:
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AttributeError
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# Size of audio window in samples
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if (self.feature_win_len * self.audio_sample_rate) % 1000 != 0:
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log_error(
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raise RuntimeError(
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"--feature_win_len value ({}) in milliseconds ({}) multiplied "
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"by --audio_sample_rate value ({}) must be an integer value. Adjust "
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"your --feature_win_len value or resample your audio accordingly."
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@ -175,7 +187,6 @@ class _SttConfig(Coqpit):
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self.audio_sample_rate,
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)
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)
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sys.exit(1)
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self.audio_window_samples = self.audio_sample_rate * (
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self.feature_win_len / 1000
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@ -183,7 +194,7 @@ class _SttConfig(Coqpit):
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# Stride for feature computations in samples
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if (self.feature_win_step * self.audio_sample_rate) % 1000 != 0:
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log_error(
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raise RuntimeError(
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"--feature_win_step value ({}) in milliseconds ({}) multiplied "
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"by --audio_sample_rate value ({}) must be an integer value. Adjust "
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"your --feature_win_step value or resample your audio accordingly."
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@ -193,19 +204,18 @@ class _SttConfig(Coqpit):
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self.audio_sample_rate,
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)
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)
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sys.exit(1)
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self.audio_step_samples = self.audio_sample_rate * (
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self.feature_win_step / 1000
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)
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if self.one_shot_infer:
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if not path_exists_remote(self.one_shot_infer):
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log_error("Path specified in --one_shot_infer is not a valid file.")
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sys.exit(1)
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if self.one_shot_infer and not path_exists_remote(self.one_shot_infer):
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raise RuntimeError(
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"Path specified in --one_shot_infer is not a valid file."
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)
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if self.train_cudnn and self.load_cudnn:
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log_error(
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raise RuntimeError(
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"Trying to use --train_cudnn, but --load_cudnn "
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"was also specified. The --load_cudnn flag is only "
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"needed when converting a CuDNN RNN checkpoint to "
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@ -213,7 +223,6 @@ class _SttConfig(Coqpit):
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"using CuDNN RNN, you can just specify the CuDNN RNN "
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"checkpoint normally with --save_checkpoint_dir."
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)
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sys.exit(1)
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# sphinx-doc: training_ref_flags_start
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train_files: List[str] = field(
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@ -727,9 +736,7 @@ class _SttConfig(Coqpit):
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def initialize_globals_from_cli():
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c = _SttConfig()
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c.parse_args(arg_prefix="")
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c.__post_init__()
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c = _SttConfig.init_from_argparse(arg_prefix="")
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_ConfigSingleton._config = c # pylint: disable=protected-access
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