| | |
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| | | |
|---|
| | | class modelscope_args(): |
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| | | def __init__(self, |
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| | | task: str = "", |
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| | | model: str = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", |
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| | | data_path: str = None, |
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| | | output_dir: str = None, |
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| | | model_revision: str = None, |
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| | | dataset_type: str = "small", |
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| | | batch_bins: int = 2000, |
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| | | max_epoch: int = None, |
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| | | lr: float = None, |
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| | | ): |
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| | | self.task = task |
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| | | self.model = model |
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| | | self.data_path = data_path |
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| | | self.output_dir = output_dir |
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| | | self.model_revision = model_revision |
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| | | self.dataset_type = dataset_type |
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| | | self.batch_bins = batch_bins |
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| | | self.max_epoch = max_epoch |
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| | | self.lr = lr |
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| | | |
|---|
| | | |
|---|
| | | |
|---|
| | | def __init__(self, |
|---|
| | | task: str = "", |
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| | | model: str = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", |
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| | | data_path: str = None, |
|---|
| | | output_dir: str = None, |
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| | | model_revision: str = None, |
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| | | dataset_type: str = "small", |
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| | | batch_bins: int = 2000, |
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| | | max_epoch: int = None, |
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| | | accum_grad: int = None, |
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| | | keep_nbest_models: int = None, |
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| | | optim: str = None, |
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| | | lr: float = None, |
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| | | scheduler: str = None, |
|---|
| | | scheduler_conf: dict = None, |
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| | | specaug: str = None, |
|---|
| | | specaug_conf: dict = None, |
|---|
| | | ): |
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| | | self.task = task |
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| | | self.model = model |
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| | | self.data_path = data_path |
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| | | self.output_dir = output_dir |
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| | | self.model_revision = model_revision |
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| | | self.dataset_type = dataset_type |
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| | | self.batch_bins = batch_bins |
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| | | self.max_epoch = max_epoch |
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| | | self.accum_grad = accum_grad |
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| | | self.keep_nbest_models = keep_nbest_models |
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| | | self.optim = optim |
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| | | self.lr = lr |
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| | | self.scheduler = scheduler |
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| | | self.scheduler_conf = scheduler_conf |
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| | | self.specaug = specaug |
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| | | self.specaug_conf = specaug_conf |
|---|
