


from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class  UpperCamelCase__(     UpperCAmelCase_ ):
				__magic_name__       :   Tuple							= "ClapFeatureExtractor"
				__magic_name__       :   Optional[int]							= ("RobertaTokenizer", "RobertaTokenizerFast")




				def __init__(	self    :				Dict   ,					lowerCAmelCase    :				List[str]   ,					lowerCAmelCase    :				Optional[int]   )->  Union[str, Any]:

										"""simple docstring"""




										super().__init__(_lowercase   ,					_lowercase   )




				def __call__(	self    :				Optional[int]   ,					lowerCAmelCase    :				List[Any]=None   ,					lowerCAmelCase    :				Dict=None   ,					lowerCAmelCase    :				str=None   ,					**lowerCAmelCase    :				Union[str, Any]   )->  List[str]:

										"""simple docstring"""




										UpperCAmelCase         =			kwargs.pop('''sampling_rate'''   ,					_lowercase   )

										if text is None and audios is None:
																raise ValueError('''You have to specify either text or audios. Both cannot be none.'''   )

										if text is not None:
																UpperCAmelCase         =			self.tokenizer(_lowercase   ,					return_tensors=_lowercase   ,					**_lowercase   )

										if audios is not None:
																UpperCAmelCase         =			self.feature_extractor(
																    _lowercase   ,					sampling_rate=_lowercase   ,					return_tensors=_lowercase   ,					**_lowercase   )

										if text is not None and audios is not None:
																UpperCAmelCase         =			audio_features.input_features
																return encoding
										elif text is not None:
																return encoding
										else:
																return BatchEncoding(data=dict(**_lowercase   )   ,					tensor_type=_lowercase   )




				def   a__(	self    :				List[Any]   ,					*lowerCAmelCase    :				Dict   ,					**lowerCAmelCase    :				Optional[int]   )->  List[str]:

										"""simple docstring"""




										return self.tokenizer.batch_decode(*_lowercase   ,					**_lowercase   )




				def   a__(	self    :				List[str]   ,					*lowerCAmelCase    :				str   ,					**lowerCAmelCase    :				Optional[int]   )->  Union[str, Any]:

										"""simple docstring"""




										return self.tokenizer.decode(*_lowercase   ,					**_lowercase   )





				@property
				def   a__(	self    :				Tuple   )->  str:

										"""simple docstring"""




										UpperCAmelCase         =			self.tokenizer.model_input_names
										UpperCAmelCase         =			self.feature_extractor.model_input_names
										return list(dict.fromkeys(tokenizer_input_names + feature_extractor_input_names   )   )









'''simple docstring'''



# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# this script dumps information about the environment

import os
import sys

import transformers


_lowercase    :    Union[str, Any]			     =  """3"""

print("""Python version:""", sys.version)
print("""transformers version:""", transformers.__version__)

try:
	import torch

	print("""Torch version:""", torch.__version__)
	print("""Cuda available:""", torch.cuda.is_available())
	print("""Cuda version:""", torch.version.cuda)
	print("""CuDNN version:""", torch.backends.cudnn.version())
	print("""Number of GPUs available:""", torch.cuda.device_count())
	print("""NCCL version:""", torch.cuda.nccl.version())
except ImportError:
	print("""Torch version:""", None)

try:
	import deepspeed

	print("""DeepSpeed version:""", deepspeed.__version__)
except ImportError:
	print("""DeepSpeed version:""", None)

try:
	import tensorflow as tf

	print("""TensorFlow version:""", tf.__version__)
	print("""TF GPUs available:""", bool(tf.config.list_physical_devices("""GPU""")))
	print("""Number of TF GPUs available:""", len(tf.config.list_physical_devices("""GPU""")))
except ImportError:
	print("""TensorFlow version:""", None)





