





'''simple docstring'''






from collections import UserDict
from typing import Union

import numpy as np
import requests

from ..utils import (
    add_end_docstrings,
    logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline


__UpperCamelCase					    =	logging.get_logger(__name__)




@add_end_docstrings(__lowercase		)
class  _A (					__lowercase		):

		def __init__(   self					:   Union[str, Any]  ,      **__magic_name__					:   int			)					->    Union[str, Any]:


					"""simple docstring"""

					super().__init__(**__UpperCamelCase			)

					if self.framework != "pt":
								raise ValueError(f'''The {self.__class__} is only available in PyTorch.'''			)
					# No specific FOR_XXX available yet

		def __call__(   self					:   Tuple  ,      __magic_name__					:   Union[np.ndarray, bytes, str]  ,      **__magic_name__					:   Any			)					->    Optional[int]:


					"""simple docstring"""

					return super().__call__(__UpperCamelCase  ,      **__UpperCamelCase			)

		def 	lowercase__     (   self					:   Tuple  ,      **__magic_name__					:   Optional[Any]			)					->    List[Any]:


					"""simple docstring"""

					__snake_case					:      int							      =     {}
					if "candidate_labels" in kwargs:
								__snake_case					:      int							      =     kwargs["""candidate_labels"""]
					if "hypothesis_template" in kwargs:
								__snake_case					:      List[str]							      =     kwargs["""hypothesis_template"""]

					return preprocess_params, {}, {}

		def 	lowercase__     (   self					:   Tuple  ,      __magic_name__					:   Tuple  ,      __magic_name__					:   List[str]=None  ,      __magic_name__					:   Any="This is a sound of {}."			)					->    Dict:


					"""simple docstring"""

					if isinstance(__UpperCamelCase  ,      __UpperCamelCase			):
								if audio.startswith("""http://"""			) or audio.startswith("""https://"""			):
											# We need to actually check for a real protocol, otherwise it's impossible to use a local file
											# like http_huggingface_co.png
											__snake_case					:      List[Any]							      =     requests.get(__UpperCamelCase			).content
								else:
											with open(__UpperCamelCase  ,      """rb"""			) as f:
														__snake_case					:      List[str]							      =     f.read()

					if isinstance(__UpperCamelCase  ,      __UpperCamelCase			):
								__snake_case					:      str							      =     ffmpeg_read(__UpperCamelCase  ,      self.feature_extractor.sampling_rate			)

					if not isinstance(__UpperCamelCase  ,      np.ndarray			):
								raise ValueError("""We expect a numpy ndarray as input"""			)
					if len(audio.shape			) != 1:
								raise ValueError("""We expect a single channel audio input for ZeroShotAudioClassificationPipeline"""			)

					__snake_case					:      Optional[Any]							      =     self.feature_extractor(
					    [audio]  ,      sampling_rate=self.feature_extractor.sampling_rate  ,      return_tensors="""pt"""			)
					__snake_case					:      str							      =     candidate_labels
					__snake_case					:      List[str]							      =     [hypothesis_template.format(__UpperCamelCase			) for x in candidate_labels]
					__snake_case					:      Any							      =     self.tokenizer(__UpperCamelCase  ,      return_tensors=self.framework  ,      padding=__UpperCamelCase			)
					__snake_case					:      Tuple							      =     [text_inputs]
					return inputs

		def 	lowercase__     (   self					:   Optional[int]  ,      __magic_name__					:   int			)					->    Optional[Any]:


					"""simple docstring"""

					__snake_case					:      Tuple							      =     model_inputs.pop("""candidate_labels"""			)
					__snake_case					:      Optional[Any]							      =     model_inputs.pop("""text_inputs"""			)
					if isinstance(text_inputs[0]  ,      __UpperCamelCase			):
								__snake_case					:      Union[str, Any]							      =     text_inputs[0]
					else:
								# Batching case.
								__snake_case					:      str							      =     text_inputs[0][0]

					__snake_case					:      List[Any]							      =     self.model(**__UpperCamelCase  ,      **__UpperCamelCase			)

					__snake_case					:      List[str]							      =     {
					    """candidate_labels""": candidate_labels,
					    """logits""": outputs.logits_per_audio,
					}
					return model_outputs

		def 	lowercase__     (   self					:   Tuple  ,      __magic_name__					:   Dict			)					->    Tuple:


					"""simple docstring"""

					__snake_case					:      Optional[Any]							      =     model_outputs.pop("""candidate_labels"""			)
					__snake_case					:      str							      =     model_outputs["""logits"""][0]

					if self.framework == "pt":
								__snake_case					:      int							      =     logits.softmax(dim=0			)
								__snake_case					:      int							      =     probs.tolist()
					else:
								raise ValueError("""`tf` framework not supported."""			)

					__snake_case					:      Optional[Any]							      =     [
					    {"""score""": score, """label""": candidate_label}
					    for score, candidate_label in sorted(zip(__UpperCamelCase  ,      __UpperCamelCase			)  ,      key=lambda __magic_name__			: -x[0]			)
					]
					return result




import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin





class    __A(					UpperCAmelCase  ,		unittest.TestCase							):
					SCREAMING_SNAKE_CASE           =     ProphetNetTokenizer
					SCREAMING_SNAKE_CASE           =     False

					def  lowercase__   (						self       :  Optional[Any] ):
												super().setUp()

												lowerCamelCase_					=       [
												    """[UNK]""",
												    """[CLS]""",
												    """[SEP]""",
												    """[PAD]""",
												    """[MASK]""",
												    """want""",
												    """##want""",
												    """##ed""",
												    """wa""",
												    """un""",
												    """runn""",
												    """##ing""",
												    """,""",
												    """low""",
												    """lowest""",
												]
												lowerCamelCase_					=       os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES["""vocab_file"""] )
												with open(self.vocab_file ,       """w""" ,       encoding="""utf-8""" ) as vocab_writer:
																			vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens] ) )

					def  lowercase__   (						self       :  int ,       __UpperCamelCase       :  int ):
												lowerCamelCase_					=       """UNwant\u00E9d,running"""
												lowerCamelCase_					=       """unwanted, running"""
												return input_text, output_text

					def  lowercase__   (						self       :  Optional[int] ):
												lowerCamelCase_					=       self.tokenizer_class(self.vocab_file )

												lowerCamelCase_					=       tokenizer.tokenize("""UNwant\u00E9d,running""" )
												self.assertListEqual(__UpperCamelCase ,       ["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""] )
												self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase ) ,       [9, 6, 7, 1_2, 1_0, 1_1] )

					def  lowercase__   (						self       :  Tuple ):
												lowerCamelCase_					=       BasicTokenizer()

												self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz""" ) ,       ["""ah""", """\u535A""", """\u63A8""", """zz"""] )

					def  lowercase__   (						self       :  Union[str, Any] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """ ) ,       ["""hello""", """!""", """how""", """are""", """you""", """?"""] )
												self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" ) ,       ["""hello"""] )

					def  lowercase__   (						self       :  Optional[Any] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       strip_accents=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""hällo""", """!""", """how""", """are""", """you""", """?"""] )
												self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" ) ,       ["""h\u00E9llo"""] )

					def  lowercase__   (						self       :  Optional[int] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       strip_accents=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""hallo""", """!""", """how""", """are""", """you""", """?"""] )
												self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" ) ,       ["""hello"""] )

					def  lowercase__   (						self       :  List[Any] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""hallo""", """!""", """how""", """are""", """you""", """?"""] )
												self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" ) ,       ["""hello"""] )

					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """ ) ,       ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )

					def  lowercase__   (						self       :  int ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       strip_accents=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )

					def  lowercase__   (						self       :  Optional[Any] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       strip_accents=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )

					def  lowercase__   (						self       :  Dict ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       never_split=["""[UNK]"""] )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]""" ) ,       ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""] )

					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       ["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

												lowerCamelCase_					=       {}
												for i, token in enumerate(__UpperCamelCase ):
																			lowerCamelCase_					=       i
												lowerCamelCase_					=       WordpieceTokenizer(vocab=__UpperCamelCase ,       unk_token="""[UNK]""" )

												self.assertListEqual(tokenizer.tokenize("""""" ) ,       [] )

												self.assertListEqual(tokenizer.tokenize("""unwanted running""" ) ,       ["""un""", """##want""", """##ed""", """runn""", """##ing"""] )

												self.assertListEqual(tokenizer.tokenize("""unwantedX running""" ) ,       ["""[UNK]""", """runn""", """##ing"""] )

					@require_torch
					def  lowercase__   (						self       :  int ):
												lowerCamelCase_					=       self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased""" )

												lowerCamelCase_					=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
												lowerCamelCase_					=       [1_0_3_7, 2_1_4_6, 2_0_4_2_3, 2_0_0_5, 7_6_8_0, 7_8_4_9, 3_9_8_9, 1_0_1_2, 1_0_2]
												lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       padding=__UpperCamelCase ,       return_tensors="""pt""" )
												self.assertIsInstance(__UpperCamelCase ,       __UpperCamelCase )
												lowerCamelCase_					=       list(batch.input_ids.numpy()[0] )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

												self.assertEqual((2, 9) ,       batch.input_ids.shape )
												self.assertEqual((2, 9) ,       batch.attention_mask.shape )

					def  lowercase__   (						self       :  List[str] ):
												self.assertTrue(_is_whitespace(""" """ ) )
												self.assertTrue(_is_whitespace("""\t""" ) )
												self.assertTrue(_is_whitespace("""\r""" ) )
												self.assertTrue(_is_whitespace("""\n""" ) )
												self.assertTrue(_is_whitespace("""\u00A0""" ) )

												self.assertFalse(_is_whitespace("""A""" ) )
												self.assertFalse(_is_whitespace("""-""" ) )

					def  lowercase__   (						self       :  Union[str, Any] ):
												self.assertTrue(_is_control("""\u0005""" ) )

												self.assertFalse(_is_control("""A""" ) )
												self.assertFalse(_is_control(""" """ ) )
												self.assertFalse(_is_control("""\t""" ) )
												self.assertFalse(_is_control("""\r""" ) )

					def  lowercase__   (						self       :  Tuple ):
												self.assertTrue(_is_punctuation("""-""" ) )
												self.assertTrue(_is_punctuation("""$""" ) )
												self.assertTrue(_is_punctuation("""`""" ) )
												self.assertTrue(_is_punctuation(""".""" ) )

												self.assertFalse(_is_punctuation("""A""" ) )
												self.assertFalse(_is_punctuation(""" """ ) )



					@slow
					def  lowercase__   (						self       :  str ):
												lowerCamelCase_					=       self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased""" )

												lowerCamelCase_					=       tokenizer.encode("""sequence builders""" ,       add_special_tokens=__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.encode("""multi-sequence build""" ,       add_special_tokens=__UpperCamelCase )

												lowerCamelCase_					=       tokenizer.build_inputs_with_special_tokens(__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.build_inputs_with_special_tokens(__UpperCamelCase ,       __UpperCamelCase )

												assert encoded_sentence == text + [1_0_2]
												assert encoded_pair == text + [1_0_2] + text_a + [1_0_2]





