



"""simple docstring"""






import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
   import torch

if is_soundfile_availble():
   import soundfile as sf

if is_vision_available():
   from PIL import Image






def 			snake_case_    ( A_   :						str=""		):


       '''simple docstring'''





       _lowerCamelCase		:							Union[str, Any]            =					tempfile.mkdtemp()
       return os.path.join(A_,							str(uuid.uuida()		) + suffix		)






@require_soundfile
@require_torch
class 			__snake_case			(      unittest.TestCase):




  def 		SCREAMING_SNAKE_CASE							(					self	:		Tuple						):






         """simple docstring"""






         _lowerCamelCase		:							Optional[int]            =					torch.rand(1_2		,   dtype=torch.floataa						) - 0.5
         _lowerCamelCase		:							List[str]            =					AgentAudio(__lowerCAmelCase						)
         _lowerCamelCase		:							Dict            =					str(agent_type.to_string()						)

         # Ensure that the tensor and the agent_type's tensor are the same
         self.assertTrue(torch.allclose(__lowerCAmelCase		,   agent_type.to_raw()		,   atol=1E-4						)						)

         del agent_type

         # Ensure the path remains even after the object deletion
         self.assertTrue(os.path.exists(__lowerCAmelCase						)						)

         # Ensure that the file contains the same value as the original tensor
         _lowerCamelCase     ,       _lowerCamelCase		:							Union[str, Any]            =					sf.read(__lowerCAmelCase						)
         self.assertTrue(torch.allclose(__lowerCAmelCase		,   torch.tensor(__lowerCAmelCase						)		,   atol=1E-4						)						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Any						):






         """simple docstring"""






         _lowerCamelCase		:							Tuple            =					torch.rand(1_2		,   dtype=torch.floataa						) - 0.5
         _lowerCamelCase		:							Union[str, Any]            =					get_new_path(suffix='''.wav'''						)
         sf.write(__lowerCAmelCase		,   __lowerCAmelCase		,   1_6_0_0_0						)

         _lowerCamelCase		:							Optional[Any]            =					AgentAudio(__lowerCAmelCase						)

         self.assertTrue(torch.allclose(__lowerCAmelCase		,   agent_type.to_raw()		,   atol=1E-4						)						)
         self.assertEqual(agent_type.to_string()		,   __lowerCAmelCase						)






@require_vision
@require_torch
class 			__snake_case			(      unittest.TestCase):




  def 		SCREAMING_SNAKE_CASE							(					self	:		Union[str, Any]						):






         """simple docstring"""






         _lowerCamelCase		:							Dict            =					torch.randint(0		,   2_5_6		,   (6_4, 6_4, 3)						)
         _lowerCamelCase		:							Tuple            =					AgentImage(__lowerCAmelCase						)
         _lowerCamelCase		:							Union[str, Any]            =					str(agent_type.to_string()						)

         # Ensure that the tensor and the agent_type's tensor are the same
         self.assertTrue(torch.allclose(__lowerCAmelCase		,   agent_type._tensor		,   atol=1E-4						)						)

         self.assertIsInstance(agent_type.to_raw()		,   Image.Image						)

         # Ensure the path remains even after the object deletion
         del agent_type
         self.assertTrue(os.path.exists(__lowerCAmelCase						)						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		str						):






         """simple docstring"""






         _lowerCamelCase		:							str            =					Path(get_tests_dir('''fixtures/tests_samples/COCO'''						)						) / '''000000039769.png'''
         _lowerCamelCase		:							Optional[int]            =					Image.open(__lowerCAmelCase						)
         _lowerCamelCase		:							List[str]            =					AgentImage(__lowerCAmelCase						)

         self.assertTrue(path.samefile(agent_type.to_string()						)						)
         self.assertTrue(image == agent_type.to_raw()						)

         # Ensure the path remains even after the object deletion
         del agent_type
         self.assertTrue(os.path.exists(__lowerCAmelCase						)						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Dict						):






         """simple docstring"""






         _lowerCamelCase		:							List[str]            =					Path(get_tests_dir('''fixtures/tests_samples/COCO'''						)						) / '''000000039769.png'''
         _lowerCamelCase		:							Dict            =					Image.open(__lowerCAmelCase						)
         _lowerCamelCase		:							Optional[Any]            =					AgentImage(__lowerCAmelCase						)

         self.assertFalse(path.samefile(agent_type.to_string()						)						)
         self.assertTrue(image == agent_type.to_raw()						)

         # Ensure the path remains even after the object deletion
         del agent_type
         self.assertTrue(os.path.exists(__lowerCAmelCase						)						)






class 			__snake_case			(      unittest.TestCase):




  def 		SCREAMING_SNAKE_CASE							(					self	:		Dict						):






         """simple docstring"""






         _lowerCamelCase		:							Optional[int]            =					'''Hey!'''
         _lowerCamelCase		:							int            =					AgentText(__lowerCAmelCase						)

         self.assertEqual(__lowerCAmelCase		,   agent_type.to_string()						)
         self.assertEqual(__lowerCAmelCase		,   agent_type.to_raw()						)
         self.assertEqual(__lowerCAmelCase		,   __lowerCAmelCase						)




"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


SCREAMING_SNAKE_CASE_            =    {
    '''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
    '''tokenization_roc_bert''': ['''RoCBertTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   pass

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE_            =    [
       '''ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''RoCBertForCausalLM''',
       '''RoCBertForMaskedLM''',
       '''RoCBertForMultipleChoice''',
       '''RoCBertForPreTraining''',
       '''RoCBertForQuestionAnswering''',
       '''RoCBertForSequenceClassification''',
       '''RoCBertForTokenClassification''',
       '''RoCBertLayer''',
       '''RoCBertModel''',
       '''RoCBertPreTrainedModel''',
       '''load_tf_weights_in_roc_bert''',
   ]

if TYPE_CHECKING:
   from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
   from .tokenization_roc_bert import RoCBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      raise OptionalDependencyNotAvailable()

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_roc_bert import (
          ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          RoCBertForCausalLM,
          RoCBertForMaskedLM,
          RoCBertForMultipleChoice,
          RoCBertForPreTraining,
          RoCBertForQuestionAnswering,
          RoCBertForSequenceClassification,
          RoCBertForTokenClassification,
          RoCBertLayer,
          RoCBertModel,
          RoCBertPreTrainedModel,
          load_tf_weights_in_roc_bert,
      )


else:
   import sys

   SCREAMING_SNAKE_CASE_            =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



