





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 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__=""						):
		lowerCamelCase_	:     List[Any] 						=      tempfile.mkdtemp()
		return os.path.join(lowerCAmelCase__							,str(uuid.uuida()						) + suffix						)






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



					def   __a     (		self     :     List[Any]						):
							lowerCamelCase_	:     str 						=      torch.rand(12       ,      dtype=torch.floataa						) - 0.5
							lowerCamelCase_	:     Dict 						=      AgentAudio(lowerCamelCase						)
							lowerCamelCase_	:     Tuple 						=      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_	:     List[str] 						=      sf.read(lowerCamelCase						)
							self.assertTrue(torch.allclose(lowerCamelCase       ,      torch.tensor(lowerCamelCase						)       ,      atol=1E-4						)						)





					def   __a     (		self     :     int						):
							lowerCamelCase_	:     Any 						=      torch.rand(12       ,      dtype=torch.floataa						) - 0.5
							lowerCamelCase_	:     List[Any] 						=      get_new_path(suffix='.wav'						)
							sf.write(lowerCamelCase       ,      lowerCamelCase       ,      1_60_00						)

							lowerCamelCase_	:     Optional[int] 						=      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 						UpperCamelCase_  (  unittest.TestCase							):



					def   __a     (		self     :     Any						):
							lowerCamelCase_	:     Dict 						=      torch.randint(0       ,      2_56       ,      (64, 64, 3)						)
							lowerCamelCase_	:     List[Any] 						=      AgentImage(lowerCamelCase						)
							lowerCamelCase_	:     Tuple 						=      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   __a     (		self     :     Union[str, Any]						):
							lowerCamelCase_	:     List[str] 						=      Path(get_tests_dir('fixtures/tests_samples/COCO'						)						) / '000000039769.png'
							lowerCamelCase_	:     Tuple 						=      Image.open(lowerCamelCase						)
							lowerCamelCase_	:     Optional[int] 						=      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   __a     (		self     :     Dict						):
							lowerCamelCase_	:     List[str] 						=      Path(get_tests_dir('fixtures/tests_samples/COCO'						)						) / '000000039769.png'
							lowerCamelCase_	:     Any 						=      Image.open(lowerCamelCase						)
							lowerCamelCase_	:     str 						=      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 						UpperCamelCase_  (  unittest.TestCase							):



					def   __a     (		self     :     List[Any]						):
							lowerCamelCase_	:     List[Any] 						=      'Hey!'
							lowerCamelCase_	:     Tuple 						=      AgentText(lowerCamelCase						)

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







import os
import sys

_lowercase		:  List[str]			       =os.path.join(os.path.dirname(__file__), """src""")
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


_lowercase		:  Optional[int]			       =[
    """torch""",
    """numpy""",
    """tokenizers""",
    """filelock""",
    """requests""",
    """tqdm""",
    """regex""",
    """sentencepiece""",
    """sacremoses""",
    """importlib_metadata""",
    """huggingface_hub""",
]


@add_start_docstrings(AutoConfig.__doc__						)
def 		_SCREAMING_SNAKE_CASE     ( *lowerCAmelCase__							,**lowerCAmelCase__						):
		return AutoConfig.from_pretrained(*lowerCAmelCase__							,**lowerCAmelCase__						)


@add_start_docstrings(AutoTokenizer.__doc__						)
def 		_SCREAMING_SNAKE_CASE     ( *lowerCAmelCase__							,**lowerCAmelCase__						):
		return AutoTokenizer.from_pretrained(*lowerCAmelCase__							,**lowerCAmelCase__						)


@add_start_docstrings(AutoModel.__doc__						)
def 		_SCREAMING_SNAKE_CASE     ( *lowerCAmelCase__							,**lowerCAmelCase__						):
		return AutoModel.from_pretrained(*lowerCAmelCase__							,**lowerCAmelCase__						)


@add_start_docstrings(AutoModelForCausalLM.__doc__						)
def 		_SCREAMING_SNAKE_CASE     ( *lowerCAmelCase__							,**lowerCAmelCase__						):
		return AutoModelForCausalLM.from_pretrained(*lowerCAmelCase__							,**lowerCAmelCase__						)


@add_start_docstrings(AutoModelForMaskedLM.__doc__						)
def 		_SCREAMING_SNAKE_CASE     ( *lowerCAmelCase__							,**lowerCAmelCase__						):
		return AutoModelForMaskedLM.from_pretrained(*lowerCAmelCase__							,**lowerCAmelCase__						)


@add_start_docstrings(AutoModelForSequenceClassification.__doc__						)
def 		_SCREAMING_SNAKE_CASE     ( *lowerCAmelCase__							,**lowerCAmelCase__						):
		return AutoModelForSequenceClassification.from_pretrained(*lowerCAmelCase__							,**lowerCAmelCase__						)





@add_start_docstrings(AutoModelForQuestionAnswering.__doc__						)
def 		_SCREAMING_SNAKE_CASE     ( *lowerCAmelCase__							,**lowerCAmelCase__						):
		return AutoModelForQuestionAnswering.from_pretrained(*lowerCAmelCase__							,**lowerCAmelCase__						)
