
from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
		import torch

if is_vision_available():
		from PIL import Image


lowercase        =  ['''text''', '''image''', '''audio''']



def      __lowerCAmelCase						(							UpperCAmelCase__				:      List[str]       )  ->    str:
							lowerCamelCase_							  =					[]

							for input_type in input_types:
														if input_type == "text":
																					inputs.append("""Text input"""       )
														elif input_type == "image":
																					inputs.append(
																					    Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""       )       ) / """000000039769.png"""       ).resize((5_1_2, 5_1_2)       )       )
														elif input_type == "audio":
																					inputs.append(torch.ones(3_0_0_0       )       )
														elif isinstance(UpperCAmelCase__			,				UpperCAmelCase__       ):
																					inputs.append(create_inputs(UpperCAmelCase__       )       )
														else:
																					raise ValueError(F'''Invalid type requested: {input_type}'''       )

							return inputs



def      __lowerCAmelCase						(							UpperCAmelCase__				:      List       )  ->    List[Any]:
							lowerCamelCase_							  =					[]

							for output in outputs:
														if isinstance(UpperCAmelCase__			,				(str, AgentText)       ):
																					output_types.append("""text"""       )
														elif isinstance(UpperCAmelCase__			,				(Image.Image, AgentImage)       ):
																					output_types.append("""image"""       )
														elif isinstance(UpperCAmelCase__			,				(torch.Tensor, AgentAudio)       ):
																					output_types.append("""audio"""       )
														else:
																					raise ValueError(F'''Invalid output: {output}'''       )

							return output_types





@is_tool_test
class       __A:

					def    lowercase__      (	self					:     int   ):
												self.assertTrue(hasattr(self.tool   ,					"""inputs"""   )   )
												self.assertTrue(hasattr(self.tool   ,					"""outputs"""   )   )

												lowerCamelCase_							  =					self.tool.inputs
												for _input in inputs:
																			if isinstance(_input   ,					__UpperCamelCase   ):
																										for __input in _input:
																																	self.assertTrue(__input in authorized_types   )
																			else:
																										self.assertTrue(_input in authorized_types   )

												lowerCamelCase_							  =					self.tool.outputs
												for _output in outputs:
																			self.assertTrue(_output in authorized_types   )

					def    lowercase__      (	self					:     Union[str, Any]   ):
												lowerCamelCase_							  =					create_inputs(self.tool.inputs   )
												lowerCamelCase_							  =					self.tool(*__UpperCamelCase   )

												# There is a single output
												if len(self.tool.outputs   ) == 1:
																			lowerCamelCase_							  =					[outputs]

												self.assertListEqual(output_types(__UpperCamelCase   )   ,					self.tool.outputs   )

					def    lowercase__      (	self					:     str   ):
												self.assertTrue(hasattr(self.tool   ,					"""description"""   )   )
												self.assertTrue(hasattr(self.tool   ,					"""default_checkpoint"""   )   )
												self.assertTrue(self.tool.description.startswith("""This is a tool that"""   )   )

					def    lowercase__      (	self					:     List[Any]   ):
												lowerCamelCase_							  =					create_inputs(self.tool.inputs   )
												lowerCamelCase_							  =					self.tool(*__UpperCamelCase   )

												if not isinstance(__UpperCamelCase   ,					__UpperCamelCase   ):
																			lowerCamelCase_							  =					[outputs]

												self.assertEqual(len(__UpperCamelCase   )   ,					len(self.tool.outputs   )   )

												for output, output_type in zip(__UpperCamelCase   ,					self.tool.outputs   ):
																			lowerCamelCase_							  =					AGENT_TYPE_MAPPING[output_type]
																			self.assertTrue(isinstance(__UpperCamelCase   ,					__UpperCamelCase   )   )



					def    lowercase__      (	self					:     List[Any]   ):
												lowerCamelCase_							  =					create_inputs(self.tool.inputs   )

												lowerCamelCase_							  =					[]

												for _input, input_type in zip(__UpperCamelCase   ,					self.tool.inputs   ):
																			if isinstance(__UpperCamelCase   ,					__UpperCamelCase   ):
																										_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input   ) for _input_type in input_type]   )
																			else:
																										_inputs.append(AGENT_TYPE_MAPPING[input_type](_input   )   )

        # Should not raise an error
												lowerCamelCase_							  =					self.tool(*__UpperCamelCase   )

												if not isinstance(__UpperCamelCase   ,					__UpperCamelCase   ):
																			lowerCamelCase_							  =					[outputs]

												self.assertEqual(len(__UpperCamelCase   )   ,					len(self.tool.outputs   )   )







from typing import TYPE_CHECKING

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


lowercase        =  {'''configuration_speech_encoder_decoder''': ['''SpeechEncoderDecoderConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase        =  ['''SpeechEncoderDecoderModel''']

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase        =  ['''FlaxSpeechEncoderDecoderModel''']

if TYPE_CHECKING:
		from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel

else:
		import sys

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





