



'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
					from ... import FeatureExtractionMixin, TensorType

snake_case_					:      List[str]    			=    logging.get_logger(__name__)

snake_case_					:      Tuple    			=    {
    'openai/imagegpt-small': '',
    'openai/imagegpt-medium': '',
    'openai/imagegpt-large': '',
}






class 				lowercase__      (				lowercase  ):
	lowercase__    							=     """imagegpt"""
	lowercase__    							=     ["""past_key_values"""]
	lowercase__    							=     {
	    """hidden_size""": """n_embd""",
	    """max_position_embeddings""": """n_positions""",
	    """num_attention_heads""": """n_head""",
	    """num_hidden_layers""": """n_layer""",
	}





	def __init__(					self   :							int					,lowerCamelCase__   :							str=512 + 1					,lowerCamelCase__   :							Tuple=32 * 32					,lowerCamelCase__   :							List[str]=512					,lowerCamelCase__   :							Optional[Any]=24					,lowerCamelCase__   :							List[Any]=8					,lowerCamelCase__   :							Any=None					,lowerCamelCase__   :							List[Any]="quick_gelu"					,lowerCamelCase__   :							List[Any]=0.1					,lowerCamelCase__   :							List[Any]=0.1					,lowerCamelCase__   :							Tuple=0.1					,lowerCamelCase__   :							Union[str, Any]=1E-5					,lowerCamelCase__   :							int=0.0_2					,lowerCamelCase__   :							Dict=True					,lowerCamelCase__   :							List[str]=True					,lowerCamelCase__   :							Optional[int]=False					,lowerCamelCase__   :							Union[str, Any]=False					,lowerCamelCase__   :							int=False					,**lowerCamelCase__   :							str					,):







							'''simple docstring'''
							_UpperCamelCase   :						Optional[int]												=  vocab_size
							_UpperCamelCase   :						Union[str, Any]												=  n_positions
							_UpperCamelCase   :						int												=  n_embd
							_UpperCamelCase   :						str												=  n_layer
							_UpperCamelCase   :						str												=  n_head
							_UpperCamelCase   :						Any												=  n_inner
							_UpperCamelCase   :						str												=  activation_function
							_UpperCamelCase   :						Union[str, Any]												=  resid_pdrop
							_UpperCamelCase   :						Optional[Any]												=  embd_pdrop
							_UpperCamelCase   :						List[str]												=  attn_pdrop
							_UpperCamelCase   :						str												=  layer_norm_epsilon
							_UpperCamelCase   :						Dict												=  initializer_range
							_UpperCamelCase   :						Any												=  scale_attn_weights
							_UpperCamelCase   :						List[str]												=  use_cache
							_UpperCamelCase   :						int												=  scale_attn_by_inverse_layer_idx
							_UpperCamelCase   :						str												=  reorder_and_upcast_attn
							_UpperCamelCase   :						int												=  tie_word_embeddings

							super().__init__(tie_word_embeddings=lowerCamelCase__					,**lowerCamelCase__					)






class 				lowercase__      (				lowercase  ):





	@property
	def       UpperCamelCase_    (					self   :							Tuple					):







							'''simple docstring'''
							return OrderedDict(
							    [
							        ('input_ids', {0: 'batch', 1: 'sequence'}),
							    ]					)





	def       UpperCamelCase_    (					self   :							Tuple					,lowerCamelCase__   :							"FeatureExtractionMixin"					,lowerCamelCase__   :							int = 1					,lowerCamelCase__   :							int = -1					,lowerCamelCase__   :							bool = False					,lowerCamelCase__   :							Optional["TensorType"] = None					,lowerCamelCase__   :							int = 3					,lowerCamelCase__   :							int = 32					,lowerCamelCase__   :							int = 32					,):







							'''simple docstring'''
							_UpperCamelCase   :						List[str]												=  self._generate_dummy_images(lowerCamelCase__					,lowerCamelCase__					,lowerCamelCase__					,lowerCamelCase__					)
							_UpperCamelCase   :						Any												=  dict(preprocessor(images=lowerCamelCase__					,return_tensors=lowerCamelCase__					)					)

							return inputs







'''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 A__       (	UpperCAmelCase_=""				):
						_UpperCamelCase   :						Any												=  tempfile.mkdtemp()
						return os.path.join(UpperCAmelCase_    ,    str(uuid.uuida()				) + suffix				)






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





	def       UpperCamelCase_    (					self   :							int					):







							'''simple docstring'''
							_UpperCamelCase   :						List[str]												=  torch.rand(12					,dtype=torch.floataa					) - 0.5
							_UpperCamelCase   :						Optional[int]												=  AgentAudio(lowerCamelCase__					)
							_UpperCamelCase   :						List[str]												=  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
							_UpperCamelCase							,     _UpperCamelCase   :						Union[str, Any]												=  sf.read(lowerCamelCase__					)
							self.assertTrue(torch.allclose(lowerCamelCase__					,torch.tensor(lowerCamelCase__					)					,atol=1E-4					)					)





	def       UpperCamelCase_    (					self   :							Dict					):







							'''simple docstring'''
							_UpperCamelCase   :						Optional[Any]												=  torch.rand(12					,dtype=torch.floataa					) - 0.5
							_UpperCamelCase   :						Any												=  get_new_path(suffix='.wav'					)
							sf.write(lowerCamelCase__					,lowerCamelCase__					,16000					)

							_UpperCamelCase   :						List[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 				lowercase__      (				unittest.TestCase  ):





	def       UpperCamelCase_    (					self   :							List[Any]					):







							'''simple docstring'''
							_UpperCamelCase   :						int												=  torch.randint(0					,256					,(64, 64, 3)					)
							_UpperCamelCase   :						Optional[Any]												=  AgentImage(lowerCamelCase__					)
							_UpperCamelCase   :						List[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       UpperCamelCase_    (					self   :							Dict					):







							'''simple docstring'''
							_UpperCamelCase   :						str												=  Path(get_tests_dir('fixtures/tests_samples/COCO'					)					) / '000000039769.png'
							_UpperCamelCase   :						Tuple												=  Image.open(lowerCamelCase__					)
							_UpperCamelCase   :						Optional[Any]												=  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       UpperCamelCase_    (					self   :							Optional[int]					):







							'''simple docstring'''
							_UpperCamelCase   :						List[Any]												=  Path(get_tests_dir('fixtures/tests_samples/COCO'					)					) / '000000039769.png'
							_UpperCamelCase   :						Union[str, Any]												=  Image.open(lowerCamelCase__					)
							_UpperCamelCase   :						List[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 				lowercase__      (				unittest.TestCase  ):





	def       UpperCamelCase_    (					self   :							Any					):







							'''simple docstring'''
							_UpperCamelCase   :						List[Any]												=  'Hey!'
							_UpperCamelCase   :						Optional[int]												=  AgentText(lowerCamelCase__					)

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


