




"""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

__A   :  Any					=      logging.get_logger(__name__)

__A   :  Any					=      {
    'openai/imagegpt-small': '',
    'openai/imagegpt-medium': '',
    'openai/imagegpt-large': '',
}




class       lowerCAmelCase__       (			lowerCAmelCase_    ):


				"""simple docstring"""





				__UpperCAmelCase :     Tuple       =      "imagegpt"
				__UpperCAmelCase :     str       =      ["past_key_values"]
				__UpperCAmelCase :     Optional[Any]       =      {
				    "hidden_size": "n_embd",
				    "max_position_embeddings": "n_positions",
				    "num_attention_heads": "n_head",
				    "num_hidden_layers": "n_layer",
				}



				def __init__(     self					:	List[str]    ,   lowercase__					:	Dict=5_1_2 + 1    ,   lowercase__					:	List[Any]=3_2 * 3_2    ,   lowercase__					:	Tuple=5_1_2    ,   lowercase__					:	Optional[int]=2_4    ,   lowercase__					:	List[Any]=8    ,   lowercase__					:	Tuple=None    ,   lowercase__					:	Any="quick_gelu"    ,   lowercase__					:	Any=0.1    ,   lowercase__					:	str=0.1    ,   lowercase__					:	Any=0.1    ,   lowercase__					:	Any=1e-5    ,   lowercase__					:	Any=0.0_2    ,   lowercase__					:	Tuple=True    ,   lowercase__					:	Optional[int]=True    ,   lowercase__					:	Tuple=False    ,   lowercase__					:	Optional[int]=False    ,   lowercase__					:	List[Any]=False    ,   **lowercase__					:	Union[str, Any]    ,   ):
						__lowercase				:		Any												=				vocab_size
						__lowercase				:		int												=				n_positions
						__lowercase				:		Tuple												=				n_embd
						__lowercase				:		Any												=				n_layer
						__lowercase				:		Dict												=				n_head
						__lowercase				:		Dict												=				n_inner
						__lowercase				:		Dict												=				activation_function
						__lowercase				:		str												=				resid_pdrop
						__lowercase				:		List[str]												=				embd_pdrop
						__lowercase				:		str												=				attn_pdrop
						__lowercase				:		Optional[Any]												=				layer_norm_epsilon
						__lowercase				:		Tuple												=				initializer_range
						__lowercase				:		Dict												=				scale_attn_weights
						__lowercase				:		int												=				use_cache
						__lowercase				:		Any												=				scale_attn_by_inverse_layer_idx
						__lowercase				:		Any												=				reorder_and_upcast_attn
						__lowercase				:		List[Any]												=				tie_word_embeddings

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





class       lowerCAmelCase__       (			lowerCAmelCase_    ):


				"""simple docstring"""





				@property
				def       snake_case    (     self					:	Tuple						):
						return OrderedDict(
						    [
						        ("input_ids", {0: "batch", 1: "sequence"}),
						    ]						)



				def       snake_case    (     self					:	List[str]    ,   lowercase__					:	"FeatureExtractionMixin"    ,   lowercase__					:	int = 1    ,   lowercase__					:	int = -1    ,   lowercase__					:	bool = False    ,   lowercase__					:	Optional["TensorType"] = None    ,   lowercase__					:	int = 3    ,   lowercase__					:	int = 3_2    ,   lowercase__					:	int = 3_2    ,   ):
						__lowercase				:		Dict												=				self._generate_dummy_images(lowercase__    ,   lowercase__    ,   lowercase__    ,   lowercase__						)
						__lowercase				:		Union[str, Any]												=				dict(preprocessor(images=lowercase__    ,   return_tensors=lowercase__						)						)

						return inputs






"""simple docstring"""







import argparse
from collections import defaultdict

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase				)			->List[str]:






		"""simple docstring"""


		__lowercase				:		Tuple												=				F'{file}_{class_name}_{test_name}'
		done_test[_id] += 1

		with open(_lowerCamelCase,  "r"				) as f:
				__lowercase				:		Union[str, Any]												=				f.readlines()

		__lowercase				:		str												=				F'class {class_name}('
		__lowercase				:		Union[str, Any]												=				F'{4 * " "}def {test_name}('
		__lowercase				:		List[Any]												=				F'{8 * " "}{correct_line.split()[0]}'
		__lowercase				:		Optional[int]												=				F'{16 * " "}{correct_line.split()[0]}'
		__lowercase				:		List[Any]												=				False
		__lowercase				:		int												=				False
		__lowercase				:		int												=				False
		__lowercase				:		List[Any]												=				False
		__lowercase				:		str												=				0
		__lowercase				:		Dict												=				0

		__lowercase				:		Optional[int]												=				[]
		for line in lines:
				if line.startswith(_lowerCamelCase				):
						__lowercase				:		Optional[int]												=				True
				elif in_class and line.startswith(_lowerCamelCase				):
						__lowercase				:		Optional[int]												=				True
				elif in_class and in_func and (line.startswith(_lowerCamelCase				) or line.startswith(_lowerCamelCase				)):
						__lowercase				:		int												=				len(line.split(correct_line.split()[0]				)[0]				)
						count += 1

						if count == done_test[_id]:
								__lowercase				:		Any												=				True

				if in_class and in_func and in_line:
						if ")" not in line:
								continue
						else:
								__lowercase				:		int												=				True

				if in_class and in_func and in_line and insert_line:
						new_lines.append(F'{spaces * " "}{correct_line}'				)
						__lowercase				:		List[Any]												=				False
				else:
						new_lines.append(_lowerCamelCase				)

		with open(_lowerCamelCase,  "w"				) as f:
				for line in new_lines:
						f.write(_lowerCamelCase				)

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase=None				)			->List[Any]:






		"""simple docstring"""


		if fail is not None:
				with open(_lowerCamelCase,  "r"				) as f:
						__lowercase				:		str												=				{l.strip() for l in f.readlines()}
		else:
				__lowercase				:		List[Any]												=				None

		with open(_lowerCamelCase,  "r"				) as f:
				__lowercase				:		str												=				f.readlines()

		__lowercase				:		List[str]												=				defaultdict(_lowerCamelCase				)
		for line in correct_lines:
				__lowercase						,__lowercase						,__lowercase						,__lowercase				:		str												=				line.split(";"				)
				if test_failures is None or "::".join([file, class_name, test_name]				) in test_failures:
						overwrite_file(_lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase				)


if __name__ == "__main__":
						__A   :  str					=      argparse.ArgumentParser()
						parser.add_argument('--correct_filename', help='filename of tests with expected result')
						parser.add_argument('--fail_filename', help='filename of test failures', type=str, default=None)
						__A   :  Union[str, Any]					=      parser.parse_args()

						main(args.correct_filename, args.fail_filename)
