



'''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

SCREAMING_SNAKE_CASE__      					=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      					=     {
    "openai/imagegpt-small": "",
    "openai/imagegpt-medium": "",
    "openai/imagegpt-large": "",
}


class 				snake_case (UpperCamelCase   ):
							lowerCAmelCase__  :str						   =					"imagegpt"
							lowerCAmelCase__  :Optional[Any]						   =					["past_key_values"]
							lowerCAmelCase__  :str						   =					{
							    "hidden_size": "n_embd",
							    "max_position_embeddings": "n_positions",
							    "num_attention_heads": "n_head",
							    "num_hidden_layers": "n_layer",
							}



							def __init__(				self     ,UpperCAmelCase_=512 + 1     ,UpperCAmelCase_=32 * 32     ,UpperCAmelCase_=512     ,UpperCAmelCase_=24     ,UpperCAmelCase_=8     ,UpperCAmelCase_=None     ,UpperCAmelCase_="quick_gelu"     ,UpperCAmelCase_=0.1     ,UpperCAmelCase_=0.1     ,UpperCAmelCase_=0.1     ,UpperCAmelCase_=1E-5     ,UpperCAmelCase_=0.02     ,UpperCAmelCase_=True     ,UpperCAmelCase_=True     ,UpperCAmelCase_=False     ,UpperCAmelCase_=False     ,UpperCAmelCase_=False     ,**UpperCAmelCase_     ,)  ->							Dict:
											lowercase__		       =						vocab_size
											lowercase__		       =						n_positions
											lowercase__		       =						n_embd
											lowercase__		       =						n_layer
											lowercase__		       =						n_head
											lowercase__		       =						n_inner
											lowercase__		       =						activation_function
											lowercase__		       =						resid_pdrop
											lowercase__		       =						embd_pdrop
											lowercase__		       =						attn_pdrop
											lowercase__		       =						layer_norm_epsilon
											lowercase__		       =						initializer_range
											lowercase__		       =						scale_attn_weights
											lowercase__		       =						use_cache
											lowercase__		       =						scale_attn_by_inverse_layer_idx
											lowercase__		       =						reorder_and_upcast_attn
											lowercase__		       =						tie_word_embeddings

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





class 				snake_case (UpperCamelCase   ):



							@property
							def 							_a      (				self      )  ->							Mapping[str, Mapping[int, str]]:
											return OrderedDict(
											    [
											        ("input_ids", {0: "batch", 1: "sequence"}),
											    ]      )







							def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = 1     ,UpperCAmelCase_ = -1     ,UpperCAmelCase_ = False     ,UpperCAmelCase_ = None     ,UpperCAmelCase_ = 3     ,UpperCAmelCase_ = 32     ,UpperCAmelCase_ = 32     ,)  ->							Mapping[str, Any]:
											lowercase__		       =						self._generate_dummy_images(UpperCAmelCase_     ,UpperCAmelCase_     ,UpperCAmelCase_     ,UpperCAmelCase_      )
											lowercase__		       =						dict(preprocessor(images=UpperCAmelCase_     ,return_tensors=UpperCAmelCase_      )      )

											return inputs









'''simple docstring'''





print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))




