"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__      						=  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      						=  {
    "bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}



class   lowerCAmelCase_    (			lowerCAmelCase					):



				"""simple docstring"""
				_lowerCAmelCase     :    Dict			  =						"""gpt_bigcode"""
				_lowerCAmelCase     :    Any			  =						["""past_key_values"""]
				_lowerCAmelCase     :    int			  =						{
				    """hidden_size""": """n_embd""",
				    """max_position_embeddings""": """n_positions""",
				    """num_attention_heads""": """n_head""",
				    """num_hidden_layers""": """n_layer""",
				}

				def __init__(				self		,    lowerCAmelCase=5_02_57		,    lowerCAmelCase=10_24		,    lowerCAmelCase=7_68		,    lowerCAmelCase=12		,    lowerCAmelCase=12		,    lowerCAmelCase=None		,    lowerCAmelCase="gelu_pytorch_tanh"		,    lowerCAmelCase=0.1		,    lowerCAmelCase=0.1		,    lowerCAmelCase=0.1		,    lowerCAmelCase=1E-5		,    lowerCAmelCase=0.02		,    lowerCAmelCase=True		,    lowerCAmelCase=True		,    lowerCAmelCase=5_02_56		,    lowerCAmelCase=5_02_56		,    lowerCAmelCase=True		,    lowerCAmelCase=True		,    lowerCAmelCase=True		,    **lowerCAmelCase		,    ):






										"""simple docstring"""

										snake_case								=			vocab_size
										snake_case								=			n_positions
										snake_case								=			n_embd
										snake_case								=			n_layer
										snake_case								=			n_head
										snake_case								=			n_inner
										snake_case								=			activation_function
										snake_case								=			resid_pdrop
										snake_case								=			embd_pdrop
										snake_case								=			attn_pdrop
										snake_case								=			layer_norm_epsilon
										snake_case								=			initializer_range
										snake_case								=			scale_attn_weights
										snake_case								=			use_cache
										snake_case								=			attention_softmax_in_fpaa
										snake_case								=			scale_attention_softmax_in_fpaa
										snake_case								=			multi_query

										snake_case								=			bos_token_id
										snake_case								=			eos_token_id

										super().__init__(bos_token_id=lowerCAmelCase		,    eos_token_id=lowerCAmelCase		,    **lowerCAmelCase    )







"""simple docstring"""
from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
					if not (is_transformers_available() and is_torch_available()):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import ShapEPipeline
else:
					from .camera import create_pan_cameras
					from .pipeline_shap_e import ShapEPipeline
					from .pipeline_shap_e_img2img import ShapEImgaImgPipeline
					from .renderer import (
					    BoundingBoxVolume,
					    ImportanceRaySampler,
					    MLPNeRFModelOutput,
					    MLPNeRSTFModel,
					    ShapEParamsProjModel,
					    ShapERenderer,
					    StratifiedRaySampler,
					    VoidNeRFModel,
					)


