



from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case     :Union[str, Any]			       =logging.get_logger(__name__)

__snake_case     :Optional[int]			       ={
    'snap-research/efficientformer-l1-300': (
        'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json'
    ),
}



class        lowerCAmelCase__					(  _lowerCamelCase       ):
				A_   :     Tuple								=     'efficientformer'


				def __init__(							self      :  Union[str, Any]						, __UpperCamelCase      :  List[int] = [3, 2, 6, 4]						, __UpperCamelCase      :  List[int] = [48, 96, 224, 448]						, __UpperCamelCase      :  List[bool] = [True, True, True, True]						, __UpperCamelCase      :  int = 448						, __UpperCamelCase      :  int = 32						, __UpperCamelCase      :  int = 4						, __UpperCamelCase      :  int = 7						, __UpperCamelCase      :  int = 5						, __UpperCamelCase      :  int = 8						, __UpperCamelCase      :  int = 4						, __UpperCamelCase      :  float = 0.0						, __UpperCamelCase      :  int = 16						, __UpperCamelCase      :  int = 3						, __UpperCamelCase      :  int = 3						, __UpperCamelCase      :  int = 3						, __UpperCamelCase      :  int = 2						, __UpperCamelCase      :  int = 1						, __UpperCamelCase      :  float = 0.0						, __UpperCamelCase      :  int = 1						, __UpperCamelCase      :  bool = True						, __UpperCamelCase      :  bool = True						, __UpperCamelCase      :  float = 1e-5						, __UpperCamelCase      :  str = "gelu"						, __UpperCamelCase      :  float = 0.0_2						, __UpperCamelCase      :  float = 1e-12						, __UpperCamelCase      :  int = 224						, __UpperCamelCase      :  float = 1e-05						, **__UpperCamelCase      :  List[Any]						, )		->     None:
											super().__init__(**__UpperCamelCase       )

											A      						=    hidden_act
											A      						=    hidden_dropout_prob
											A      						=    hidden_sizes
											A      						=    num_hidden_layers
											A      						=    num_attention_heads
											A      						=    initializer_range
											A      						=    layer_norm_eps
											A      						=    patch_size
											A      						=    num_channels
											A      						=    depths
											A      						=    mlp_expansion_ratio
											A      						=    downsamples
											A      						=    dim
											A      						=    key_dim
											A      						=    attention_ratio
											A      						=    resolution
											A      						=    pool_size
											A      						=    downsample_patch_size
											A      						=    downsample_stride
											A      						=    downsample_pad
											A      						=    drop_path_rate
											A      						=    num_metaad_blocks
											A      						=    distillation
											A      						=    use_layer_scale
											A      						=    layer_scale_init_value
											A      						=    image_size
											A      						=    batch_norm_eps

'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re

from ..utils import cached_file


# docstyle-ignore
lowercase__						       =      "\nHuman: <<task>>\n\nAssistant: "


lowercase__						       =      "huggingface-tools/default-prompts"
lowercase__						       =      {"chat": "chat_prompt_template.txt", "run": "run_prompt_template.txt"}




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__="run"			)  ->							Dict:


		'''simple docstring'''


		if prompt_or_repo_id is None:
				snake_case  :       Union[str, Any]     			=						DEFAULT_PROMPTS_REPO

		# prompt is considered a repo ID when it does not contain any kind of space
		if re.search('''\\s''' ,       SCREAMING_SNAKE_CASE__			) is not None:
				return prompt_or_repo_id

		snake_case  :       List[Any]     			=						cached_file(
		    SCREAMING_SNAKE_CASE__ ,       PROMPT_FILES[mode] ,       repo_type='''dataset''' ,       user_agent={'''agent''': agent_name}			)
		with open(SCREAMING_SNAKE_CASE__ ,       '''r''' ,       encoding='''utf-8'''			) as f:
				return f.read()


