




# Copyright 2023 The HuggingFace 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.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCamelCase								=					{
    'configuration_efficientnet': [
        'EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EfficientNetConfig',
        'EfficientNetOnnxConfig',
    ]
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase								=					['EfficientNetImageProcessor']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase								=					[
         'EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST',
         'EfficientNetForImageClassification',
         'EfficientNetModel',
         'EfficientNetPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_efficientnet import (
         EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
         EfficientNetConfig,
         EfficientNetOnnxConfig,
     )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_efficientnet import EfficientNetImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_efficientnet import (
              EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              EfficientNetForImageClassification,
              EfficientNetModel,
              EfficientNetPreTrainedModel,
          )

else:
     import sys

     UpperCamelCase								=					_LazyModule(__name__, globals()['__file__'], _import_structure)






from statistics import mean, stdev



def 							_A       (						lowerCAmelCase_					: list       ,    lowerCAmelCase_					: int = 3      ):
     """simple docstring"""

     lowerCAmelCase__          =			min(lowerCAmelCase_      )
     lowerCAmelCase__          =			max(lowerCAmelCase_      )
     # normalize data
     return [round((x - x_min) / (x_max - x_min)       ,    lowerCAmelCase_      ) for x in data]






def 							_A       (						lowerCAmelCase_					: list       ,    lowerCAmelCase_					: int = 3      ):
     """simple docstring"""

     lowerCAmelCase__          =			mean(lowerCAmelCase_      )
     lowerCAmelCase__          =			stdev(lowerCAmelCase_      )
     # standardize data
     return [round((x - mu) / (sigma)       ,    lowerCAmelCase_      ) for x in data]
