





'''simple docstring'''



import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand




def 				snake_case_      (		SCREAMING_SNAKE_CASE__       ):







  '''simple docstring'''



  return EnvironmentCommand()




class       __SCREAMING_SNAKE_CASE	(						UpperCamelCase_			):



     '''simple docstring'''






     @staticmethod
     def 	UpperCamelCase(					lowerCamelCase	):
       _snake_case     		=				parser.add_parser("env"	)
       download_parser.set_defaults(func=lowerCamelCase	)

     def 	UpperCamelCase(					self	):
       _snake_case     		=				huggingface_hub.__version__

       _snake_case     		=				'''not installed'''
       _snake_case     		=				'''NA'''
       if is_torch_available():
         import torch

         _snake_case     		=				torch.__version__
         _snake_case     		=				torch.cuda.is_available()

       _snake_case     		=				'''not installed'''
       if is_transformers_available():
         import transformers

         _snake_case     		=				transformers.__version__

       _snake_case     		=				'''not installed'''
       if is_accelerate_available():
         import accelerate

         _snake_case     		=				accelerate.__version__

       _snake_case     		=				'''not installed'''
       if is_xformers_available():
         import xformers

         _snake_case     		=				xformers.__version__

       _snake_case     		=				{
           '''`diffusers` version''': version,
           '''Platform''': platform.platform(),
           '''Python version''': platform.python_version(),
           '''PyTorch version (GPU?)''': F'''{pt_version} ({pt_cuda_available})''',
           '''Huggingface_hub version''': hub_version,
           '''Transformers version''': transformers_version,
           '''Accelerate version''': accelerate_version,
           '''xFormers version''': xformers_version,
           '''Using GPU in script?''': '''<fill in>''',
           '''Using distributed or parallel set-up in script?''': '''<fill in>''',
       }

       print("\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n"	)
       print(self.format_dict(lowerCamelCase	)	)

       return info






     @staticmethod
     def 	UpperCamelCase(					lowerCamelCase	):
       return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]	) + "\n"









'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__magic_name__   :						Dict    =			logging.get_logger(__name__)

__magic_name__   :						Dict    =			{
    """google/mobilenet_v1_1.0_224""": """https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v1_0.75_192""": """https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json""",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}


class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase			):



     '''simple docstring'''






     UpperCAmelCase__       :						List[Any]      =   '''mobilenet_v1'''

     def __init__(					self						,   lowerCamelCase=3						,   lowerCamelCase=224						,   lowerCamelCase=1.0						,   lowerCamelCase=8						,   lowerCamelCase="relu6"						,   lowerCamelCase=True						,   lowerCamelCase=0.999						,   lowerCamelCase=0.02						,   lowerCamelCase=0.001						,   **lowerCamelCase						,   ):
       super().__init__(**lowerCamelCase	)

       if depth_multiplier <= 0:
         raise ValueError("depth_multiplier must be greater than zero."	)

       _snake_case     		=				num_channels
       _snake_case     		=				image_size
       _snake_case     		=				depth_multiplier
       _snake_case     		=				min_depth
       _snake_case     		=				hidden_act
       _snake_case     		=				tf_padding
       _snake_case     		=				classifier_dropout_prob
       _snake_case     		=				initializer_range
       _snake_case     		=				layer_norm_eps







class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase			):



     '''simple docstring'''






     UpperCAmelCase__       :						int      =   version.parse('''1.11'''			)

     @property
     def 	UpperCamelCase(					self	):
       return OrderedDict([("pixel_values", {0: "batch"})]	)

     @property
     def 	UpperCamelCase(					self	):
       if self.task == "image-classification":
         return OrderedDict([("logits", {0: "batch"})]	)
       else:
         return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]	)






     @property
     def 	UpperCamelCase(					self	):
       return 1e-4


