



import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand




def      __UpperCamelCase     (  _lowerCAmelCase		)	->  int:



    """simple docstring"""






    return EnvironmentCommand()




def      __UpperCamelCase     (  _lowerCAmelCase		)	->  Optional[int]:



    """simple docstring"""






    return EnvironmentCommand(args.accelerate_config_file		)






class SCREAMING_SNAKE_CASE__					(		SCREAMING_SNAKE_CASE__   ):




    '''simple docstring'''






    @staticmethod
    def       _lowerCAmelCase (	lowerCamelCase__		):
        A			:	Optional[Any]										=       parser.add_parser("""env"""		)
        download_parser.set_defaults(func=lowerCamelCase__		)
        download_parser.add_argument(
            """--accelerate-config_file""",		default=lowerCamelCase__,		help="""The accelerate config file to use for the default values in the launching script.""",		)
        download_parser.set_defaults(func=lowerCamelCase__		)






    def __init__(	self,		lowerCamelCase__,		*lowerCamelCase__		):
        A			:	str										=       accelerate_config_file






    def       _lowerCAmelCase (	self		):
        A			:	Dict										=       """not installed"""
        if is_safetensors_available():
            import safetensors

            A			:	str										=       safetensors.__version__
        elif importlib.util.find_spec("""safetensors"""		) is not None:
            import safetensors

            A			:	List[str]										=       f'''{safetensors.__version__} but is ignored because of PyTorch version too old.'''

        A			:	List[str]										=       """not installed"""
        A			:	Any										=       """not found"""
        if is_accelerate_available():
            import accelerate
            from accelerate.commands.config import default_config_file, load_config_from_file

            A			:	Optional[Any]										=       accelerate.__version__
            # Get the default from the config file.
            if self._accelerate_config_file is not None or os.path.isfile(lowerCamelCase__		):
                A			:	List[Any]										=       load_config_from_file(self._accelerate_config_file		).to_dict()

            A			:	Tuple										=       (
                """\n""".join([f'''\t- {prop}: {val}''' for prop, val in accelerate_config.items()]		)
                if isinstance(lowerCamelCase__,		lowerCamelCase__		)
                else f'''\t{accelerate_config}'''
            )

        A			:	str										=       """not installed"""
        A			:	List[str]										=       """NA"""
        if is_torch_available():
            import torch

            A			:	int										=       torch.__version__
            A			:	Dict										=       torch.cuda.is_available()

        A			:	str										=       """not installed"""
        A			:	Optional[Any]										=       """NA"""
        if is_tf_available():
            import tensorflow as tf

            A			:	Union[str, Any]										=       tf.__version__
            try:
                # deprecated in v2.1
                A			:	int										=       tf.test.is_gpu_available()
            except AttributeError:
                # returns list of devices, convert to bool
                A			:	Tuple										=       bool(tf.config.list_physical_devices("""GPU"""		)		)

        A			:	List[str]										=       """not installed"""
        A			:	List[Any]										=       """not installed"""
        A			:	List[Any]										=       """not installed"""
        A			:	List[Any]										=       """NA"""
        if is_flax_available():
            import flax
            import jax
            import jaxlib

            A			:	Union[str, Any]										=       flax.__version__
            A			:	Any										=       jax.__version__
            A			:	Tuple										=       jaxlib.__version__
            A			:	Any										=       jax.lib.xla_bridge.get_backend().platform

        A			:	int										=       {
            """`transformers` version""": version,
            """Platform""": platform.platform(),
            """Python version""": platform.python_version(),
            """Huggingface_hub version""": huggingface_hub.__version__,
            """Safetensors version""": f'''{safetensors_version}''',
            """Accelerate version""": f'''{accelerate_version}''',
            """Accelerate config""": f'''{accelerate_config_str}''',
            """PyTorch version (GPU?)""": f'''{pt_version} ({pt_cuda_available})''',
            """Tensorflow version (GPU?)""": f'''{tf_version} ({tf_cuda_available})''',
            """Flax version (CPU?/GPU?/TPU?)""": f'''{flax_version} ({jax_backend})''',
            """Jax version""": f'''{jax_version}''',
            """JaxLib version""": f'''{jaxlib_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       _lowerCAmelCase (	lowerCamelCase__		):
        return "\n".join([f'''- {prop}: {val}''' for prop, val in d.items()]		) + "\n"







import os
from pathlib import Path




def      __UpperCamelCase     (  )	->  Any:



    """simple docstring"""






    from torch.utils.cpp_extension import load

    A			:	Any										=       Path(_lowerCAmelCase		).resolve().parent.parent.parent / """kernels""" / """deformable_detr"""
    A			:	int										=       [
        root / filename
        for filename in [
            """vision.cpp""",
            os.path.join("""cpu"""				,					"""ms_deform_attn_cpu.cpp"""		),
            os.path.join("""cuda"""				,					"""ms_deform_attn_cuda.cu"""		),
        ]
    ]

    load(
        """MultiScaleDeformableAttention"""				,					_lowerCAmelCase				,					with_cuda=_lowerCAmelCase				,					extra_include_paths=[str(_lowerCAmelCase		)]				,					extra_cflags=["""-DWITH_CUDA=1"""]				,					extra_cuda_cflags=[
            """-DCUDA_HAS_FP16=1""",
            """-D__CUDA_NO_HALF_OPERATORS__""",
            """-D__CUDA_NO_HALF_CONVERSIONS__""",
            """-D__CUDA_NO_HALF2_OPERATORS__""",
        ]				,					)

    import MultiScaleDeformableAttention as MSDA

    return MSDA


