



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__    (    lowercase__   ) ->      Tuple:
						return EnvironmentCommand()






def  UpperCAmelCase__    (    lowercase__   ) ->      Union[str, Any]:
						return EnvironmentCommand(args.accelerate_config_file   )







class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			@staticmethod
			def 		snake_case__			(				lowercase	:       ArgumentParser   )						->					Any:
									"""simple docstring"""







									__lowercase					=				parser.add_parser("""env"""   )
									download_parser.set_defaults(func=lowercase   )
									download_parser.add_argument(
									    """--accelerate-config_file"""			,     default=lowercase			,     help="""The accelerate config file to use for the default values in the launching script."""			,     )
									download_parser.set_defaults(func=lowercase   )





			def __init__(				self	:       Dict			,     lowercase	:       Tuple			,     *lowercase	:       Optional[int]   )						->					None:
									"""simple docstring"""







									__lowercase					=				accelerate_config_file





			def 		snake_case__			(				self	:       List[Any]   )						->					Any:
									"""simple docstring"""







									__lowercase					=				"""not installed"""
									if is_safetensors_available():
															import safetensors

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

															__lowercase					=				F"{safetensors.__version__} but is ignored because of PyTorch version too old."

									__lowercase					=				"""not installed"""
									__lowercase					=				__lowercase					=				"""not found"""
									if is_accelerate_available():
															import accelerate
															from accelerate.commands.config import default_config_file, load_config_from_file

															__lowercase					=				accelerate.__version__
															# Get the default from the config file.
															if self._accelerate_config_file is not None or os.path.isfile(lowercase   ):
																					__lowercase					=				load_config_from_file(self._accelerate_config_file   ).to_dict()

															__lowercase					=				(
															    """\n""".join([F"\t- {prop}: {val}" for prop, val in accelerate_config.items()]   )
															    if isinstance(lowercase			,     lowercase   )
															    else F"\t{accelerate_config}"
															)

									__lowercase					=				"""not installed"""
									__lowercase					=				"""NA"""
									if is_torch_available():
															import torch

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

									__lowercase					=				"""not installed"""
									__lowercase					=				"""NA"""
									if is_tf_available():
															import tensorflow as tf

															__lowercase					=				tf.__version__
															try:
																					# deprecated in v2.1
																					__lowercase					=				tf.test.is_gpu_available()
															except AttributeError:
																					# returns list of devices, convert to bool
																					__lowercase					=				bool(tf.config.list_physical_devices("""GPU"""   )   )

									__lowercase					=				"""not installed"""
									__lowercase					=				"""not installed"""
									__lowercase					=				"""not installed"""
									__lowercase					=				"""NA"""
									if is_flax_available():
															import flax
															import jax
															import jaxlib

															__lowercase					=				flax.__version__
															__lowercase					=				jax.__version__
															__lowercase					=				jaxlib.__version__
															__lowercase					=				jax.lib.xla_bridge.get_backend().platform

									__lowercase					=				{
									    """`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(lowercase   )   )

									return info







			@staticmethod
			def 		snake_case__			(				lowercase	:       str   )						->					str:
									"""simple docstring"""







									return "\n".join([F"- {prop}: {val}" for prop, val in d.items()]   ) + "\n"








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


UpperCamelCase__ =						{
    "configuration_ctrl": ["CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP", "CTRLConfig"],
    "tokenization_ctrl": ["CTRLTokenizer"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    "CTRL_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "CTRLForSequenceClassification",
			    "CTRLLMHeadModel",
			    "CTRLModel",
			    "CTRLPreTrainedModel",
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    "TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "TFCTRLForSequenceClassification",
			    "TFCTRLLMHeadModel",
			    "TFCTRLModel",
			    "TFCTRLPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
			from .tokenization_ctrl import CTRLTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_ctrl import (
						    CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CTRLForSequenceClassification,
						    CTRLLMHeadModel,
						    CTRLModel,
						    CTRLPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_ctrl import (
						    TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFCTRLForSequenceClassification,
						    TFCTRLLMHeadModel,
						    TFCTRLModel,
						    TFCTRLPreTrainedModel,
						)

else:
			import sys

			UpperCamelCase__ =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





