





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      _lowercase					(						_UpperCAmelCase				)						->  Dict:
				return EnvironmentCommand()




class       __A     (						a__    ):


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


				def _snake_case       (		self							):
								lowerCamelCase	 =huggingface_hub.__version__

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

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

								lowerCamelCase	 ="""not installed"""
								if is_transformers_available():
												import transformers

												lowerCamelCase	 =transformers.__version__

								lowerCamelCase	 ="""not installed"""
								if is_accelerate_available():
												import accelerate

												lowerCamelCase	 =accelerate.__version__

								lowerCamelCase	 ="""not installed"""
								if is_xformers_available():
												import xformers

												lowerCamelCase	 =xformers.__version__

								lowerCamelCase	 ={
								    """`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 _snake_case       (		UpperCAmelCase_							):
								return "\n".join([f"""- {prop}: {val}""" for prop, val in d.items()]							) + "\n"












from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch

from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch

@require_torch
@require_tf
class       __A     (						a    ):


				def _snake_case       (		self							):
								lowerCamelCase	 =SMALL_MODEL_IDENTIFIER
								lowerCamelCase	 ="""pt"""
								lowerCamelCase	 ="""tf"""


				def _snake_case       (		self   , UpperCAmelCase_							):
								lowerCamelCase	 =AutoModel.from_pretrained(self.test_model							)
								model_pt.save_pretrained(UpperCAmelCase_							)


				def _snake_case       (		self   , UpperCAmelCase_							):
								lowerCamelCase	 =TFAutoModel.from_pretrained(self.test_model   , from_pt=UpperCAmelCase_							)
								model_tf.save_pretrained(UpperCAmelCase_							)


				def _snake_case       (		self							):
								lowerCamelCase	 ="""mock_framework"""

								# Framework provided - return whatever the user provides
								lowerCamelCase	 =FeaturesManager.determine_framework(self.test_model   , UpperCAmelCase_							)
								self.assertEqual(UpperCAmelCase_   , UpperCAmelCase_							)

								# Local checkpoint and framework provided - return provided framework
								# PyTorch checkpoint
								with TemporaryDirectory() as local_pt_ckpt:
												self._setup_pt_ckpt(UpperCAmelCase_							)
												lowerCamelCase	 =FeaturesManager.determine_framework(UpperCAmelCase_   , UpperCAmelCase_							)
												self.assertEqual(UpperCAmelCase_   , UpperCAmelCase_							)

								# TensorFlow checkpoint
								with TemporaryDirectory() as local_tf_ckpt:
												self._setup_tf_ckpt(UpperCAmelCase_							)
												lowerCamelCase	 =FeaturesManager.determine_framework(UpperCAmelCase_   , UpperCAmelCase_							)
												self.assertEqual(UpperCAmelCase_   , UpperCAmelCase_							)


				def _snake_case       (		self							):
								# PyTorch checkpoint
								with TemporaryDirectory() as local_pt_ckpt:
												self._setup_pt_ckpt(UpperCAmelCase_							)
												lowerCamelCase	 =FeaturesManager.determine_framework(UpperCAmelCase_							)
												self.assertEqual(UpperCAmelCase_   , self.framework_pt							)

								# TensorFlow checkpoint
								with TemporaryDirectory() as local_tf_ckpt:
												self._setup_tf_ckpt(UpperCAmelCase_							)
												lowerCamelCase	 =FeaturesManager.determine_framework(UpperCAmelCase_							)
												self.assertEqual(UpperCAmelCase_   , self.framework_tf							)

								# Invalid local checkpoint
								with TemporaryDirectory() as local_invalid_ckpt:
												with self.assertRaises(UpperCAmelCase_							):
																lowerCamelCase	 =FeaturesManager.determine_framework(UpperCAmelCase_							)


				def _snake_case       (		self							):
								lowerCamelCase	 =MagicMock(return_value=UpperCAmelCase_							)
								with patch("""transformers.onnx.features.is_tf_available"""   , UpperCAmelCase_							):
												lowerCamelCase	 =FeaturesManager.determine_framework(self.test_model							)
												self.assertEqual(UpperCAmelCase_   , self.framework_pt							)

								# PyTorch not in environment -> use TensorFlow
								lowerCamelCase	 =MagicMock(return_value=UpperCAmelCase_							)
								with patch("""transformers.onnx.features.is_torch_available"""   , UpperCAmelCase_							):
												lowerCamelCase	 =FeaturesManager.determine_framework(self.test_model							)
												self.assertEqual(UpperCAmelCase_   , self.framework_tf							)

								# Both in environment -> use PyTorch
								lowerCamelCase	 =MagicMock(return_value=UpperCAmelCase_							)
								lowerCamelCase	 =MagicMock(return_value=UpperCAmelCase_							)
								with patch("""transformers.onnx.features.is_tf_available"""   , UpperCAmelCase_							), patch(
								    """transformers.onnx.features.is_torch_available"""   , UpperCAmelCase_							):
												lowerCamelCase	 =FeaturesManager.determine_framework(self.test_model							)
												self.assertEqual(UpperCAmelCase_   , self.framework_pt							)

								# Both not in environment -> raise error
								lowerCamelCase	 =MagicMock(return_value=UpperCAmelCase_							)
								lowerCamelCase	 =MagicMock(return_value=UpperCAmelCase_							)
								with patch("""transformers.onnx.features.is_tf_available"""   , UpperCAmelCase_							), patch(
								    """transformers.onnx.features.is_torch_available"""   , UpperCAmelCase_							):
												with self.assertRaises(UpperCAmelCase_							):
																lowerCamelCase	 =FeaturesManager.determine_framework(self.test_model							)





