


'''simple docstring'''




from collections import OrderedDict
from dataclasses import fields
from typing import Any, Tuple

import numpy as np

from .import_utils import is_torch_available

def       __UpperCamelCase     (     _A     :					List[str]					)     ->   Any:




	"""simple docstring"""





	if is_torch_available():
		import torch

		if isinstance(_A       , torch.Tensor					):
			return True

	return isinstance(_A       , np.ndarray					)






class 			lowerCAmelCase					(					a				):



	def 					lowercase  (       self     ):
		lowerCAmelCase       :     List[str]   				=			fields(self     )

		# Safety and consistency checks
		if not len(snake_case__     ):
			raise ValueError(f"{self.__class__.__name__} has no fields."     )

		lowerCAmelCase       :     List[str]   				=			getattr(self			,       class_fields[0].name     )
		lowerCAmelCase       :     List[Any]   				=			all(getattr(self			,       field.name     ) is None for field in class_fields[1:]     )

		if other_fields_are_none and isinstance(snake_case__			,       snake_case__     ):
			for key, value in first_field.items():
				lowerCAmelCase       :     Optional[int]   				=			value
		else:
			for field in class_fields:
				lowerCAmelCase       :     str   				=			getattr(self			,       field.name     )
				if v is not None:
					lowerCAmelCase       :     Optional[Any]   				=			v



	def __delitem__(       self			,       *snake_case__			,       **snake_case__     ):
		raise Exception(f"You cannot use ``__delitem__`` on a {self.__class__.__name__} instance."     )



	def 					lowercase  (       self			,       *snake_case__			,       **snake_case__     ):
		raise Exception(f"You cannot use ``setdefault`` on a {self.__class__.__name__} instance."     )



	def 					lowercase  (       self			,       *snake_case__			,       **snake_case__     ):
		raise Exception(f"You cannot use ``pop`` on a {self.__class__.__name__} instance."     )



	def 					lowercase  (       self			,       *snake_case__			,       **snake_case__     ):
		raise Exception(f"You cannot use ``update`` on a {self.__class__.__name__} instance."     )



	def __getitem__(       self			,       snake_case__     ):
		if isinstance(snake_case__			,       snake_case__     ):
			lowerCAmelCase       :     Dict   				=			dict(self.items()     )
			return inner_dict[k]
		else:
			return self.to_tuple()[k]



	def __setattr__(       self			,       snake_case__			,       snake_case__     ):
		if name in self.keys() and value is not None:
			# Don't call self.__setitem__ to avoid recursion errors
			super().__setitem__(snake_case__			,       snake_case__     )
		super().__setattr__(snake_case__			,       snake_case__     )



	def __setitem__(       self			,       snake_case__			,       snake_case__     ):
		# Will raise a KeyException if needed
		super().__setitem__(snake_case__			,       snake_case__     )
		# Don't call self.__setattr__ to avoid recursion errors
		super().__setattr__(snake_case__			,       snake_case__     )



	def 					lowercase  (       self     ):
		return tuple(self[k] for k in self.keys()     )




'''simple docstring'''




import importlib.metadata
import sys

from transformers.testing_utils import TestCasePlus
from transformers.utils.versions import require_version, require_version_core


_lowerCAmelCase	:		Optional[int]		  =						importlib.metadata.version('numpy')
_lowerCAmelCase	:		List[Any]		  =						'.'.join([str(x) for x in sys.version_info[:3]])



class 			lowerCAmelCase					(					a				):



	def 					lowercase  (       self     ):
		# lt + different version strings
		require_version_core('numpy<1000.4.5'     )
		require_version_core('numpy<1000.4'     )
		require_version_core('numpy<1000'     )

		# le
		require_version_core('numpy<=1000.4.5'     )
		require_version_core(f"numpy<={numpy_ver}"     )

		# eq
		require_version_core(f"numpy=={numpy_ver}"     )

		# ne
		require_version_core('numpy!=1000.4.5'     )

		# ge
		require_version_core('numpy>=1.0'     )
		require_version_core('numpy>=1.0.0'     )
		require_version_core(f"numpy>={numpy_ver}"     )

		# gt
		require_version_core('numpy>1.0.0'     )

		# mix
		require_version_core('numpy>1.0.0,<1000'     )

		# requirement w/o version
		require_version_core('numpy'     )

		# unmet requirements due to version conflict
		for req in ["numpy==1.0.0", "numpy>=1000.0.0", f"numpy<{numpy_ver}"]:
			try:
				require_version_core(snake_case__     )
			except ImportError as e:
				self.assertIn(f"{req} is required"			,       str(snake_case__     )     )
				self.assertIn('but found'			,       str(snake_case__     )     )

        # unmet requirements due to missing module
		for req in ["numpipypie>1", "numpipypie2"]:
			try:
				require_version_core(snake_case__     )
			except importlib.metadata.PackageNotFoundError as e:
				self.assertIn(f"The '{req}' distribution was not found and is required by this application"			,       str(snake_case__     )     )
				self.assertIn('Try: pip install transformers -U'			,       str(snake_case__     )     )

        # bogus requirements formats:
        # 1. whole thing
		for req in ["numpy??1.0.0", "numpy1.0.0"]:
			try:
				require_version_core(snake_case__     )
			except ValueError as e:
				self.assertIn('requirement needs to be in the pip package format'			,       str(snake_case__     )     )
        # 2. only operators
		for req in ["numpy=1.0.0", "numpy == 1.00", "numpy<>1.0.0", "numpy><1.00", "numpy>>1.0.0"]:
			try:
				require_version_core(snake_case__     )
			except ValueError as e:
				self.assertIn('need one of '			,       str(snake_case__     )     )



	def 					lowercase  (       self     ):
		# matching requirement
		require_version('python>=3.6.0'     )

		# not matching requirements
		for req in ["python>9.9.9", "python<3.0.0"]:
			try:
				require_version_core(snake_case__     )
			except ImportError as e:
				self.assertIn(f"{req} is required"			,       str(snake_case__     )     )
				self.assertIn(f"but found python=={python_ver}"			,       str(snake_case__     )     )
