


'''simple docstring'''



# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import torch

from accelerate import PartialState
from accelerate.utils.operations import broadcast, gather, gather_object, pad_across_processes, reduce






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Tuple   ):
					return (torch.arange(state.num_processes   ) + 1.0 + (state.num_processes * state.process_index)).to(state.device   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Tuple   ):
					__a			:       Tuple					    =  create_tensor(_SCREAMING_SNAKE_CASE   )
					__a			:       List[str]					    =  gather(_SCREAMING_SNAKE_CASE   )
					assert gathered_tensor.tolist() == list(range(1						,      state.num_processes**2 + 1   )   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Tuple   ):
					__a			:       int					    =  [state.process_index]
					__a			:       Tuple					    =  gather_object(_SCREAMING_SNAKE_CASE   )
					assert len(_SCREAMING_SNAKE_CASE   ) == state.num_processes, F"""{gathered_obj}, {len(_SCREAMING_SNAKE_CASE   )} != {state.num_processes}"""
					assert gathered_obj == list(range(state.num_processes   )   ), F"""{gathered_obj} != {list(range(state.num_processes   )   )}"""






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Dict   ):
					__a			:       List[str]					    =  create_tensor(_SCREAMING_SNAKE_CASE   )
					__a			:       str					    =  broadcast(_SCREAMING_SNAKE_CASE   )
					assert broadcasted_tensor.shape == torch.Size([state.num_processes]   )
					assert broadcasted_tensor.tolist() == list(range(1						,      state.num_processes + 1   )   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   str   ):
					# We need to pad the tensor with one more element if we are the main process
					# to ensure that we can pad
					if state.is_main_process:
										__a			:       Tuple					    =  torch.arange(state.num_processes + 1   ).to(state.device   )
					else:
										__a			:       List[str]					    =  torch.arange(state.num_processes   ).to(state.device   )
					__a			:       int					    =  pad_across_processes(_SCREAMING_SNAKE_CASE   )
					assert padded_tensor.shape == torch.Size([state.num_processes + 1]   )
					if not state.is_main_process:
										assert padded_tensor.tolist() == list(range(0						,      state.num_processes   )   ) + [0]






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   int   ):
					# For now runs on only two processes
					if state.num_processes != 2:
										return
					__a			:       List[Any]					    =  create_tensor(_SCREAMING_SNAKE_CASE   )
					__a			:       int					    =  reduce(_SCREAMING_SNAKE_CASE						,      'sum'   )
					__a			:       int					    =  torch.tensor([4.0, 6]   ).to(state.device   )
					assert torch.allclose(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ), F"""{reduced_tensor} != {truth_tensor}"""






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   int   ):
					# For now runs on only two processes
					if state.num_processes != 2:
										return
					__a			:       Union[str, Any]					    =  create_tensor(_SCREAMING_SNAKE_CASE   )
					__a			:       Dict					    =  reduce(_SCREAMING_SNAKE_CASE						,      'mean'   )
					__a			:       int					    =  torch.tensor([2.0, 3]   ).to(state.device   )
					assert torch.allclose(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ), F"""{reduced_tensor} != {truth_tensor}"""






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any   ):
					# For xla_spawn (TPUs)
					main()






def   lowerCamelCase							():
					__a			:       Any					    =  PartialState()
					state.print(F"""State: {state}"""   )
					state.print('testing gather'   )
					test_gather(_SCREAMING_SNAKE_CASE   )
					state.print('testing gather_object'   )
					test_gather_object(_SCREAMING_SNAKE_CASE   )
					state.print('testing broadcast'   )
					test_broadcast(_SCREAMING_SNAKE_CASE   )
					state.print('testing pad_across_processes'   )
					test_pad_across_processes(_SCREAMING_SNAKE_CASE   )
					state.print('testing reduce_sum'   )
					test_reduce_sum(_SCREAMING_SNAKE_CASE   )
					state.print('testing reduce_mean'   )
					test_reduce_mean(_SCREAMING_SNAKE_CASE   )


if __name__ == "__main__":
	main()







'''simple docstring'''



import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('.')






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[Any]   ):
					__a			:       Any					    =  test_file.split(os.path.sep   )
					if components[0:2] != ["tests", "models"]:
										raise ValueError(
										    '`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '
										    F"""{test_file} instead."""   )
					__a			:       Tuple					    =  components[-1]
					if not test_fn.endswith('py'   ):
										raise ValueError(F"""`test_file` should be a python file. Got {test_fn} instead."""   )
					if not test_fn.startswith('test_modeling_'   ):
										raise ValueError(
										    F"""`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead."""   )

					__a			:       List[str]					    =  components[:-1] + [test_fn.replace('.py'						,      ''   )]
					__a			:       Optional[Any]					    =  '.'.join(_SCREAMING_SNAKE_CASE   )

					return test_module_path






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Tuple   ):
					__a			:       List[str]					    =  get_module_path(_SCREAMING_SNAKE_CASE   )
					__a			:       Dict					    =  importlib.import_module(_SCREAMING_SNAKE_CASE   )

					return test_module






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Tuple   ):
					__a			:       List[str]					    =  []
					__a			:       List[str]					    =  get_test_module(_SCREAMING_SNAKE_CASE   )
					for attr in dir(_SCREAMING_SNAKE_CASE   ):
										if attr.endswith('ModelTester'   ):
															tester_classes.append(getattr(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   )   )

    # sort with class names
					return sorted(_SCREAMING_SNAKE_CASE						,      key=lambda _SCREAMING_SNAKE_CASE   : x.__name__   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Tuple   ):
					__a			:       Any					    =  []
					__a			:       str					    =  get_test_module(_SCREAMING_SNAKE_CASE   )
					for attr in dir(_SCREAMING_SNAKE_CASE   ):
										__a			:       int					    =  getattr(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   )
										# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
										# `all_model_classes` is not empty (which also excludes other special classes).
										__a			:       Optional[Any]					    =  getattr(_SCREAMING_SNAKE_CASE						,      'all_model_classes'						,      []   )
										if len(_SCREAMING_SNAKE_CASE   ) > 0:
															test_classes.append(_SCREAMING_SNAKE_CASE   )

    # sort with class names
					return sorted(_SCREAMING_SNAKE_CASE						,      key=lambda _SCREAMING_SNAKE_CASE   : x.__name__   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   int   ):
					__a			:       str					    =  get_test_classes(_SCREAMING_SNAKE_CASE   )
					__a			:       Any					    =  set()
					for test_class in test_classes:
										model_classes.update(test_class.all_model_classes   )

					# sort with class names
					return sorted(_SCREAMING_SNAKE_CASE						,      key=lambda _SCREAMING_SNAKE_CASE   : x.__name__   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[Any]   ):
					__a			:       Tuple					    =  test_class()
					if hasattr(_SCREAMING_SNAKE_CASE						,      'setUp'   ):
										test.setUp()

					__a			:       List[Any]					    =  None
					if hasattr(_SCREAMING_SNAKE_CASE						,      'model_tester'   ):
										# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
										if test.model_tester is not None:
															__a			:       List[str]					    =  test.model_tester.__class__

					return model_tester






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   int						,      _SCREAMING_SNAKE_CASE      :   Optional[Any]   ):
					__a			:       str					    =  get_test_classes(_SCREAMING_SNAKE_CASE   )

					__a			:       int					    =  []
					for test_class in test_classes:
										if model_class in test_class.all_model_classes:
															target_test_classes.append(_SCREAMING_SNAKE_CASE   )

    # sort with class names
					return sorted(_SCREAMING_SNAKE_CASE						,      key=lambda _SCREAMING_SNAKE_CASE   : x.__name__   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Tuple						,      _SCREAMING_SNAKE_CASE      :   List[str]   ):
					__a			:       List[Any]					    =  get_test_classes_for_model(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   )

					__a			:       Any					    =  []
					for test_class in test_classes:
										__a			:       Any					    =  get_model_tester_from_test_class(_SCREAMING_SNAKE_CASE   )
										if tester_class is not None:
															tester_classes.append(_SCREAMING_SNAKE_CASE   )

    # sort with class names
					return sorted(_SCREAMING_SNAKE_CASE						,      key=lambda _SCREAMING_SNAKE_CASE   : x.__name__   )






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Optional[int]   ):
					__a			:       str					    =  get_test_classes(_SCREAMING_SNAKE_CASE   )
					__a			:       int					    =  {test_class: get_model_tester_from_test_class(_SCREAMING_SNAKE_CASE   ) for test_class in test_classes}
					return test_tester_mapping






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[str]   ):
					__a			:       Optional[Any]					    =  get_model_classes(_SCREAMING_SNAKE_CASE   )
					__a			:       Optional[int]					    =  {
					    model_class: get_test_classes_for_model(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ) for model_class in model_classes
					}
					return model_test_mapping






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[str]   ):
					__a			:       Optional[Any]					    =  get_model_classes(_SCREAMING_SNAKE_CASE   )
					__a			:       str					    =  {
					    model_class: get_tester_classes_for_model(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ) for model_class in model_classes
					}
					return model_to_tester_mapping






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   str   ):
					if isinstance(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ):
										return o
					elif isinstance(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ):
										return o.__name__
					elif isinstance(_SCREAMING_SNAKE_CASE						,      (list, tuple)   ):
										return [to_json(_SCREAMING_SNAKE_CASE   ) for x in o]
					elif isinstance(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   ):
										return {to_json(_SCREAMING_SNAKE_CASE   ): to_json(_SCREAMING_SNAKE_CASE   ) for k, v in o.items()}
					else:
										return o



