
'''simple docstring'''


import sys
from pathlib import Path


lowerCAmelCase__						:       List[Any]										=						Path(__file__).resolve().parents[3] / """src"""
sys.path.insert(1, str(git_repo_path))

import dataclasses  # noqa
import io  # noqa
import itertools  # noqa
import json  # noqa
import os  # noqa
import unittest  # noqa
from copy import deepcopy  # noqa

from parameterized import parameterized  # noqa
from transformers import TrainingArguments, is_torch_available  # noqa
from transformers.deepspeed import is_deepspeed_available  # noqa
from transformers.file_utils import WEIGHTS_NAME  # noqa
from transformers.testing_utils import (  # noqa
    CaptureLogger,
    ExtendSysPath,
    TestCasePlus,
    execute_subprocess_async,
    get_gpu_count,
    mockenv_context,
    require_deepspeed,
    require_torch_gpu,
    require_torch_multi_gpu,
    slow,
)
from transformers.trainer_utils import set_seed  # noqa


set_seed(42)

lowerCAmelCase__						:       Dict										=						{"""base""": """patrickvonplaten/wav2vec2_tiny_random""", """robust""": """patrickvonplaten/wav2vec2_tiny_random_robust"""}

lowerCAmelCase__						:       Dict										=						"""zero2"""
lowerCAmelCase__						:       Any										=						"""zero3"""
lowerCAmelCase__						:       Optional[Any]										=						[ZEROa, ZEROa]




def 	_a       (				__lowerCAmelCase		:      Any   ,							__lowerCAmelCase		:      str   ,							__lowerCAmelCase		:      Optional[Any]     ):

		"""simple docstring"""

		snake_case__						:       int       						=  parameterized.to_safe_name('''_'''.join(str(__lowerCAmelCase     ) for x in param.args     )     )
		return F"""{func.__name__}_{param_based_name}"""


# Cartesian-product of zero stages with models to test
lowerCAmelCase__						:       List[Any]										=						list(itertools.product(stages, models.keys()))





@slow
@require_deepspeed
@require_torch_gpu
class     a			(				SCREAMING_SNAKE_CASE       ):






						"""simple docstring"""




						@parameterized.expand(snake_case_			,			name_func=snake_case_  )
						def       __magic_name__							(							self					:      Union[str, Any]			,			snake_case_					:      Optional[Any]			,			snake_case_					:      Tuple  ):



								'''simple docstring'''



								self.run_and_check(
								    stage=snake_case_			,			model=snake_case_			,			distributed=snake_case_			,			fpaa=snake_case_			,			)







						@require_torch_multi_gpu
						@parameterized.expand(snake_case_			,			name_func=snake_case_  )
						def       __magic_name__							(							self					:      str			,			snake_case_					:      Union[str, Any]			,			snake_case_					:      List[str]  ):



								'''simple docstring'''



								self.run_and_check(
								    stage=snake_case_			,			model=snake_case_			,			distributed=snake_case_			,			fpaa=snake_case_			,			)







						@parameterized.expand(snake_case_			,			name_func=snake_case_  )
						def       __magic_name__							(							self					:      Optional[Any]			,			snake_case_					:      int			,			snake_case_					:      Union[str, Any]  ):



								'''simple docstring'''



								self.run_and_check(
								    stage=snake_case_			,			model=snake_case_			,			distributed=snake_case_			,			fpaa=snake_case_			,			)







						@require_torch_multi_gpu
						@parameterized.expand(snake_case_			,			name_func=snake_case_  )
						def       __magic_name__							(							self					:      Tuple			,			snake_case_					:      Dict			,			snake_case_					:      List[Any]  ):



								'''simple docstring'''



								self.run_and_check(
								    stage=snake_case_			,			model=snake_case_			,			distributed=snake_case_			,			fpaa=snake_case_			,			)







						def       __magic_name__							(							self					:      Any			,			snake_case_					:      List[str]  ):



								'''simple docstring'''



								pass







						def       __magic_name__							(							self					:      Union[str, Any]			,			snake_case_					:      str			,			snake_case_					:      str			,			snake_case_					:      int = 1_0			,			snake_case_					:      bool = True			,			snake_case_					:      bool = True			,			snake_case_					:      bool = True			,			):



								'''simple docstring'''



								snake_case__						:       Tuple       						=  models[model]

								snake_case__						:       Any       						=  self.run_trainer(
								    stage=snake_case_			,			model_name=snake_case_			,			eval_steps=snake_case_			,			num_train_epochs=1			,			distributed=snake_case_			,			fpaa=snake_case_			,			)

								self.do_checks(snake_case_  )

								return output_dir







						def       __magic_name__							(							self					:      Any			,			snake_case_					:      str			,			snake_case_					:      str			,			snake_case_					:      int = 1_0			,			snake_case_					:      int = 1			,			snake_case_					:      bool = True			,			snake_case_					:      bool = True			,			):



								'''simple docstring'''



								snake_case__						:       str       						=  self.get_auto_remove_tmp_dir('''./xxx'''			,			after=snake_case_  )
								snake_case__						:       List[Any]       						=  F"""
            --model_name_or_path {model_name}
            --dataset_name hf-internal-testing/librispeech_asr_dummy
            --dataset_config_name clean
            --train_split_name validation
            --validation_split_name validation
            --output_dir {output_dir}
            --num_train_epochs {str(snake_case_  )}
            --per_device_train_batch_size 2
            --per_device_eval_batch_size 2
            --evaluation_strategy steps
            --learning_rate 5e-4
            --warmup_steps 8
            --orthography timit
            --preprocessing_num_workers 1
            --group_by_length
            --freeze_feature_extractor
            --report_to none
            --save_steps 0
            --eval_steps {eval_steps}
            --report_to none
        """.split()

								if fpaa:
										args.extend(['''--fp16''']  )

								# currently ds_config_wav2vec2_zero.json requires "zero_optimization.find_unused_parameters": true,
								# hence the separate config files
								snake_case__						:       Optional[Any]       						=  F"""--deepspeed {self.test_file_dir_str}/ds_config_wav2vec2_{stage}.json""".split()
								snake_case__						:       Dict       						=  [F"""{self.examples_dir_str}/research_projects/wav2vec2/run_asr.py"""]
								snake_case__						:       List[Any]       						=  self.get_launcher(snake_case_  )

								snake_case__						:       str       						=  launcher + script + args + ds_args
								# keep for quick debug
								# print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] +cmd)); die
								execute_subprocess_async(snake_case_			,			env=self.get_env()  )

								return output_dir







						def       __magic_name__							(							self					:      int			,			snake_case_					:      str=False  ):



								'''simple docstring'''



								snake_case__						:       Union[str, Any]       						=  min(2			,			get_gpu_count()  ) if distributed else 1
								return F"""deepspeed --num_nodes 1 --num_gpus {num_gpus}""".split()






'''simple docstring'''


from __future__ import annotations

from typing import Any




class     a			:






						"""simple docstring"""




						def __init__(							self					:      Tuple			,			snake_case_					:      int			,			snake_case_					:      int			,			snake_case_					:      float = 0  ):



								'''simple docstring'''



								snake_case__						,       snake_case__						:       Optional[Any]       						=  row, column
								snake_case__						:       Dict       						=  [[default_value for c in range(snake_case_  )] for r in range(snake_case_  )]







						def __str__(							self					:      Optional[Any]  ):



								'''simple docstring'''



								snake_case__						:       Optional[int]       						=  F"""Matrix consist of {self.row} rows and {self.column} columns\n"""

								# Make string identifier
								snake_case__						:       List[str]       						=  0
								for row_vector in self.array:
										for obj in row_vector:
												snake_case__						:       str       						=  max(snake_case_			,			len(str(snake_case_  )  )  )
								snake_case__						:       Dict       						=  F"""%{max_element_length}s"""

								# Make string and return
								def single_line(snake_case_					:      list[float]  ) -> str:
										nonlocal string_format_identifier
										snake_case__						:       str       						=  '''['''
										line += ", ".join(string_format_identifier % (obj,) for obj in row_vector  )
										line += "]"
										return line

								s += "\n".join(single_line(snake_case_  ) for row_vector in self.array  )
								return s







						def __repr__(							self					:      Optional[int]  ):



								'''simple docstring'''



								return str(self  )







						def       __magic_name__							(							self					:      Optional[int]			,			snake_case_					:      tuple[int, int]  ):



								'''simple docstring'''



								if not (isinstance(snake_case_			,			(list, tuple)  ) and len(snake_case_  ) == 2):
										return False
								elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
										return False
								else:
										return True







						def __getitem__(							self					:      List[str]			,			snake_case_					:      tuple[int, int]  ):



								'''simple docstring'''



								assert self.validate_indicies(snake_case_  )
								return self.array[loc[0]][loc[1]]







						def __setitem__(							self					:      int			,			snake_case_					:      tuple[int, int]			,			snake_case_					:      float  ):



								'''simple docstring'''



								assert self.validate_indicies(snake_case_  )
								snake_case__						:       Optional[Any]       						=  value







						def __add__(							self					:      Dict			,			snake_case_					:      Matrix  ):



								'''simple docstring'''



								assert isinstance(snake_case_			,			snake_case_  )
								assert self.row == another.row and self.column == another.column

								# Add
								snake_case__						:       str       						=  Matrix(self.row			,			self.column  )
								for r in range(self.row  ):
										for c in range(self.column  ):
												snake_case__						:       Optional[Any]       						=  self[r, c] + another[r, c]
								return result







						def __neg__(							self					:      Optional[Any]  ):



								'''simple docstring'''



								snake_case__						:       int       						=  Matrix(self.row			,			self.column  )
								for r in range(self.row  ):
										for c in range(self.column  ):
												snake_case__						:       str       						=  -self[r, c]
								return result







						def __sub__(							self					:      Optional[int]			,			snake_case_					:      Matrix  ):



								'''simple docstring'''



								return self + (-another)







						def __mul__(							self					:      int			,			snake_case_					:      int | float | Matrix  ):



								'''simple docstring'''



								if isinstance(snake_case_			,			(int, float)  ):  # Scalar multiplication
										snake_case__						:       Dict       						=  Matrix(self.row			,			self.column  )
										for r in range(self.row  ):
												for c in range(self.column  ):
														snake_case__						:       Tuple       						=  self[r, c] * another
										return result
								elif isinstance(snake_case_			,			snake_case_  ):  # Matrix multiplication
										assert self.column == another.row
										snake_case__						:       List[Any]       						=  Matrix(self.row			,			another.column  )
										for r in range(self.row  ):
												for c in range(another.column  ):
														for i in range(self.column  ):
																result[r, c] += self[r, i] * another[i, c]
										return result
								else:
										snake_case__						:       Union[str, Any]       						=  F"""Unsupported type given for another ({type(snake_case_  )})"""
										raise TypeError(snake_case_  )







						def       __magic_name__							(							self					:      List[str]  ):



								'''simple docstring'''



								snake_case__						:       Optional[int]       						=  Matrix(self.column			,			self.row  )
								for r in range(self.row  ):
										for c in range(self.column  ):
												snake_case__						:       List[Any]       						=  self[r, c]
								return result







						def       __magic_name__							(							self					:      Tuple			,			snake_case_					:      Matrix			,			snake_case_					:      Matrix  ):



								'''simple docstring'''



								assert isinstance(snake_case_			,			snake_case_  ) and isinstance(snake_case_			,			snake_case_  )
								assert self.row == self.column == u.row == v.row  # u, v should be column vector
								assert u.column == v.column == 1  # u, v should be column vector

								# Calculate
								snake_case__						:       Tuple       						=  v.transpose()
								snake_case__						:       Optional[Any]       						=  (v_t * self * u)[0, 0] + 1
								if numerator_factor == 0:
										return None  # It's not invertable
								return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":




					def 	_a       (				):

							"""simple docstring"""

							snake_case__						:       Tuple       						=  Matrix(3   ,							3   ,							0     )
							for i in range(3     ):
									snake_case__						:       Any       						=  1
							print(F"""a^(-1) is {ainv}"""     )
							# u, v
							snake_case__						:       int       						=  Matrix(3   ,							1   ,							0     )
							snake_case__						,       snake_case__						,       snake_case__						:       List[Any]       						=  1, 2, -3
							snake_case__						:       Any       						=  Matrix(3   ,							1   ,							0     )
							snake_case__						,       snake_case__						,       snake_case__						:       Optional[int]       						=  4, -2, 5
							print(F"""u is {u}"""     )
							print(F"""v is {v}"""     )
							print(F"""uv^T is {u * v.transpose()}"""     )
							# Sherman Morrison
							print(F"""(a + uv^T)^(-1) is {ainv.sherman_morrison(__lowerCAmelCase   ,							__lowerCAmelCase     )}"""     )




					def 	_a       (				):

							"""simple docstring"""

							import doctest

							doctest.testmod()





					testa()



