# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path


__lowercase											=      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)

__lowercase											=      {'''base''': '''patrickvonplaten/wav2vec2_tiny_random''', '''robust''': '''patrickvonplaten/wav2vec2_tiny_random_robust'''}

__lowercase											=      '''zero2'''
__lowercase											=      '''zero3'''
__lowercase											=      [ZEROa, ZEROa]



def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    __UpperCamelCase  :str    						=	parameterized.to_safe_name('''_'''.join(str(SCREAMING_SNAKE_CASE			) for x in param.args			)			)
    return f"""{func.__name__}_{param_based_name}"""


# Cartesian-product of zero stages with models to test
__lowercase											=      list(itertools.product(stages, models.keys()))


@slow
@require_deepspeed
@require_torch_gpu
class 			lowerCamelCase_  (     UpperCAmelCase_				):






    '''simple docstring'''






    @parameterized.expand(__lowercase				,				name_func=__lowercase)
    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase) ->			str:
        self.run_and_check(
            stage=__lowercase				,				model=__lowercase				,				distributed=__lowercase				,				fpaa=__lowercase				,				)







    @require_torch_multi_gpu
    @parameterized.expand(__lowercase				,				name_func=__lowercase)
    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase) ->			Dict:
        self.run_and_check(
            stage=__lowercase				,				model=__lowercase				,				distributed=__lowercase				,				fpaa=__lowercase				,				)







    @parameterized.expand(__lowercase				,				name_func=__lowercase)
    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase) ->			Optional[int]:
        self.run_and_check(
            stage=__lowercase				,				model=__lowercase				,				distributed=__lowercase				,				fpaa=__lowercase				,				)







    @require_torch_multi_gpu
    @parameterized.expand(__lowercase				,				name_func=__lowercase)
    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase) ->			Optional[int]:
        self.run_and_check(
            stage=__lowercase				,				model=__lowercase				,				distributed=__lowercase				,				fpaa=__lowercase				,				)







    def     UpperCamelCase__     (			self				,				__lowercase) ->			Union[str, Any]:
        # XXX: run_asr is premature and doesn't save any results
        # so all we check for now is that the process didn't fail
        pass







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase				,				__lowercase = 10				,				__lowercase = True				,				__lowercase = True				,				__lowercase = True				,				) ->			List[Any]:
        __UpperCamelCase  :Optional[int]    						=	models[model]

        __UpperCamelCase  :int    						=	self.run_trainer(
            stage=__lowercase				,				model_name=__lowercase				,				eval_steps=__lowercase				,				num_train_epochs=1				,				distributed=__lowercase				,				fpaa=__lowercase				,				)

        self.do_checks(__lowercase)

        return output_dir







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase				,				__lowercase = 10				,				__lowercase = 1				,				__lowercase = True				,				__lowercase = True				,				) ->			List[Any]:
        __UpperCamelCase  :Optional[int]    						=	self.get_auto_remove_tmp_dir('''./xxx'''				,				after=__lowercase)
        __UpperCamelCase  :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(__lowercase)}
            --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
        __UpperCamelCase  :Optional[Any]    						=	f"""--deepspeed {self.test_file_dir_str}/ds_config_wav2vec2_{stage}.json""".split()
        __UpperCamelCase  :Optional[Any]    						=	[f"""{self.examples_dir_str}/research_projects/wav2vec2/run_asr.py"""]
        __UpperCamelCase  :Any    						=	self.get_launcher(__lowercase)

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

        return output_dir







    def     UpperCamelCase__     (			self				,				__lowercase=False) ->			str:
        # 1. explicitly set --num_nodes=1 just in case these tests end up run on a multi-node setup
        # - it won't be able to handle that
        # 2. for now testing with just 2 gpus max (since some quality tests may give different
        # results with mode gpus because we use very little data)
        __UpperCamelCase  :Any    						=	min(2				,				get_gpu_count()) if distributed else 1
        return f"""deepspeed --num_nodes 1 --num_gpus {num_gpus}""".split()






def lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    return 1 if input_a == input_a else 0



def lowerCamelCase						(     ):
    '''simple docstring'''







    assert xnor_gate(0						,    0			) == 1
    assert xnor_gate(0						,    1			) == 0
    assert xnor_gate(1						,    0			) == 0
    assert xnor_gate(1						,    1			) == 1


if __name__ == "__main__":
    print(xnor_gate(0, 0))
    print(xnor_gate(0, 1))
    print(xnor_gate(1, 0))
    print(xnor_gate(1, 1))





