



import argparse
import json
import logging
import os
import sys
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


UpperCAmelCase_									=							[
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        "text-classification",
        "language-modeling",
        "summarization",
        "token-classification",
        "question-answering",
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
    import run_clm_flax
    import run_flax_glue
    import run_flax_ner
    import run_mlm_flax
    import run_qa
    import run_summarization_flax
    import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

UpperCAmelCase_									=							logging.getLogger()
def 							UpperCAmelCase__		(				)->Optional[int]:
      _lowerCAmelCase 			=  argparse.ArgumentParser()
      parser.add_argument('''-f'''				)
      _lowerCAmelCase 			=  parser.parse_args()
      return args.f
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	List[Any]     ,				_SCREAMING_SNAKE_CASE   :	str="eval"				)->str:
      _lowerCAmelCase 			=  os.path.join(_SCREAMING_SNAKE_CASE     ,				f'''{split}_results.json'''				)
      if os.path.exists(_SCREAMING_SNAKE_CASE				):
            with open(_SCREAMING_SNAKE_CASE     ,				'''r'''				) as f:
                  return json.load(_SCREAMING_SNAKE_CASE				)
      raise ValueError(f'''can\'t find {path}'''				)


UpperCAmelCase_									=							logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)





class 		UpperCAmelCase						(						snake_case_				):

   '''simple docstring'''





   def 	__lowerCAmelCase							(	self			):
         _lowerCAmelCase 			=  self.get_auto_remove_tmp_dir()
         _lowerCAmelCase 			=  F'''\n            run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --eval_steps=2\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            '''.split()

         with patch.object(__UpperCamelCase       ,     '''argv'''       ,     __UpperCamelCase			):
               run_flax_glue.main()
               _lowerCAmelCase 			=  get_results(__UpperCamelCase			)
               self.assertGreaterEqual(result['''eval_accuracy''']       ,     0.75			)





   @slow
   def 	__lowerCAmelCase							(	self			):
         _lowerCAmelCase 			=  self.get_auto_remove_tmp_dir()
         _lowerCAmelCase 			=  F'''\n            run_clm_flax.py\n            --model_name_or_path distilgpt2\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --block_size 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '''.split()

         with patch.object(__UpperCamelCase       ,     '''argv'''       ,     __UpperCamelCase			):
               run_clm_flax.main()
               _lowerCAmelCase 			=  get_results(__UpperCamelCase			)
               self.assertLess(result['''eval_perplexity''']       ,     100			)





   @slow
   def 	__lowerCAmelCase							(	self			):
         _lowerCAmelCase 			=  self.get_auto_remove_tmp_dir()
         _lowerCAmelCase 			=  F'''\n            run_summarization.py\n            --model_name_or_path t5-small\n            --train_file tests/fixtures/tests_samples/xsum/sample.json\n            --validation_file tests/fixtures/tests_samples/xsum/sample.json\n            --test_file tests/fixtures/tests_samples/xsum/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=8\n            --do_train\n            --do_eval\n            --do_predict\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --predict_with_generate\n        '''.split()

         with patch.object(__UpperCamelCase       ,     '''argv'''       ,     __UpperCamelCase			):
               run_summarization_flax.main()
               _lowerCAmelCase 			=  get_results(__UpperCamelCase       ,     split='''test'''			)
               self.assertGreaterEqual(result['''test_rouge1''']       ,     10			)
               self.assertGreaterEqual(result['''test_rouge2''']       ,     2			)
               self.assertGreaterEqual(result['''test_rougeL''']       ,     7			)
               self.assertGreaterEqual(result['''test_rougeLsum''']       ,     7			)





   @slow
   def 	__lowerCAmelCase							(	self			):
         _lowerCAmelCase 			=  self.get_auto_remove_tmp_dir()
         _lowerCAmelCase 			=  F'''\n            run_mlm.py\n            --model_name_or_path distilroberta-base\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --logging_steps 2 --eval_steps 2\n            --do_train\n            --do_eval\n            --num_train_epochs=1\n        '''.split()

         with patch.object(__UpperCamelCase       ,     '''argv'''       ,     __UpperCamelCase			):
               run_mlm_flax.main()
               _lowerCAmelCase 			=  get_results(__UpperCamelCase			)
               self.assertLess(result['''eval_perplexity''']       ,     42			)





   @slow
   def 	__lowerCAmelCase							(	self			):
         _lowerCAmelCase 			=  self.get_auto_remove_tmp_dir()
         _lowerCAmelCase 			=  F'''\n            run_t5_mlm_flax.py\n            --model_name_or_path t5-small\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '''.split()

         with patch.object(__UpperCamelCase       ,     '''argv'''       ,     __UpperCamelCase			):
               run_ta_mlm_flax.main()
               _lowerCAmelCase 			=  get_results(__UpperCamelCase			)
               self.assertGreaterEqual(result['''eval_accuracy''']       ,     0.42			)





   @slow
   def 	__lowerCAmelCase							(	self			):
         # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
         _lowerCAmelCase 			=  7 if get_gpu_count() > 1 else 2

         _lowerCAmelCase 			=  self.get_auto_remove_tmp_dir()
         _lowerCAmelCase 			=  F'''\n            run_flax_ner.py\n            --model_name_or_path bert-base-uncased\n            --train_file tests/fixtures/tests_samples/conll/sample.json\n            --validation_file tests/fixtures/tests_samples/conll/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --do_train\n            --do_eval\n            --warmup_steps=2\n            --learning_rate=2e-4\n            --logging_steps 2 --eval_steps 2\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=2\n            --num_train_epochs={epochs}\n            --seed 7\n        '''.split()

         with patch.object(__UpperCamelCase       ,     '''argv'''       ,     __UpperCamelCase			):
               run_flax_ner.main()
               _lowerCAmelCase 			=  get_results(__UpperCamelCase			)
               self.assertGreaterEqual(result['''eval_accuracy''']       ,     0.75			)
               self.assertGreaterEqual(result['''eval_f1''']       ,     0.3			)





   @slow
   def 	__lowerCAmelCase							(	self			):
         _lowerCAmelCase 			=  self.get_auto_remove_tmp_dir()
         _lowerCAmelCase 			=  F'''\n            run_qa.py\n            --model_name_or_path bert-base-uncased\n            --version_2_with_negative\n            --train_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=2\n            --do_train\n            --do_eval\n            --logging_steps 2 --eval_steps 2\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n        '''.split()

         with patch.object(__UpperCamelCase       ,     '''argv'''       ,     __UpperCamelCase			):
               run_qa.main()
               _lowerCAmelCase 			=  get_results(__UpperCamelCase			)
               self.assertGreaterEqual(result['''eval_f1''']       ,     30			)
               self.assertGreaterEqual(result['''eval_exact''']       ,     30			)




# Copyright 2021 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 argparse
import os

from accelerate.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


UpperCAmelCase_									=							"Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine"
def 							UpperCAmelCase__		(				)->Any:
      _lowerCAmelCase 			=  _ask_options(
          '''In which compute environment are you running?'''     ,				['''This machine''', '''AWS (Amazon SageMaker)''']     ,				_convert_compute_environment     ,				)
      if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
            _lowerCAmelCase 			=  get_sagemaker_input()
      else:
            _lowerCAmelCase 			=  get_cluster_input()
      return config
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	int=None				)->str:
      if subparsers is not None:
            _lowerCAmelCase 			=  subparsers.add_parser('''config'''     ,				description=_SCREAMING_SNAKE_CASE				)
      else:
            _lowerCAmelCase 			=  argparse.ArgumentParser('''Accelerate config command'''     ,				description=_SCREAMING_SNAKE_CASE				)

      parser.add_argument(
          '''--config_file'''     ,				default=_SCREAMING_SNAKE_CASE     ,				help=(
              '''The path to use to store the config file. Will default to a file named default_config.yaml in the cache '''
              '''location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '''
              '''such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '''
              '''with \'huggingface\'.'''
          )     ,				)

      if subparsers is not None:
            parser.set_defaults(func=_SCREAMING_SNAKE_CASE				)
      return parser
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Dict				)->str:
      _lowerCAmelCase 			=  get_user_input()
      if args.config_file is not None:
            _lowerCAmelCase 			=  args.config_file
      else:
            if not os.path.isdir(_SCREAMING_SNAKE_CASE				):
                  os.makedirs(_SCREAMING_SNAKE_CASE				)
            _lowerCAmelCase 			=  default_yaml_config_file

      if config_file.endswith('''.json'''				):
            config.to_json_file(_SCREAMING_SNAKE_CASE				)
      else:
            config.to_yaml_file(_SCREAMING_SNAKE_CASE				)
      print(f'''accelerate configuration saved at {config_file}'''				)
def 							UpperCAmelCase__		(				)->List[Any]:
      _lowerCAmelCase 			=  config_command_parser()
      _lowerCAmelCase 			=  parser.parse_args()
      config_command(_SCREAMING_SNAKE_CASE				)


if __name__ == "__main__":
    main()