



"""simple docstring"""





import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock

import torch

from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import write_basic_config


# DataLoaders built from `test_samples/MRPC` for quick testing
# Should mock `{script_name}.get_dataloaders` via:
# @mock.patch("{script_name}.get_dataloaders", mocked_dataloaders)

lowerCamelCase      =		[
    '''cross_validation.py''',
    '''gradient_accumulation.py''',
    '''local_sgd.py''',
    '''multi_process_metrics.py''',
    '''memory.py''',
    '''automatic_gradient_accumulation.py''',
    '''fsdp_with_peak_mem_tracking.py''',
    '''deepspeed_with_config_support.py''',
    '''megatron_lm_gpt_pretraining.py''',
]
class    lowercase__     (					unittest.TestCase   ):







       '''simple docstring'''


       def   lowercase__       (							self    :						Tuple	,       _UpperCAmelCase    :						str	,       _UpperCAmelCase    :						bool	,       _UpperCAmelCase    :						str = None	,       _UpperCAmelCase    :						list = None					)				->		Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_    				=							None
             UpperCAmelCase_    				=							os.path.abspath(os.path.join("examples"	,       "by_feature"					)					)
             UpperCAmelCase_    				=							os.path.abspath("examples"					)
             for item in os.listdir(UpperCamelCase_					):
                   if item not in EXCLUDE_EXAMPLES:
                         UpperCAmelCase_    				=							os.path.join(UpperCamelCase_	,       UpperCamelCase_					)
                         if os.path.isfile(UpperCamelCase_					) and ".py" in item_path:
                               with self.subTest(
                                   tested_script=UpperCamelCase_	,       feature_script=UpperCamelCase_	,       tested_section="main()" if parser_only else "training_function()"	,       ):
                                     UpperCAmelCase_    				=							compare_against_test(
                                         os.path.join(UpperCamelCase_	,       UpperCamelCase_					)	,       UpperCamelCase_	,       UpperCamelCase_	,       UpperCamelCase_					)
                                     UpperCAmelCase_    				=							'\n'.join(UpperCamelCase_					)
                                     if special_strings is not None:
                                           for string in special_strings:
                                                 UpperCAmelCase_    				=							diff.replace(UpperCamelCase_	,       ""					)
                                     self.assertEqual(UpperCamelCase_	,       ""					)



       def   lowercase__       (							self    :						List[str]					)				->		Any:


             '''simple docstring'''




             self.one_complete_example("complete_nlp_example.py"	,       UpperCamelCase_					)
             self.one_complete_example("complete_nlp_example.py"	,       UpperCamelCase_					)







       def   lowercase__       (							self    :						List[str]					)				->		int:


             '''simple docstring'''




             UpperCAmelCase_    				=							os.path.abspath(os.path.join("examples"	,       "cv_example.py"					)					)
             UpperCAmelCase_    				=							[
                 ' ' * 16 + '{\n\n',
                 ' ' * 20 + '"accuracy": eval_metric["accuracy"],\n\n',
                 ' ' * 20 + '"f1": eval_metric["f1"],\n\n',
                 ' ' * 20 + '"train_loss": total_loss.item() / len(train_dataloader),\n\n',
                 ' ' * 20 + '"epoch": epoch,\n\n',
                 ' ' * 16 + '},\n\n',
                 ' ' * 16 + 'step=epoch,\n',
                 ' ' * 12,
                 ' ' * 8 + 'for step, batch in enumerate(active_dataloader):\n',
             ]
             self.one_complete_example("complete_cv_example.py"	,       UpperCamelCase_	,       UpperCamelCase_	,       UpperCamelCase_					)
             self.one_complete_example("complete_cv_example.py"	,       UpperCamelCase_	,       UpperCamelCase_	,       UpperCamelCase_					)



@mock.patch.dict(os.environ       ,      {'''TESTING_MOCKED_DATALOADERS''': '''1'''}   )
class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       UpperCamelCase		=  False



       @classmethod
       def   lowercase__       (							cls    :						Optional[int]					)				->		Tuple:


             '''simple docstring'''




             super().setUpClass()
             UpperCAmelCase_    				=							tempfile.mkdtemp()
             UpperCAmelCase_    				=							os.path.join(cls._tmpdir	,       "default_config.yml"					)

             write_basic_config(save_location=cls.configPath					)
             UpperCAmelCase_    				=							['accelerate', 'launch', '--config_file', cls.configPath]



       @classmethod
       def   lowercase__       (							cls    :						List[Any]					)				->		Any:


             '''simple docstring'''




             super().tearDownClass()
             shutil.rmtree(cls._tmpdir					)



       def   lowercase__       (							self    :						str					)				->		List[Any]:


             '''simple docstring'''




             UpperCAmelCase_    				=							F"""
        examples/by_feature/checkpointing.py
        --checkpointing_steps epoch
        --output_dir {self.tmpdir}
        """.split()
             run_command(self._launch_args + testargs					)
             self.assertTrue(os.path.exists(os.path.join(self.tmpdir	,       "epoch_0"					)					)					)



       def   lowercase__       (							self    :						str					)				->		str:


             '''simple docstring'''




             UpperCAmelCase_    				=							F"""
        examples/by_feature/checkpointing.py
        --checkpointing_steps 1
        --output_dir {self.tmpdir}
        """.split()
             UpperCAmelCase_    				=							run_command(self._launch_args + testargs					)
             self.assertTrue(os.path.exists(os.path.join(self.tmpdir	,       "step_2"					)					)					)



       def   lowercase__       (							self    :						Any					)				->		List[str]:


             '''simple docstring'''




             UpperCAmelCase_    				=							F"""
        examples/by_feature/checkpointing.py
        --resume_from_checkpoint {os.path.join(self.tmpdir	,       'epoch_0'					)}
        """.split()
             UpperCAmelCase_    				=							run_command(self._launch_args + testargs	,       return_stdout=UpperCamelCase_					)
             self.assertNotIn("epoch 0:"	,       UpperCamelCase_					)
             self.assertIn("epoch 1:"	,       UpperCamelCase_					)



       def   lowercase__       (							self    :						List[str]					)				->		Tuple:


             '''simple docstring'''




             UpperCAmelCase_    				=							F"""
        examples/by_feature/checkpointing.py
        --resume_from_checkpoint {os.path.join(self.tmpdir	,       'step_2'					)}
        """.split()
             UpperCAmelCase_    				=							run_command(self._launch_args + testargs	,       return_stdout=UpperCamelCase_					)
             if torch.cuda.is_available():
                   UpperCAmelCase_    				=							torch.cuda.device_count()
             else:
                   UpperCAmelCase_    				=							1
             if num_processes > 1:
                   self.assertNotIn("epoch 0:"	,       UpperCamelCase_					)
                   self.assertIn("epoch 1:"	,       UpperCamelCase_					)
             else:
                   self.assertIn("epoch 0:"	,       UpperCamelCase_					)
                   self.assertIn("epoch 1:"	,       UpperCamelCase_					)



       @slow
       def   lowercase__       (							self    :						List[str]					)				->		int:


             '''simple docstring'''




             UpperCAmelCase_    				=							'\n        examples/by_feature/cross_validation.py\n        --num_folds 2\n        '.split()
             with mock.patch.dict(os.environ	,       {"TESTING_MOCKED_DATALOADERS": "0"}					):
                   UpperCAmelCase_    				=							run_command(self._launch_args + testargs	,       return_stdout=UpperCamelCase_					)
                   UpperCAmelCase_    				=							re.findall("({.+})"	,       UpperCamelCase_					)
                   UpperCAmelCase_    				=							[r for r in results if 'accuracy' in r][-1]
                   UpperCAmelCase_    				=							ast.literal_eval(UpperCamelCase_					)
                   self.assertGreaterEqual(results["accuracy"]	,       0.75					)



       def   lowercase__       (							self    :						List[Any]					)				->		str:


             '''simple docstring'''




             UpperCAmelCase_    				=							['examples/by_feature/multi_process_metrics.py']
             run_command(self._launch_args + testargs					)



       @require_trackers
       @mock.patch.dict(os.environ	,       {"WANDB_MODE": "offline"}					)
       def   lowercase__       (							self    :						Dict					)				->		Dict:


             '''simple docstring'''




             with tempfile.TemporaryDirectory() as tmpdir:
                   UpperCAmelCase_    				=							F"""
            examples/by_feature/tracking.py
            --with_tracking
            --project_dir {tmpdir}
            """.split()
                   run_command(self._launch_args + testargs					)
                   self.assertTrue(os.path.exists(os.path.join(UpperCamelCase_	,       "tracking"					)					)					)



       def   lowercase__       (							self    :						Union[str, Any]					)				->		Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_    				=							['examples/by_feature/gradient_accumulation.py']
             run_command(self._launch_args + testargs					)







       def   lowercase__       (							self    :						Any					)				->		Optional[Any]:


             '''simple docstring'''




             UpperCAmelCase_    				=							['examples/by_feature/local_sgd.py']
             run_command(self._launch_args + testargs					)




"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase      =		{
    """configuration_perceiver""": ["""PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PerceiverConfig""", """PerceiverOnnxConfig"""],
    """tokenization_perceiver""": ["""PerceiverTokenizer"""],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase      =		["""PerceiverFeatureExtractor"""]
  lowerCamelCase      =		["""PerceiverImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase      =		[
      """PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """PerceiverForImageClassificationConvProcessing""",
      """PerceiverForImageClassificationFourier""",
      """PerceiverForImageClassificationLearned""",
      """PerceiverForMaskedLM""",
      """PerceiverForMultimodalAutoencoding""",
      """PerceiverForOpticalFlow""",
      """PerceiverForSequenceClassification""",
      """PerceiverLayer""",
      """PerceiverModel""",
      """PerceiverPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_perceiver import PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP, PerceiverConfig, PerceiverOnnxConfig
  from .tokenization_perceiver import PerceiverTokenizer

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_perceiver import PerceiverFeatureExtractor
    from .image_processing_perceiver import PerceiverImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_perceiver import (
        PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST,
        PerceiverForImageClassificationConvProcessing,
        PerceiverForImageClassificationFourier,
        PerceiverForImageClassificationLearned,
        PerceiverForMaskedLM,
        PerceiverForMultimodalAutoencoding,
        PerceiverForOpticalFlow,
        PerceiverForSequenceClassification,
        PerceiverLayer,
        PerceiverModel,
        PerceiverPreTrainedModel,
    )

else:
  import sys

  lowerCamelCase      =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




