



"""simple docstring"""





import collections
import os
import re
from pathlib import Path


__lowerCAmelCase							:       str          =       '''src/transformers'''


# Matches is_xxx_available()
__lowerCAmelCase							:       Dict          =       re.compile(R'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
__lowerCAmelCase							:       Dict          =       re.compile(R'''^_import_structure\s+=\s+\{([^\}]+)\}''')
# Catches a line with a key-values pattern: "bla": ["foo", "bar"]
__lowerCAmelCase							:       List[str]          =       re.compile(R'''\s+"\S*":\s+\[([^\]]*)\]''')
# Catches a line if not is_foo_available
__lowerCAmelCase							:       List[str]          =       re.compile(R'''^\s*if\s+not\s+is\_[a-z_]*\_available\(\)''')
# Catches a line _import_struct["bla"].append("foo")
__lowerCAmelCase							:       int          =       re.compile(R'''^\s*_import_structure\["\S*"\]\.append\("(\S*)"\)''')
# Catches a line _import_struct["bla"].extend(["foo", "bar"]) or _import_struct["bla"] = ["foo", "bar"]
__lowerCAmelCase							:       Tuple          =       re.compile(R'''^\s*_import_structure\[\S*\](?:\.extend\(|\s*=\s+)\[([^\]]*)\]''')
# Catches a line with an object between quotes and a comma:     "MyModel",
__lowerCAmelCase							:       Dict          =       re.compile(R'''^\s+"([^"]+)",''')
# Catches a line with objects between brackets only:    ["foo", "bar"],
__lowerCAmelCase							:       Union[str, Any]          =       re.compile(R'''^\s+\[([^\]]+)\]''')
# Catches a line with from foo import bar, bla, boo
__lowerCAmelCase							:       int          =       re.compile(R'''\s+from\s+\S*\s+import\s+([^\(\s].*)\n''')
# Catches a line with try:
__lowerCAmelCase							:       Optional[int]          =       re.compile(R'''^\s*try:''')
# Catches a line with else:
__lowerCAmelCase							:       Dict          =       re.compile(R'''^\s*else:''')
def 						__lowerCAmelCase    (		__UpperCamelCase   :      List[str]     ):


						'''simple docstring'''






						if _re_test_backend.search(__UpperCamelCase     ) is None:
												return None
						snake_case_ :			Union[str, Any]            =      [b[0] for b in _re_backend.findall(__UpperCamelCase     )]
						backends.sort()
						return "_and_".join(__UpperCamelCase     )
def 						__lowerCAmelCase    (		__UpperCamelCase   :      List[str]     ):


						'''simple docstring'''






						with open(__UpperCamelCase       ,			"""r"""       ,			encoding="""utf-8"""       ,			newline="""\n"""     ) as f:
												snake_case_ :			int            =      f.readlines()

						snake_case_ :			Union[str, Any]            =      0
						while line_index < len(__UpperCamelCase     ) and not lines[line_index].startswith("""_import_structure = {"""     ):
												line_index += 1

						# If this is a traditional init, just return.
						if line_index >= len(__UpperCamelCase     ):
												return None

						# First grab the objects without a specific backend in _import_structure
						snake_case_ :			Optional[Any]            =      []
						while not lines[line_index].startswith("""if TYPE_CHECKING"""     ) and find_backend(lines[line_index]     ) is None:
												snake_case_ :			Any            =      lines[line_index]
												# If we have everything on a single line, let's deal with it.
												if _re_one_line_import_struct.search(__UpperCamelCase     ):
																		snake_case_ :			Dict            =      _re_one_line_import_struct.search(__UpperCamelCase     ).groups()[0]
																		snake_case_ :			Optional[Any]            =      re.findall(r"""\[([^\]]+)\]"""       ,			__UpperCamelCase     )
																		for imp in imports:
																								objects.extend([obj[1:-1] for obj in imp.split(""", """     )]     )
																		line_index += 1
																		continue
												snake_case_ :			int            =      _re_import_struct_key_value.search(__UpperCamelCase     )
												if single_line_import_search is not None:
																		snake_case_ :			Tuple            =      [obj[1:-1] for obj in single_line_import_search.groups()[0].split(""", """     ) if len(__UpperCamelCase     ) > 0]
																		objects.extend(__UpperCamelCase     )
												elif line.startswith(""" """ * 8 + """\""""     ):
																		objects.append(line[9:-3]     )
												line_index += 1

						snake_case_ :			int            =      {"""none""": objects}
						# Let's continue with backend-specific objects in _import_structure
						while not lines[line_index].startswith("""if TYPE_CHECKING"""     ):
												# If the line is an if not is_backend_available, we grab all objects associated.
												snake_case_ :			Optional[int]            =      find_backend(lines[line_index]     )
												# Check if the backend declaration is inside a try block:
												if _re_try.search(lines[line_index - 1]     ) is None:
																		snake_case_ :			Optional[int]            =      None

												if backend is not None:
																		line_index += 1

																		# Scroll until we hit the else block of try-except-else
																		while _re_else.search(lines[line_index]     ) is None:
																								line_index += 1

																		line_index += 1

																		snake_case_ :			Optional[int]            =      []
																		# Until we unindent, add backend objects to the list
																		while len(lines[line_index]     ) <= 1 or lines[line_index].startswith(""" """ * 4     ):
																								snake_case_ :			Tuple            =      lines[line_index]
																								if _re_import_struct_add_one.search(__UpperCamelCase     ) is not None:
																														objects.append(_re_import_struct_add_one.search(__UpperCamelCase     ).groups()[0]     )
																								elif _re_import_struct_add_many.search(__UpperCamelCase     ) is not None:
																														snake_case_ :			int            =      _re_import_struct_add_many.search(__UpperCamelCase     ).groups()[0].split(""", """     )
																														snake_case_ :			Optional[int]            =      [obj[1:-1] for obj in imports if len(__UpperCamelCase     ) > 0]
																														objects.extend(__UpperCamelCase     )
																								elif _re_between_brackets.search(__UpperCamelCase     ) is not None:
																														snake_case_ :			Optional[Any]            =      _re_between_brackets.search(__UpperCamelCase     ).groups()[0].split(""", """     )
																														snake_case_ :			Any            =      [obj[1:-1] for obj in imports if len(__UpperCamelCase     ) > 0]
																														objects.extend(__UpperCamelCase     )
																								elif _re_quote_object.search(__UpperCamelCase     ) is not None:
																														objects.append(_re_quote_object.search(__UpperCamelCase     ).groups()[0]     )
																								elif line.startswith(""" """ * 8 + """\""""     ):
																														objects.append(line[9:-3]     )
																								elif line.startswith(""" """ * 1_2 + """\""""     ):
																														objects.append(line[1_3:-3]     )
																								line_index += 1

																		snake_case_ :			List[Any]            =      objects
												else:
																		line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
						snake_case_ :			Any            =      []
						while (
						    line_index < len(__UpperCamelCase     )
						    and find_backend(lines[line_index]     ) is None
						    and not lines[line_index].startswith("""else"""     )
						):
												snake_case_ :			List[str]            =      lines[line_index]
												snake_case_ :			Optional[int]            =      _re_import.search(__UpperCamelCase     )
												if single_line_import_search is not None:
																		objects.extend(single_line_import_search.groups()[0].split(""", """     )     )
												elif line.startswith(""" """ * 8     ):
																		objects.append(line[8:-2]     )
												line_index += 1

						snake_case_ :			Optional[Any]            =      {"""none""": objects}
						# Let's continue with backend-specific objects
						while line_index < len(__UpperCamelCase     ):
												# If the line is an if is_backend_available, we grab all objects associated.
												snake_case_ :			Dict            =      find_backend(lines[line_index]     )
												# Check if the backend declaration is inside a try block:
												if _re_try.search(lines[line_index - 1]     ) is None:
																		snake_case_ :			int            =      None

												if backend is not None:
																		line_index += 1

																		# Scroll until we hit the else block of try-except-else
																		while _re_else.search(lines[line_index]     ) is None:
																								line_index += 1

																		line_index += 1

																		snake_case_ :			Optional[int]            =      []
																		# Until we unindent, add backend objects to the list
																		while len(lines[line_index]     ) <= 1 or lines[line_index].startswith(""" """ * 8     ):
																								snake_case_ :			int            =      lines[line_index]
																								snake_case_ :			List[str]            =      _re_import.search(__UpperCamelCase     )
																								if single_line_import_search is not None:
																														objects.extend(single_line_import_search.groups()[0].split(""", """     )     )
																								elif line.startswith(""" """ * 1_2     ):
																														objects.append(line[1_2:-2]     )
																								line_index += 1

																		snake_case_ :			int            =      objects
												else:
																		line_index += 1

						return import_dict_objects, type_hint_objects
def 						__lowerCAmelCase    (		__UpperCamelCase   :      List[Any]       ,			__UpperCamelCase   :      List[Any]     ):


						'''simple docstring'''






						def find_duplicates(__UpperCamelCase   :      Any     ):
												return [k for k, v in collections.Counter(__UpperCamelCase     ).items() if v > 1]

						if list(import_dict_objects.keys()     ) != list(type_hint_objects.keys()     ):
												return ["Both sides of the init do not have the same backends!"]

						snake_case_ :			List[str]            =      []
						for key in import_dict_objects.keys():
												snake_case_ :			Tuple            =      find_duplicates(import_dict_objects[key]     )
												if duplicate_imports:
																		errors.append(F'Duplicate _import_structure definitions for: {duplicate_imports}'     )
												snake_case_ :			int            =      find_duplicates(type_hint_objects[key]     )
												if duplicate_type_hints:
																		errors.append(F'Duplicate TYPE_CHECKING objects for: {duplicate_type_hints}'     )

												if sorted(set(import_dict_objects[key]     )     ) != sorted(set(type_hint_objects[key]     )     ):
																		snake_case_ :			int            =      """base imports""" if key == """none""" else F'{key} backend'
																		errors.append(F'Differences for {name}:'     )
																		for a in type_hint_objects[key]:
																								if a not in import_dict_objects[key]:
																														errors.append(F'  {a} in TYPE_HINT but not in _import_structure.'     )
																		for a in import_dict_objects[key]:
																								if a not in type_hint_objects[key]:
																														errors.append(F'  {a} in _import_structure but not in TYPE_HINT.'     )
						return errors
def 						__lowerCAmelCase    (		):


						'''simple docstring'''






						snake_case_ :			Any            =      []
						for root, _, files in os.walk(__UpperCamelCase     ):
												if "__init__.py" in files:
																		snake_case_ :			Tuple            =      os.path.join(__UpperCamelCase       ,			"""__init__.py"""     )
																		snake_case_ :			List[Any]            =      parse_init(__UpperCamelCase     )
																		if objects is not None:
																								snake_case_ :			Tuple            =      analyze_results(*__UpperCamelCase     )
																								if len(__UpperCamelCase     ) > 0:
																														snake_case_ :			List[str]            =      F'Problem in {fname}, both halves do not define the same objects.\n{errors[0]}'
																														failures.append("""\n""".join(__UpperCamelCase     )     )
						if len(__UpperCamelCase     ) > 0:
												raise ValueError("""\n\n""".join(__UpperCamelCase     )     )
def 						__lowerCAmelCase    (		):


						'''simple docstring'''






						snake_case_ :			Tuple            =      []
						for path, directories, files in os.walk(__UpperCamelCase     ):
												for folder in directories:
																		# Ignore private modules
																		if folder.startswith("""_"""     ):
																								directories.remove(__UpperCamelCase     )
																								continue
																		# Ignore leftovers from branches (empty folders apart from pycache)
																		if len(list((Path(__UpperCamelCase     ) / folder).glob("""*.py"""     )     )     ) == 0:
																								continue
																		snake_case_ :			List[str]            =      str((Path(__UpperCamelCase     ) / folder).relative_to(__UpperCamelCase     )     )
																		snake_case_ :			Optional[Any]            =      short_path.replace(os.path.sep       ,			"""."""     )
																		submodules.append(__UpperCamelCase     )
												for fname in files:
																		if fname == "__init__.py":
																								continue
																		snake_case_ :			List[Any]            =      str((Path(__UpperCamelCase     ) / fname).relative_to(__UpperCamelCase     )     )
																		snake_case_ :			Union[str, Any]            =      short_path.replace(""".py"""       ,			""""""     ).replace(os.path.sep       ,			"""."""     )
																		if len(submodule.split("""."""     )     ) == 1:
																								submodules.append(__UpperCamelCase     )
						return submodules


__lowerCAmelCase							:       Tuple          =       [
    '''convert_pytorch_checkpoint_to_tf2''',
    '''modeling_flax_pytorch_utils''',
    '''models.esm.openfold_utils''',
]
def 						__lowerCAmelCase    (		):


						'''simple docstring'''






						from transformers.utils import direct_transformers_import

						snake_case_ :			Tuple            =      direct_transformers_import(__UpperCamelCase     )

						snake_case_ :			Dict            =      set(transformers._import_structure.keys()     )
						# This contains all the base keys of the _import_structure object defined in the init, but if the user is missing
						# some optional dependencies, they may not have all of them. Thus we read the init to read all additions and
						# (potentiall re-) add them.
						with open(os.path.join(__UpperCamelCase       ,			"""__init__.py"""     )       ,			"""r"""     ) as f:
												snake_case_ :			Optional[int]            =      f.read()
						import_structure_keys.update(set(re.findall(r"""import_structure\[\"([^\"]*)\"\]"""       ,			__UpperCamelCase     )     )     )

						snake_case_ :			Dict            =      [
						    module
						    for module in get_transformers_submodules()
						    if module not in IGNORE_SUBMODULES and module not in import_structure_keys
						]

						if len(__UpperCamelCase     ) > 0:
												snake_case_ :			Optional[Any]            =      """\n""".join(F'- {module}' for module in module_not_registered     )
												raise ValueError(
												    """The following submodules are not properly registed in the main init of Transformers:\n"""
												    F'{list_of_modules}\n'
												    """Make sure they appear somewhere in the keys of `_import_structure` with an empty list as value."""     )


if __name__ == "__main__":
					check_all_inits()
					check_submodules()




import json
import os
import subprocess
import unittest
from ast import literal_eval

import pytest
from parameterized import parameterized, parameterized_class

from . import is_sagemaker_available


if is_sagemaker_available():
	from sagemaker import Session, TrainingJobAnalytics
	from sagemaker.huggingface import HuggingFace



@pytest.mark.skipif(
    literal_eval(os.getenv('''TEST_SAGEMAKER'''						,  '''False'''							)							) is not True						,  reason='''Skipping test because should only be run when releasing minor transformers version'''						,  )
@pytest.mark.usefixtures('''sm_env'''							)
@parameterized_class(
    [
        {
            '''framework''': '''pytorch''',
            '''script''': '''run_glue.py''',
            '''model_name_or_path''': '''distilbert-base-cased''',
            '''instance_type''': '''ml.p3.16xlarge''',
            '''results''': {'''train_runtime''': 6_50, '''eval_accuracy''': 0.7, '''eval_loss''': 0.6},
        },
        {
            '''framework''': '''pytorch''',
            '''script''': '''run_ddp.py''',
            '''model_name_or_path''': '''distilbert-base-cased''',
            '''instance_type''': '''ml.p3.16xlarge''',
            '''results''': {'''train_runtime''': 6_00, '''eval_accuracy''': 0.7, '''eval_loss''': 0.6},
        },
        {
            '''framework''': '''tensorflow''',
            '''script''': '''run_tf_dist.py''',
            '''model_name_or_path''': '''distilbert-base-cased''',
            '''instance_type''': '''ml.p3.16xlarge''',
            '''results''': {'''train_runtime''': 6_00, '''eval_accuracy''': 0.6, '''eval_loss''': 0.7},
        },
    ]							)
class        _a		(unittest.TestCase							):


					'''simple docstring'''






					def     __A     (					self     ):
						if self.framework == "pytorch":
							subprocess.run(
							    F"""cp ./examples/pytorch/text-classification/run_glue.py {self.env.test_path}/run_glue.py""".split()       ,			encoding="""utf-8"""       ,			check=A__       ,			)
						assert hasattr(self       ,			"""env"""     )






					def     __A     (					self       ,			A__     ):
						A__				:       int	  =						F"""{self.env.base_job_name}-{instance_count}-{'ddp' if 'ddp' in self.script else 'smd'}"""
						# distributed data settings
						A__				:       str	  =						{"""smdistributed""": {"""dataparallel""": {"""enabled""": True}}} if self.script != """run_ddp.py""" else None

						# creates estimator
						return HuggingFace(
						    entry_point=self.script       ,			source_dir=self.env.test_path       ,			role=self.env.role       ,			image_uri=self.env.image_uri       ,			base_job_name=A__       ,			instance_count=A__       ,			instance_type=self.instance_type       ,			debugger_hook_config=A__       ,			hyperparameters={**self.env.distributed_hyperparameters, """model_name_or_path""": self.model_name_or_path}       ,			metric_definitions=self.env.metric_definitions       ,			distribution=A__       ,			py_version="""py36"""       ,			)






					def     __A     (					self       ,			A__     ):
						TrainingJobAnalytics(A__     ).export_csv(F"""{self.env.test_path}/{job_name}_metrics.csv"""     )






					@parameterized.expand([(2,)]     )
					def     __A     (					self       ,			A__     ):
						# create estimator
						A__				:       str	  =						self.create_estimator(A__     )

						# run training
						estimator.fit()

						# result dataframe
						A__				:       str	  =						TrainingJobAnalytics(estimator.latest_training_job.name     ).dataframe()

						# extract kpis
						A__				:       List[Any]	  =						list(result_metrics_df[result_metrics_df.metric_name == """eval_accuracy"""]["""value"""]     )
						A__				:       Optional[Any]	  =						list(result_metrics_df[result_metrics_df.metric_name == """eval_loss"""]["""value"""]     )
						# get train time from SageMaker job, this includes starting, preprocessing, stopping
						A__				:       str	  =						(
						    Session().describe_training_job(estimator.latest_training_job.name     ).get("""TrainingTimeInSeconds"""       ,			99_9999     )
						)

						# assert kpis
						assert train_runtime <= self.results["train_runtime"]
						assert all(t >= self.results["""eval_accuracy"""] for t in eval_accuracy     )
						assert all(t <= self.results["""eval_loss"""] for t in eval_loss     )

						# dump tests result into json file to share in PR
						with open(F"""{estimator.latest_training_job.name}.json"""       ,			"""w"""     ) as outfile:
							json.dump({"""train_time""": train_runtime, """eval_accuracy""": eval_accuracy, """eval_loss""": eval_loss}       ,			A__     )



