





"""simple docstring"""
import collections
import importlib.util
import os
import re
from pathlib import Path


_snake_case     :		Optional[Any]       						= 'src/transformers'


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






def 					A__				(			UpperCamelCase       ):
							if _re_test_backend.search(UpperCamelCase       ) is None:
														return None
							A		=  [b[0] for b in _re_backend.findall(UpperCamelCase       )]
							backends.sort()
							return "_and_".join(UpperCamelCase       )






def 					A__				(			UpperCamelCase       ):
							with open(UpperCamelCase					,  "r"					,  encoding="utf-8"					,  newline="\n"       ) as f:
														A		=  f.readlines()

							A		=  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
							A		=  []
							while not lines[line_index].startswith("if TYPE_CHECKING"       ) and find_backend(lines[line_index]       ) is None:
														A		=  lines[line_index]
														# If we have everything on a single line, let's deal with it.
														if _re_one_line_import_struct.search(UpperCamelCase       ):
																					A		=  _re_one_line_import_struct.search(UpperCamelCase       ).groups()[0]
																					A		=  re.findall("\[([^\]]+)\]"					,  UpperCamelCase       )
																					for imp in imports:
																												objects.extend([obj[1:-1] for obj in imp.split(", "       )]       )
																					line_index += 1
																					continue
														A		=  _re_import_struct_key_value.search(UpperCamelCase       )
														if single_line_import_search is not None:
																					A		=  [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

							A		=  {"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.
														A		=  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:
																					A		=  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

																					A		=  []
																					# Until we unindent, add backend objects to the list
																					while len(lines[line_index]       ) <= 1 or lines[line_index].startswith(" " * 4       ):
																												A		=  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:
																																			A		=  _re_import_struct_add_many.search(UpperCamelCase       ).groups()[0].split(", "       )
																																			A		=  [obj[1:-1] for obj in imports if len(UpperCamelCase       ) > 0]
																																			objects.extend(UpperCamelCase       )
																												elif _re_between_brackets.search(UpperCamelCase       ) is not None:
																																			A		=  _re_between_brackets.search(UpperCamelCase       ).groups()[0].split(", "       )
																																			A		=  [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(" " * 12 + "\""       ):
																																			objects.append(line[13:-3]       )
																												line_index += 1

																					A		=  objects
														else:
																					line_index += 1

    # At this stage we are in the TYPE_CHECKING part, first grab the objects without a specific backend
							A		=  []
							while (
							    line_index < len(UpperCamelCase       )
							    and find_backend(lines[line_index]       ) is None
							    and not lines[line_index].startswith("else"       )
							):
														A		=  lines[line_index]
														A		=  _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

							A		=  {"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.
														A		=  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:
																					A		=  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

																					A		=  []
																					# Until we unindent, add backend objects to the list
																					while len(lines[line_index]       ) <= 1 or lines[line_index].startswith(" " * 8       ):
																												A		=  lines[line_index]
																												A		=  _re_import.search(UpperCamelCase       )
																												if single_line_import_search is not None:
																																			objects.extend(single_line_import_search.groups()[0].split(", "       )       )
																												elif line.startswith(" " * 12       ):
																																			objects.append(line[12:-2]       )
																												line_index += 1

																					A		=  objects
														else:
																					line_index += 1

							return import_dict_objects, type_hint_objects






def 					A__				(			UpperCamelCase					,  UpperCamelCase       ):

							def find_duplicates(UpperCamelCase       ):
														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!"]

							A		=  []
							for key in import_dict_objects.keys():
														A		=  find_duplicates(import_dict_objects[key]       )
														if duplicate_imports:
																					errors.append(F"Duplicate _import_structure definitions for: {duplicate_imports}"       )
														A		=  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]       )       ):
																					A		=  "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 					A__				(			):
							A		=  []
							for root, _, files in os.walk(UpperCamelCase       ):
														if "__init__.py" in files:
																					A		=  os.path.join(UpperCamelCase					,  "__init__.py"       )
																					A		=  parse_init(UpperCamelCase       )
																					if objects is not None:
																												A		=  analyze_results(*UpperCamelCase       )
																												if len(UpperCamelCase       ) > 0:
																																			A		=  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 					A__				(			):
							A		=  []
							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
																					A		=  str((Path(UpperCamelCase       ) / folder).relative_to(UpperCamelCase       )       )
																					A		=  short_path.replace(os.path.sep					,  "."       )
																					submodules.append(UpperCamelCase       )
														for fname in files:
																					if fname == "__init__.py":
																												continue
																					A		=  str((Path(UpperCamelCase       ) / fname).relative_to(UpperCamelCase       )       )
																					A		=  short_path.replace(".py"					,  ""       ).replace(os.path.sep					,  "."       )
																					if len(submodule.split("."       )       ) == 1:
																												submodules.append(UpperCamelCase       )
							return submodules


_snake_case     :		Tuple       						= [
    'convert_pytorch_checkpoint_to_tf2',
    'modeling_flax_pytorch_utils',
]






def 					A__				(			):
							# This is to make sure the transformers module imported is the one in the repo.
							A		=  importlib.util.spec_from_file_location(
							    "transformers"					,  os.path.join(UpperCamelCase					,  "__init__.py"       )					,  submodule_search_locations=[PATH_TO_TRANSFORMERS]					,  )
							A		=  spec.loader.load_module()

							A		=  [
							    module
							    for module in get_transformers_submodules()
							    if module not in IGNORE_SUBMODULES and module not in transformers._import_structure.keys()
							]
							if len(UpperCamelCase       ) > 0:
														A		=  "\n".join(F"- {module}" for module in module_not_registered       )
														raise ValueError(
														    "The following submodules are not properly registered 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()









"""simple docstring"""
import hashlib
import unittest

from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_timm,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_torch_available():
		import torch

if is_vision_available():
		from PIL import Image
else:






		class 					_UpperCAmelCase   :


							@staticmethod
							def 	lowerCamelCase       (					*__UpperCamelCase			:List[Any]     ,       **__UpperCamelCase			:List[Any]		):
														pass






def 					A__				(			UpperCamelCase       ):
							A		=  hashlib.mda(image.tobytes()       )
							return m.hexdigest()






@is_pipeline_test
@require_vision
@require_timm
@require_torch
class 					_UpperCAmelCase   (	unittest.TestCase ):
					UpperCamelCase      =							MODEL_FOR_DEPTH_ESTIMATION_MAPPING


					def 	lowerCamelCase       (					self			:Optional[Any]     ,       __UpperCamelCase			:Union[str, Any]     ,       __UpperCamelCase			:List[str]     ,       __UpperCamelCase			:Optional[int]		):
												A		=  DepthEstimationPipeline(model=__UpperCamelCase     ,       image_processor=__UpperCamelCase		)
												return depth_estimator, [
												    "./tests/fixtures/tests_samples/COCO/000000039769.png",
												    "./tests/fixtures/tests_samples/COCO/000000039769.png",
												]


					def 	lowerCamelCase       (					self			:Dict     ,       __UpperCamelCase			:Optional[int]     ,       __UpperCamelCase			:Optional[Any]		):
												A		=  depth_estimator("./tests/fixtures/tests_samples/COCO/000000039769.png"		)
												self.assertEqual({"predicted_depth": ANY(torch.Tensor		), "depth": ANY(Image.Image		)}     ,       __UpperCamelCase		)
												import datasets

												A		=  datasets.load_dataset("hf-internal-testing/fixtures_image_utils"     ,       "image"     ,       split="test"		)
												A		=  depth_estimator(
												    [
												        Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"		),
												        "http://images.cocodataset.org/val2017/000000039769.jpg",
												        # RGBA
												        dataset[0]["file"],
												        # LA
												        dataset[1]["file"],
												        # L
												        dataset[2]["file"],
												    ]		)
												self.assertEqual(
												    [
												        {"predicted_depth": ANY(torch.Tensor		), "depth": ANY(Image.Image		)},
												        {"predicted_depth": ANY(torch.Tensor		), "depth": ANY(Image.Image		)},
												        {"predicted_depth": ANY(torch.Tensor		), "depth": ANY(Image.Image		)},
												        {"predicted_depth": ANY(torch.Tensor		), "depth": ANY(Image.Image		)},
												        {"predicted_depth": ANY(torch.Tensor		), "depth": ANY(Image.Image		)},
												    ]     ,       __UpperCamelCase     ,       )


					@require_tf
					@unittest.skip("Depth estimation is not implemented in TF"		)
					def 	lowerCamelCase       (					self			:Optional[Any]		):
												pass


					@slow
					@require_torch
					def 	lowerCamelCase       (					self			:Optional[Any]		):
												A		=  "Intel/dpt-large"
												A		=  pipeline("depth-estimation"     ,       model=__UpperCamelCase		)
												A		=  depth_estimator("http://images.cocodataset.org/val2017/000000039769.jpg"		)
												A		=  hashimage(outputs["depth"]		)

												# This seems flaky.
												# self.assertEqual(outputs["depth"], "1a39394e282e9f3b0741a90b9f108977")
												self.assertEqual(nested_simplify(outputs["predicted_depth"].max().item()		)     ,       29.304		)
												self.assertEqual(nested_simplify(outputs["predicted_depth"].min().item()		)     ,       2.662		)


					@require_torch
					def 	lowerCamelCase       (					self			:Optional[Any]		):
												# This is highly irregular to have no small tests.
												self.skipTest("There is not hf-internal-testing tiny model for either GLPN nor DPT"		)


