import argparse
import glob
import inspect
import os
import re
import unittest

from get_test_info import get_test_classes

from tests.test_pipeline_mixin import pipeline_test_mapping


lowerCAmelCase__	:  Tuple						=  {}
for task, _ in pipeline_test_mapping.items():
				lowerCAmelCase__	:  Union[str, Any]						=  {'pt': None, 'tf': None}


# DO **NOT** add item to this set (unless the reason is approved)
lowerCAmelCase__	:  List[Any]						=  {
    'tests/models/esm/test_modeling_esmfold.py',  # The pipeline test mapping is added to `test_modeling_esm.py`
}
def 					UpperCamelCase__		(							A__       )  ->   Dict:

				if "ModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
								return "pt"
				elif "TFModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
								return "tf"
				elif "FlaxModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
								return "flax"
				else:
								return None
def 					UpperCamelCase__		(							A__     ,					A__       )  ->   Union[str, Any]:

				if PIPELINE_TEST_MAPPING[task].get(__lowercase     ,					__lowercase       ) is not None:
								return PIPELINE_TEST_MAPPING[task][framework]

				snake_case__   :      List[Any]   				= pipeline_test_mapping[task]["test"]
				snake_case__   :      Optional[Any]   				= None

				if framework == "pt":
								snake_case__   :      Optional[int]   				= getattr(__lowercase     ,					'model_mapping'     ,					__lowercase       )
				elif framework == "tf":
								snake_case__   :      int   				= getattr(__lowercase     ,					'tf_model_mapping'     ,					__lowercase       )

				if mapping is not None:
								snake_case__   :      int   				= dict(mapping.items()       )

				# cache the results
				snake_case__   :      Optional[int]   				= mapping
				return mapping
def 					UpperCamelCase__		(							A__     ,					A__       )  ->   Union[str, Any]:
				snake_case__   :      Optional[int]   				= get_framework(__lowercase       )
				if framework is None:
								return None
				snake_case__   :      Union[str, Any]   				= get_mapping_for_task(__lowercase     ,					__lowercase       )
				if mapping is None:
								return None

				snake_case__   :      Optional[int]   				= list({model_class.config_class for model_class in test_class.all_model_classes}       )
				if len(__lowercase       ) != 1:
								raise ValueError('There should be exactly one configuration class from `test_class.all_model_classes`.'       )

				# This could be a list/tuple of model classes, but it's rare.
				snake_case__   :      List[Any]   				= mapping.get(config_classes[0]     ,					__lowercase       )
				if isinstance(__lowercase     ,					(tuple, list)       ):
								snake_case__   :      Optional[Any]   				= sorted(__lowercase     ,					key=lambda A__       : x.__name__       )

				return model_class
def 					UpperCamelCase__		(							A__       )  ->   str:
				snake_case__   :      List[Any]   				= [(task, get_model_for_pipeline_test(__lowercase     ,					__lowercase       )) for task in pipeline_test_mapping]
				snake_case__   :      List[Any]   				= sorted([(task, model) for task, model in mapping if model is not None]     ,					key=lambda A__       : x[0]       )

				return dict(__lowercase       )
def 					UpperCamelCase__		(							A__       )  ->   str:
				snake_case__   :      Union[str, Any]   				= get_framework(__lowercase       )
				if framework == "pt":
								snake_case__   :      List[str]   				= "torch"
				snake_case__   :      str   				= "{}"

				snake_case__   :      List[str]   				= get_pipeline_model_mapping(__lowercase       )
				if len(__lowercase       ) == 0:
								return ""

				snake_case__   :      int   				= []
				for task, model_classes in mapping.items():
								if isinstance(__lowercase     ,					(tuple, list)       ):
												# A list/tuple of model classes
												snake_case__   :      Any   				= "(" + ", ".join([x.__name__ for x in model_classes]       ) + ")"
								else:
												# A single model class
												snake_case__   :      str   				= model_classes.__name__
								texts.append(F"""\"{task}\": {value}"""       )
				snake_case__   :      Optional[int]   				= "{" + ", ".join(__lowercase       ) + "}"
				snake_case__   :      str   				= F"""pipeline_model_mapping = {text} if is_{framework}_available() else {default_value}"""

				return text
def 					UpperCamelCase__		(							A__       )  ->   Union[str, Any]:
				snake_case__   :      Any   				= {"ModelTesterMixin", "TFModelTesterMixin", "FlaxModelTesterMixin"}
				if not issubclass(__lowercase     ,					unittest.TestCase       ):
								return False
				return len(base_class_names.intersection([x.__name__ for x in test_class.__bases__]       )       ) > 0
def 					UpperCamelCase__		(							A__       )  ->   Union[str, Any]:
				snake_case__   :      int   				= [x for x in get_test_classes(__lowercase       ) if is_valid_test_class(__lowercase       )]

				snake_case__   :      Tuple   				= None
				for test_class in test_classes:
								# If a test class has defined `pipeline_model_mapping`, let's take it
								if getattr(__lowercase     ,					'pipeline_model_mapping'     ,					__lowercase       ) is not None:
												snake_case__   :      Any   				= test_class
												break
    # Take the test class with the shortest name (just a heuristic)
				if target_test_class is None and len(__lowercase       ) > 0:
								snake_case__   :      List[Any]   				= sorted(__lowercase     ,					key=lambda A__       : (len(x.__name__       ), x.__name__)       )[0]

				return target_test_class
def 					UpperCamelCase__		(							A__     ,					A__     ,					A__       )  ->   int:
				snake_case__   :      Tuple   				= start_idx
				for idx, line in enumerate(lines[start_idx:]       ):
								snake_case__   :      str   				= len(__lowercase       ) - len(line.lstrip()       )
								if idx == 0 or indent > indent_level or (indent == indent_level and line.strip() == ")"):
												snake_case__   :      List[Any]   				= start_idx + idx
								elif idx > 0 and indent <= indent_level:
												# Outside the definition block of `pipeline_model_mapping`
												break

				return end_idx
def 					UpperCamelCase__		(							A__     ,					A__=False       )  ->   int:

				if getattr(__lowercase     ,					'pipeline_model_mapping'     ,					__lowercase       ) is not None:
								if not overwrite:
												return "", -1

				snake_case__   :      Any   				= get_pipeline_model_mapping_string(__lowercase       )
				if len(__lowercase       ) == 0:
								return "", -1
				snake_case__   :      Tuple   				= line_to_add + "\n"

				# The code defined the class `test_class`
				snake_case__   :      List[Any]   				= inspect.getsourcelines(__lowercase       )
				# `inspect` gives the code for an object, including decorator(s) if any.
				# We (only) need the exact line of the class definition.
				for idx, line in enumerate(__lowercase       ):
								if line.lstrip().startswith('class '       ):
												snake_case__   :      int   				= class_lines[idx:]
												class_start_line_no += idx
												break
				snake_case__   :      int   				= class_start_line_no + len(__lowercase       ) - 1

				# The index in `class_lines` that starts the definition of `all_model_classes`, `all_generative_model_classes` or
				# `pipeline_model_mapping`. This assumes they are defined in such order, and we take the start index of the last
				# block that appears in a `test_class`.
				snake_case__   :      str   				= None
				# The indent level of the line at `class_lines[start_idx]` (if defined)
				snake_case__   :      Any   				= 0
				# To record if `pipeline_model_mapping` is found in `test_class`.
				snake_case__   :      Any   				= None
				for idx, line in enumerate(__lowercase       ):
								if line.strip().startswith('all_model_classes = '       ):
												snake_case__   :      Any   				= len(__lowercase       ) - len(line.lstrip()       )
												snake_case__   :      Dict   				= idx
								elif line.strip().startswith('all_generative_model_classes = '       ):
												snake_case__   :      Tuple   				= len(__lowercase       ) - len(line.lstrip()       )
												snake_case__   :      str   				= idx
								elif line.strip().startswith('pipeline_model_mapping = '       ):
												snake_case__   :      Optional[int]   				= len(__lowercase       ) - len(line.lstrip()       )
												snake_case__   :      Tuple   				= idx
												snake_case__   :      Optional[Any]   				= line
												break

				if start_idx is None:
								return "", -1
				# Find the ending index (inclusive) of the above found block.
				snake_case__   :      Optional[Any]   				= find_block_ending(__lowercase     ,					__lowercase     ,					__lowercase       )

				# Extract `is_xxx_available()` from existing blocks: some models require specific libraries like `timm` and use
				# `is_timm_available()` instead of `is_torch_available()`.
				# Keep leading and trailing whitespaces
				snake_case__   :      List[Any]   				= re.compile(r'\s(is_\S+?_available\(\))\s'       )
				for line in class_lines[start_idx : end_idx + 1]:
								snake_case__   :      List[Any]   				= r.search(__lowercase       )
								if backend_condition is not None:
												# replace the leading and trailing whitespaces to the space character " ".
												snake_case__   :      List[Any]   				= " " + backend_condition[0][1:-1] + " "
												snake_case__   :      int   				= r.sub(__lowercase     ,					__lowercase       )
												break

				if def_line is None:
								# `pipeline_model_mapping` is not defined. The target index is set to the ending index (inclusive) of
								# `all_model_classes` or `all_generative_model_classes`.
								snake_case__   :      str   				= end_idx
				else:
								# `pipeline_model_mapping` is defined. The target index is set to be one **BEFORE** its start index.
								snake_case__   :      int   				= start_idx - 1
								# mark the lines of the currently existing `pipeline_model_mapping` to be removed.
								for idx in range(__lowercase     ,					end_idx + 1       ):
												# These lines are going to be removed before writing to the test file.
												snake_case__   :      Optional[Any]   				= None  # noqa

    # Make sure the test class is a subclass of `PipelineTesterMixin`.
				snake_case__   :      Any   				= [x.__name__ for x in test_class.__bases__]
				if "PipelineTesterMixin" not in parent_classes:
								# Put `PipelineTesterMixin` just before `unittest.TestCase`
								snake_case__   :      Tuple   				= [x for x in parent_classes if x != "TestCase"] + ["PipelineTesterMixin"]
								if "TestCase" in parent_classes:
												# Here we **assume** the original string is always with `unittest.TestCase`.
												_parent_classes.append('unittest.TestCase'       )
								snake_case__   :      Optional[Any]   				= ", ".join(_parent_classes       )
								for idx, line in enumerate(__lowercase       ):
												# Find the ending of the declaration of `test_class`
												if line.strip().endswith('):'       ):
																# mark the lines of the declaration of `test_class` to be removed
																for _idx in range(idx + 1       ):
																				snake_case__   :      int   				= None  # noqa
																break
        # Add the new, one-line, class declaration for `test_class`
								snake_case__   :      Tuple   				= F"""class {test_class.__name__}({parent_classes}):\n"""

				# Add indentation
				snake_case__   :      Dict   				= " " * indent_level + line_to_add
				# Insert `pipeline_model_mapping` to `class_lines`.
				# (The line at `target_idx` should be kept by definition!)
				snake_case__   :      Union[str, Any]   				= class_lines[: target_idx + 1] + [line_to_add] + class_lines[target_idx + 1 :]
				# Remove the lines that are marked to be removed
				snake_case__   :      List[Any]   				= [x for x in class_lines if x is not None]

				# Move from test class to module (in order to write to the test file)
				snake_case__   :      int   				= inspect.getsourcelines(inspect.getmodule(__lowercase       )       )[0]
				# Be careful with the 1-off between line numbers and array indices
				snake_case__   :      int   				= module_lines[: class_start_line_no - 1] + class_lines + module_lines[class_end_line_no:]
				snake_case__   :      Tuple   				= "".join(__lowercase       )

				snake_case__   :      Union[str, Any]   				= inspect.getsourcefile(__lowercase       )
				with open(__lowercase     ,					'w'     ,					encoding='UTF-8'     ,					newline='\n'       ) as fp:
								fp.write(__lowercase       )

				return line_to_add
def 					UpperCamelCase__		(							A__     ,					A__=False       )  ->   Tuple:
				snake_case__   :      Tuple   				= find_test_class(__lowercase       )
				if test_class:
								add_pipeline_model_mapping(__lowercase     ,					overwrite=__lowercase       )


if __name__ == "__main__":
				lowerCAmelCase__	:  Dict						=  argparse.ArgumentParser()
				parser.add_argument(
				    '''--test_file''', type=str, help='''A path to the test file, starting with the repository\'s `tests` directory.'''
				)
				parser.add_argument(
				    '''--all''',
				    action='''store_true''',
				    help='''If to check and modify all test files.''',
				)
				parser.add_argument(
				    '''--overwrite''',
				    action='''store_true''',
				    help='''If to overwrite a test class if it has already defined `pipeline_model_mapping`.''',
				)
				lowerCAmelCase__	:  Any						=  parser.parse_args()

				if not args.all and not args.test_file:
								raise ValueError('''Please specify either `test_file` or pass `--all` to check/modify all test files.''')
				elif args.all and args.test_file:
								raise ValueError('''Only one of `--test_file` and `--all` could be specified.''')

				lowerCAmelCase__	:  List[str]						=  []
				if args.test_file:
								lowerCAmelCase__	:  List[str]						=  [args.test_file]
				else:
								lowerCAmelCase__	:  str						=  os.path.join('''tests''', '''models''', '''**''', '''test_modeling_*.py''')
								for test_file in glob.glob(pattern):
												# `Flax` is not concerned at this moment
												if not test_file.startswith('''test_modeling_flax_'''):
																test_files.append(test_file)

				for test_file in test_files:
								if test_file in TEST_FILE_TO_IGNORE:
												print(F'''[SKIPPED] {test_file} is skipped as it is in `TEST_FILE_TO_IGNORE` in the file {__file__}.''')
												continue
								add_pipeline_model_mapping_to_test_file(test_file, overwrite=args.overwrite)







import json
import os
import unittest

from transformers import BartTokenizer, BartTokenizerFast, BatchEncoding
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors




@require_tokenizers
class 				lowerCAmelCase__	(						UpperCamelCase       ,				unittest.TestCase    ):
					__A  :     Any     =    BartTokenizer
					__A  :     str     =    BartTokenizerFast
					__A  :     Optional[int]     =    True
					__A  :     Optional[int]     =    filter_roberta_detectors







					def 			_lowercase      (							self   :  Dict):
											super().setUp()
											A__						:				Union[str, Any]         =			[
											    "l",
											    "o",
											    "w",
											    "e",
											    "r",
											    "s",
											    "t",
											    "i",
											    "d",
											    "n",
											    "\u0120",
											    "\u0120l",
											    "\u0120n",
											    "\u0120lo",
											    "\u0120low",
											    "er",
											    "\u0120lowest",
											    "\u0120newer",
											    "\u0120wider",
											    "<unk>",
											]
											A__						:				List[str]         =			dict(zip(_A      ,		range(len(_A))))
											A__						:				List[str]         =			["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
											A__						:				str         =			{"unk_token": "<unk>"}

											A__						:				Dict         =			os.path.join(self.tmpdirname      ,		VOCAB_FILES_NAMES["vocab_file"])
											A__						:				Optional[Any]         =			os.path.join(self.tmpdirname      ,		VOCAB_FILES_NAMES["merges_file"])
											with open(self.vocab_file      ,		"w"      ,		encoding="utf-8") as fp:
																	fp.write(json.dumps(_A) + "\n")
											with open(self.merges_file      ,		"w"      ,		encoding="utf-8") as fp:
																	fp.write("\n".join(_A))







					def 			_lowercase      (							self   :  Union[str, Any]      ,		**_A   :  str):
											kwargs.update(self.special_tokens_map)
											return self.tokenizer_class.from_pretrained(self.tmpdirname      ,		**_A)







					def 			_lowercase      (							self   :  Union[str, Any]      ,		**_A   :  List[Any]):
											kwargs.update(self.special_tokens_map)
											return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      ,		**_A)







					def 			_lowercase      (							self   :  Tuple      ,		_A   :  Union[str, Any]):
											return "lower newer", "lower newer"







					@cached_property
					def 			_lowercase      (							self   :  Optional[int]):
											return BartTokenizer.from_pretrained("facebook/bart-large")







					@cached_property
					def 			_lowercase      (							self   :  Optional[int]):
											return BartTokenizerFast.from_pretrained("facebook/bart-large")







					@require_torch
					def 			_lowercase      (							self   :  Dict):
											A__						:				Optional[int]         =			["A long paragraph for summarization.", "Another paragraph for summarization."]
											A__						:				List[Any]         =			[0, 250, 251, 1_7818, 13, 3_9186, 1938, 4, 2]

											for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	A__						:				Tuple         =			tokenizer(_A      ,		max_length=len(_A)      ,		padding=_A      ,		return_tensors="pt")
																	self.assertIsInstance(_A      ,		_A)

																	self.assertEqual((2, 9)      ,		batch.input_ids.shape)
																	self.assertEqual((2, 9)      ,		batch.attention_mask.shape)
																	A__						:				Dict         =			batch.input_ids.tolist()[0]
																	self.assertListEqual(_A      ,		_A)
																	# Test that special tokens are reset







					@require_torch
					def 			_lowercase      (							self   :  List[Any]):
											A__						:				Optional[Any]         =			["A long paragraph for summarization.", "Another paragraph for summarization."]
											for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	A__						:				Tuple         =			tokenizer(_A      ,		padding=_A      ,		return_tensors="pt")
																	# check if input_ids are returned and no labels
																	self.assertIn("input_ids"      ,		_A)
																	self.assertIn("attention_mask"      ,		_A)
																	self.assertNotIn("labels"      ,		_A)
																	self.assertNotIn("decoder_attention_mask"      ,		_A)







					@require_torch
					def 			_lowercase      (							self   :  int):
											A__						:				Optional[Any]         =			[
											    "Summary of the text.",
											    "Another summary.",
											]
											for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	A__						:				int         =			tokenizer(text_target=_A      ,		max_length=32      ,		padding="max_length"      ,		return_tensors="pt")
																	self.assertEqual(32      ,		targets["input_ids"].shape[1])







					@require_torch
					def 			_lowercase      (							self   :  List[str]):
											for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	A__						:				List[str]         =			tokenizer(
																	    ["I am a small frog" * 1024, "I am a small frog"]      ,		padding=_A      ,		truncation=_A      ,		return_tensors="pt")
																	self.assertIsInstance(_A      ,		_A)
																	self.assertEqual(batch.input_ids.shape      ,		(2, 1024))







					@require_torch
					def 			_lowercase      (							self   :  List[str]):
											A__						:				int         =			["A long paragraph for summarization."]
											A__						:				List[str]         =			[
											    "Summary of the text.",
											]
											for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	A__						:				Optional[Any]         =			tokenizer(_A      ,		return_tensors="pt")
																	A__						:				Union[str, Any]         =			tokenizer(text_target=_A      ,		return_tensors="pt")
																	A__						:				Tuple         =			inputs["input_ids"]
																	A__						:				str         =			targets["input_ids"]
																	self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item())
																	self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item())
																	self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item())
																	self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item())







					def 			_lowercase      (							self   :  Optional[int]):
											pass







					def 			_lowercase      (							self   :  Any):
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'):
																							A__						:				Union[str, Any]         =			self.rust_tokenizer_class.from_pretrained(_A      ,		**_A)
																							A__						:				int         =			self.tokenizer_class.from_pretrained(_A      ,		**_A)
																							A__						:				Union[str, Any]         =			"A, <mask> AllenNLP sentence."
																							A__						:				Dict         =			tokenizer_r.encode_plus(_A      ,		add_special_tokens=_A      ,		return_token_type_ids=_A)
																							A__						:				Optional[Any]         =			tokenizer_p.encode_plus(_A      ,		add_special_tokens=_A      ,		return_token_type_ids=_A)

																							# token_type_ids should put 0 everywhere
																							self.assertEqual(sum(tokens_r["token_type_ids"])      ,		sum(tokens_p["token_type_ids"]))

																							# attention_mask should put 1 everywhere, so sum over length should be 1
																							self.assertEqual(
																							    sum(tokens_r["attention_mask"]) / len(tokens_r["attention_mask"])      ,		sum(tokens_p["attention_mask"]) / len(tokens_p["attention_mask"])      ,		)

																							A__						:				Optional[int]         =			tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"])
																							A__						:				Dict         =			tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"])

																							# Rust correctly handles the space before the mask while python doesnt
																							self.assertSequenceEqual(tokens_p["input_ids"]      ,		[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2])
																							self.assertSequenceEqual(tokens_r["input_ids"]      ,		[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2])

																							self.assertSequenceEqual(
																							    _A      ,		["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"])
																							self.assertSequenceEqual(
																							    _A      ,		["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"])