

"""simple docstring"""





import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Optional, Tuple, Union, get_type_hints

import yaml


__UpperCamelCase    : Dict				 =						NewType('''DataClass''', Any)
__UpperCamelCase    : Optional[Any]				 =						NewType('''DataClassType''', Any)

def     __SCREAMING_SNAKE_CASE    ( A_					):
	if isinstance(__UpperCAmelCase		,	__UpperCAmelCase					):
		return v
	if v.lower() in ("yes", "true", "t", "y", "1"):
		return True
	elif v.lower() in ("no", "false", "f", "n", "0"):
		return False
	else:
		raise ArgumentTypeError(
		    f'Truthy value expected: got {v} but expected one of yes/no, true/false, t/f, y/n, 1/0 (case insensitive).'					)

def     __SCREAMING_SNAKE_CASE    ( A_					):
	lowerCAmelCase__      :		List[Any]    							=      {str(__UpperCAmelCase					): choice for choice in choices}
	return lambda A_					: str_to_choice.get(__UpperCAmelCase		,	__UpperCAmelCase					)

def     __SCREAMING_SNAKE_CASE    ( *,
    A_ = None		,	A_ = None		,	A_ = dataclasses.MISSING		,	A_ = dataclasses.MISSING		,	A_ = None		,	**A_		,	):
	if metadata is None:
		# Important, don't use as default param in function signature because dict is mutable and shared across function calls
		lowerCAmelCase__      :		Any    							=      {}
	if aliases is not None:
		lowerCAmelCase__      :		Optional[Any]    							=      aliases
	if help is not None:
		lowerCAmelCase__      :		Dict    							=      help

	return dataclasses.field(metadata=__UpperCAmelCase		,	default=__UpperCAmelCase		,	default_factory=__UpperCAmelCase		,	**__UpperCAmelCase					)







class 							SCREAMING_SNAKE_CASE   (						SCREAMING_SNAKE_CASE_			):






					"""simple docstring"""



					lowercase__												=			42







					def __init__(			self     :							Optional[Any]  ,lowercase_     :							Union[DataClassType, Iterable[DataClassType]]  ,**lowercase_     :							int						):
						# To make the default appear when using --help
						if "formatter_class" not in kwargs:
							lowerCAmelCase__      :		int    							=      ArgumentDefaultsHelpFormatter
						super().__init__(**__snake_case						)
						if dataclasses.is_dataclass(__snake_case						):
							lowerCAmelCase__      :		Union[str, Any]    							=      [dataclass_types]
						lowerCAmelCase__      :		str    							=      list(__snake_case						)
						for dtype in self.dataclass_types:
							self._add_dataclass_arguments(__snake_case						)







					@staticmethod
					def 			__lowerCAmelCase					(			lowercase_     :							ArgumentParser  ,lowercase_     :							dataclasses.Field						):
						lowerCAmelCase__      :		Tuple    							=      F'--{field.name}'
						lowerCAmelCase__      :		Optional[int]    							=      field.metadata.copy()
						# field.metadata is not used at all by Data Classes,
						# it is provided as a third-party extension mechanism.
						if isinstance(field.type  ,__snake_case						):
							raise RuntimeError(
							    '''Unresolved type detected, which should have been done with the help of '''
							    '''`typing.get_type_hints` method by default'''						)

						lowerCAmelCase__      :		Optional[Any]    							=      kwargs.pop('''aliases'''  ,[]						)
						if isinstance(__snake_case  ,__snake_case						):
							lowerCAmelCase__      :		Optional[Any]    							=      [aliases]

						lowerCAmelCase__      :		str    							=      getattr(field.type  ,'''__origin__'''  ,field.type						)
						if origin_type is Union or (hasattr(__snake_case  ,'''UnionType'''						) and isinstance(__snake_case  ,types.UnionType						)):
							if str not in field.type.__args__ and (
							    len(field.type.__args__						) != 2 or type(__snake_case						) not in field.type.__args__
							):
								raise ValueError(
								    '''Only `Union[X, NoneType]` (i.e., `Optional[X]`) is allowed for `Union` because'''
								    ''' the argument parser only supports one type per argument.'''
								    F' Problem encountered in field \'{field.name}\'.'						)
							if type(__snake_case						) not in field.type.__args__:
								# filter `str` in Union
								lowerCAmelCase__      :		int    							=      field.type.__args__[0] if field.type.__args__[1] == str else field.type.__args__[1]
								lowerCAmelCase__      :		Union[str, Any]    							=      getattr(field.type  ,'''__origin__'''  ,field.type						)
							elif bool not in field.type.__args__:
								# filter `NoneType` in Union (except for `Union[bool, NoneType]`)
								lowerCAmelCase__      :		str    							=      (
								    field.type.__args__[0] if isinstance(__snake_case  ,field.type.__args__[1]						) else field.type.__args__[1]
								)
								lowerCAmelCase__      :		List[str]    							=      getattr(field.type  ,'''__origin__'''  ,field.type						)

        # A variable to store kwargs for a boolean field, if needed
        # so that we can init a `no_*` complement argument (see below)
						lowerCAmelCase__      :		Tuple    							=      {}
						if origin_type is Literal or (isinstance(field.type  ,__snake_case						) and issubclass(field.type  ,__snake_case						)):
							if origin_type is Literal:
								lowerCAmelCase__      :		Optional[Any]    							=      field.type.__args__
							else:
								lowerCAmelCase__      :		List[Any]    							=      [x.value for x in field.type]

							lowerCAmelCase__      :		Dict    							=      make_choice_type_function(kwargs['''choices''']						)

							if field.default is not dataclasses.MISSING:
								lowerCAmelCase__      :		Optional[Any]    							=      field.default
							else:
								lowerCAmelCase__      :		Union[str, Any]    							=      True
						elif field.type is bool or field.type == Optional[bool]:
							# Copy the currect kwargs to use to instantiate a `no_*` complement argument below.
							# We do not initialize it here because the `no_*` alternative must be instantiated after the real argument
							lowerCAmelCase__      :		int    							=      copy(__snake_case						)

							# Hack because type=bool in argparse does not behave as we want.
							lowerCAmelCase__      :		List[str]    							=      string_to_bool
							if field.type is bool or (field.default is not None and field.default is not dataclasses.MISSING):
								# Default value is False if we have no default when of type bool.
								lowerCAmelCase__      :		List[Any]    							=      False if field.default is dataclasses.MISSING else field.default
								# This is the value that will get picked if we don't include --field_name in any way
								lowerCAmelCase__      :		List[str]    							=      default
								# This tells argparse we accept 0 or 1 value after --field_name
								lowerCAmelCase__      :		List[Any]    							=      """?"""
								# This is the value that will get picked if we do --field_name (without value)
								lowerCAmelCase__      :		List[Any]    							=      True
						elif isclass(__snake_case						) and issubclass(__snake_case  ,__snake_case						):
							lowerCAmelCase__      :		Dict    							=      field.type.__args__[0]
							lowerCAmelCase__      :		str    							=      """+"""
							if field.default_factory is not dataclasses.MISSING:
								lowerCAmelCase__      :		Optional[Any]    							=      field.default_factory()
							elif field.default is dataclasses.MISSING:
								lowerCAmelCase__      :		Tuple    							=      True
						else:
							lowerCAmelCase__      :		Dict    							=      field.type
							if field.default is not dataclasses.MISSING:
								lowerCAmelCase__      :		Any    							=      field.default
							elif field.default_factory is not dataclasses.MISSING:
								lowerCAmelCase__      :		Any    							=      field.default_factory()
							else:
								lowerCAmelCase__      :		Tuple    							=      True
						parser.add_argument(__snake_case  ,*__snake_case  ,**__snake_case						)

						# Add a complement `no_*` argument for a boolean field AFTER the initial field has already been added.
						# Order is important for arguments with the same destination!
						# We use a copy of earlier kwargs because the original kwargs have changed a lot before reaching down
						# here and we do not need those changes/additional keys.
						if field.default is True and (field.type is bool or field.type == Optional[bool]):
							lowerCAmelCase__      :		Optional[Any]    							=      False
							parser.add_argument(F'--no_{field.name}'  ,action='''store_false'''  ,dest=field.name  ,**__snake_case						)







					def 			__lowerCAmelCase					(			self     :							str  ,lowercase_     :							DataClassType						):
						if hasattr(__snake_case  ,'''_argument_group_name'''						):
							lowerCAmelCase__      :		Tuple    							=      self.add_argument_group(dtype._argument_group_name						)
						else:
							lowerCAmelCase__      :		Union[str, Any]    							=      self

						try:
							lowerCAmelCase__      :		Dict[str, type]    							=      get_type_hints(__snake_case						)
						except NameError:
							raise RuntimeError(
							    F'Type resolution failed for {dtype}. Try declaring the class in global scope or '
							    '''removing line of `from __future__ import annotations` which opts in Postponed '''
							    '''Evaluation of Annotations (PEP 563)'''						)
						except TypeError as ex:
							# Remove this block when we drop Python 3.9 support
							if sys.version_info[:2] < (3, 1_0) and "unsupported operand type(s) for |" in str(__snake_case						):
								lowerCAmelCase__      :		int    							=      """.""".join(map(__snake_case  ,sys.version_info[:3]						)						)
								raise RuntimeError(
								    F'Type resolution failed for {dtype} on Python {python_version}. Try removing '
								    '''line of `from __future__ import annotations` which opts in union types as '''
								    '''`X | Y` (PEP 604) via Postponed Evaluation of Annotations (PEP 563). To '''
								    '''support Python versions that lower than 3.10, you need to use '''
								    '''`typing.Union[X, Y]` instead of `X | Y` and `typing.Optional[X]` instead of '''
								    '''`X | None`.'''						) from ex
							raise

						for field in dataclasses.fields(__snake_case						):
							if not field.init:
								continue
							lowerCAmelCase__      :		List[str]    							=      type_hints[field.name]
							self._parse_dataclass_field(__snake_case  ,__snake_case						)







					def 			__lowerCAmelCase					(			self     :							str  ,lowercase_     :							Optional[Any]=None  ,lowercase_     :							Optional[int]=False  ,lowercase_     :							int=True  ,lowercase_     :							Optional[Any]=None  ,lowercase_     :							List[Any]=None  ,):

						if args_file_flag or args_filename or (look_for_args_file and len(sys.argv						)):
							lowerCAmelCase__      :		str    							=      []

							if args_filename:
								args_files.append(Path(__snake_case						)						)
							elif look_for_args_file and len(sys.argv						):
								args_files.append(Path(sys.argv[0]						).with_suffix('''.args'''						)						)

							# args files specified via command line flag should overwrite default args files so we add them last
							if args_file_flag:
								# Create special parser just to extract the args_file_flag values
								lowerCAmelCase__      :		Dict    							=      ArgumentParser()
								args_file_parser.add_argument(__snake_case  ,type=__snake_case  ,action='''append'''						)

								# Use only remaining args for further parsing (remove the args_file_flag)
								lowerCAmelCase__      :		Union[str, Any]    							=      args_file_parser.parse_known_args(args=__snake_case						)
								lowerCAmelCase__      :		Any    							=      vars(__snake_case						).get(args_file_flag.lstrip('''-'''						)  ,__snake_case						)

								if cmd_args_file_paths:
									args_files.extend([Path(__snake_case						) for p in cmd_args_file_paths]						)

							lowerCAmelCase__      :		int    							=      []
							for args_file in args_files:
								if args_file.exists():
									file_args += args_file.read_text().split()

            # in case of duplicate arguments the last one has precedence
            # args specified via the command line should overwrite args from files, so we add them last
							lowerCAmelCase__      :		List[str]    							=      file_args + args if args is not None else file_args + sys.argv[1:]
						lowerCAmelCase__      :		Optional[Any]    							=      self.parse_known_args(args=__snake_case						)
						lowerCAmelCase__      :		List[Any]    							=      []
						for dtype in self.dataclass_types:
							lowerCAmelCase__      :		Optional[Any]    							=      {f.name for f in dataclasses.fields(__snake_case						) if f.init}
							lowerCAmelCase__      :		List[Any]    							=      {k: v for k, v in vars(__snake_case						).items() if k in keys}
							for k in keys:
								delattr(__snake_case  ,__snake_case						)
							lowerCAmelCase__      :		Dict    							=      dtype(**__snake_case						)
							outputs.append(__snake_case						)
						if len(namespace.__dict__						) > 0:
							# additional namespace.
							outputs.append(__snake_case						)
						if return_remaining_strings:
							return (*outputs, remaining_args)
						else:
							if remaining_args:
								raise ValueError(F'Some specified arguments are not used by the HfArgumentParser: {remaining_args}'						)

							return (*outputs,)







					def 			__lowerCAmelCase					(			self     :							List[Any]  ,lowercase_     :							Dict[str, Any]  ,lowercase_     :							bool = False						):
						lowerCAmelCase__      :		List[Any]    							=      set(args.keys()						)
						lowerCAmelCase__      :		Dict    							=      []
						for dtype in self.dataclass_types:
							lowerCAmelCase__      :		int    							=      {f.name for f in dataclasses.fields(__snake_case						) if f.init}
							lowerCAmelCase__      :		Union[str, Any]    							=      {k: v for k, v in args.items() if k in keys}
							unused_keys.difference_update(inputs.keys()						)
							lowerCAmelCase__      :		Optional[int]    							=      dtype(**__snake_case						)
							outputs.append(__snake_case						)
						if not allow_extra_keys and unused_keys:
							raise ValueError(F'Some keys are not used by the HfArgumentParser: {sorted(__snake_case						)}'						)
						return tuple(__snake_case						)







					def 			__lowerCAmelCase					(			self     :							Union[str, Any]  ,lowercase_     :							str  ,lowercase_     :							bool = False						):
						with open(Path(__snake_case						)  ,encoding='''utf-8'''						) as open_json_file:
							lowerCAmelCase__      :		List[Any]    							=      json.loads(open_json_file.read()						)
						lowerCAmelCase__      :		Optional[Any]    							=      self.parse_dict(__snake_case  ,allow_extra_keys=__snake_case						)
						return tuple(__snake_case						)







					def 			__lowerCAmelCase					(			self     :							Optional[int]  ,lowercase_     :							str  ,lowercase_     :							bool = False						):
						lowerCAmelCase__      :		Optional[int]    							=      self.parse_dict(yaml.safe_load(Path(__snake_case						).read_text()						)  ,allow_extra_keys=__snake_case						)
						return tuple(__snake_case						)












"""simple docstring"""





import unittest

from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device

from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
							import torch

							from transformers.models.esm.modeling_esmfold import EsmForProteinFolding



class       __A		:

					def __init__(			self  :      str     ,		__snake_case  :      int     ,		__snake_case  :      Dict=1_3     ,		__snake_case  :      Dict=7     ,		__snake_case  :      str=False     ,		__snake_case  :      Dict=True     ,		__snake_case  :      Tuple=False     ,		__snake_case  :      List[Any]=False     ,		__snake_case  :      Dict=1_9     ,		__snake_case  :      Dict=3_2     ,		__snake_case  :      Union[str, Any]=5     ,		__snake_case  :      List[Any]=4     ,		__snake_case  :      List[Any]=3_7     ,		__snake_case  :      Union[str, Any]="gelu"     ,		__snake_case  :      List[str]=0.1     ,		__snake_case  :      Union[str, Any]=0.1     ,		__snake_case  :      List[str]=5_1_2     ,		__snake_case  :      List[str]=1_6     ,		__snake_case  :      Tuple=2     ,		__snake_case  :      Optional[Any]=0.02     ,		__snake_case  :      str=3     ,		__snake_case  :      List[str]=4     ,		__snake_case  :      Optional[int]=None     ,		)			->							Optional[int]:
											__magic_name__:	Any							=       parent
											__magic_name__:	Optional[Any]							=       batch_size
											__magic_name__:	Optional[Any]							=       seq_length
											__magic_name__:	Optional[Any]							=       is_training
											__magic_name__:	str							=       use_input_mask
											__magic_name__:	Optional[Any]							=       use_token_type_ids
											__magic_name__:	List[str]							=       use_labels
											__magic_name__:	List[str]							=       vocab_size
											__magic_name__:	Union[str, Any]							=       hidden_size
											__magic_name__:	List[Any]							=       num_hidden_layers
											__magic_name__:	Dict							=       num_attention_heads
											__magic_name__:	int							=       intermediate_size
											__magic_name__:	List[Any]							=       hidden_act
											__magic_name__:	int							=       hidden_dropout_prob
											__magic_name__:	List[str]							=       attention_probs_dropout_prob
											__magic_name__:	Tuple							=       max_position_embeddings
											__magic_name__:	Any							=       type_vocab_size
											__magic_name__:	Union[str, Any]							=       type_sequence_label_size
											__magic_name__:	List[str]							=       initializer_range
											__magic_name__:	Optional[Any]							=       num_labels
											__magic_name__:	List[str]							=       num_choices
											__magic_name__:	Tuple							=       scope

					def   lowerCamelCase__   (			self  :      Optional[int]					)			->							Any:
											__magic_name__:	Union[str, Any]							=       ids_tensor([self.batch_size, self.seq_length]     ,		self.vocab_size					)

											__magic_name__:	Dict							=       None
											if self.use_input_mask:
																	__magic_name__:	Optional[int]							=       random_attention_mask([self.batch_size, self.seq_length]					)

											__magic_name__:	str							=       None
											__magic_name__:	Optional[Any]							=       None
											__magic_name__:	int							=       None
											if self.use_labels:
																	__magic_name__:	List[Any]							=       ids_tensor([self.batch_size]     ,		self.type_sequence_label_size					)
																	__magic_name__:	str							=       ids_tensor([self.batch_size, self.seq_length]     ,		self.num_labels					)
																	__magic_name__:	Dict							=       ids_tensor([self.batch_size]     ,		self.num_choices					)

											__magic_name__:	Dict							=       self.get_config()

											return config, input_ids, input_mask, sequence_labels, token_labels, choice_labels

					def   lowerCamelCase__   (			self  :      int					)			->							Any:
											__magic_name__:	List[Any]							=       EsmConfig(
											    vocab_size=3_3     ,		hidden_size=self.hidden_size     ,		pad_token_id=1     ,		num_hidden_layers=self.num_hidden_layers     ,		num_attention_heads=self.num_attention_heads     ,		intermediate_size=self.intermediate_size     ,		hidden_act=self.hidden_act     ,		hidden_dropout_prob=self.hidden_dropout_prob     ,		attention_probs_dropout_prob=self.attention_probs_dropout_prob     ,		max_position_embeddings=self.max_position_embeddings     ,		type_vocab_size=self.type_vocab_size     ,		initializer_range=self.initializer_range     ,		is_folding_model=__snake_case     ,		esmfold_config={"""trunk""": {"""num_blocks""": 2}, """fp16_esm""": False}     ,		)
											return config

					def   lowerCamelCase__   (			self  :      Optional[int]     ,		__snake_case  :      Optional[Any]     ,		__snake_case  :      Optional[Any]     ,		__snake_case  :      Any     ,		__snake_case  :      List[Any]     ,		__snake_case  :      Any     ,		__snake_case  :      Union[str, Any]					)			->							Optional[Any]:
											__magic_name__:	str							=       EsmForProteinFolding(config=__snake_case					).float()
											model.to(__snake_case					)
											model.eval()
											__magic_name__:	str							=       model(__snake_case     ,		attention_mask=__snake_case					)
											__magic_name__:	Any							=       model(__snake_case					)
											__magic_name__:	Dict							=       model(__snake_case					)

											self.parent.assertEqual(result.positions.shape     ,		(8, self.batch_size, self.seq_length, 1_4, 3)					)
											self.parent.assertEqual(result.angles.shape     ,		(8, self.batch_size, self.seq_length, 7, 2)					)






					def   lowerCamelCase__   (			self  :      Any					)			->							int:
											__magic_name__:	str							=       self.prepare_config_and_inputs()
											(
											    (
											    __magic_name__
											),			(
											    __magic_name__
											),			(
											    __magic_name__
											),			(
											    __magic_name__
											),			(
											    __magic_name__
											),			(
											    __magic_name__
											),			
											):	Union[str, Any]							=       config_and_inputs
											__magic_name__:	Any							=       {"""input_ids""": input_ids, """attention_mask""": input_mask}
											return config, inputs_dict



@require_torch
class       __A		(   SCREAMING_SNAKE_CASE_     ,SCREAMING_SNAKE_CASE_     ,unittest.TestCase			):
					UpperCAmelCase__								=				False

					UpperCAmelCase__								=				(EsmForProteinFolding,) if is_torch_available() else ()
					UpperCAmelCase__								=				()
					UpperCAmelCase__								=				{} if is_torch_available() else {}
					UpperCAmelCase__								=				False

					def   lowerCamelCase__   (			self  :      List[Any]					)			->							Optional[Any]:
											__magic_name__:	Optional[int]							=       EsmFoldModelTester(self					)
											__magic_name__:	Optional[Any]							=       ConfigTester(self     ,		config_class=__snake_case     ,		hidden_size=3_7					)

					def   lowerCamelCase__   (			self  :      Optional[int]					)			->							Any:
											self.config_tester.run_common_tests()

					def   lowerCamelCase__   (			self  :      List[str]					)			->							str:
											__magic_name__:	Tuple							=       self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_model(*__snake_case					)

					@unittest.skip("""Does not support attention outputs"""					)
					def   lowerCamelCase__   (			self  :      List[str]					)			->							str:
											pass

					@unittest.skip
					def   lowerCamelCase__   (			self  :      List[Any]					)			->							Tuple:
											pass

					@unittest.skip("""Esm does not support embedding resizing"""					)
					def   lowerCamelCase__   (			self  :      List[Any]					)			->							Optional[int]:
											pass

					@unittest.skip("""Esm does not support embedding resizing"""					)
					def   lowerCamelCase__   (			self  :      str					)			->							str:
											pass

					@unittest.skip("""ESMFold does not support passing input embeds!"""					)
					def   lowerCamelCase__   (			self  :      Optional[int]					)			->							List[Any]:
											pass

					@unittest.skip("""ESMFold does not support head pruning."""					)
					def   lowerCamelCase__   (			self  :      Any					)			->							List[str]:
											pass

					@unittest.skip("""ESMFold does not support head pruning."""					)
					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							List[Any]:
											pass

					@unittest.skip("""ESMFold does not support head pruning."""					)
					def   lowerCamelCase__   (			self  :      int					)			->							Tuple:
											pass

					@unittest.skip("""ESMFold does not support head pruning."""					)
					def   lowerCamelCase__   (			self  :      Optional[int]					)			->							Optional[Any]:
											pass

					@unittest.skip("""ESMFold does not support head pruning."""					)
					def   lowerCamelCase__   (			self  :      Optional[Any]					)			->							Optional[Any]:
											pass

					@unittest.skip("""ESMFold does not output hidden states in the normal way."""					)
					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							List[Any]:
											pass

					@unittest.skip("""ESMfold does not output hidden states in the normal way."""					)
					def   lowerCamelCase__   (			self  :      Any					)			->							int:
											pass

					@unittest.skip("""ESMFold only has one output format."""					)
					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							str:
											pass

					@unittest.skip("""This test doesn't work for ESMFold and doesn't test core functionality"""					)
					def   lowerCamelCase__   (			self  :      List[Any]					)			->							Dict:
											pass

					@unittest.skip("""ESMFold does not support input chunking."""					)
					def   lowerCamelCase__   (			self  :      int					)			->							Any:
											pass

					@unittest.skip("""ESMFold doesn't respect you and it certainly doesn't respect your initialization arguments."""					)
					def   lowerCamelCase__   (			self  :      int					)			->							Union[str, Any]:
											pass

					@unittest.skip("""ESMFold doesn't support torchscript compilation."""					)
					def   lowerCamelCase__   (			self  :      Any					)			->							Optional[Any]:
											pass

					@unittest.skip("""ESMFold doesn't support torchscript compilation."""					)
					def   lowerCamelCase__   (			self  :      Optional[int]					)			->							int:
											pass

					@unittest.skip("""ESMFold doesn't support torchscript compilation."""					)
					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							List[str]:
											pass

					@unittest.skip("""ESMFold doesn't support data parallel."""					)
					def   lowerCamelCase__   (			self  :      List[str]					)			->							str:
											pass






					@unittest.skip("""Will be fixed soon by reducing the size of the model used for common tests."""					)
					def   lowerCamelCase__   (			self  :      Union[str, Any]					)			->							Dict:
											pass



@require_torch
class       __A		(   SCREAMING_SNAKE_CASE_			):

					@slow
					def   lowerCamelCase__   (			self  :      Optional[Any]					)			->							List[Any]:
											__magic_name__:	Any							=       EsmForProteinFolding.from_pretrained("""facebook/esmfold_v1"""					).float()
											model.eval()
											__magic_name__:	Optional[int]							=       torch.tensor([[0, 6, 4, 1_3, 5, 4, 1_6, 1_2, 1_1, 7, 2]]					)
											__magic_name__:	Dict							=       model(__snake_case					)["""positions"""]
											__magic_name__:	Tuple							=       torch.tensor([2.5828, 0.7993, -10.9334]     ,		dtype=torch.floataa					)
											self.assertTrue(torch.allclose(position_outputs[0, 0, 0, 0]     ,		__snake_case     ,		atol=1E-4					)					)



