






import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase								=		get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
							from transformers.models.plbart.modeling_plbart import shift_tokens_right

UpperCamelCase								=		50_003
UpperCamelCase								=		50_002

@require_sentencepiece
@require_tokenizers
class 				lowerCAmelCase_	(		__snake_case   ,		unittest.TestCase			):
				_UpperCamelCase					:       List[Any]							       = PLBartTokenizer
				_UpperCamelCase					:       Tuple							       = None
				_UpperCamelCase					:       int							       = False


				def 						__a					(					self      ):
											super().setUp()

											# We have a SentencePiece fixture for testing
											_lowercase							:   List[Any] 							=   PLBartTokenizer(_lowerCAmelCase ,						language_codes='base' ,						keep_accents=_lowerCAmelCase      )
											tokenizer.save_pretrained(self.tmpdirname      )


				def 						__a					(					self      ):
											_lowercase							:   Tuple 							=   PLBartTokenizer(_lowerCAmelCase ,						language_codes='base' ,						keep_accents=_lowerCAmelCase      )

											_lowercase							:   Dict 							=   tokenizer.tokenize('This is a test'      )
											self.assertListEqual(_lowerCAmelCase ,						['▁This', '▁is', '▁a', '▁t', 'est']      )

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(_lowerCAmelCase      ) ,						[value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]] ,						)

											_lowercase							:   Any 							=   tokenizer.tokenize('I was born in 92000, and this is falsé.'      )
											self.assertListEqual(
											    _lowerCAmelCase ,						[
											        SPIECE_UNDERLINE + 'I',
											        SPIECE_UNDERLINE + 'was',
											        SPIECE_UNDERLINE + 'b',
											        'or',
											        'n',
											        SPIECE_UNDERLINE + 'in',
											        SPIECE_UNDERLINE + '',
											        '9',
											        '2',
											        '0',
											        '0',
											        '0',
											        ',',
											        SPIECE_UNDERLINE + 'and',
											        SPIECE_UNDERLINE + 'this',
											        SPIECE_UNDERLINE + 'is',
											        SPIECE_UNDERLINE + 'f',
											        'al',
											        's',
											        'é',
											        '.',
											    ] ,						)
											_lowercase							:   Optional[Any] 							=   tokenizer.convert_tokens_to_ids(_lowerCAmelCase      )
											self.assertListEqual(
											    _lowerCAmelCase ,						[
											        value + tokenizer.fairseq_offset
											        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
											    ] ,						)

											_lowercase							:   Tuple 							=   tokenizer.convert_ids_to_tokens(_lowerCAmelCase      )
											self.assertListEqual(
											    _lowerCAmelCase ,						[
											        SPIECE_UNDERLINE + 'I',
											        SPIECE_UNDERLINE + 'was',
											        SPIECE_UNDERLINE + 'b',
											        'or',
											        'n',
											        SPIECE_UNDERLINE + 'in',
											        SPIECE_UNDERLINE + '',
											        '<unk>',
											        '2',
											        '0',
											        '0',
											        '0',
											        ',',
											        SPIECE_UNDERLINE + 'and',
											        SPIECE_UNDERLINE + 'this',
											        SPIECE_UNDERLINE + 'is',
											        SPIECE_UNDERLINE + 'f',
											        'al',
											        's',
											        '<unk>',
											        '.',
											    ] ,						)

											_lowercase							:   str 							=   tokenizer.vocab_size
											_lowercase							:   List[Any] 							=   [tokenizer.convert_ids_to_tokens(_lowerCAmelCase      ) for x in range(end - 4 ,						_lowerCAmelCase      )]

											self.assertListEqual(_lowerCAmelCase ,						['__java__', '__python__', '__en_XX__', '<mask>']      )

											_lowercase							:   Optional[Any] 							=   'java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'
											_lowercase							:   str 							=   tokenizer(_lowerCAmelCase      ).input_ids
											self.assertEqual(
											    tokenizer.decode(_lowerCAmelCase ,						skip_special_tokens=_lowerCAmelCase ,						clean_up_tokenization_spaces=_lowerCAmelCase      ) ,						_lowerCAmelCase ,						)


				def 						__a					(					self      ):
											_lowercase							:   Union[str, Any] 							=   PLBartTokenizer(_lowerCAmelCase ,						language_codes='multi' ,						keep_accents=_lowerCAmelCase      )

											_lowercase							:   Dict 							=   tokenizer.tokenize('This is a test'      )
											self.assertListEqual(_lowerCAmelCase ,						['▁This', '▁is', '▁a', '▁t', 'est']      )

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(_lowerCAmelCase      ) ,						[value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]] ,						)

											_lowercase							:   str 							=   tokenizer.tokenize('I was born in 92000, and this is falsé.'      )
											self.assertListEqual(
											    _lowerCAmelCase ,						[
											        SPIECE_UNDERLINE + 'I',
											        SPIECE_UNDERLINE + 'was',
											        SPIECE_UNDERLINE + 'b',
											        'or',
											        'n',
											        SPIECE_UNDERLINE + 'in',
											        SPIECE_UNDERLINE + '',
											        '9',
											        '2',
											        '0',
											        '0',
											        '0',
											        ',',
											        SPIECE_UNDERLINE + 'and',
											        SPIECE_UNDERLINE + 'this',
											        SPIECE_UNDERLINE + 'is',
											        SPIECE_UNDERLINE + 'f',
											        'al',
											        's',
											        'é',
											        '.',
											    ] ,						)
											_lowercase							:   Dict 							=   tokenizer.convert_tokens_to_ids(_lowerCAmelCase      )
											self.assertListEqual(
											    _lowerCAmelCase ,						[
											        value + tokenizer.fairseq_offset
											        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
											    ] ,						)

											_lowercase							:   Any 							=   tokenizer.convert_ids_to_tokens(_lowerCAmelCase      )
											self.assertListEqual(
											    _lowerCAmelCase ,						[
											        SPIECE_UNDERLINE + 'I',
											        SPIECE_UNDERLINE + 'was',
											        SPIECE_UNDERLINE + 'b',
											        'or',
											        'n',
											        SPIECE_UNDERLINE + 'in',
											        SPIECE_UNDERLINE + '',
											        '<unk>',
											        '2',
											        '0',
											        '0',
											        '0',
											        ',',
											        SPIECE_UNDERLINE + 'and',
											        SPIECE_UNDERLINE + 'this',
											        SPIECE_UNDERLINE + 'is',
											        SPIECE_UNDERLINE + 'f',
											        'al',
											        's',
											        '<unk>',
											        '.',
											    ] ,						)
											_lowercase							:   int 							=   tokenizer.vocab_size
											_lowercase							:   Union[str, Any] 							=   [tokenizer.convert_ids_to_tokens(_lowerCAmelCase      ) for x in range(end - 7 ,						_lowerCAmelCase      )]

											self.assertListEqual(
											    _lowerCAmelCase ,						['__java__', '__python__', '__en_XX__', '__javascript__', '__php__', '__ruby__', '__go__']      )
											_lowercase							:   Any 							=   'java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'
											_lowercase							:   List[Any] 							=   tokenizer(_lowerCAmelCase      ).input_ids
											self.assertEqual(
											    tokenizer.decode(_lowerCAmelCase ,						skip_special_tokens=_lowerCAmelCase ,						clean_up_tokenization_spaces=_lowerCAmelCase      ) ,						_lowerCAmelCase ,						)




@require_torch
@require_sentencepiece
@require_tokenizers
class 				lowerCAmelCase_	(		unittest.TestCase			):
				_UpperCamelCase					:       Optional[Any]							       = "uclanlp/plbart-python-en_XX"
				_UpperCamelCase					:       Dict							       = [
				    "def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])",
				    "def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])",
				]
				_UpperCamelCase					:       List[str]							       = [
				    "Returns the maximum value of a b c.",
				    "Sums the values of a b c.",
				]
				_UpperCamelCase					:       Optional[Any]							       = [
				    134,
				    5452,
				    33460,
				    33441,
				    33463,
				    33465,
				    33463,
				    33449,
				    988,
				    20,
				    33456,
				    19,
				    33456,
				    771,
				    39,
				    4258,
				    889,
				    3318,
				    33441,
				    33463,
				    33465,
				    33463,
				    33449,
				    2471,
				    2,
				    PYTHON_CODE,
				]


				@classmethod
				def 						__a					(					cls      ):
											_lowercase							:   PLBartTokenizer 							=   PLBartTokenizer.from_pretrained(
											    cls.checkpoint_name ,						language_codes='base' ,						src_lang='python' ,						tgt_lang='en_XX'      )
											_lowercase							:   Optional[Any] 							=   1
											return cls


				def 						__a					(					self      ):
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__java__'] ,						5_0_0_0_1      )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__python__'] ,						5_0_0_0_2      )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__en_XX__'] ,						5_0_0_0_3      )


				def 						__a					(					self      ):
											_lowercase							:   Any 							=   self.tokenizer.batch_encode_plus(self.src_text      ).input_ids[0]
											self.assertListEqual(self.expected_src_tokens ,						_lowerCAmelCase      )


				def 						__a					(					self      ):
											self.assertIn(_lowerCAmelCase ,						self.tokenizer.all_special_ids      )
											_lowercase							:   Any 							=   [EN_CODE, 9_0_3_7, 3_3_4_4_2, 5_7, 7_5_2, 1_5_3, 1_4, 5_6, 1_8, 9, 2]
											_lowercase							:   Optional[int] 							=   self.tokenizer.decode(_lowerCAmelCase ,						skip_special_tokens=_lowerCAmelCase      )
											_lowercase							:   str 							=   self.tokenizer.decode(generated_ids[1:] ,						skip_special_tokens=_lowerCAmelCase      )
											self.assertEqual(_lowerCAmelCase ,						_lowerCAmelCase      )
											self.assertNotIn(self.tokenizer.eos_token ,						_lowerCAmelCase      )


				def 						__a					(					self      ):
											_lowercase							:   Optional[Any] 							=   ['def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])' * 2_0]
											self.assertIsInstance(src_text[0] ,						_lowerCAmelCase      )
											_lowercase							:   List[str] 							=   1_0
											_lowercase							:   List[str] 							=   self.tokenizer(_lowerCAmelCase ,						max_length=_lowerCAmelCase ,						truncation=_lowerCAmelCase      ).input_ids[0]
											self.assertEqual(ids[-2] ,						2      )
											self.assertEqual(ids[-1] ,						_lowerCAmelCase      )
											self.assertEqual(len(_lowerCAmelCase      ) ,						_lowerCAmelCase      )


				def 						__a					(					self      ):
											self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', '__java__']      ) ,						[5_0_0_0_4, 5_0_0_0_1]      )


				def 						__a					(					self      ):
											_lowercase							:   Tuple 							=   tempfile.mkdtemp()
											_lowercase							:   Tuple 							=   self.tokenizer.fairseq_tokens_to_ids
											self.tokenizer.save_pretrained(_lowerCAmelCase      )
											_lowercase							:   Any 							=   PLBartTokenizer.from_pretrained(_lowerCAmelCase      )
											self.assertDictEqual(new_tok.fairseq_tokens_to_ids ,						_lowerCAmelCase      )


				@require_torch
				def 						__a					(					self      ):
											_lowercase							:   List[Any] 							=   self.tokenizer(self.src_text ,						text_target=self.tgt_text ,						padding=_lowerCAmelCase ,						return_tensors='pt'      )
											_lowercase							:   Optional[int] 							=   shift_tokens_right(batch['labels'] ,						self.tokenizer.pad_token_id      )

											# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
											self.assertEqual(batch.input_ids[1][-2:].tolist() ,						[2, PYTHON_CODE]      )
											self.assertEqual(batch.decoder_input_ids[1][0] ,						_lowerCAmelCase      )
											self.assertEqual(batch.decoder_input_ids[1][-1] ,						2      )
											self.assertEqual(batch.labels[1][-2:].tolist() ,						[2, EN_CODE]      )


				@require_torch
				def 						__a					(					self      ):
											_lowercase							:   int 							=   self.tokenizer(
											    self.src_text ,						text_target=self.tgt_text ,						padding=_lowerCAmelCase ,						truncation=_lowerCAmelCase ,						max_length=len(self.expected_src_tokens      ) ,						return_tensors='pt' ,						)
											_lowercase							:   List[str] 							=   shift_tokens_right(batch['labels'] ,						self.tokenizer.pad_token_id      )

											self.assertIsInstance(_lowerCAmelCase ,						_lowerCAmelCase      )

											self.assertEqual((2, 2_6) ,						batch.input_ids.shape      )
											self.assertEqual((2, 2_6) ,						batch.attention_mask.shape      )
											_lowercase							:   Tuple 							=   batch.input_ids.tolist()[0]
											self.assertListEqual(self.expected_src_tokens ,						_lowerCAmelCase      )
											self.assertEqual(2 ,						batch.decoder_input_ids[0, -1]      )  # EOS
											# Test that special tokens are reset
											self.assertEqual(self.tokenizer.prefix_tokens ,						[]      )
											self.assertEqual(self.tokenizer.suffix_tokens ,						[self.tokenizer.eos_token_id, PYTHON_CODE]      )


				def 						__a					(					self      ):
											_lowercase							:   List[str] 							=   self.tokenizer(self.src_text ,						padding=_lowerCAmelCase ,						truncation=_lowerCAmelCase ,						max_length=3 ,						return_tensors='pt'      )
											_lowercase							:   int 							=   self.tokenizer(
											    text_target=self.tgt_text ,						padding=_lowerCAmelCase ,						truncation=_lowerCAmelCase ,						max_length=1_0 ,						return_tensors='pt'      )
											_lowercase							:   Any 							=   targets['input_ids']
											_lowercase							:   Optional[int] 							=   shift_tokens_right(_lowerCAmelCase ,						self.tokenizer.pad_token_id      )

											self.assertEqual(batch.input_ids.shape[1] ,						3      )
											self.assertEqual(batch.decoder_input_ids.shape[1] ,						1_0      )


				@require_torch
				def 						__a					(					self      ):
											_lowercase							:   Tuple 							=   self.tokenizer._build_translation_inputs(
											    'A test' ,						return_tensors='pt' ,						src_lang='en_XX' ,						tgt_lang='java'      )

											self.assertEqual(
											    nested_simplify(_lowerCAmelCase      ) ,						{
											        # A, test, EOS, en_XX
											        'input_ids': [[1_5_0, 2_4_2, 2, 5_0_0_0_3]],
											        'attention_mask': [[1, 1, 1, 1]],
											        # java
											        'forced_bos_token_id': 5_0_0_0_1,
											    } ,						)












import copy
from typing import Dict, List, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


UpperCAmelCase__      			=						{
    '''facebook/mask2former-swin-small-coco-instance''': (
        '''https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json'''
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

UpperCAmelCase__      			=						logging.get_logger(__name__)




class 							snake_case_       (    __UpperCamelCase      ):

						"""simple docstring"""



						snake_case__        =      """mask2former"""
						snake_case__        =      ["""swin"""]
						snake_case__        =      {"""hidden_size""": """hidden_dim"""}



						def __init__(self:					Any ,					__UpperCAmelCase:					Optional[Dict] = None ,					__UpperCAmelCase:					int = 256 ,					__UpperCAmelCase:					int = 256 ,					__UpperCAmelCase:					int = 256 ,					__UpperCAmelCase:					int = 1024 ,					__UpperCAmelCase:					str = "relu" ,					__UpperCAmelCase:					int = 6 ,					__UpperCAmelCase:					int = 10 ,					__UpperCAmelCase:					int = 8 ,					__UpperCAmelCase:					float = 0.0 ,					__UpperCAmelCase:					int = 2048 ,					__UpperCAmelCase:					bool = False ,					__UpperCAmelCase:					bool = False ,					__UpperCAmelCase:					int = 4 ,					__UpperCAmelCase:					int = 255 ,					__UpperCAmelCase:					int = 100 ,					__UpperCAmelCase:					float = 0.1 ,					__UpperCAmelCase:					float = 2.0 ,					__UpperCAmelCase:					float = 5.0 ,					__UpperCAmelCase:					float = 5.0 ,					__UpperCAmelCase:					int = 12544 ,					__UpperCAmelCase:					float = 3.0 ,					__UpperCAmelCase:					float = 0.75 ,					__UpperCAmelCase:					float = 0.02 ,					__UpperCAmelCase:					float = 1.0 ,					__UpperCAmelCase:					bool = True ,					__UpperCAmelCase:					List[int] = [4, 8, 16, 32] ,					__UpperCAmelCase:					bool = None ,					**__UpperCAmelCase:					Any ,					)    ->     int:




											'''simple docstring'''



											if backbone_config is None:
																logger.info("`backbone_config` is `None`. Initializing the config with the default `Swin` backbone."   )
																__a					:						str      =					CONFIG_MAPPING["swin"](
																    image_size=224 ,					in_channels=3 ,					patch_size=4 ,					embed_dim=96 ,					depths=[2, 2, 18, 2] ,					num_heads=[3, 6, 12, 24] ,					window_size=7 ,					drop_path_rate=0.3 ,					use_absolute_embeddings=__UpperCAmelCase ,					out_features=["stage1", "stage2", "stage3", "stage4"] ,					)

											if isinstance(__UpperCAmelCase ,					__UpperCAmelCase   ):
																__a					:						List[Any]      =					backbone_config.pop("model_type"   )
																__a					:						List[str]      =					CONFIG_MAPPING[backbone_model_type]
																__a					:						Dict      =					config_class.from_dict(__UpperCAmelCase   )

											# verify that the backbone is supported
											if backbone_config.model_type not in self.backbones_supported:
																logger.warning_once(
																    f'Backbone {backbone_config.model_type} is not a supported model and may not be compatible with Mask2Former. '
																    f'Supported model types: {",".join(self.backbones_supported   )}'   )

											__a					:						Tuple      =					backbone_config
											__a					:						Any      =					feature_size
											__a					:						int      =					mask_feature_size
											__a					:						Optional[int]      =					hidden_dim
											__a					:						int      =					encoder_feedforward_dim
											__a					:						List[str]      =					activation_function
											__a					:						Optional[Any]      =					encoder_layers
											__a					:						List[Any]      =					decoder_layers
											__a					:						Union[str, Any]      =					num_attention_heads
											__a					:						Optional[Any]      =					dropout
											__a					:						Tuple      =					dim_feedforward
											__a					:						List[str]      =					pre_norm
											__a					:						int      =					enforce_input_projection
											__a					:						List[str]      =					common_stride
											__a					:						Any      =					ignore_value
											__a					:						Union[str, Any]      =					num_queries
											__a					:						int      =					no_object_weight
											__a					:						Tuple      =					class_weight
											__a					:						int      =					mask_weight
											__a					:						Union[str, Any]      =					dice_weight
											__a					:						int      =					train_num_points
											__a					:						Any      =					oversample_ratio
											__a					:						Any      =					importance_sample_ratio
											__a					:						List[str]      =					init_std
											__a					:						List[str]      =					init_xavier_std
											__a					:						Dict      =					use_auxiliary_loss
											__a					:						List[Any]      =					feature_strides
											__a					:						Tuple      =					output_auxiliary_logits
											__a					:						List[Any]      =					decoder_layers

											super().__init__(**__UpperCAmelCase   )



						@classmethod
						def        UpperCAmelCase__					(cls:					Tuple ,					__UpperCAmelCase:					PretrainedConfig ,					**__UpperCAmelCase:					List[str]   )    ->     Any:




											'''simple docstring'''



											return cls(
											    backbone_config=__UpperCAmelCase ,					**__UpperCAmelCase ,					)



						def        UpperCAmelCase__					(self:					str   )    ->     Dict[str, any]:




											'''simple docstring'''



											__a					:						Tuple      =					copy.deepcopy(self.__dict__   )
											__a					:						List[str]      =					self.backbone_config.to_dict()
											__a					:						Any      =					self.__class__.model_type
											return output





