


"""simple docstring"""







import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a__       :							Tuple        =  get_tests_dir('''fixtures/test_sentencepiece.model''')




@require_sentencepiece
@require_tokenizers
class 				UpperCamelCase_			(				UpperCamelCase    ,						unittest.TestCase):

	"""simple docstring"""





	snake_case__       :						str					      =    XGLMTokenizer
	snake_case__       :						int					      =    XGLMTokenizerFast
	snake_case__       :						List[Any]					      =    True
	snake_case__       :						Union[str, Any]					      =    True




	def 						UpperCAmelCase_   (				self    :       int     ) ->			Tuple:
						super().setUp()

						# We have a SentencePiece fixture for testing
						__SCREAMING_SNAKE_CASE		     =       XGLMTokenizer(UpperCAmelCase__    ,    keep_accents=UpperCAmelCase__     )
						tokenizer.save_pretrained(self.tmpdirname     )




	def 						UpperCAmelCase_   (				self    :       Dict     ) ->			Any:
						__SCREAMING_SNAKE_CASE		     =       "<pad>"
						__SCREAMING_SNAKE_CASE		     =       1

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase__     )    ,    UpperCAmelCase__     )
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase__     )    ,    UpperCAmelCase__     )




	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			Any:
						__SCREAMING_SNAKE_CASE		     =       list(self.get_tokenizer().get_vocab().keys()     )

						self.assertEqual(vocab_keys[0]    ,    "<s>"     )
						self.assertEqual(vocab_keys[1]    ,    "<pad>"     )
						self.assertEqual(len(UpperCAmelCase__     )    ,    1_0_0_8     )




	def 						UpperCAmelCase_   (				self    :       str     ) ->			Optional[int]:
						self.assertEqual(self.get_tokenizer().vocab_size    ,    1_0_0_8     )




	def 						UpperCAmelCase_   (				self    :       int     ) ->			Union[str, Any]:
						__SCREAMING_SNAKE_CASE		     =       XGLMTokenizer(UpperCAmelCase__    ,    keep_accents=UpperCAmelCase__     )

						__SCREAMING_SNAKE_CASE		     =       tokenizer.tokenize("This is a test"     )
						self.assertListEqual(UpperCAmelCase__    ,    ["▁This", "▁is", "▁a", "▁t", "est"]     )

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

						__SCREAMING_SNAKE_CASE		     =       tokenizer.tokenize("I was born in 92000, and this is falsé."     )
						self.assertListEqual(
						    UpperCAmelCase__    ,    [
						        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",
						        ".",
						    ]    ,    )
						__SCREAMING_SNAKE_CASE		     =       tokenizer.convert_tokens_to_ids(UpperCAmelCase__     )
						self.assertListEqual(
						    UpperCAmelCase__    ,    [
						        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]
						    ]    ,    )

						__SCREAMING_SNAKE_CASE		     =       tokenizer.convert_ids_to_tokens(UpperCAmelCase__     )
						self.assertListEqual(
						    UpperCAmelCase__    ,    [
						        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>",
						        ".",
						    ]    ,    )




	@cached_property
	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			str:
						return XGLMTokenizer.from_pretrained("facebook/xglm-564M"     )




	def 						UpperCAmelCase_   (				self    :       Union[str, Any]     ) ->			Dict:
						with tempfile.NamedTemporaryFile() as f:
											shutil.copyfile(UpperCAmelCase__    ,    f.name     )
											__SCREAMING_SNAKE_CASE		     =       XGLMTokenizer(f.name    ,    keep_accents=UpperCAmelCase__     )
											__SCREAMING_SNAKE_CASE		     =       pickle.dumps(UpperCAmelCase__     )
						pickle.loads(UpperCAmelCase__     )




	def 						UpperCAmelCase_   (				self    :       Union[str, Any]     ) ->			Union[str, Any]:
						if not self.test_rust_tokenizer:
											return

						__SCREAMING_SNAKE_CASE		     =       self.get_tokenizer()
						__SCREAMING_SNAKE_CASE		     =       self.get_rust_tokenizer()

						__SCREAMING_SNAKE_CASE		     =       "I was born in 92000, and this is falsé."

						__SCREAMING_SNAKE_CASE		     =       tokenizer.tokenize(UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       rust_tokenizer.tokenize(UpperCAmelCase__     )
						self.assertListEqual(UpperCAmelCase__    ,    UpperCAmelCase__     )

						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(UpperCAmelCase__    ,    add_special_tokens=UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       rust_tokenizer.encode(UpperCAmelCase__    ,    add_special_tokens=UpperCAmelCase__     )
						self.assertListEqual(UpperCAmelCase__    ,    UpperCAmelCase__     )

						__SCREAMING_SNAKE_CASE		     =       self.get_rust_tokenizer()
						__SCREAMING_SNAKE_CASE		     =       tokenizer.encode(UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       rust_tokenizer.encode(UpperCAmelCase__     )
						self.assertListEqual(UpperCAmelCase__    ,    UpperCAmelCase__     )




	@slow
	def 						UpperCAmelCase_   (				self    :       int     ) ->			Union[str, Any]:
						__SCREAMING_SNAKE_CASE		     =       "Hello World!"
						__SCREAMING_SNAKE_CASE		     =       [2, 3_1_2_2_7, 4_4_4_7, 3_5]

						self.assertListEqual(UpperCAmelCase__    ,    self.big_tokenizer.encode(UpperCAmelCase__     )     )




	@slow
	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			Tuple:
						__SCREAMING_SNAKE_CASE		     =       (
						    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
						    " add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth"
						)
						# fmt: off
						__SCREAMING_SNAKE_CASE		     =       [2, 1_0_1_8, 6_7, 1_1, 1_9_8_8, 2_6_1_7, 5_6_3_1, 2_7_8, 1_1, 3_4_0_7, 4_8, 7_1_6_3_0, 2_8_0_8_5, 4, 3_2_3_4, 1_5_7, 1_3, 6, 5, 6, 4, 3_5_2_6, 7_6_8, 1_5, 6_5_9, 5_7, 2_9_8, 3_9_8_3, 8_6_4, 1_2_9, 2_1, 6, 5, 1_3_6_7_5, 3_7_7, 6_5_2, 7_5_8_0, 1_0_3_4_1, 1_5_5, 2_8_1_7, 4_2_2, 1_6_6_6, 7, 1_6_7_4, 5_3, 1_1_3, 2_0_2_2_7_7, 1_7_8_9_2, 3_3, 6_0, 8_7, 4, 3_2_3_4, 1_5_7, 6_1, 2_6_6_7, 5_2_3_7_6, 1_9, 8_8, 2_3, 7_3_5]
						# fmt: on

						self.assertListEqual(UpperCAmelCase__    ,    self.big_tokenizer.encode(UpperCAmelCase__     )     )




	@slow
	def 						UpperCAmelCase_   (				self    :       Union[str, Any]     ) ->			List[Any]:
						# fmt: off
						__SCREAMING_SNAKE_CASE		     =       {
						    "input_ids": [[2, 1_0_8_8_2_5, 1_1_6_3, 1_5, 8_8_0_1_0, 4_7_3, 1_5_8_9_8, 1_5_7, 1_3_6_7_2, 1_8_5_7, 3_1_2, 8, 2_3_8_0_2_1, 1_1_6_3, 5_3, 1_3_6_7_2, 1_8_5_7, 3_1_2, 8, 5_3_2_8_3, 1_8_2_3_9_6, 8, 1_8_5_6_6, 1_6, 3_6_7_3_3, 4_1_0_1, 8, 2_3_0, 2_4_4_0_1_7, 1_2_2_5_5_3, 7, 1_5, 1_3_2_5_9_7, 4, 2_9_3, 1_2_5_1_1, 7_6_1_0, 4, 3_4_1_4, 1_3_2_5_9_7, 9, 4, 3_2_3_6_1, 3_6_2, 4, 7_3_4, 2_8_5_1_2, 3_2_5_6_9, 1_8, 4, 3_2_3_6_1, 2_6_0_9_6, 1_4_9_8_2, 7_3, 1_8_7_1_5, 2_1_4_3_3, 2_3_5_2_6_1, 1_5, 4_9_2, 1_2_4_2_7, 1_6, 5_3, 1_8_7_1_5, 2_1_4_3_3, 6_5_4_5_4, 1_5, 2_3_6_5_9, 5_6_3, 1_6, 2_7_8, 5_9_7, 2_8_4_3, 5_9_5, 7_9_3_1, 1_8_2_3_9_6, 6_4_1_8_6, 2_2, 8_8_6, 5_9_5, 1_3_2_9_8_1, 5_3, 2_5_5_4_0, 3_4_4_9, 4_3_9_8_2, 3_9_9_0_1, 5_9_5_1, 8_7_8, 3_3_0, 4, 2_7_6_9_4, 8_0_2_6_9, 3_1_2, 5_3, 6_5_1_7, 1_1_7_8_0, 6_1_1, 2_0_4_0_8, 5], [2, 6, 1_3_2_5_9_7, 6_7, 4_2_8_9_7, 3_3, 5_9_2, 8, 1_6_3_7_2_9, 2_5_5_4_0, 3_6_1, 1_3_6_9_9_7, 1_0_9_5_1_4, 1_7_3_2_3_0, 7, 5_0_1, 6_0, 1_0_2_9_1_3, 1_9_6, 5_6_3_1, 2_3_5, 6_3_2_4_3, 4_7_3, 6, 2_3_1_7_5_7, 7_4, 5_2_7_7, 7_9_0_5, 5_3, 3_0_9_5, 3_7_3_1_7, 2_2, 4_5_4, 1_8_3_8_7_4, 5], [2, 2_6_8, 3_1_2_9_8, 4_6_5_3_0, 6, 1_3_2_9_3_5, 4_3_8_3_1, 7, 5_9_7, 3_2, 2_4, 3_6_8_8, 9_8_6_5, 5]],
						    "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
						}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=UpperCAmelCase__    ,    model_name="facebook/xglm-564M"    ,    padding=UpperCAmelCase__    ,    )




"""simple docstring"""







import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig


a__       :							Dict        =  logging.get_logger(__name__)

a__       :							str        =  {
    '''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''',
    # See all DPT models at https://huggingface.co/models?filter=dpt
}




class 				UpperCamelCase_			(				UpperCamelCase):

	"""simple docstring"""





	snake_case__       :						Optional[Any]					      =    "dpt"




	def __init__(				self    :       Tuple    ,    UpperCAmelCase__    :       int=7_6_8    ,    UpperCAmelCase__    :       List[str]=1_2    ,    UpperCAmelCase__    :       Any=1_2    ,    UpperCAmelCase__    :       int=3_0_7_2    ,    UpperCAmelCase__    :       List[str]="gelu"    ,    UpperCAmelCase__    :       Union[str, Any]=0.0    ,    UpperCAmelCase__    :       Any=0.0    ,    UpperCAmelCase__    :       List[Any]=0.02    ,    UpperCAmelCase__    :       List[Any]=1E-12    ,    UpperCAmelCase__    :       List[str]=3_8_4    ,    UpperCAmelCase__    :       Tuple=1_6    ,    UpperCAmelCase__    :       Optional[Any]=3    ,    UpperCAmelCase__    :       str=False    ,    UpperCAmelCase__    :       Any=True    ,    UpperCAmelCase__    :       Optional[Any]=[2, 5, 8, 1_1]    ,    UpperCAmelCase__    :       Union[str, Any]="project"    ,    UpperCAmelCase__    :       Dict=[4, 2, 1, 0.5]    ,    UpperCAmelCase__    :       Optional[Any]=[9_6, 1_9_2, 3_8_4, 7_6_8]    ,    UpperCAmelCase__    :       List[str]=2_5_6    ,    UpperCAmelCase__    :       Optional[Any]=-1    ,    UpperCAmelCase__    :       Union[str, Any]=False    ,    UpperCAmelCase__    :       Any=True    ,    UpperCAmelCase__    :       Dict=0.4    ,    UpperCAmelCase__    :       Union[str, Any]=2_5_5    ,    UpperCAmelCase__    :       List[Any]=0.1    ,    UpperCAmelCase__    :       Optional[int]=[1, 1_0_2_4, 2_4, 2_4]    ,    UpperCAmelCase__    :       List[Any]=[0, 1]    ,    UpperCAmelCase__    :       List[str]=None    ,    **UpperCAmelCase__    :       List[Any]    ,    ) ->			Dict:
						super().__init__(**UpperCAmelCase__     )

						__SCREAMING_SNAKE_CASE		     =       hidden_size
						__SCREAMING_SNAKE_CASE		     =       is_hybrid

						if self.is_hybrid:
											if backbone_config is None:
																logger.info("Initializing the config with a `BiT` backbone."     )
																__SCREAMING_SNAKE_CASE		     =       {
																    "global_padding": "same",
																    "layer_type": "bottleneck",
																    "depths": [3, 4, 9],
																    "out_features": ["stage1", "stage2", "stage3"],
																    "embedding_dynamic_padding": True,
																}
																__SCREAMING_SNAKE_CASE		     =       BitConfig(**UpperCAmelCase__     )
											elif isinstance(UpperCAmelCase__    ,    UpperCAmelCase__     ):
																logger.info("Initializing the config with a `BiT` backbone."     )
																__SCREAMING_SNAKE_CASE		     =       BitConfig(**UpperCAmelCase__     )
											elif isinstance(UpperCAmelCase__    ,    UpperCAmelCase__     ):
																__SCREAMING_SNAKE_CASE		     =       backbone_config
											else:
																raise ValueError(
																    F"""backbone_config must be a dictionary or a `PretrainedConfig`, got {backbone_config.__class__}."""     )

											__SCREAMING_SNAKE_CASE		     =       backbone_featmap_shape
											__SCREAMING_SNAKE_CASE		     =       neck_ignore_stages

											if readout_type != "project":
																raise ValueError("Readout type must be 'project' when using `DPT-hybrid` mode."     )
						else:
											__SCREAMING_SNAKE_CASE		     =       None
											__SCREAMING_SNAKE_CASE		     =       None
											__SCREAMING_SNAKE_CASE		     =       []

						__SCREAMING_SNAKE_CASE		     =       num_hidden_layers
						__SCREAMING_SNAKE_CASE		     =       num_attention_heads
						__SCREAMING_SNAKE_CASE		     =       intermediate_size
						__SCREAMING_SNAKE_CASE		     =       hidden_act
						__SCREAMING_SNAKE_CASE		     =       hidden_dropout_prob
						__SCREAMING_SNAKE_CASE		     =       attention_probs_dropout_prob
						__SCREAMING_SNAKE_CASE		     =       initializer_range
						__SCREAMING_SNAKE_CASE		     =       layer_norm_eps
						__SCREAMING_SNAKE_CASE		     =       image_size
						__SCREAMING_SNAKE_CASE		     =       patch_size
						__SCREAMING_SNAKE_CASE		     =       num_channels
						__SCREAMING_SNAKE_CASE		     =       qkv_bias
						__SCREAMING_SNAKE_CASE		     =       backbone_out_indices
						if readout_type not in ["ignore", "add", "project"]:
											raise ValueError("Readout_type must be one of ['ignore', 'add', 'project']"     )
						__SCREAMING_SNAKE_CASE		     =       readout_type
						__SCREAMING_SNAKE_CASE		     =       reassemble_factors
						__SCREAMING_SNAKE_CASE		     =       neck_hidden_sizes
						__SCREAMING_SNAKE_CASE		     =       fusion_hidden_size
						__SCREAMING_SNAKE_CASE		     =       head_in_index
						__SCREAMING_SNAKE_CASE		     =       use_batch_norm_in_fusion_residual
						# auxiliary head attributes (semantic segmentation)
						__SCREAMING_SNAKE_CASE		     =       use_auxiliary_head
						__SCREAMING_SNAKE_CASE		     =       auxiliary_loss_weight
						__SCREAMING_SNAKE_CASE		     =       semantic_loss_ignore_index
						__SCREAMING_SNAKE_CASE		     =       semantic_classifier_dropout




	def 						UpperCAmelCase_   (				self    :       Optional[int]     ) ->			str:
						__SCREAMING_SNAKE_CASE		     =       copy.deepcopy(self.__dict__     )

						if output["backbone_config"] is not None:
											__SCREAMING_SNAKE_CASE		     =       self.backbone_config.to_dict()

						__SCREAMING_SNAKE_CASE		     =       self.__class__.model_type
						return output
