



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


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



@require_sentencepiece
@require_tokenizers
class 						UpperCAmelCase_					( __lowerCAmelCase     ,      unittest.TestCase):
							lowerCamelCase__         =	XGLMTokenizer
							lowerCamelCase__         =	XGLMTokenizerFast
							lowerCamelCase__         =	True
							lowerCamelCase__         =	True







							def      snake_case__   (     self):

														'''simple docstring'''

														super().setUp()

														# We have a SentencePiece fixture for testing
														_lowerCAmelCase  :							Dict				     =					XGLMTokenizer(lowerCamelCase__,    keep_accents=lowerCamelCase__)
														tokenizer.save_pretrained(self.tmpdirname)







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[Any]				     =					'''<pad>'''
														_lowerCAmelCase  :							Tuple				     =					1

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







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Dict				     =					list(self.get_tokenizer().get_vocab().keys())

														self.assertEqual(vocab_keys[0],    "<s>")
														self.assertEqual(vocab_keys[1],    "<pad>")
														self.assertEqual(len(lowerCamelCase__),    1008)







							def      snake_case__   (     self):

														'''simple docstring'''

														self.assertEqual(self.get_tokenizer().vocab_size,    1008)







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Any				     =					XGLMTokenizer(lowerCamelCase__,    keep_accents=lowerCamelCase__)

														_lowerCAmelCase  :							int				     =					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 [285, 46, 10, 170, 382]],    )

														_lowerCAmelCase  :							Dict				     =					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",
														        ".",
														    ],    )
														_lowerCAmelCase  :							Tuple				     =					tokenizer.convert_tokens_to_ids(lowerCamelCase__)
														self.assertListEqual(
														    lowerCamelCase__,    [
														        value + tokenizer.fairseq_offset
														        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
														    ],    )

														_lowerCAmelCase  :							Optional[int]				     =					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>",
														        ".",
														    ],    )







							@cached_property
							def      snake_case__   (     self):

														'''simple docstring'''

														return XGLMTokenizer.from_pretrained("facebook/xglm-564M")







							def      snake_case__   (     self):

														'''simple docstring'''

														with tempfile.NamedTemporaryFile() as f:
																					shutil.copyfile(lowerCamelCase__,    f.name)
																					_lowerCAmelCase  :							Optional[int]				     =					XGLMTokenizer(f.name,    keep_accents=lowerCamelCase__)
																					_lowerCAmelCase  :							Dict				     =					pickle.dumps(lowerCamelCase__)
														pickle.loads(lowerCamelCase__)







							def      snake_case__   (     self):

														'''simple docstring'''

														if not self.test_rust_tokenizer:
																					return

														_lowerCAmelCase  :							List[str]				     =					self.get_tokenizer()
														_lowerCAmelCase  :							Tuple				     =					self.get_rust_tokenizer()

														_lowerCAmelCase  :							Tuple				     =					'''I was born in 92000, and this is falsé.'''

														_lowerCAmelCase  :							Optional[int]				     =					tokenizer.tokenize(lowerCamelCase__)
														_lowerCAmelCase  :							Optional[Any]				     =					rust_tokenizer.tokenize(lowerCamelCase__)
														self.assertListEqual(lowerCamelCase__,    lowerCamelCase__)

														_lowerCAmelCase  :							Dict				     =					tokenizer.encode(lowerCamelCase__,    add_special_tokens=lowerCamelCase__)
														_lowerCAmelCase  :							List[str]				     =					rust_tokenizer.encode(lowerCamelCase__,    add_special_tokens=lowerCamelCase__)
														self.assertListEqual(lowerCamelCase__,    lowerCamelCase__)

														_lowerCAmelCase  :							Any				     =					self.get_rust_tokenizer()
														_lowerCAmelCase  :							str				     =					tokenizer.encode(lowerCamelCase__)
														_lowerCAmelCase  :							Union[str, Any]				     =					rust_tokenizer.encode(lowerCamelCase__)
														self.assertListEqual(lowerCamelCase__,    lowerCamelCase__)







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[int]				     =					'''Hello World!'''
														_lowerCAmelCase  :							Union[str, Any]				     =					[2, 3_1227, 4447, 35]

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







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Optional[Any]				     =					(
														    '''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
														_lowerCAmelCase  :							int				     =					[2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 7_1630, 2_8085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 1_3675, 377, 652, 7580, 1_0341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 20_2277, 1_7892, 33, 60, 87, 4, 3234, 157, 61, 2667, 5_2376, 19, 88, 23, 735]
														# fmt: on

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







							@slow
							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							Tuple				     =					{
														    '''input_ids''': [[2, 10_8825, 1163, 15, 8_8010, 473, 1_5898, 157, 1_3672, 1857, 312, 8, 23_8021, 1163, 53, 1_3672, 1857, 312, 8, 5_3283, 18_2396, 8, 1_8566, 16, 3_6733, 4101, 8, 230, 24_4017, 12_2553, 7, 15, 13_2597, 4, 293, 1_2511, 7610, 4, 3414, 13_2597, 9, 4, 3_2361, 362, 4, 734, 2_8512, 3_2569, 18, 4, 3_2361, 2_6096, 1_4982, 73, 1_8715, 2_1433, 23_5261, 15, 492, 1_2427, 16, 53, 1_8715, 2_1433, 6_5454, 15, 2_3659, 563, 16, 278, 597, 2843, 595, 7931, 18_2396, 6_4186, 22, 886, 595, 13_2981, 53, 2_5540, 3449, 4_3982, 3_9901, 5951, 878, 330, 4, 2_7694, 8_0269, 312, 53, 6517, 1_1780, 611, 2_0408, 5], [2, 6, 13_2597, 67, 4_2897, 33, 592, 8, 16_3729, 2_5540, 361, 13_6997, 10_9514, 17_3230, 7, 501, 60, 10_2913, 196, 5631, 235, 6_3243, 473, 6, 23_1757, 74, 5277, 7905, 53, 3095, 3_7317, 22, 454, 18_3874, 5], [2, 268, 3_1298, 4_6530, 6, 13_2935, 4_3831, 7, 597, 32, 24, 3688, 9865, 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=lowerCamelCase__,    model_name="facebook/xglm-564M",    padding=lowerCamelCase__,    )




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_snake_case	=						logging.get_logger(__name__)

_snake_case	=						{
    "facebook/data2vec-vision-base-ft": (
        "https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json"
    ),
}



class 						UpperCAmelCase_					( a):
							lowerCamelCase__         =	'data2vec-vision'







							def __init__(     self,    __a=768,    __a=12,    __a=12,    __a=3072,    __a="gelu",    __a=0.0,    __a=0.0,    __a=0.02,    __a=1E-12,    __a=224,    __a=16,    __a=3,    __a=False,    __a=False,    __a=False,    __a=False,    __a=0.1,    __a=0.1,    __a=True,    __a=[3, 5, 7, 11],    __a=[1, 2, 3, 6],    __a=True,    __a=0.4,    __a=256,    __a=1,    __a=False,    __a=255,    **__a,    ):

														'''simple docstring'''

														super().__init__(**__a)

														_lowerCAmelCase  :							Dict				     =					hidden_size
														_lowerCAmelCase  :							List[Any]				     =					num_hidden_layers
														_lowerCAmelCase  :							Any				     =					num_attention_heads
														_lowerCAmelCase  :							str				     =					intermediate_size
														_lowerCAmelCase  :							Optional[Any]				     =					hidden_act
														_lowerCAmelCase  :							int				     =					hidden_dropout_prob
														_lowerCAmelCase  :							Dict				     =					attention_probs_dropout_prob
														_lowerCAmelCase  :							Dict				     =					initializer_range
														_lowerCAmelCase  :							List[str]				     =					layer_norm_eps

														_lowerCAmelCase  :							Optional[int]				     =					image_size
														_lowerCAmelCase  :							List[Any]				     =					patch_size
														_lowerCAmelCase  :							Optional[Any]				     =					num_channels
														_lowerCAmelCase  :							str				     =					use_mask_token
														_lowerCAmelCase  :							List[str]				     =					use_absolute_position_embeddings
														_lowerCAmelCase  :							str				     =					use_relative_position_bias
														_lowerCAmelCase  :							List[str]				     =					use_shared_relative_position_bias
														_lowerCAmelCase  :							List[str]				     =					layer_scale_init_value
														_lowerCAmelCase  :							List[Any]				     =					drop_path_rate
														_lowerCAmelCase  :							Union[str, Any]				     =					use_mean_pooling
														# decode head attributes (semantic segmentation)
														_lowerCAmelCase  :							Tuple				     =					out_indices
														_lowerCAmelCase  :							Tuple				     =					pool_scales
														# auxiliary head attributes (semantic segmentation)
														_lowerCAmelCase  :							Optional[int]				     =					use_auxiliary_head
														_lowerCAmelCase  :							Optional[Any]				     =					auxiliary_loss_weight
														_lowerCAmelCase  :							int				     =					auxiliary_channels
														_lowerCAmelCase  :							Optional[Any]				     =					auxiliary_num_convs
														_lowerCAmelCase  :							int				     =					auxiliary_concat_input
														_lowerCAmelCase  :							Dict				     =					semantic_loss_ignore_index



class 						UpperCAmelCase_					( a):
							lowerCamelCase__         =	version.parse('1.11')







							@property
							def      snake_case__   (     self):

														'''simple docstring'''

														return OrderedDict(
														    [
														        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
														    ])







							@property
							def      snake_case__   (     self):

														'''simple docstring'''

														return 1E-4
