



import unittest

from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


A_		:     int        =     '''▁'''

A_		:     str        =     get_tests_dir('''fixtures/test_sentencepiece.model''')



@require_sentencepiece
@require_tokenizers
class 		_lowercase		(       UpperCAmelCase__,   unittest.TestCase	):
   _UpperCAmelCase     	=			BigBirdTokenizer
   _UpperCAmelCase     	=			BigBirdTokenizerFast
   _UpperCAmelCase     	=			True
   _UpperCAmelCase     	=			True

   def 		A							(      self			:       Optional[Any]							)       ->				Dict:


    """simple docstring"""






    super().setUp()

    a						=		self.tokenizer_class(__lowerCAmelCase							,   keep_accents=__lowerCAmelCase							)
    tokenizer.save_pretrained(self.tmpdirname							)

   def 		A							(      self			:       Optional[int]							)       ->				int:


    """simple docstring"""






    a						=		"<s>"
    a						=		1

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

   def 		A							(      self			:       Optional[Any]							)       ->				Any:


    """simple docstring"""






    a						=		list(self.get_tokenizer().get_vocab().keys()							)

    self.assertEqual(vocab_keys[0]							,   "<unk>"							)
    self.assertEqual(vocab_keys[1]							,   "<s>"							)
    self.assertEqual(vocab_keys[-1]							,   "[MASK]"							)
    self.assertEqual(len(__lowerCAmelCase							)							,   1004							)

   def 		A							(      self			:       Tuple							)       ->				List[Any]:


    """simple docstring"""






    self.assertEqual(self.get_tokenizer().vocab_size							,   1000							)

   def 		A							(      self			:       Tuple							)       ->				List[str]:


    """simple docstring"""






    if not self.test_rust_tokenizer:
     return

    a						=		self.get_tokenizer()
    a						=		self.get_rust_tokenizer()

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

    a						=		tokenizer.tokenize(__lowerCAmelCase							)
    a						=		rust_tokenizer.tokenize(__lowerCAmelCase							)
    self.assertListEqual(__lowerCAmelCase							,   __lowerCAmelCase							)

    a						=		tokenizer.encode(__lowerCAmelCase							,   add_special_tokens=__lowerCAmelCase							)
    a						=		rust_tokenizer.encode(__lowerCAmelCase							,   add_special_tokens=__lowerCAmelCase							)
    self.assertListEqual(__lowerCAmelCase							,   __lowerCAmelCase							)

    a						=		self.get_rust_tokenizer()
    a						=		tokenizer.encode(__lowerCAmelCase							)
    a						=		rust_tokenizer.encode(__lowerCAmelCase							)
    self.assertListEqual(__lowerCAmelCase							,   __lowerCAmelCase							)

   def 		A							(      self			:       int							)       ->				Optional[Any]:


    """simple docstring"""






    a						=		BigBirdTokenizer(__lowerCAmelCase							,   keep_accents=__lowerCAmelCase							)

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

    self.assertListEqual(
        tokenizer.convert_tokens_to_ids(__lowerCAmelCase							)							,   [285, 46, 10, 170, 382]							,   )

    a						=		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",
            ".",
        ]							,   )
    a						=		tokenizer.convert_tokens_to_ids(__lowerCAmelCase							)
    self.assertListEqual(
        __lowerCAmelCase							,   [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]							,   )

    a						=		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 		A							(      self			:       List[Any]							)       ->				Tuple:


    """simple docstring"""






    return BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base"							)

   @slow
   def 		A							(      self			:       int							)       ->				Any:


    """simple docstring"""






    a						=		"Hello World!"
    a						=		[65, 1_8536, 2260, 101, 66]

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

   @slow
   def 		A							(      self			:       Optional[int]							)       ->				Optional[Any]:


    """simple docstring"""






    a						=		(
        "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
    a						=		[65, 871, 419, 358, 946, 991, 2521, 452, 358, 1357, 387, 7751, 3536, 112, 985, 456, 126, 865, 938, 5400, 5734, 458, 1368, 467, 786, 2462, 5246, 1159, 633, 865, 4519, 457, 582, 852, 2557, 427, 916, 508, 405, 3_4324, 497, 391, 408, 1_1342, 1244, 385, 100, 938, 985, 456, 574, 362, 1_2597, 3200, 3129, 1172, 66]  # noqa: E231
    # fmt: on
    self.assertListEqual(__lowerCAmelCase							,   self.big_tokenizer.encode(__lowerCAmelCase							)							)

   @require_torch
   @slow
   def 		A							(      self			:       Dict							)       ->				Tuple:


    """simple docstring"""






    import torch

    from transformers import BigBirdConfig, BigBirdModel

    # Build sequence
    a						=		list(self.big_tokenizer.get_vocab().keys()							)[:10]
    a						=		" ".join(__lowerCAmelCase							)
    a						=		self.big_tokenizer.encode_plus(__lowerCAmelCase							,   return_tensors="pt"							,   return_token_type_ids=__lowerCAmelCase							)
    a						=		self.big_tokenizer.batch_encode_plus(
        [sequence + " " + sequence]							,   return_tensors="pt"							,   return_token_type_ids=__lowerCAmelCase							)

    a						=		BigBirdConfig(attention_type="original_full"							)
    a						=		BigBirdModel(__lowerCAmelCase							)

    assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

    with torch.no_grad():
     model(**__lowerCAmelCase							)
     model(**__lowerCAmelCase							)

   @slow
   def 		A							(      self			:       Union[str, Any]							)       ->				List[str]:


    """simple docstring"""






    a						=		BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base"							)
    a						=		tokenizer.decode(tokenizer("Paris is the [MASK]."							).input_ids							)

    self.assertTrue(decoded_text == "[CLS] Paris is the[MASK].[SEP]"							)




   @slow
   def 		A							(      self			:       int							)       ->				str:


    """simple docstring"""






    a						=		{"input_ids": [[65, 3_9286, 458, 3_6335, 2001, 456, 1_3073, 1_3266, 455, 113, 7746, 1741, 1_1157, 391, 1_3073, 1_3266, 455, 113, 3967, 3_5412, 113, 4936, 109, 3870, 2377, 113, 3_0084, 4_5720, 458, 134, 1_7496, 112, 503, 1_1672, 113, 118, 112, 5665, 1_3347, 3_8687, 112, 1496, 3_1389, 112, 3268, 4_7264, 134, 962, 112, 1_6377, 8035, 2_3130, 430, 1_2169, 1_5518, 2_8592, 458, 146, 4_1697, 109, 391, 1_2169, 1_5518, 1_6689, 458, 146, 4_1358, 109, 452, 726, 4034, 111, 763, 3_5412, 5082, 388, 1903, 111, 9051, 391, 2870, 4_8918, 1900, 1123, 550, 998, 112, 9586, 1_5985, 455, 391, 410, 2_2955, 3_7636, 114, 66], [65, 448, 1_7496, 419, 3663, 385, 763, 113, 2_7533, 2870, 3283, 1_3043, 1639, 2_4713, 523, 656, 2_4013, 1_8550, 2521, 517, 2_7014, 2_1244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 1_1786, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [65, 484, 2169, 7687, 2_1932, 1_8146, 726, 363, 1_7032, 3391, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
    # fmt: on

    self.tokenizer_integration_test_util(
        expected_encoding=__lowerCAmelCase							,   model_name="google/bigbird-roberta-base"							,   revision="215c99f1600e06f83acce68422f2035b2b5c3510"							,   )






from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


A_		:     int        =     logging.get_logger(__name__)

A_		:     str        =     {
    '''microsoft/focalnet-tiny''': '''https://huggingface.co/microsoft/focalnet-tiny/resolve/main/config.json''',
}



class 		_lowercase		(       UpperCAmelCase__,   UpperCAmelCase__	):
   _UpperCAmelCase     	=			'''focalnet'''

   def __init__(      self			:       int							,   __lowerCAmelCase			:       Optional[Any]=224							,   __lowerCAmelCase			:       Any=4							,   __lowerCAmelCase			:       Any=3							,   __lowerCAmelCase			:       Tuple=96							,   __lowerCAmelCase			:       Dict=False							,   __lowerCAmelCase			:       Optional[int]=[192, 384, 768, 768]							,   __lowerCAmelCase			:       Union[str, Any]=[2, 2, 6, 2]							,   __lowerCAmelCase			:       Optional[int]=[2, 2, 2, 2]							,   __lowerCAmelCase			:       Union[str, Any]=[3, 3, 3, 3]							,   __lowerCAmelCase			:       str="gelu"							,   __lowerCAmelCase			:       Any=4.0							,   __lowerCAmelCase			:       Optional[int]=0.0							,   __lowerCAmelCase			:       Tuple=0.1							,   __lowerCAmelCase			:       str=False							,   __lowerCAmelCase			:       Optional[int]=1E-4							,   __lowerCAmelCase			:       Optional[Any]=False							,   __lowerCAmelCase			:       Union[str, Any]=False							,   __lowerCAmelCase			:       str=False							,   __lowerCAmelCase			:       Any=0.0_2							,   __lowerCAmelCase			:       str=1E-5							,   __lowerCAmelCase			:       Optional[Any]=32							,   __lowerCAmelCase			:       Dict=None							,   __lowerCAmelCase			:       str=None							,   **__lowerCAmelCase			:       Any							,   )       ->				List[str]:


    """simple docstring"""






    super().__init__(**__lowerCAmelCase							)

    a						=		image_size
    a						=		patch_size
    a						=		num_channels
    a						=		embed_dim
    a						=		use_conv_embed
    a						=		hidden_sizes
    a						=		depths
    a						=		focal_levels
    a						=		focal_windows
    a						=		hidden_act
    a						=		mlp_ratio
    a						=		hidden_dropout_prob
    a						=		drop_path_rate
    a						=		use_layerscale
    a						=		layerscale_value
    a						=		use_post_layernorm
    a						=		use_post_layernorm_in_modulation
    a						=		normalize_modulator
    a						=		initializer_range
    a						=		layer_norm_eps
    a						=		encoder_stride
    a						=		["stem"] + [f"""stage{idx}""" for idx in range(1							,   len(self.depths							) + 1							)]
    a		,  a						=		get_aligned_output_features_output_indices(
        out_features=__lowerCAmelCase							,   out_indices=__lowerCAmelCase							,   stage_names=self.stage_names							)

