

"""simple docstring"""





import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin




class  _lowerCAmelCase  (     lowercase					,unittest.TestCase       ):







 """simple docstring"""







 __UpperCAmelCase     : Optional[int]       		=     XLMTokenizer
 __UpperCAmelCase     : List[Any]       		=     False


 def  _lowercase			(      self							:      Dict     ):
    super().setUp()

    # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
    __lowercase								=						[
        "l",
        "o",
        "w",
        "e",
        "r",
        "s",
        "t",
        "i",
        "d",
        "n",
        "w</w>",
        "r</w>",
        "t</w>",
        "lo",
        "low",
        "er</w>",
        "low</w>",
        "lowest</w>",
        "newer</w>",
        "wider</w>",
        "<unk>",
    ]
    __lowercase								=						dict(zip(UpperCAmelCase__, range(len(UpperCAmelCase__     )     )     )     )
    __lowercase								=						["l o 123", "lo w 1456", "e r</w> 1789", ""]

    __lowercase								=						os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"]     )
    __lowercase								=						os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["merges_file"]     )
    with open(self.vocab_file, "w"     ) as fp:
       fp.write(json.dumps(UpperCAmelCase__     )     )
    with open(self.merges_file, "w"     ) as fp:
       fp.write("\n".join(UpperCAmelCase__     )     )


 def  _lowercase			(      self							:      Tuple, UpperCAmelCase__							:      Optional[int]     ):
    __lowercase								=						"lower newer"
    __lowercase								=						"lower newer"
    return input_text, output_text


 def  _lowercase			(      self							:      Tuple     ):
    __lowercase								=						XLMTokenizer(self.vocab_file, self.merges_file     )

    __lowercase								=						"lower"
    __lowercase								=						["low", "er</w>"]
    __lowercase								=						tokenizer.tokenize(UpperCAmelCase__     )
    self.assertListEqual(UpperCAmelCase__, UpperCAmelCase__     )

    __lowercase								=						tokens + ["<unk>"]
    __lowercase								=						[1_4, 1_5, 2_0]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase__     ), UpperCAmelCase__     )



 @slow
 def  _lowercase			(      self							:      List[Any]     ):
    __lowercase								=						XLMTokenizer.from_pretrained("xlm-mlm-en-2048"     )

    __lowercase								=						tokenizer.encode("sequence builders", add_special_tokens=UpperCAmelCase__     )
    __lowercase								=						tokenizer.encode("multi-sequence build", add_special_tokens=UpperCAmelCase__     )

    __lowercase								=						tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__     )
    __lowercase								=						tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__, UpperCAmelCase__     )

    assert encoded_sentence == [0] + text + [1]
    assert encoded_pair == [0] + text + [1] + text_a + [1]







"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_a							=							logging.get_logger(__name__)

_a							=							{
    'caidas/swin2sr-classicalsr-x2-64': (
        'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
    ),
}




class  _lowerCAmelCase  (     lowercase       ):







 """simple docstring"""







 __UpperCAmelCase     : List[Any]       		=     "swin2sr"

 __UpperCAmelCase     : List[Any]       		=     {
     "hidden_size": "embed_dim",
     "num_attention_heads": "num_heads",
     "num_hidden_layers": "num_layers",
 }


 def __init__(      self							:      Any, UpperCAmelCase__							:      Dict=6_4, UpperCAmelCase__							:      List[Any]=1, UpperCAmelCase__							:      Dict=3, UpperCAmelCase__							:      Optional[Any]=1_8_0, UpperCAmelCase__							:      Any=[6, 6, 6, 6, 6, 6], UpperCAmelCase__							:      Dict=[6, 6, 6, 6, 6, 6], UpperCAmelCase__							:      Tuple=8, UpperCAmelCase__							:      Optional[int]=2.0, UpperCAmelCase__							:      List[str]=True, UpperCAmelCase__							:      Tuple=0.0, UpperCAmelCase__							:      Optional[Any]=0.0, UpperCAmelCase__							:      List[str]=0.1, UpperCAmelCase__							:      Dict="gelu", UpperCAmelCase__							:      Dict=False, UpperCAmelCase__							:      Dict=0.02, UpperCAmelCase__							:      Tuple=1E-5, UpperCAmelCase__							:      str=2, UpperCAmelCase__							:      str=1.0, UpperCAmelCase__							:      Optional[int]="1conv", UpperCAmelCase__							:      Dict="pixelshuffle", **UpperCAmelCase__							:      List[Any], ):
    super().__init__(**UpperCAmelCase__     )

    __lowercase								=						image_size
    __lowercase								=						patch_size
    __lowercase								=						num_channels
    __lowercase								=						embed_dim
    __lowercase								=						depths
    __lowercase								=						len(UpperCAmelCase__     )
    __lowercase								=						num_heads
    __lowercase								=						window_size
    __lowercase								=						mlp_ratio
    __lowercase								=						qkv_bias
    __lowercase								=						hidden_dropout_prob
    __lowercase								=						attention_probs_dropout_prob
    __lowercase								=						drop_path_rate
    __lowercase								=						hidden_act
    __lowercase								=						use_absolute_embeddings
    __lowercase								=						layer_norm_eps
    __lowercase								=						initializer_range
    __lowercase								=						upscale
    __lowercase								=						img_range
    __lowercase								=						resi_connection
    __lowercase								=						upsampler




