





'''simple docstring'''



import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase					,    unittest.TestCase			):



     '''simple docstring'''






     UpperCAmelCase__       :						Union[str, Any]      =   LxmertTokenizer
     UpperCAmelCase__       :						Optional[int]      =   LxmertTokenizerFast
     UpperCAmelCase__       :						Any      =   True
     UpperCAmelCase__       :						str      =   True

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

       _snake_case     		=				[
           "[UNK]",
           "[CLS]",
           "[SEP]",
           "want",
           "##want",
           "##ed",
           "wa",
           "un",
           "runn",
           "##ing",
           ",",
           "low",
           "lowest",
       ]
       _snake_case     		=				os.path.join(self.tmpdirname						,   VOCAB_FILES_NAMES["vocab_file"]	)
       with open(self.vocab_file						,   "w"						,   encoding="utf-8"	) as vocab_writer:
         vocab_writer.write("".join([x + "\n" for x in vocab_tokens]	)	)

     def 	UpperCamelCase(					self						,   lowerCamelCase	):
       _snake_case     		=				"UNwant\u00E9d,running"
       _snake_case     		=				"unwanted, running"
       return input_text, output_text

     def 	UpperCamelCase(					self	):
       _snake_case     		=				self.tokenizer_class(self.vocab_file	)

       _snake_case     		=				tokenizer.tokenize("UNwant\u00E9d,running"	)
       self.assertListEqual(lowerCamelCase						,   ["un", "##want", "##ed", ",", "runn", "##ing"]	)
       self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase	)						,   [7, 4, 5, 10, 8, 9]	)






     def 	UpperCamelCase(					self	):
       if not self.test_rust_tokenizer:
         return

       _snake_case     		=				self.get_tokenizer()
       _snake_case     		=				self.get_rust_tokenizer()

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

       _snake_case     		=				tokenizer.tokenize(lowerCamelCase	)
       _snake_case     		=				rust_tokenizer.tokenize(lowerCamelCase	)
       self.assertListEqual(lowerCamelCase						,   lowerCamelCase	)

       _snake_case     		=				tokenizer.encode(lowerCamelCase						,   add_special_tokens=lowerCamelCase	)
       _snake_case     		=				rust_tokenizer.encode(lowerCamelCase						,   add_special_tokens=lowerCamelCase	)
       self.assertListEqual(lowerCamelCase						,   lowerCamelCase	)

       _snake_case     		=				self.get_rust_tokenizer()
       _snake_case     		=				tokenizer.encode(lowerCamelCase	)
       _snake_case     		=				rust_tokenizer.encode(lowerCamelCase	)
       self.assertListEqual(lowerCamelCase						,   lowerCamelCase	)









'''simple docstring'''



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


__magic_name__   :						Dict    =			logging.get_logger(__name__)

__magic_name__   :						Dict    =			{
    """google/mobilenet_v1_1.0_224""": """https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v1_0.75_192""": """https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json""",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}


class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase			):



     '''simple docstring'''






     UpperCAmelCase__       :						List[Any]      =   '''mobilenet_v1'''

     def __init__(					self						,   lowerCamelCase=3						,   lowerCamelCase=224						,   lowerCamelCase=1.0						,   lowerCamelCase=8						,   lowerCamelCase="relu6"						,   lowerCamelCase=True						,   lowerCamelCase=0.999						,   lowerCamelCase=0.02						,   lowerCamelCase=0.001						,   **lowerCamelCase						,   ):
       super().__init__(**lowerCamelCase	)

       if depth_multiplier <= 0:
         raise ValueError("depth_multiplier must be greater than zero."	)

       _snake_case     		=				num_channels
       _snake_case     		=				image_size
       _snake_case     		=				depth_multiplier
       _snake_case     		=				min_depth
       _snake_case     		=				hidden_act
       _snake_case     		=				tf_padding
       _snake_case     		=				classifier_dropout_prob
       _snake_case     		=				initializer_range
       _snake_case     		=				layer_norm_eps







class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase			):



     '''simple docstring'''






     UpperCAmelCase__       :						int      =   version.parse('''1.11'''			)

     @property
     def 	UpperCamelCase(					self	):
       return OrderedDict([("pixel_values", {0: "batch"})]	)

     @property
     def 	UpperCamelCase(					self	):
       if self.task == "image-classification":
         return OrderedDict([("logits", {0: "batch"})]	)
       else:
         return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]	)






     @property
     def 	UpperCamelCase(					self	):
       return 1e-4


