


"""simple docstring"""


import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 			A__	(						__lowercase ,     unittest.TestCase):


     """simple docstring"""
     snake_case__	:					Any													=OpenAIGPTTokenizer
     snake_case__	:					Tuple													=OpenAIGPTTokenizerFast
     snake_case__	:					Any													=True
     snake_case__	:					str													=False

     def 		a__						(	self:						Tuple	)->    Optional[int]:
           super().setUp()

           # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
           lowerCamelCase					:					Optional[int]        =	[
               """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>""",
           ]
           lowerCamelCase					:					Optional[Any]        =	dict(zip(__a     ,		range(len(__a	)	)	)	)
           lowerCamelCase					:					Optional[int]        =	["""#version: 0.2""", """l o""", """lo w""", """e r</w>""", """"""]

           lowerCamelCase					:					List[Any]        =	os.path.join(self.tmpdirname     ,		VOCAB_FILES_NAMES["""vocab_file"""]	)
           lowerCamelCase					:					Union[str, Any]        =	os.path.join(self.tmpdirname     ,		VOCAB_FILES_NAMES["""merges_file"""]	)
           with open(self.vocab_file     ,		"""w"""	) as fp:
                 fp.write(json.dumps(__a	)	)
           with open(self.merges_file     ,		"""w"""	) as fp:
                 fp.write("""\n""".join(__a	)	)

     def 		a__						(	self:						Dict     ,		__a:						Dict	)->    str:
           return "lower newer", "lower newer"

     def 		a__						(	self:						int	)->    int:
           lowerCamelCase					:					List[Any]        =	OpenAIGPTTokenizer(self.vocab_file     ,		self.merges_file	)

           lowerCamelCase					:					str        =	"""lower"""
           lowerCamelCase					:					str        =	["""low""", """er</w>"""]
           lowerCamelCase					:					List[Any]        =	tokenizer.tokenize(__a	)
           self.assertListEqual(__a     ,		__a	)

           lowerCamelCase					:					Union[str, Any]        =	tokens + ["""<unk>"""]
           lowerCamelCase					:					Tuple        =	[14, 15, 20]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(__a	)     ,		__a	)

     def 		a__						(	self:						List[str]     ,		__a:						Optional[int]=15	)->    Dict:
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'	):
                       lowerCamelCase					:					int        =	self.rust_tokenizer_class.from_pretrained(__a     ,		**__a	)

                       # Simple input
                       lowerCamelCase					:					List[Any]        =	"""This is a simple input"""
                       lowerCamelCase					:					Dict        =	["""This is a simple input 1""", """This is a simple input 2"""]
                       lowerCamelCase					:					Any        =	("""This is a simple input""", """This is a pair""")
                       lowerCamelCase					:					Any        =	[
                           ("""This is a simple input 1""", """This is a simple input 2"""),
                           ("""This is a simple pair 1""", """This is a simple pair 2"""),
                       ]

                       # Simple input tests
                       self.assertRaises(__a     ,		tokenizer_r.encode     ,		__a     ,		max_length=__a     ,		padding="""max_length"""	)

                       # Simple input
                       self.assertRaises(__a     ,		tokenizer_r.encode_plus     ,		__a     ,		max_length=__a     ,		padding="""max_length"""	)

                       # Simple input
                       self.assertRaises(
                           __a     ,		tokenizer_r.batch_encode_plus     ,		__a     ,		max_length=__a     ,		padding="""max_length"""     ,		)

                       # Pair input
                       self.assertRaises(__a     ,		tokenizer_r.encode     ,		__a     ,		max_length=__a     ,		padding="""max_length"""	)

                       # Pair input
                       self.assertRaises(__a     ,		tokenizer_r.encode_plus     ,		__a     ,		max_length=__a     ,		padding="""max_length"""	)

                       # Pair input
                       self.assertRaises(
                           __a     ,		tokenizer_r.batch_encode_plus     ,		__a     ,		max_length=__a     ,		padding="""max_length"""     ,		)







     def 		a__						(	self:						Optional[Any]	)->    List[str]:
           pass


@require_ftfy
@require_spacy
@require_tokenizers
class 			A__	(						__lowercase):


     """simple docstring"""
     pass








"""simple docstring"""


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


__lowerCamelCase      :Tuple	    =		logging.get_logger(__name__)

__lowerCamelCase      :Any	    =		{
    'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}


class 			A__	(						__lowercase):


     """simple docstring"""
     snake_case__	:					Tuple													='''glpn'''

     def __init__(	self:						Dict     ,		__a:						List[str]=3     ,		__a:						Optional[int]=4     ,		__a:						Dict=[2, 2, 2, 2]     ,		__a:						str=[8, 4, 2, 1]     ,		__a:						Optional[int]=[32, 64, 160, 256]     ,		__a:						Dict=[7, 3, 3, 3]     ,		__a:						Dict=[4, 2, 2, 2]     ,		__a:						Optional[Any]=[1, 2, 5, 8]     ,		__a:						Tuple=[4, 4, 4, 4]     ,		__a:						int="gelu"     ,		__a:						Union[str, Any]=0.0     ,		__a:						str=0.0     ,		__a:						Union[str, Any]=0.02     ,		__a:						str=0.1     ,		__a:						Union[str, Any]=1e-6     ,		__a:						Any=64     ,		__a:						Dict=10     ,		__a:						Union[str, Any]=-1     ,		**__a:						Optional[Any]     ,		)->    Dict:
           super().__init__(**__a	)

           lowerCamelCase					:					Dict        =	num_channels
           lowerCamelCase					:					Any        =	num_encoder_blocks
           lowerCamelCase					:					Dict        =	depths
           lowerCamelCase					:					List[str]        =	sr_ratios
           lowerCamelCase					:					Dict        =	hidden_sizes
           lowerCamelCase					:					Tuple        =	patch_sizes
           lowerCamelCase					:					Optional[int]        =	strides
           lowerCamelCase					:					Optional[Any]        =	mlp_ratios
           lowerCamelCase					:					Union[str, Any]        =	num_attention_heads
           lowerCamelCase					:					List[str]        =	hidden_act
           lowerCamelCase					:					Any        =	hidden_dropout_prob
           lowerCamelCase					:					Optional[int]        =	attention_probs_dropout_prob
           lowerCamelCase					:					List[Any]        =	initializer_range
           lowerCamelCase					:					Dict        =	drop_path_rate
           lowerCamelCase					:					Any        =	layer_norm_eps
           lowerCamelCase					:					Optional[Any]        =	decoder_hidden_size
           lowerCamelCase					:					Tuple        =	max_depth
           lowerCamelCase					:					Optional[Any]        =	head_in_index




