

"""simple docstring"""


import os
import unittest

from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english





@require_tokenizers
class        snake_case      (							__a,				unittest.TestCase    ):
				SCREAMING_SNAKE_CASE_  : List[str]   =    MobileBertTokenizer
				SCREAMING_SNAKE_CASE_  : str   =    MobileBertTokenizerFast
				SCREAMING_SNAKE_CASE_  : Optional[int]   =    True
				SCREAMING_SNAKE_CASE_  : List[Any]   =    True
				SCREAMING_SNAKE_CASE_  : Union[str, Any]   =    filter_non_english
				SCREAMING_SNAKE_CASE_  : Union[str, Any]   =    '''google/mobilebert-uncased'''

				def 				lowercase_	(      self				:							Union[str, Any])->  List[Any]:



						'''simple docstring'''


						super().setUp()

						__lowerCAmelCase:			List[str]        =     [
						    """[UNK]""",
						    """[CLS]""",
						    """[SEP]""",
						    """[PAD]""",
						    """[MASK]""",
						    """want""",
						    """##want""",
						    """##ed""",
						    """wa""",
						    """un""",
						    """runn""",
						    """##ing""",
						    """,""",
						    """low""",
						    """lowest""",
						]
						__lowerCAmelCase:			List[Any]        =     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]))

						__lowerCAmelCase:			Any        =     [
						    (tokenizer_def[0], self.pre_trained_model_path, tokenizer_def[2])  # else the 'google/' prefix is stripped
						    for tokenizer_def in self.tokenizers_list
						]

				def 				lowercase_	(      self				:							Union[str, Any]	,    UpperCamelCase__				:							int)->  Tuple:



						'''simple docstring'''


						__lowerCAmelCase:			Union[str, Any]        =     """UNwant\u00E9d,running"""
						__lowerCAmelCase:			Tuple        =     """unwanted, running"""
						return input_text, output_text

				def 				lowercase_	(      self				:							Any)->  int:



						'''simple docstring'''


						__lowerCAmelCase:			List[str]        =     self.tokenizer_class(self.vocab_file)

						__lowerCAmelCase:			str        =     tokenizer.tokenize("UNwant\u00E9d,running")
						self.assertListEqual(__UpperCamelCase	,    ["un", "##want", "##ed", ",", "runn", "##ing"])
						self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase)	,    [9, 6, 7, 1_2, 1_0, 1_1])

				def 				lowercase_	(      self				:							Union[str, Any])->  Any:



						'''simple docstring'''


						if not self.test_rust_tokenizer:
								return

						__lowerCAmelCase:			Optional[int]        =     self.get_tokenizer()
						__lowerCAmelCase:			Optional[int]        =     self.get_rust_tokenizer()

						__lowerCAmelCase:			Any        =     """UNwant\u00E9d,running"""

						__lowerCAmelCase:			List[str]        =     tokenizer.tokenize(__UpperCamelCase)
						__lowerCAmelCase:			Tuple        =     rust_tokenizer.tokenize(__UpperCamelCase)
						self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)

						__lowerCAmelCase:			Tuple        =     tokenizer.encode(__UpperCamelCase	,    add_special_tokens=__UpperCamelCase)
						__lowerCAmelCase:			List[Any]        =     rust_tokenizer.encode(__UpperCamelCase	,    add_special_tokens=__UpperCamelCase)
						self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)

						__lowerCAmelCase:			List[str]        =     self.get_rust_tokenizer()
						__lowerCAmelCase:			Tuple        =     tokenizer.encode(__UpperCamelCase)
						__lowerCAmelCase:			Tuple        =     rust_tokenizer.encode(__UpperCamelCase)
						self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)

						# With lower casing
						__lowerCAmelCase:			List[Any]        =     self.get_tokenizer(do_lower_case=__UpperCamelCase)
						__lowerCAmelCase:			Dict        =     self.get_rust_tokenizer(do_lower_case=__UpperCamelCase)

						__lowerCAmelCase:			str        =     """UNwant\u00E9d,running"""

						__lowerCAmelCase:			Tuple        =     tokenizer.tokenize(__UpperCamelCase)
						__lowerCAmelCase:			int        =     rust_tokenizer.tokenize(__UpperCamelCase)
						self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)

						__lowerCAmelCase:			Optional[int]        =     tokenizer.encode(__UpperCamelCase	,    add_special_tokens=__UpperCamelCase)
						__lowerCAmelCase:			Tuple        =     rust_tokenizer.encode(__UpperCamelCase	,    add_special_tokens=__UpperCamelCase)
						self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)

						__lowerCAmelCase:			List[Any]        =     self.get_rust_tokenizer()
						__lowerCAmelCase:			Optional[Any]        =     tokenizer.encode(__UpperCamelCase)
						__lowerCAmelCase:			Union[str, Any]        =     rust_tokenizer.encode(__UpperCamelCase)
						self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)

				def 				lowercase_	(      self				:							Optional[Any])->  Tuple:



						'''simple docstring'''


						__lowerCAmelCase:			Tuple        =     BasicTokenizer()

						self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz")	,    ["ah", "\u535A", "\u63A8", "zz"])

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



						'''simple docstring'''


						__lowerCAmelCase:			Any        =     BasicTokenizer(do_lower_case=__UpperCamelCase)

						self.assertListEqual(
						    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  ")	,    ["hello", "!", "how", "are", "you", "?"])
						self.assertListEqual(tokenizer.tokenize("H\u00E9llo")	,    ["hello"])

				def 				lowercase_	(      self				:							str)->  Any:



						'''simple docstring'''


						__lowerCAmelCase:			Union[str, Any]        =     BasicTokenizer(do_lower_case=__UpperCamelCase	,    strip_accents=__UpperCamelCase)

						self.assertListEqual(
						    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")	,    ["hällo", "!", "how", "are", "you", "?"])
						self.assertListEqual(tokenizer.tokenize("H\u00E9llo")	,    ["h\u00E9llo"])

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



						'''simple docstring'''


						__lowerCAmelCase:			Tuple        =     BasicTokenizer(do_lower_case=__UpperCamelCase	,    strip_accents=__UpperCamelCase)

						self.assertListEqual(
						    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")	,    ["hallo", "!", "how", "are", "you", "?"])
						self.assertListEqual(tokenizer.tokenize("H\u00E9llo")	,    ["hello"])

				def 				lowercase_	(      self				:							str)->  List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:			Optional[int]        =     BasicTokenizer(do_lower_case=__UpperCamelCase)

						self.assertListEqual(
						    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")	,    ["hallo", "!", "how", "are", "you", "?"])
						self.assertListEqual(tokenizer.tokenize("H\u00E9llo")	,    ["hello"])

				def 				lowercase_	(      self				:							Any)->  str:



						'''simple docstring'''


						__lowerCAmelCase:			Union[str, Any]        =     BasicTokenizer(do_lower_case=__UpperCamelCase)

						self.assertListEqual(
						    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  ")	,    ["HeLLo", "!", "how", "Are", "yoU", "?"])

				def 				lowercase_	(      self				:							str)->  List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:			Union[str, Any]        =     BasicTokenizer(do_lower_case=__UpperCamelCase	,    strip_accents=__UpperCamelCase)

						self.assertListEqual(
						    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")	,    ["HäLLo", "!", "how", "Are", "yoU", "?"])

				def 				lowercase_	(      self				:							int)->  int:



						'''simple docstring'''


						__lowerCAmelCase:			int        =     BasicTokenizer(do_lower_case=__UpperCamelCase	,    strip_accents=__UpperCamelCase)

						self.assertListEqual(
						    tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  ")	,    ["HaLLo", "!", "how", "Are", "yoU", "?"])

				def 				lowercase_	(      self				:							Dict)->  Tuple:



						'''simple docstring'''


						__lowerCAmelCase:			str        =     BasicTokenizer(do_lower_case=__UpperCamelCase	,    never_split=["[UNK]"])

						self.assertListEqual(
						    tokenizer.tokenize(" \tHeLLo!how  \n Are yoU? [UNK]")	,    ["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"])

				def 				lowercase_	(      self				:							List[str])->  List[str]:



						'''simple docstring'''


						__lowerCAmelCase:			Any        =     ["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

						__lowerCAmelCase:			List[str]        =     {}
						for i, token in enumerate(__UpperCamelCase):
								__lowerCAmelCase:			Any        =     i
						__lowerCAmelCase:			Tuple        =     WordpieceTokenizer(vocab=__UpperCamelCase	,    unk_token="[UNK]")

						self.assertListEqual(tokenizer.tokenize("")	,    [])

						self.assertListEqual(tokenizer.tokenize("unwanted running")	,    ["un", "##want", "##ed", "runn", "##ing"])

						self.assertListEqual(tokenizer.tokenize("unwantedX running")	,    ["[UNK]", "runn", "##ing"])

				def 				lowercase_	(      self				:							Tuple)->  Any:



						'''simple docstring'''


						self.assertTrue(_is_whitespace(" "))
						self.assertTrue(_is_whitespace("\t"))
						self.assertTrue(_is_whitespace("\r"))
						self.assertTrue(_is_whitespace("\n"))
						self.assertTrue(_is_whitespace("\u00A0"))

						self.assertFalse(_is_whitespace("A"))
						self.assertFalse(_is_whitespace("-"))

				def 				lowercase_	(      self				:							Dict)->  Dict:



						'''simple docstring'''


						self.assertTrue(_is_control("\u0005"))

						self.assertFalse(_is_control("A"))
						self.assertFalse(_is_control(" "))
						self.assertFalse(_is_control("\t"))
						self.assertFalse(_is_control("\r"))

				def 				lowercase_	(      self				:							List[str])->  Any:



						'''simple docstring'''


						self.assertTrue(_is_punctuation("-"))
						self.assertTrue(_is_punctuation("$"))
						self.assertTrue(_is_punctuation("`"))
						self.assertTrue(_is_punctuation("."))

						self.assertFalse(_is_punctuation("A"))
						self.assertFalse(_is_punctuation(" "))

				def 				lowercase_	(      self				:							List[str])->  Any:



						'''simple docstring'''


						__lowerCAmelCase:			Optional[Any]        =     self.get_tokenizer()
						__lowerCAmelCase:			str        =     self.get_rust_tokenizer()

						# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
						self.assertListEqual([tokenizer.tokenize(__UpperCamelCase) for t in ["Test", "\xad", "test"]]	,    [["[UNK]"], [], ["[UNK]"]])

						self.assertListEqual(
						    [rust_tokenizer.tokenize(__UpperCamelCase) for t in ["Test", "\xad", "test"]]	,    [["[UNK]"], [], ["[UNK]"]])

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



						'''simple docstring'''


						__lowerCAmelCase:			Union[str, Any]        =     self.tokenizer_class.from_pretrained("google/mobilebert-uncased")

						__lowerCAmelCase:			Union[str, Any]        =     tokenizer.encode("sequence builders"	,    add_special_tokens=__UpperCamelCase)
						__lowerCAmelCase:			Dict        =     tokenizer.encode("multi-sequence build"	,    add_special_tokens=__UpperCamelCase)

						__lowerCAmelCase:			Tuple        =     tokenizer.build_inputs_with_special_tokens(__UpperCamelCase)
						__lowerCAmelCase:			Dict        =     tokenizer.build_inputs_with_special_tokens(__UpperCamelCase	,    __UpperCamelCase)

						assert encoded_sentence == [1_0_1] + text + [1_0_2]
						assert encoded_pair == [1_0_1] + text + [1_0_2] + text_a + [1_0_2]

				def 				lowercase_	(      self				:							int)->  int:



						'''simple docstring'''


						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
								with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
										__lowerCAmelCase:			Dict        =     self.rust_tokenizer_class.from_pretrained(__UpperCamelCase	,    **__UpperCamelCase)

										__lowerCAmelCase:			Dict        =     f"A, naïve {tokenizer_r.mask_token} AllenNLP sentence."
										__lowerCAmelCase:			Tuple        =     tokenizer_r.encode_plus(
										    __UpperCamelCase	,    return_attention_mask=__UpperCamelCase	,    return_token_type_ids=__UpperCamelCase	,    return_offsets_mapping=__UpperCamelCase	,    add_special_tokens=__UpperCamelCase	,    )

										__lowerCAmelCase:			List[Any]        =     tokenizer_r.do_lower_case if hasattr(__UpperCamelCase	,    "do_lower_case") else False
										__lowerCAmelCase:			Optional[Any]        =     (
										    [
										        ((0, 0), tokenizer_r.cls_token),
										        ((0, 1), """A"""),
										        ((1, 2), ""","""),
										        ((3, 5), """na"""),
										        ((5, 6), """##ï"""),
										        ((6, 8), """##ve"""),
										        ((9, 1_5), tokenizer_r.mask_token),
										        ((1_6, 2_1), """Allen"""),
										        ((2_1, 2_3), """##NL"""),
										        ((2_3, 2_4), """##P"""),
										        ((2_5, 3_3), """sentence"""),
										        ((3_3, 3_4), """."""),
										        ((0, 0), tokenizer_r.sep_token),
										    ]
										    if not do_lower_case
										    else [
										        ((0, 0), tokenizer_r.cls_token),
										        ((0, 1), """a"""),
										        ((1, 2), ""","""),
										        ((3, 8), """naive"""),
										        ((9, 1_5), tokenizer_r.mask_token),
										        ((1_6, 2_1), """allen"""),
										        ((2_1, 2_3), """##nl"""),
										        ((2_3, 2_4), """##p"""),
										        ((2_5, 3_3), """sentence"""),
										        ((3_3, 3_4), """."""),
										        ((0, 0), tokenizer_r.sep_token),
										    ]
										)

										self.assertEqual(
										    [e[1] for e in expected_results]	,    tokenizer_r.convert_ids_to_tokens(tokens["input_ids"]))
										self.assertEqual([e[0] for e in expected_results]	,    tokens["offset_mapping"])




				def 				lowercase_	(      self				:							Optional[int])->  Dict:



						'''simple docstring'''


						__lowerCAmelCase:			Optional[Any]        =     ["""的""", """人""", """有"""]
						__lowerCAmelCase:			int        =     """""".join(__UpperCamelCase)
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
								with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
										__lowerCAmelCase:			Union[str, Any]        =     True
										__lowerCAmelCase:			Union[str, Any]        =     self.tokenizer_class.from_pretrained(__UpperCamelCase	,    **__UpperCamelCase)
										__lowerCAmelCase:			Tuple        =     self.rust_tokenizer_class.from_pretrained(__UpperCamelCase	,    **__UpperCamelCase)

										__lowerCAmelCase:			Any        =     tokenizer_p.encode(__UpperCamelCase	,    add_special_tokens=__UpperCamelCase)
										__lowerCAmelCase:			List[str]        =     tokenizer_r.encode(__UpperCamelCase	,    add_special_tokens=__UpperCamelCase)

										__lowerCAmelCase:			Dict        =     tokenizer_r.convert_ids_to_tokens(__UpperCamelCase)
										__lowerCAmelCase:			str        =     tokenizer_p.convert_ids_to_tokens(__UpperCamelCase)

										# it is expected that each Chinese character is not preceded by "##"
										self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)
										self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)

										__lowerCAmelCase:			List[Any]        =     False
										__lowerCAmelCase:			Optional[int]        =     self.rust_tokenizer_class.from_pretrained(__UpperCamelCase	,    **__UpperCamelCase)
										__lowerCAmelCase:			Any        =     self.tokenizer_class.from_pretrained(__UpperCamelCase	,    **__UpperCamelCase)

										__lowerCAmelCase:			Union[str, Any]        =     tokenizer_r.encode(__UpperCamelCase	,    add_special_tokens=__UpperCamelCase)
										__lowerCAmelCase:			Optional[Any]        =     tokenizer_p.encode(__UpperCamelCase	,    add_special_tokens=__UpperCamelCase)

										__lowerCAmelCase:			Tuple        =     tokenizer_r.convert_ids_to_tokens(__UpperCamelCase)
										__lowerCAmelCase:			List[str]        =     tokenizer_p.convert_ids_to_tokens(__UpperCamelCase)

										# it is expected that only the first Chinese character is not preceded by "##".
										__lowerCAmelCase:			Optional[Any]        =     [
										    f"##{token}" if idx != 0 else token for idx, token in enumerate(__UpperCamelCase)
										]
										self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)
										self.assertListEqual(__UpperCamelCase	,    __UpperCamelCase)



import math
from typing import Optional

import numpy as np

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


SCREAMING_SNAKE_CASE		:     Union[str, Any]         =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:     Tuple         =	{
    "facebook/encodec_24khz": "https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json",
    "facebook/encodec_48khz": "https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json",
}

class        UpperCamelCase						(				__a				):
						a__		:int      =			'''encodec'''





						def __init__(self			,     __UpperCamelCase=[1.5, 3.0, 6.0, 12.0, 24.0]			,     __UpperCamelCase=24_000			,     __UpperCamelCase=1			,     __UpperCamelCase=False			,     __UpperCamelCase=None			,     __UpperCamelCase=None			,     __UpperCamelCase=128			,     __UpperCamelCase=32			,     __UpperCamelCase=1			,     __UpperCamelCase=[8, 5, 4, 2]			,     __UpperCamelCase="weight_norm"			,     __UpperCamelCase=7			,     __UpperCamelCase=7			,     __UpperCamelCase=3			,     __UpperCamelCase=2			,     __UpperCamelCase=True			,     __UpperCamelCase="reflect"			,     __UpperCamelCase=2			,     __UpperCamelCase=2			,     __UpperCamelCase=1.0			,     __UpperCamelCase=1_024			,     __UpperCamelCase=None			,     __UpperCamelCase=True			,     **__UpperCamelCase			,     )				->				Dict:
												UpperCamelCase_		:							str  =		target_bandwidths
												UpperCamelCase_		:							Tuple  =		sampling_rate
												UpperCamelCase_		:							str  =		audio_channels
												UpperCamelCase_		:							Any  =		normalize
												UpperCamelCase_		:							Union[str, Any]  =		chunk_length_s
												UpperCamelCase_		:							Optional[Any]  =		overlap
												UpperCamelCase_		:							Any  =		hidden_size
												UpperCamelCase_		:							Dict  =		num_filters
												UpperCamelCase_		:							List[str]  =		num_residual_layers
												UpperCamelCase_		:							Optional[int]  =		upsampling_ratios
												UpperCamelCase_		:							str  =		norm_type
												UpperCamelCase_		:							str  =		kernel_size
												UpperCamelCase_		:							Tuple  =		last_kernel_size
												UpperCamelCase_		:							int  =		residual_kernel_size
												UpperCamelCase_		:							str  =		dilation_growth_rate
												UpperCamelCase_		:							str  =		use_causal_conv
												UpperCamelCase_		:							str  =		pad_mode
												UpperCamelCase_		:							Union[str, Any]  =		compress
												UpperCamelCase_		:							Dict  =		num_lstm_layers
												UpperCamelCase_		:							Optional[int]  =		trim_right_ratio
												UpperCamelCase_		:							int  =		codebook_size
												UpperCamelCase_		:							str  =		codebook_dim if codebook_dim is not None else hidden_size
												UpperCamelCase_		:							Optional[int]  =		use_conv_shortcut

												if self.norm_type not in ["weight_norm", "time_group_norm"]:
																		raise ValueError(
																		    f'''self.norm_type must be one of `"weight_norm"`, `"time_group_norm"`), got {self.norm_type}'''						)

												super().__init__(**__UpperCamelCase						)





						@property
						def        A_							(self						)				->				Optional[int]:
												if self.chunk_length_s is None:
																		return None
												else:
																		return int(self.chunk_length_s * self.sampling_rate						)





						@property
						def        A_							(self						)				->				Optional[int]:
												if self.chunk_length_s is None or self.overlap is None:
																		return None
												else:
																		return max(1			,     int((1.0 - self.overlap) * self.chunk_length						)						)





						@property
						def        A_							(self						)				->				int:
												UpperCamelCase_		:							int  =		np.prod(self.upsampling_ratios						)
												return math.ceil(self.sampling_rate / hop_length						)





						@property
						def        A_							(self						)				->				int:
												return int(1_000 * self.target_bandwidths[-1] // (self.frame_rate * 10)						)






