code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
FlaxFor... | 90 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def __UpperCamelCase ( lowerCAmelCase__ : str ):
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikiped... | 90 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torch
class ... | 90 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 1 |
import colorsys
from PIL import Image # type: ignore
def __UpperCamelCase ( lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : int ):
__a : int = x
__a : Dict = y
for step in range(lowerCAmelCase__ ): # noqa: B00... | 90 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ ={'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()... | 90 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 1 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class UpperCamelCase__ :
_SCREAMING_SNAKE_CASE : Tuple = None
def lowerCAmelCase (self : int ):
__a : Optional[Any] = self.feature_extraction_class... | 90 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 1 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepiece
@slow # see ... | 90 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTester... | 90 | 1 |
from __future__ import annotations
class UpperCamelCase__ :
def __init__(self : Union[str, Any] , snake_case_ : str , snake_case_ : str ):
__a , __a : str = text, pattern
__a , __a : Tuple = len(snake_case_ ), len(snake_case_ )
def lowerCAme... | 90 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : str ):
__a : int = [int(lowerCAmelCase__ ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(lowerCAmelCase__ ) == 4 and all(0 <= int(lowerCAmelCase__ ) <= 2_5_4 for octet in octets )
if __name__ == "__main__":
lo... | 90 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 1 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enable_... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 1 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowercase__ =False
class UpperCamelCase__ ( unittest.TestCase ):
pass
@ni... | 90 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0 , lowerCAmelCase__ : int = 1_0_0_0 , lowerCAmelCase__ : bool = True ):
assert (
isinstance(lowerCAmelCase__ , lowerCAmelCase__ )
and isinstance(lowerCAmelCase__ , lowerCAmelCase__ )
... | 90 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
__a : Union[str, Any] = str(bin(lowerCAmelCase__ ) )[2:] # remove the leading "0b"
__a : Dict ... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 | 1 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __UpperCamelCase ( lowerCAmelCase__ : int ):
# A local function to see if a dot lands in the circle.
def is_in_circle(lowerCAmelCase__ : float , lower... | 90 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
lowercase__ ={
'configuration_audio_spectrogram_transformer': [
'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ASTConfig',
]
}
... | 90 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart impor... | 90 | 1 |
from math import factorial
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0 ):
return sum(int(lowerCAmelCase__ ) for x in str(factorial(lowerCAmelCase__ ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
| 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 1 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from tra... | 90 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
lowercase... | 90 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import ... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
def merge(lowerCAmelCase__ : list , lowerCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
re... | 90 | 1 |
from math import sqrt
def __UpperCamelCase ( lowerCAmelCase__ : int ):
assert isinstance(_UpperCAmelCase , _UpperCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
__a : Tuple = True
# 0 and 1 are none primes.
if number <= 1:
__a : Di... | 350 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __UpperC... | 90 | 0 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_token... | 351 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTester
from ...... | 352 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 0 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowerCAmelCase__ : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('''Undefined for non-integers''' )
elif precision < 1:
raise ValueError('''Undefi... | 353 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 0 |
import numpy as np
import torch
from ..models.clipseg import CLIPSegForImageSegmentation
from ..utils import is_vision_available, requires_backends
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class UpperCamelCase__ ( a__ ):
_SCREAMING_SNAKE_CASE : Optiona... | 354 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 0 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowercase__ =pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paws''', '''csv... | 355 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 0 |
from sklearn.metrics import recall_score
import datasets
lowercase__ ="""
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is the true positives and FN is the false negatives.
"""
... | 356 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 0 |
import argparse
from collections import defaultdict
def __UpperCamelCase ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Dict , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : List[Any] ):
... | 357 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 0 |
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def __UpperCamelCase ( lowerCAmelCase__ : str ):
__a : Any = tmp_... | 358 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 0 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigT... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 0 |
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configuration_... | 360 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTester... | 90 | 0 |
from __future__ import annotations
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : list[int] ):
__a : Optional[Any] = 1
__a : Union[str, Any] = max(lowerCAmelCase__ )
while placement <= max_digit:
# declare and initialize empty buckets
__a ... | 361 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 0 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.test... | 362 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 0 |
def __UpperCamelCase ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Union[str, Any] ):
__a : str = [0 for i in range(r + 1 )]
# nc0 = 1
__a : Union[str, Any] = 1
for i in range(1 , n + 1 ):
# to compute current row from previous row.
__a ... | 363 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 0 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase__ =logging.get_logger(__name__)
class UpperCamelCase__ ( a_ ):
def __init__(self : Union[str, Any] , *snake_case_ : Union[str, Any] , **snake_case_ : List[Any] ... | 364 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 0 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : Union[str, Any] = 2**power
__a : Union[str, Any] = 0
while n:
__a : Dict = r + n % 1_0, n // 1_0
return r
if __name__ == "__main__":
print(solution(int(str(input()).strip())))
| 365 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTe... | 366 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 | 0 |
class UpperCamelCase__ :
def __init__(self : Tuple ):
__a : Tuple = {}
def lowerCAmelCase (self : Union[str, Any] ):
print(self.vertex )
for i in self.vertex:
print(lowerCAmelCase__ , ''' -> ''' , ''' -> '''.join([str(lowerCAmelCase__ ) for ... | 367 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 0 |
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class UpperCamelCase__ ( _UpperCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = 'openai/whisper-base'
_SCREAMING_SNAKE_CASE : Optional[Any] = (
'This is a too... | 368 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart impor... | 90 | 0 |
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowercase__ ='''▁'''
lowercase__ ... | 369 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 0 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def __UpperCamelCase ( *lowerCAmelCase__ : int , lowerCAmelCase__ : Optional[Union[Dict, Any]] = None , lowerCAmelCase__ : Any=True , lowerCAmelC... | 370 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
lowercase... | 90 | 0 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ =logging.get_logger(__name__)
lowercase__ ={
"snap-research/efficientformer-l1-300": (
"https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.... | 371 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
def merge(lowerCAmelCase__ : list , lowerCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
re... | 90 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_xlnet import X... | 350 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __UpperC... | 90 | 0 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : Tuple ):
__a : int = int(number**0.5 )
return number == sq * sq
def __UpperCamelCase ( lowerCAmelCase__ : Any ... | 351 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 | 0 |
import argparse
import json
from tqdm import tqdm
def __UpperCamelCase( ):
__a : List[str] = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_path''' , type=_snake_case , default='''biencoder-nq-dev.json''' , help='''Path to raw DPR tra... | 352 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
logging.set_... | 353 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 0 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class UpperCamelCase__ ( __lowercase ):
def __init__(self : Union[str, Any] , snake_cas... | 354 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 0 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 355 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 0 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCamelCase__ ( __UpperCamelCase ):
_SC... | 356 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 0 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def __UpperCamelCase ( ):
__a : List[Any] = 9
__a : str = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
[2, 8, 2],
[8, 6, 6],
[2, 3, 7],
[2, 5, 4],
[6, 5, 2],
... | 357 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowercase__ ={'processing_wav2vec2_with_lm': ['Wav2Vec2ProcessorWithLM']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
lowercase__ =_LazyModule(__name_... | 358 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 0 |
from math import pi, sqrt, tan
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''' )
return 6 * side_length**2
def __UpperCamelCase ( lowerCAmelCase__ : floa... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 0 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase__ =logging.get_logger(__name__)
lowercase__ ={
"""nielsr/canine-s""": 2048,
}
# Unicode defines 1,114,112 total “codepoints”
lowercase__ ... | 360 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTester... | 90 | 0 |
from __future__ import annotations
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : int ):
if len(a__ ) == 0:
return False
__a : Optional[Any] = len(a__ ) // 2
if a_list[midpoint] == item:
return True
if item < a_list[midpoint]:
ret... | 361 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 0 |
def __UpperCamelCase ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Dict ):
while a != 0:
__a , __a : int = b % a, a
return b
def __UpperCamelCase ( lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : Any ):... | 362 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ ={
'configuration_electra': ['ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ElectraConfi... | 363 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class UpperCamelCase__ ( unittest.TestCase ):
def lowerCAmelCase... | 364 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 0 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
logg... | 365 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torc... | 366 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 | 0 |
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def __UpperCamelCase ( ):
raise RuntimeError('''CUDA out of memory.''' )
class UpperCamelCase__ ( nn.Module ):
... | 367 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 0 |
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
__a : Optional[int] = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
__a : Dict = n - k
# Calculate C(n,k)
for i in range(__lowerCamelCase ):
resu... | 368 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart impor... | 90 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
lowercase__ ={"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 369 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 0 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 3 , lowerCAmelCase__ : int = 7 , lowerCAmelCase__ : int = 1_0_0_0_0_0_0 ):
__a : List[str] = 0
__a : Any = 1
for current_denominator in range(1 , limit + 1 ):
__a : str = cur... | 370 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
lowercase... | 90 | 0 |
import os
from datetime import datetime as dt
from github import Github
lowercase__ =[
'good first issue',
'feature request',
'wip',
]
def __UpperCamelCase ( ):
__a : List[Any] = Github(os.environ['''GITHUB_TOKEN'''] )
__a : Union[str, Any] = g.get_repo(''... | 371 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
def merge(lowerCAmelCase__ : list , lowerCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
re... | 90 | 0 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,... | 350 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __UpperC... | 90 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ =logging.get_logger(__name__)
lowercase__ ={
"""facebook/data2vec-text-base""": """https://huggingface.co/... | 351 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer
lowe... | 352 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 0 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class UpperCamelCase__ ( snake_case_ ):
def lowerCAmelCase (self : Optional[Any] ):
return [
{"col_1": 3, "col_2": "a"},
{"col_1": 2, "col_2": "b"},
{"co... | 353 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 0 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
lowercase__ =logging.... | 354 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 0 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
lowercase__ =logging.getLogger(__name__)
if __name__ == "__main__":
lowercase__ ... | 355 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 0 |
def __UpperCamelCase ( lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Any ):
__a : Union[str, Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def __UpperCamelCase ( lowerCAmelCase__ : Dict , lowerCAmel... | 356 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 0 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configurati... | 357 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 0 |
import string
def __UpperCamelCase ( lowerCAmelCase__ : Optional[Any] ):
for key in range(len(string.ascii_uppercase ) ):
__a : List[str] = ''''''
for symbol in message:
if symbol in string.ascii_uppercase:
__a : Optional[int] = string.ascii_uppercase... | 358 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 0 |
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is_tf_available() and not... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 0 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( _lowercase ,unittest.TestCase ):
_SCREAMIN... | 360 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTester... | 90 | 0 |
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Optional[Any] = '''openai/whisper-base'''
_SCREAMING_SNAKE_CASE : str = (
'''This is a... | 361 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 0 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test... | 362 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
logging... | 363 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, Dist... | 364 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 0 |
import random
from typing import Any
def __UpperCamelCase ( lowerCAmelCase__ : list ):
for _ in range(len(_a ) ):
__a : List[str] = random.randint(0 , len(_a ) - 1 )
__a : Any = random.randint(0 , len(_a ) - 1 )
__a : Dict = data[b],... | 365 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 0 |
from collections import defaultdict
from math import ceil, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : Any = 1_0_0_0_0_0_0 , lowerCAmelCase__ : Optional[int] = 1_0 ):
__a : int = defaultdict(SCREAMING_SNAKE_CASE_ )
for outer_width in range(3 , (t_limit... | 366 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 | 0 |
from itertools import product
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
__a : List[Any] = sides_number
__a : Optional[Any] = max_face_number * dice_number
__a : List[Any] = [0] * (max_total + 1)
__a : Union[s... | 367 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 0 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowercase__ =get_tests_dir('fixtures/spiece.model')
@req... | 368 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart impor... | 90 | 0 |
def __UpperCamelCase ( ):
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
lowercase__ =generate_large_matrix()
lowercase__ =(
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[[3, 2], [1, 0]],
[[7, 7, 6]],... | 369 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 0 |
import socket
def __UpperCamelCase ( ):
__a : Optional[int] = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
__a : Union[str, Any] = socket.gethostname()
__a : Tuple = 1_2_3_1_2
sock.connect((host, port) )
sock.send(b'''Hello server!''' )
with open(''... | 370 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
lowercase... | 90 | 0 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging
from .benchmark... | 371 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
def merge(lowerCAmelCase__ : list , lowerCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
re... | 90 | 0 |
from math import factorial
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
if n < k or k < 0:
raise ValueError('''Please enter positive integers for n and k where n >= k''' )
return factorial(lowerCamelCase__ ) // (factorial(lowerCamelCase... | 350 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __UpperC... | 90 | 0 |
def __UpperCamelCase ( lowerCAmelCase__ : Any=2_8_1_2_3 ):
__a : Tuple = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1 ):
sum_divs[k * i] += k + i
__a : Union[str, Any] = set... | 351 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 | 0 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class UpperCamelCase__ ( nn.Module ):
_SCREAMING_SNAKE_CASE : Optional[Any] = 42
_SCREAMING_SNAKE_CASE : List[str] = jnp.floataa
def lowerCAmelCase (self : Optional[int] ):
__a : Option... | 352 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 0 |
import sys
import turtle
def __UpperCamelCase ( lowerCAmelCase__ : tuple[float, float] , lowerCAmelCase__ : tuple[float, float] ):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def __UpperCamelCase ( lowerCAmelCase__ : tuple[float, float] , ... | 353 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline... | 354 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 0 |
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, r... | 355 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 0 |
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowercase__ ='src/transformers'
# This is to make sure the transformers module imported is the one in t... | 356 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}
class UpperCamelCase__ ( A__... | 357 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 0 |
from __future__ import annotations
from cmath import sqrt
def __UpperCamelCase ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ):
if a == 0:
raise ValueError('''Coefficient \'a\' must not be zero.''' ... | 358 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 0 |
import itertools
import math
def __UpperCamelCase ( lowerCAmelCase__ : str ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# A... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 0 |
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
lowercase__ ="facebook/wmt19-en-de"
lowercase__ =FSMTTokenizer.from_pretrained(mname)
# get the correct vocab sizes, etc. from the master model
lowercase__ =FSMTConfig.from_pretrained(mname)
config.update(
... | 360 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTester... | 90 | 0 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowercase__ =version.parse(version.parse(torch.__version__).base_version) < version.parse('1.11')
def __UpperCamelCase ( lowerCAmelCas... | 361 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI... | 362 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 0 |
from __future__ import annotations
from functools import lru_cache
from math import ceil
lowercase__ =100
lowercase__ =set(range(3, NUM_PRIMES, 2))
primes.add(2)
lowercase__ =42
for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
if prime not in primes:
continue
primes.difference_up... | 363 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDetection
from t... | 364 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 0 |
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub_u... | 365 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 0 |
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