code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE :Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE :Dict = {
'k... | 55 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE ( lowerCAmelCase , unittest.Tes... | 62 | 0 |
'''simple docstring'''
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 a ( snake_case__ ):
'... | 424 |
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
from .feat... | 424 | 1 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 132 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
'studio-ousia/luke-large': 'https://huggingface... | 132 | 1 |
'''simple docstring'''
from collections.abc import Iterable
from typing import Generic, TypeVar
lowerCAmelCase : Optional[Any] = TypeVar("""_T""")
class _UpperCamelCase ( Generic[_T]):
'''simple docstring'''
def __init__( self , a_ = None ) -> ... | 425 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
f... | 425 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, 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 i... | 523 | '''simple docstring'''
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMix... | 523 | 1 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCA... | 648 |
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
lowerCAmelCase__ = {
"""sample_size""": 3_2,
"""in_channels""": 3,
"""out_channels""": 3,
"""layers_per_block""": 2,
"""num_class_embeds""... | 648 | 1 |
'''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, requ... | 51 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchau... | 292 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_... | 197 | """simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
... | 197 | 1 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class _UpperCAmelCase ( __low... | 145 |
def _lowercase ( __lowerCamelCase : Optional[int] ,__lowerCamelCase : Dict ,__lowerCamelCase : str ,__lowerCamelCase : Optional[int] ) -> List[str]:
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0... | 344 | 0 |
'''simple docstring'''
def lowercase_ ( __A : str , __A : Dict ) -> int:
"""simple docstring"""
return number | (1 << position)
def lowercase_ ( __A : Union[str, Any] , __A : List[Any] ) -> int:
"""sim... | 717 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import ... | 8 | 0 |
import argparse
import os
import re
import packaging.version
SCREAMING_SNAKE_CASE :Optional[Any] = """examples/"""
SCREAMING_SNAKE_CASE :Dict = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
... | 628 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE :Optional[Any] = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""https://huggingf... | 628 | 1 |
"""simple docstring"""
from __future__ import annotations
def __a ( A , A , A ):
'''simple docstring'''
lowercase__ = list(range(len(A ) ) )
lowercase__ = [v / w for v, w in zip(A , A )]
index.sort(key=lambda A ... | 715 | """simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import Flax... | 668 | 0 |
'''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
__A = logging.get_logger(__name__)
__A = {
"facebook/data... | 325 |
def lowerCAmelCase ( UpperCAmelCase ) ->str:
"""simple docstring"""
return " ".join(
''''''.join(word[::-1] ) if len(UpperCAmelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
do... | 154 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational i... | 721 |
'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import comput... | 502 | 0 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
SCREAMING_SNAKE_CASE :Tuple = logging.get_logger(__name__)
def UpperCAmelCase ( a_... | 55 |
import os
def UpperCAmelCase ( ) -> Any:
"""simple docstring"""
__A = os.path.dirname(os.path.realpath(a_ ) )
__A = os.path.join(a_ , "triangle.txt" )
with open(a_ ) as f:
__A = f.readlines()
__A = []
f... | 55 | 1 |
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
lowercase__ : str = logging.get_logger(__name__)
def A_ ( ... | 706 |
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 451 | 0 |
'''simple docstring'''
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 transformer... | 50 |
'''simple docstring'''
# 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... | 50 | 1 |
'''simple docstring'''
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 = {
"""andreasmadsen/efficient_mlm_m0... | 706 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowercase = 300 # TEMPERATURE (unit = K)
def A (__lowerCamelCase :float , __lowerCamelCase :float , __lowerCamelCase :float , ):
if donor_conc <= 0:
raise V... | 162 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transf... | 602 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _a :
"""simple docstring"""
def __init__( self : int , __UpperCamelCase : list[str] )->Dict:
_UpperCAmelCase = []
self.adlist.append(
... | 602 | 1 |
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
logg... | 701 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
... | 224 | 0 |
'''simple docstring'''
def _snake_case ( A_ : int ):
"""simple docstring"""
if number > 0:
raise ValueError("""input must be a negative integer""" )
a_ : str = len(bin(_snake_case )[3:] )
a_ : str = bin(abs(_snake_case ) - (1 << binary_num... | 577 | """simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
A : int = get_logger(__name__)
A : Dict = r'\n Args:\n input_ids (`jnp.... | 516 | 0 |
import string
from math import logaa
def SCREAMING_SNAKE_CASE( __UpperCamelCase , __UpperCamelCase ) -> int:
a__ : str = document.translate(
str.maketrans("" , "" , string.punctuation ) ).replace("\n" , "" )
a__ : int = docum... | 720 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("""3.8"""):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
lowerCamelCase = ... | 207 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
SCREAMING_SNAKE_CASE = logging.g... | 554 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def UpperCAmelCase ( A : dict , A : str , A : set , A : set , A : dict , A : dict , A : PriorityQueue , A : dict... | 527 | 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 (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 590 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
UpperCAmelCase_ : Dict = (3, 9, -11, 0, 7, 5, 1, -1)
UpperCAmelCase_ : Optional[Any] = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class _SCREAMING_SNAKE_CASE :
s... | 590 | 1 |
# 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 a... | 312 | import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enabl... | 312 | 1 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requ... | 180 |
# 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 (... | 180 | 1 |
from __future__ import annotations
import os
from typing import Any
import requests
UpperCamelCase__ ='''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
UpperCamelCase__ =BASE_URL + '''/user'''
# https://github.com/settings/t... | 249 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
fr... | 445 | 0 |
'''simple docstring'''
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase : Union[str, Any] = logging.get_logger(__name__)
lowercase : Any = {
'''vocab_file''':... | 721 |
def lowerCAmelCase__ ( _a : str , _a : int ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
snake_case_ : Optional[Any] = (boundary[1] - boundary[0]) / steps
snake_case_ : str = boundary[0]
snake_case_ ... | 114 | 0 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_p... | 432 |
'''simple docstring'''
def UpperCamelCase ( a , a ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F'''{price_plus_tax(100, 0.25) = }''')
print(F'''{price_plus_tax(125.50, 0.05) = }''')
| 432 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky... | 569 |
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __lowerCamelCase ( snake_case__ ,snake_case__ ,snake_case__ ,snake_case__ ,sn... | 569 | 1 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class UpperCAmelCase__( yaml.SafeLoader ):
'''simple docstring'''
def UpperCAmelCase ( self : str , lowerCAmelCase : Any) -> Optional[Any]:
... | 622 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise ... | 486 | 0 |
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
A__ : List[str] = logging.get_logger(__name__)
A__ : Optional[Any] = {
... | 671 |
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
A__ : Dict = 50_00_00
A__ , A__ : str = os.path.split(__file__)
A__ : Optional[Any] = os.path.join(RESULTS_BASEPATH, 'res... | 671 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__a :int = {'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}
try:
if not is_torch_available():
... | 86 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a_ : Tuple = {'configuration_unispeech': ['UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechConfig']}
... | 623 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {'vocab_file': 'spiece.model'}
_sn... | 567 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def _a ( ) -> Tuple:
"""simple docstring"""
__UpperCamelCase , __UpperCamelCase = 9, 14 # noqa: F841
__UpperCamelCase = [
... | 567 | 1 |
from __future__ import annotations
_lowerCamelCase : Any = [True] * 1_000_001
_lowerCamelCase : Any = 2
while i * i <= 1_000_000:
if seive[i]:
for j in range(i * i, 1_000_001, i):
_lowerCamelCase : Optional[int] = False
i += 1
def ... | 352 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __a ( __lowerCAmelCase ) -> int:
for param in module.parameters():
SCREAMING_SNAKE_CASE : List[Any] = False
def __a ( ) -> List[str]:
SCREAMIN... | 352 | 1 |
"""simple docstring"""
from __future__ import annotations
__lowerCamelCase :int = 1.6_021e-19 # units = C
def snake_case ( UpperCamelCase__ : float , UpperCamelCase__ : float , UpperCamelCase__ : float , ) -> tuple[str, float]:
if ... | 706 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowerCamelCase :str = get_tests_dir... | 42 | 0 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
lowercase_: Tuple = TypeVar('T')
class lowercase__ (Generic[T] ):
"""simple docstring"""
__UpperCamelCase : deque[T] # Cache... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase ( lowercase__ ):
... | 441 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def Uppe... | 441 | 1 |
def _SCREAMING_SNAKE_CASE ( ) -> Tuple:
"""simple docstring"""
__A = []
__A = 1
while len(UpperCamelCase__ ) < 1E6:
constant.append(str(UpperCamelCase__ ) )
i += 1
__A = """""".join(UpperCamelCase__ )
... | 637 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavin... | 407 | 0 |
'''simple docstring'''
from functools import reduce
a_ : Any = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"1254069874715852386305071569329096... | 532 |
'''simple docstring'''
import datasets
a_ : List[Any] = "\\n@InProceedings{conneau2018xnli,\n author = \"Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n ... | 532 | 1 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCamelCase : Optional[Any] = get_tests_dir("""fixtures/test_sentencep... | 87 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
A__ : Optional[int] ='''.'''
if __name__ == "__main__":
A__ : int =os.path.join(... | 207 | 0 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def _lowerCamelCase ( _a ):
"""simple docstring"""
_lowerCamelCase = prime_factors(_a )
if is_square_free(_a ):
return -1 if len(_a ) % 2 else 1
return 0
if __name__ ==... | 715 |
from __future__ import annotations
from collections.abc import MutableSequence
class __magic_name__ :
"""simple docstring"""
def __init__( self , a__ , a__ ):
if len(a__ ) != degree + 1:
raise ValueError(
'''The number of coefficients should be equal to the degree + 1.... | 297 | 0 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_... | 444 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase : Any = {
"""configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """C... | 444 | 1 |
"""simple docstring"""
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizatio... | 710 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ : List[str] = logging.get_logger(__name__)
UpperCAmelCase_ : Dic... | 176 | 0 |
"""simple docstring"""
import functools
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
# Validation
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or not all(isinstance(SCREAMING_SNAKE_CASE , SCREAM... | 102 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e im... | 259 | 0 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class _UpperCAmelCase ( lowercase ):
lowerCamelCase_ : Union[str, Any] = """EncodecFeatureExtractor"""
lowerCamelCase_ : Any = ("""T5Tokenizer""",... | 140 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"configuration_albert": ["ALBERT_PRE... | 140 | 1 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class lowercase_ ( unittest.TestCase , _UpperCamelCase ):
"""simple docstring"""
def __UpperCAmelCase ( self : List[str] ) -> Union[s... | 107 |
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 center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEA... | 542 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoToken... | 714 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fro... | 11 | 0 |
import requests
UpperCAmelCase = '''''' # <-- Put your OpenWeatherMap appid here!
UpperCAmelCase = '''https://api.openweathermap.org/data/2.5/'''
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE = "Chicago" , __SCREAMING_SNAKE_CASE = APPID ):
return requests.get(URL_BASE ... | 84 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class _SCREAMING_SNAKE_CASE :
lowerCAmelCase__ = 42 # [batch_size x 3]
lowerCAmelCase__ = 42 # [batch_size x 3]
lowerCAmelCase__ = 42 # [batch_size x 3]
lowerCAmelCase__ = 42... | 463 | 0 |
class lowercase__ :
def __init__( self : List[Any] , _lowercase : Dict , _lowercase : Dict , _lowercase : str ):
"""simple docstring"""
UpperCAmelCase__ = name
UpperCAmelC... | 716 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
A = 6378137.0
A = 6356752.314245
A = 637_8137
def __UpperCAmelCase ( __A , __A , __A , __A ) -> float:
'''simple docstring'''
... | 277 | 0 |
"""simple docstring"""
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 ...tes... | 169 |
"""simple docstring"""
from math import log
from scipy.constants import Boltzmann, physical_constants
a = 3_0_0 # TEMPERATURE (unit = K)
def lowercase (snake_case__ : float , snake_case__ : float , snake_case__ : float , ) -> float:
'''simple docstr... | 169 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerConfig''',
'''Bri... | 478 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
... | 478 | 1 |
'''simple docstring'''
# 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
#
... | 92 |
'''simple docstring'''
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _a (__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE=1024 ):
"""simple docstring"""
_UpperCa... | 404 | 0 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
_UpperCamelCase : Tuple =logging.get_logger(__name__)
def a__ (__lowercase :Optio... | 332 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_UpperCamelCase : Union[str, Any] ='\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},... | 332 | 1 |
'''simple docstring'''
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
fro... | 378 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concaten... | 229 | 0 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__a = get_logger(__name__)
class __lowercase ( enum.Enum ):
UpperCamelCase = '''all_checks'''
UpperCamelCase = ... | 627 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 1 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A_ : Dict = logging.get_logger(__name__)
A_ : Union[str, Any] = {
"vocab_file": "vocab.... | 38 |
import math
snake_case__ = 10
snake_case__ = 7
snake_case__ = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCamelCase__ ( a : int = 20 ) -> str:
"""simple docstring"""
a__ :List[str] = math.comb(a , a )
a__ :Optional[int] ... | 395 | 0 |
"""simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class snake_case :
def __init__(self , SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
... | 708 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def ... | 628 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase__ ( lowercase__ : list[float] ):
snake_case : Optional[Any] = 0.00
snake_case : Any = 0
for resistor in resistors:
if resistor <= 0:
snake_case : List[str... | 134 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch... | 134 | 1 |
'''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _SCREAMING_SNAKE_CASE ( A : Union[str, Any] , A : Any , A : Tuple ) -> Any:
"""simple docstring"""
__snake_case ... | 61 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( A : list ) -> list:
"""simple docstring"""
__snake_case : Tuple = False
while is_sorted is False: # Until all the indices are traversed keep looping
__snake_case : ... | 61 | 1 |
from collections import defaultdict
from math import ceil, sqrt
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ = 1000000 , SCREAMING_SNAKE_CASE__ = 10 ):
snake_case_ = defaultdict(SCREAMING_SNAKE_CASE__ )
for outer_width in range(3 , (t_limit // 4) + 2 ):
... | 39 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE__ ( lowercase ):
"""simple docstring"""
a : int ="Speech2TextFeatureExtractor"
a : int ="Speech... | 645 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def A ( snake_case__ , snake_case__ , snake_case__ ):
... | 719 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
A_ : Un... | 616 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 693 |
import argparse
import json
from tqdm import tqdm
def _A ( ) -> Optional[int]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" , type=__snake_case , defau... | 693 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokeni... | 600 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( __UpperCAmelCase ):
if n == 1 or not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
return 0
elif n == 2:
return 1
else:
_lowercase : int = [0, 1]
for i in range(2 , n + 1 ):
... | 600 | 1 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, Re... | 23 |
"""simple docstring"""
from collections.abc import Callable
class a__ :
def __init__( self :Tuple , _lowerCamelCase :Callable | None = None ):
'''simple docstring'''
UpperCamelCase_ : list =[]
# Stores indexes of each item for supporting u... | 357 | 0 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInput,
... | 161 |
from math import ceil
def UpperCamelCase( lowercase_ , lowercase_ ) -> Any:
'''simple docstring'''
snake_case_ = list(range(0 , lowercase_ ) )
snake_case_ = [item for sublist in list(device_map.values() ) for item in sublist]
# D... | 161 | 1 |
from math import ceil
def __a ( A__ : str , A__ : Optional[Any] ):
SCREAMING_SNAKE_CASE = list(range(0 , A__ ) )
SCREAMING_SNAKE_CASE = [item for sublist in list(device_map.values() ) for item in sublist]
# Duplicate c... | 16 | def UpperCAmelCase ( lowercase , lowercase ):
"""simple docstring"""
__lowercase = word.split()
def justify(lowercase , lowercase , lowercase ) -> str:
__lowercase = max_width - width
__lowercase = len(lo... | 534 | 0 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ... | 705 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = [
["""attention""", """attn"""],
["""encoder_at... | 648 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def UpperCamelCase_ ( UpperCamelCase : ArgumentParser ):
'''simple docstring'''
... | 411 |
def lowerCamelCase_ ( lowerCAmelCase: str )-> str:
_snake_case : str = 0
# if input_string is "aba" than new_input_string become "a|b|a"
_snake_case : List[Any] = ''
_snake_case : Dict = ''
# append each character + "|" in new_strin... | 411 | 1 |
"""simple docstring"""
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
Alber... | 719 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_conf... | 215 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : int = {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}
try:
if not is_torch_available():
... | 49 |
import requests
_SCREAMING_SNAKE_CASE : Optional[int] = "" # <-- Put your OpenWeatherMap appid here!
_SCREAMING_SNAKE_CASE : Optional[Any] = "https://api.openweathermap.org/data/2.5/"
def UpperCAmelCase__ (UpperCamelCase_ = "Chicago" ,UpperCamelCase_ = APPID ... | 550 | 0 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class _UpperCamelCase ( lowerCAmelCase ):
UpperCAmelCase_ ... | 717 |
import math
def lowerCAmelCase ( _lowerCAmelCase : int ):
"""simple docstring"""
UpperCAmelCase__ = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(_lowerCAmelCase )
def lowerCAmelCase ( _lowerCAmelCase : float = 1... | 364 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import random
class lowerCAmelCase :
def __init__( self , __SCREAMING_SNAKE_CASE = None ) -> Any:
'''simple docstring'''
__snake_case = value
__snake_case ... | 24 |
import gc
import unittest
from transformers import CTRLConfig, 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 ModelTe... | 149 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
snake_case : Tuple = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
snake_case : Optional[int] = [file for ... | 706 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case : Dict = logging.get_logger(__name__)
snake_case : Any = {name: getattr(transformers, name + '''Fast''') for na... | 657 | 0 |
"""simple docstring"""
from __future__ import annotations
A : str = 'Muhammad Umer Farooq'
A : Dict = 'MIT'
A : Optional[Any] = '1.0.0'
A : Optional[int] = 'Muhammad Umer Farooq'
A : Tuple = 'contact@muhammadumerfaroo... | 516 | """simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -... | 516 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase )
class UpperCAmelCase__ ( UpperCamelCase ):
lowerCAmelC... | 109 |
"""simple docstring"""
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowerCAmelCase__ ( ) -> Optional[Any]:
import os as original_os
from os import path as original_path
from os import rename as original_rename
... | 109 | 1 |
'''simple docstring'''
def UpperCAmelCase_ ( __lowercase : int ) -> str:
'''simple docstring'''
if isinstance(__lowercase , __lowercase ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(__lowercase , __lower... | 236 |
'''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
... | 236 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def _lowerCamelCase ( lowercase : str , lowercase : i... | 521 |
'''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def _lowerCamelCase ( lowercase : str , lowercase : i... | 521 | 1 |
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase ( metaclass=_A ):
"""simple docstring"""
A = ['''torch''']
def __init__( self , *_lowerCAmelCase , **_lowerCAmelCase ):
'''simple docstring'''
requires_... | 145 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class _UpperCAmelCase ( _A ):
"""simple docstring"""
A = '''EncodecFeatureExtractor'''
A = ('''T5Tokenizer''', '''T5TokenizerFas... | 145 | 1 |
def lowerCamelCase__ ( _lowercase = 1000 ):
'''simple docstring'''
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution()) | 300 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 300 | 1 |
"""simple docstring"""
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 ..... | 19 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_comm... | 599 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Dict = logging.get_logger(__name__)
snake_case_ : List[Any] = {
"""asapp/sew-tiny-100k""": """https://huggingface.co/as... | 292 |
"""simple docstring"""
def lowercase_ ( _lowercase : int , _lowercase : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def lowercase_ ( ):
'''simple docstring'''
print("Truth Table of NOR Gate:" )
print("| I... | 292 | 1 |
'''simple docstring'''
from itertools import product
def lowerCamelCase ( lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
__magic_name__ : Any = sides_number
__magic_name__ : List[str] = max_face_numbe... | 561 |
'''simple docstring'''
import os
lowerCAmelCase :Dict = {'''I''': 1, '''V''': 5, '''X''': 1_0, '''L''': 5_0, '''C''': 1_0_0, '''D''': 5_0_0, '''M''': 1_0_0_0}
def lowerCamelCase ( lowerCAmelCase : str ):
"""simple docstring"""
__magic_name__ : str ... | 561 | 1 |
"""simple docstring"""
import operator
def lowerCAmelCase ( UpperCamelCase_: list , UpperCamelCase_: bool = False , UpperCamelCase_: list | None = None ) -> list:
'''simple docstring'''
_a = operator.lt if reverse else operat... | 719 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase ( UpperCamelCase_: ndarray ) -> float:
'''simple docstring'''
return np.dot(UpperCamelCase_ , Uppe... | 612 | 0 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
cla... | 670 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def snake_case ( A__ ):
UpperCAmelCase_ : int = int(number**0.5 )
return number == sq * sq
def snake_case ( A__ ,A__ ,A__ ,A__ ,A__ ,A... | 95 | 0 |
from collections.abc import Callable
class lowerCamelCase__ :
def __init__(self : Tuple , _snake_case : Callable | None = None ) -> None:
"""simple docstring"""
lowerCamelCase_ : list = []
# Stores indexes of each... | 702 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
UpperCamelCase = re.compile(r'''\b(a|an|the)\b''', re.UNICODE)
UpperCamelCase = None
def _a ( ) -> Tuple:
lowerCamelCase_ : Optional[int] = ar... | 144 | 0 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class __UpperCamelCase ( unittest.TestCase ):
def __UpperCAmelCase ( self ):
'''simple docstring'''
... | 476 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowerCamelCase (_SCREAMING_SNAKE_CASE : dict , _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : set , _SCREAMING_SNAKE_CASE : set , _SCREAMING_SNAKE_CASE : dict , _SCREAMING_SNAKE_CASE... | 476 | 1 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_switc... | 321 |
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ... | 321 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import... | 308 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTe... | 457 | 0 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __lowercase( __lowercase ):
'''simple... | 705 |
"""simple docstring"""
from cva import destroyAllWindows, imread, imshow, waitKey
def UpperCAmelCase ( A__: Tuple ) -> Union[str, Any]:
# getting number of pixels in the image
__lowerCamelCase , __lowerCamelCase : Optional[Any] = img.shape[0], img.shape[1]... | 263 | 0 |
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_flax_available():
impo... | 439 |
import re
from filelock import FileLock
try:
import nltk
a_ : Optional[Any] = True
except (ImportError, ModuleNotFoundError):
a_ : Union[str, Any] = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", quiet=True)
def ... | 439 | 1 |
'''simple docstring'''
import torch
from diffusers import DiffusionPipeline
class a ( snake_case__ ):
'''simple docstring'''
def __init__( self , lowerCamelCase_ , lowerCamelCase_ ) -> Tuple:
super().__init__()
self.register_modules(unet=lowerCamelCase_ , ... | 701 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : List[str] = logging.get_logger(__name__)
UpperCAmelCase_ : Optional[int] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
... | 424 | 0 |
from ...processing_utils import ProcessorMixin
class _lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[int] ="SpeechT5FeatureExtractor"
SCREAMING_SNAKE_CASE_ : Optional[Any] ="SpeechT5Tokenizer"
def __init__( ... | 282 |
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
DPR_CONT... | 282 | 1 |
"""simple docstring"""
def __lowercase ( a : int ) -> bool:
if not isinstance(a , a ):
raise ValueError('''check_bouncy() accepts only integer arguments''' )
__snake_case : List[str] =str(a )
__snake_case : Optional[int] ='''... | 497 |
"""simple docstring"""
def __lowercase ( a : str , a : str ) -> str:
__snake_case : int =len(a )
__snake_case : int =len(a )
__snake_case : int =(
first_str_length if first_str_length > second_str_length else sec... | 497 | 1 |
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
@maybe_allow_in_g... | 268 |
# Copyright 2021 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 ... | 268 | 1 |
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_... | 328 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import... | 328 | 1 |
"""simple docstring"""
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
class UpperCAmelCase (a__ ):
"""simple docstring"""
_UpperCA... | 586 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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 Backbo... | 646 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
__lowercase = logging.get_logger(__name__)
class _lowercase ( _A ):
"""simple docstring"""
def __init__( se... | 717 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, 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
... | 296 | 0 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
lowerCAmelCase__ : Optional[Any] = year % 19
lowerCAmelCase__ : Tuple = year % 4
lowerCAmelCase__ : ... | 565 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 283 | 0 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ):
"""simple docstring"""
return (
num != den and num % 10 == den // 10 and (num // 10) /... | 701 | '''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __... | 389 | 0 |
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