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 |
|---|---|---|---|---|
'''simple docstring'''
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
Chann... | 276 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
"""simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _UpperCAmelCase( unittest.TestCase ):
... | 358 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead.""... | 100 | 0 |
def lowerCAmelCase__ ( _SCREAMING_SNAKE_CASE : Any ):
"""simple docstring"""
__a = []
__a = []
__a = {
"""^""": 3,
"""*""": 2,
"""/""": 2,
"""%""": 2,
"""+""": 1,
"""-""": 1,
} # Priority... | 302 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class SCREAMING_SNAKE_CASE ( lowerCamelCase__ ):
__lowerC... | 302 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
'''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2VecAudioCo... | 363 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbed... | 334 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
_lowerCAmelCase = 50_0000
_lowerCAmelCase , _lowerCAmelCase = os.path.split(__file__)
_lowerCAmelCase = os.path.... | 37 |
# 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 req... | 187 | 0 |
"""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,
fsspec_head,
ftp_g... | 362 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def _a ( _SCREAMING_SNAKE_CASE = 1_500_000 ) -> int:
snake_case_ = defaultdict(_SCREAMING_SNAKE_CASE )
snake_case_ = 2
while 2 * euclid_m * (euclid_m + 1) <= limit:
... | 233 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_... | 23 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowerCamelCase ( A__ ):
'''simple docstring'''
a_ : str = ["""image_processor""", """tokenizer"""]
a_ : List[str] ... | 241 | 0 |
# Copyright 2023 The HuggingFace Inc. 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 requ... | 329 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ... | 329 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extracti... | 28 |
"""simple docstring"""
from collections import defaultdict
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ ):
__SCREAMING_SNAKE_CASE = first_str.lower().strip()
__SCREAMING_SNAKE_CASE = second_str.lower().strip()
# Remove whitespace
__SCREAMING_SNAKE_CA... | 100 | 0 |
'''simple docstring'''
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase_ :
"""simple docstr... | 369 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list ) -> list:
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
A_ : List[str] = []
def generate(lowerCamelCase__ : int , lowerCame... | 4 | 0 |
'''simple docstring'''
import warnings
from ..trainer import Trainer
from ..utils import logging
__a: List[Any] = logging.get_logger(__name__)
class UpperCAmelCase ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self , __lowerCAmelCase=None , **__l... | 198 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCamelCase =logging.get_logger(__name__)
_lowerCamelCase ... | 334 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ (UpperCamelCase ) -> Dict:
if not isinstance(UpperCamelCase , UpperCamelCase ):
lowerCamelCase__ : List[str] = f'''Input value of [number={number}] must be an integer'''
raise ... | 370 |
'''simple docstring'''
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main impo... | 129 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassific... | 64 |
from itertools import permutations
def snake_case_ ( lowerCAmelCase_ : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__lowercase : ... | 233 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class a ( _lowerCamelCase ):
snake_case_ = (DDPMParallelScheduler,)
def A_ ( self : List[Any] , **lowercase_ : str ):
snak... | 370 |
'''simple docstring'''
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
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 72 | 0 |
def lowerCAmelCase__ ( a__: list ) -> bool:
'''simple docstring'''
if not isinstance(a__ , a__ ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(a__ ) == 0:
raise ValueError('Input list mus... | 329 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 1 |
"""simple docstring"""
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 __lowe... | 366 |
"""simple docstring"""
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_... | 161 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list ):
"""simple docstring"""
def merge(snake_case__ : list , snake_case__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0]... | 64 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/f... | 4 | 0 |
'''simple docstring'''
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 compute_effec... | 366 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProc... | 299 | 0 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# 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_docst... | 39 |
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import PreT... | 129 | 0 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDM... | 183 |
'''simple docstring'''
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
SCREAMING_SNAKE_CASE__ = ... | 183 | 1 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def UpperCamelCase__( UpperCamelCase__ : str , UpperCamelCase__ : float | Decimal , UpperCamelCase__ : float = 10**-10 )->Optional[Any]:
... | 193 |
"""simple docstring"""
import math
def snake_case_ ( A_ : int ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, ... | 72 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, 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, rando... | 185 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :List[str] = {
'''configuration_x_clip''': [
'''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XCLIPConfig''',
'''XCLIPTextConfig''',
... | 185 | 1 |
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... | 270 |
'''simple docstring'''
import math
import unittest
def snake_case ( UpperCAmelCase )-> bool:
"""simple docstring"""
assert isinstance(UpperCAmelCase , UpperCAmelCase ) and (
number >= 0
), "'number' must been an int and posi... | 161 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __A ( a_ :str) -> None:
__a : Union[str, Any] = analyze_text(a_)
__a : List[str] = list('... | 360 |
"""simple docstring"""
def __A ( a_ :int = 1_00_00_00) -> int:
__a : Tuple = [i - 1 for i in range(limit + 1)]
for i in range(2 , limit + 1):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , a_):
... | 188 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class lowercase ( unittest.TestCase ):
"""simple docstring"""
def lowerCAmelCase__ ( self ):
'''simple ... | 97 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCAmelCase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
... | 299 | 0 |
"""simple docstring"""
from ....utils import logging
__snake_case : Optional[Any] = logging.get_logger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self: str , _SCREAMING_SNAKE_CA... | 58 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.nump... | 58 | 1 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
A... | 183 |
"""simple docstring"""
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_SCREAMING_SNAKE_CASE : List[Any] ... | 183 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Union[str, Any] ) -> Any:
# vision encoder
if "img_encoder.pos_embed" in... | 362 | """simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_model... | 126 | 0 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def UpperCAmelCase__ ( UpperCAmelCase_ : Any , UpperCAmelCase_ : Any , UpperCAmelCase_ : List[str] , UpperCAmelCase_ : str ) -> int:
__lowerCamelCase : Dict... | 185 |
'''simple docstring'''
def UpperCAmelCase__ ( UpperCAmelCase_ : List[Any] ) -> str:
__lowerCamelCase : Tuple = 0
__lowerCamelCase : Optional[int] = len(UpperCAmelCase_ )
for i in range(n - 1 ):
for j in range(i + 1 , UpperCA... | 185 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def a__ ( ) -> Generator[int, None, None]:
UpperCAmelCase__ : dict[int, int] = {}
UpperCAmelCase__ : Tuple = 2
while True:
UpperCAmelCase__ : str ... | 166 |
"""simple docstring"""
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
... | 166 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowerCAmelCase ( lowerCamelCase__ ):
__UpperCAmelCase : List[Any] = ['image_processor', 'tokenizer']
__UpperCAmelCase : Dict ... | 203 |
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
lowerCamelCase = logging.get_logger(__name__)
... | 188 | 0 |
"""simple docstring"""
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def _snake_case ( _snake_case : List[Any] , _snake_case : List[Any] = True , _snake_case : int = math.inf , _snake_case : Tuple = -math.inf , _snake_... | 358 |
"""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_bert import BertTokenizer
snake_case__ : str = logging.get_logger... | 314 | 0 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. 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... | 58 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerat... | 58 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Optional[int] = ['image_processor', 'tokenizer']
A : Opt... | 360 | '''simple docstring'''
import unittest
from transformers import XLMConfig, 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 impo... | 345 | 0 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int = 100 ) -> int:
__lowercase = n * (n + 1) * (2 * n + 1) / 6
__lowercase = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__main__":
print(F'''{solutio... | 325 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import... | 126 | 0 |
'''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 ... | 369 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from... | 251 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowerCamelCase = False
class _UpperCamelCase ( unittest.Test... | 166 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
lowerCamelCase = """
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correlation.... | 166 | 1 |
"""simple docstring"""
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,
)
if is_sentencepiece_av... | 354 |
"""simple docstring"""
_lowerCAmelCase : dict[tuple[int, int, int], int] = {}
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ) -> int:
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days lef... | 340 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from ... | 66 |
from functools import reduce
_SCREAMING_SNAKE_CASE : Any = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
... | 314 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase_ ( _lowerCamelCase ):
lowerCA... | 295 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
UpperCAmelCase_ = logging.get_lo... | 295 | 1 |
from collections import defaultdict
def SCREAMING_SNAKE_CASE_ ( __A : int ) -> int:
"""simple docstring"""
a_ : str = 1
a_ : Optional[Any] = True
for v in tree[start]:
if v not in visited:
... | 32 |
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=__snake_case ):
'''simple docstring'''
A__ : Tuple = ["flax"]
def __init__( self: str ,*lowerCamelCase_: int ,**lowerCamelCase_: List[str] ) -> str:
requires... | 345 | 0 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_c... | 355 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
_lowercase : Tuple = False
class __SCREAMING_SNAKE_CASE ... | 272 | 0 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def a__ ( A_ = True, *A_, **A_ ):
'''simple docstring'''
if not is_tqdm_available():
raise ImportError("""Accelerate... | 88 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase_ = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_a... | 251 | 0 |
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
@requ... | 365 |
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
A_ : str = [
'word_embeddings_la... | 292 | 0 |
"""simple docstring"""
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():... | 173 |
import collections
import importlib.util
import os
import re
from pathlib import Path
a_ = '''src/transformers'''
# Matches is_xxx_available()
a_ = re.compile(r'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
a_ = re.compile(r'''^_import_structure\s+=\s+\{(... | 340 | 0 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def A_ ( snake_case_ : int ):
'''simple docstring'''
UpperCamelCase : int = int(number**0.5 )
return number == sq * sq
def ... | 27 |
"""simple docstring"""
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A_ ( snake_case_ : Dataset ,snake_case_ : Dict[str, str] ):
... | 27 | 1 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowerCAmelCase = (3, 9, -1_1, 0, 7, 5, 1, -1)
lowerCAmelCase = (4, 6, 2, 0, 8, 1_0, 3, -2)
@dataclass
class A :
UpperCamelCase_ : int
UpperCa... | 295 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCAmelCase = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/deformable_detr/cuda/ms_deform_im2col_cuda.c... | 295 | 1 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
UpperCAmelCase_ : Dict = False
try:
... | 364 |
'''simple docstring'''
import os
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : Any ):
'''simple docstring'''
UpperCAmelCase__ = len(grid[0] )
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ = 0
UpperCAmelCase__ ... | 61 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int , lowercase : int ) -> int:
while a != 0:
_a , _a = b % a, a
return b
def _lowerCamelCase ( lowercase : int , lowercase : int ) -> int:... | 63 | '''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def snake_case__ ( _A: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
lowerCAmelCase = dict(zip(_A , _A ) )
return lower_to_upper.get(sentence[0] , sentence[0] ) ... | 272 | 0 |
"""simple docstring"""
from math import pow, sqrt
def __UpperCAmelCase ( *lowercase ):
"""simple docstring"""
_UpperCAmelCase = len(lowercase ) > 0 and all(value > 0.0 for value in values )
return result
def __UpperCAmelCase ( lowercase ,lowercase ... | 30 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf... | 30 | 1 |
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_m... | 207 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler... | 292 | 0 |
from string import ascii_uppercase
a_ = {char: i for i, char in enumerate(ascii_uppercase)}
a_ = dict(enumerate(ascii_uppercase))
def __lowercase ( lowerCamelCase : str , lowerCamelCase : str ):
UpperCamelCase_ : Tuple = len(lowerCamelCase )
UpperCamelCase_ : ... | 50 | from __future__ import annotations
import numpy as np
def __lowercase ( lowerCamelCase : list[float] ):
return np.maximum(0 , lowerCamelCase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 50 | 1 |
'''simple docstring'''
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... | 27 |
'''simple docstring'''
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('.')
def lowerCamelCase (_SCREAMING_SNAKE_CASE : List[Any] ):
__a : Any = te... | 27 | 1 |
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 ...te... | 362 | def lowercase( UpperCamelCase_ ) -> Tuple:
'''simple docstring'''
UpperCamelCase = 0
UpperCamelCase = len(UpperCamelCase_ )
for i in range(n - 1 ):
for j in range(i + 1 , UpperCamelCase_ ):
if arr[i] > arr[j]:
num_inversions += 1
return num_inversi... | 165 | 0 |
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
snake_case_ = HUGGINGFACE_HUB_CACHE
snake_case_ = 'config.json'
snake_case_ = 'diffusion_pytorch_model.bin'
snake_case_ = 'diffusion_flax_model.msgpack'
snake_case_ = 'model.onnx'
s... | 24 |
"""simple docstring"""
from collections import namedtuple
_a = namedtuple('from_to', 'from_ to')
_a = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.001, 1_000),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0454, 264.172),
'cubicyard': from_to(0.7_6455, 1.... | 61 | 0 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : Dict , __UpperCamelCase : Optional[int]=False ) -> Any:
UpperCAmelCase_ = Omeg... | 177 |
import baseaa
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : str ) -> bytes:
return baseaa.baaencode(string.encode('''utf-8''' ) )
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : bytes ) -> str:
return baseaa.baadecode(__UpperCam... | 177 | 1 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import t... | 30 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__a = logging.get_logger(__name__)
class lowercase__( UpperCAmelCase ):
"""simple docstring"""
a :Union[str, Any] =... | 30 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A : str = logging.get_logger(__name__)
A : Union[str, Any] = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/res... | 353 | import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils i... | 305 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
_UpperCAmelCase : str = {
"""google/pix2struct-textcaps-base""": (
"""https... | 50 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import require_elasticsearch, re... | 50 | 1 |
def snake_case__ ( SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : str ):
'''simple docstring'''
lowercase__ : Optional[Any] = len(SCREAMING_SNAKE_CASE_ )
lowercase__ : List[str] = []
for i in range(len(SCREAMING_SNAKE_CASE_ ... | 365 |
import math
import sys
def snake_case__ ( SCREAMING_SNAKE_CASE_ : int ):
'''simple docstring'''
if number != int(SCREAMING_SNAKE_CASE_ ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueError('the valu... | 216 | 0 |
"""simple docstring"""
def lowercase ( __snake_case : Optional[Any] , __snake_case : Tuple ):
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
lowercase_ : str = str(bin(snake_case__ ) )[2:] # remove the le... | 33 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
A_ : str = logging.get_logger(__name__)
# TODO: upload to AWS
A_ : Optional[int] = {
"yjernite/retribert-base-uncased": (
"https://huggingface.... | 165 | 0 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as s... | 294 |
'''simple docstring'''
import os
def lowerCamelCase ():
with open(os.path.dirname(_SCREAMING_SNAKE_CASE ) + '/p022_names.txt' ) as file:
__a : List[Any] = str(file.readlines()[0] )
__a : str = names.replace('"' , '' ).split('... | 294 | 1 |
"""simple docstring"""
from functools import lru_cache
@lru_cache
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> int:
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import do... | 177 | """simple docstring"""
from __future__ import annotations
from fractions import Fraction
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> bool:
return (
num != den and num % 1_0 == den // 1_0 and (num // 1_0) / (den % 1_0) == num / den
)
def SCREAMING_SNAKE_... | 177 | 1 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data impo... | 214 | '''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Co... | 214 | 1 |
"""simple docstring"""
def lowercase ( A_ )-> int:
'''simple docstring'''
if not isinstance(A_ , A_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise ValueError("Input must be positive" )
return su... | 40 |
from __future__ import annotations
def UpperCamelCase ( __magic_name__ : list[float] , __magic_name__ : list[float] ) -> float:
"""simple docstring"""
lowercase__ = sorted(numsa + numsa )
lowercase__ , lowercase__ = divmod(l... | 305 | 0 |
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 PreTrainedTokenizer
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = '''▁'''
... | 367 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
a__ = ['''small''', '''medium''', '''large''']
a__ = '''lm_head.decoder.weight'''
a__ = '''lm_head.weight'''
def __UpperCAmelCase ( __a : str ,__a : str ) -> ... | 15 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def lowerCamelCase__ ( __snake_case ) -> Optional[int]:
"""simple docstring"""
if "img_enc... | 194 |
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
lowercase__ ={
'E': 12.70,
'T': 9.06,
'A': 8.17,
'O': 7.51,
'I': 6.97,
'N': 6.75,
'S': 6.33,
'H': 6.09,
'R': 5.99,
'D': 4.25,
'L': 4.03,
'C': 2.78,
'U': 2.76,
'M': 2.41,
... | 216 | 0 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | 351 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
lowercase__ :Union[str, Any] = {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"]}
try:
if... | 97 | 0 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
_a : List[Any] = FileLock(str(tmpdir / """foo.lock""" ) )... | 294 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
'''simple docstring'''
_a : Optional[Any] = [redshift, radiation_density, matter_... | 294 | 1 |
"""simple docstring"""
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
a_ = logging.get_logger(__name__)
def __lowercase ( sna... | 291 |
"""simple docstring"""
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
a_ = {
"""E""": 12.70,
"""T""": 9.06,
"""A""": 8.17,
"""O""": 7.51,
"""I""": 6.97,
"""N""": 6.75,
"""S""": 6.33,
"""H""": 6.09,
"""R""": 5.99,
"""D""": 4.25... | 291 | 1 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
snake_case_ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ (__snake_case ):
def __init__( self , *a , **a):
warnings.warn(
'The class D... | 214 |
import unittest
from transformers import DonutProcessor
snake_case_ = '''naver-clova-ix/donut-base'''
class SCREAMING_SNAKE_CASE__ (unittest.TestCase ):
def snake_case_ ( self):
lowercase__ : Dict = DonutProcessor.from_pretrained(a)
def ... | 214 | 1 |
import string
from math import logaa
def lowerCamelCase_ ( UpperCamelCase__ : str, UpperCamelCase__ : str ):
'''simple docstring'''
UpperCamelCase__ = document.translate(
str.maketrans('''''', '''''', string.punctuat... | 370 | from __future__ import annotations
class __lowercase :
'''simple docstring'''
def __init__( self : List[Any] , _a : int ):
UpperCamelCase__ = data
UpperCamelCase__ = None
UpperCamelCase__ = ... | 35 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowercase = {'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}
try:
if not is_torch_available():
raise Optional... | 43 |
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
SCREAMING_SNAKE_CASE :Union[str, Any] = False
SCREAMING_SNAKE_CASE :Any = True
SCREAMING_SNAKE_CASE :Tuple = False
... | 15 | 0 |
from datetime import datetime
import requests
def A__ ( lowerCamelCase ) -> bytes:
UpperCamelCase_: Any = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
UpperCamelCase_: int = requests.get(base_url + url ).json()[0]["""urls"""][0]["""src"""]
... | 223 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from tor... | 223 | 1 |
'''simple docstring'''
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 OptionalDepe... | 139 |
'''simple docstring'''
import csv
import tweepy
# Twitter API credentials
__snake_case = ''''''
__snake_case = ''''''
__snake_case = ''''''
__snake_case = ''''''
def a ( __a ) -> None:
'''simple docstring'''
UpperCame... | 97 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = str(lowerCAmelCase )
return n == n[::-1]
def UpperCamelCase__ ( lowerCAmelCas... | 220 |
'''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = ... | 220 | 1 |
"""simple docstring"""
import numpy as np
def a__ ( snake_case__ ) -> np.ndarray:
return 1 / (1 + np.exp(-vector ))
def a__ ( snake_case__ ) -> np.ndarray:
return vector * sigmoid(snake_case__ )
if __name__ == "__main__":
import doctest
docte... | 291 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTMSNConfig
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_configuration_common import... | 291 | 1 |
from collections.abc import Iterable
from typing import Generic, TypeVar
snake_case = TypeVar("""_T""")
class SCREAMING_SNAKE_CASE ( Generic[_T] ):
'''simple docstring'''
def __init__( self : Tuple , UpperCAmelCase_ : Iterable[_T] | None = None ):
SCREAMI... | 353 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import loggin... | 319 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfi... | 184 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaV... | 35 | 0 |
"""simple docstring"""
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
__lowerCAmelCase : List[Any] =yaml.safe_load(
"""\
name: \"\"
allow_empty: false
allow... | 32 | """simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def UpperCAmelCase__ ( lowerCAmelCase__ :Union[str, Any] ) -> Dict:
'''simple docstring'''
if "img... | 32 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_... | 223 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import to... | 223 | 1 |
import collections
import os
import re
from pathlib import Path
__lowercase = "src/transformers"
# Matches is_xxx_available()
__lowercase = re.compile(r'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
__lowercase = re.compile(r'''^_import_structure\s+=\s... | 360 | 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.... | 105 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : Dict = {
'configuration_roberta': ['ROBERTA_PR... | 220 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( __snake_case : int = 4_00_00_00 ):
'''simple docstring'''
lowercase = []
lowercase , lowercase = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__snake_case )
lowerca... | 220 | 1 |
from argparse import ArgumentParser
from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command... | 350 | import requests
from bsa import BeautifulSoup
def snake_case ( snake_case__ :str = "AAPL") -> str:
_A = F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
_A = BeautifulSoup(requests.get(snake_case__).text , """html.parser"""... | 81 | 0 |
"""simple docstring"""
# 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/lic... | 105 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 319 | 0 |
"""simple docstring"""
# 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... | 298 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch... | 298 | 1 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_... | 32 |
import math
import flax.linen as nn
import jax.numpy as jnp
def SCREAMING_SNAKE_CASE_ ( __A : jnp.ndarray , __A : int , __A : float = 1 , __A : float = 1 , __A : float = 1.0e4 , __A : bool = False , __A : float = 1.0 , ) -> jnp.ndarray:
... | 32 | 1 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
smartaa_timest... | 282 |
import unittest
from transformers import LiltConfig, 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 ModelTesterMi... | 282 | 1 |
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ ) -> int:
while b:
__lowerCamelCase , __lowerCamelCase : Any = b, a % b
return a
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ ) -> int:
return a if b ==... | 73 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def _SCREAMING_SNAKE_CASE ( _lowercase : int ) ->str:
'''simple docstring'''
if not isinstance(_lowercase , _lowercase ):
rais... | 105 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A : Any = {
'''configuration_bloom''': ['''BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BloomConfig''', '''BloomOnnxConfig'''],
}
try:
if not is_to... | 323 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
smartaa_timesteps,
sma... | 323 | 1 |
import random
from typing import Any
def lowercase_ ( _lowerCamelCase : list):
for _ in range(len(_lowerCamelCase)):
lowercase__ : Dict = random.randint(0 , len(_lowerCamelCase) - 1)
lowercase__ : Union[str, Any] = random.randint(0 , len(_lowerC... | 87 |
"""simple docstring"""
from math import factorial
def _A ( lowercase = 1_00 ):
"""simple docstring"""
return sum(int(lowercase ) for x in str(factorial(lowercase ) ) )
if __name__ == "__main__":
print(solution(int(input("""Enter the Number: """).... | 81 | 0 |
'''simple docstring'''
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __A ( ):
_UpperCAmelCase : List[Any] = [randint(-1000 , 1000 ) for i in range(10 )]
_UpperCAmelCase : Dict =... | 353 |
'''simple docstring'''
from __future__ import annotations
def __A ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , ):
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError("""You cannot supply more or less than 2 values""" )
elif stress < 0:
... | 170 | 0 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_inpu... | 298 |
'''simple docstring'''
def __lowerCAmelCase ( snake_case__ ):
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(snake_case__ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('''doctest''').testmod(... | 298 | 1 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from numpy import array
def _A ( _lowerCAmelCase ):
"""simple docstring"""
__lowercase =Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this impl... | 353 |
'''simple docstring'''
from math import factorial
def _A ( _lowerCAmelCase = 20 ):
"""simple docstring"""
__lowercase =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
__lowercase =n // 2
return int(facto... | 48 | 0 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
'''simple docstring'''
def A ( self : Tuple ):
'''simple docstring'''
_snake_case ... | 282 |
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
_lowerCamelCase : List[str] = logging.get... | 282 | 1 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :Optional[int] , SCREAMING_SNAKE_CASE :Tuple ) -> int:
print("""\nThe shortest path matrix using Floyd Warshall algorithm\n""" )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(SCREAMING_SNAKE_CASE ):
if dist[i][j] != float(... | 232 |
from datetime import datetime
import requests
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :str ) -> bytes:
__lowerCAmelCase : List[Any] = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
__lowerCAmelCase : Dict = requests.get(b... | 232 | 1 |
'''simple docstring'''
def __A ( lowerCamelCase_ , lowerCamelCase_ ):
"""simple docstring"""
return number | (1 << position)
def __A ( lowerCamelCase_ , lowerCamelCase_ ):
"""simple docstring"""
return number & ~(1 << position)
... | 323 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/gi... | 323 | 1 |
"""simple docstring"""
from __future__ import annotations
_A = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , ) ... | 212 |
"""simple docstring"""
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> List[Any]:
... | 212 | 1 |
def __UpperCamelCase ( _lowerCAmelCase ) -> bool:
"""simple docstring"""
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def __UpperCamelCase ( _lowerCAmelCase ) -> bool:
"""simple docstring"""
A : str ... | 116 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[int] =logging.get_logger(__name__)
_lowercase : Tuple ={
"microsoft/swinv2-tiny-patch4-window8-256": (
"https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-25... | 170 | 0 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE__ : str ) -> list[int]:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = [0 for i in range(len(SCREAMING_SNAKE_CASE__ ) )]
# initialize interval's left pointer an... | 202 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCAmelCase : Union[str, Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 202 | 1 |
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