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 |
|---|---|---|---|---|
import os
from datetime import datetime as dt
from github import Github
UpperCAmelCase_ : Dict = [
"good first issue",
"good second issue",
"good difficult issue",
"enhancement",
"new pipeline/model",
"new scheduler",
"wip",
]
def UpperCamelCase ( )-> str:... | 491 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()... | 77 | 0 |
'''simple docstring'''
import warnings
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 Tenso... | 123 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_toke... | 123 | 1 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
return abs(__UpperCamelCase ) if a == 0 else greatest_common_divisor(b % a , __UpperCamelCase )
def A ( _lowerCamelCase , _lowerCamelCase ):
... | 500 |
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,
)
__a :Dict = {'configuration_xglm': ['XGLM_PRETRAIN... | 86 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase : Tuple = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 721 |
'''simple docstring'''
from manim import *
class _snake_case ( a_ ):
def _SCREAMING_SNAKE_CASE ( self ):
'''simple docstring'''
lowerCAmelCase = Rectangle(height=0.5 , width=0.5 )
lowerCAmelCase = Rectangle(height=0.46 , widt... | 514 | 0 |
import math
import unittest
def UpperCamelCase (lowercase_: int ) -> bool:
assert isinstance(lowercase_ , lowercase_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == ... | 456 |
A_ : Union[str, Any] = '\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/tra... | 456 | 1 |
"""simple docstring"""
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, ... | 720 |
"""simple docstring"""
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import di... | 158 | 0 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
UpperCAmelCase_ : Union[str, Any] = logging.getLogge... | 24 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ : List[str] = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'... | 24 | 1 |
from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE ) -> Tuple:
"""simple docstring"""
_UpperCAmelCase : str = [True] * limit
_UpperCAmelCase : int = False
_UpperCAmelCase : List[str] ... | 705 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
__lowerCamelCase = logging.get_logger(__name__)
class _UpperCamelCase( SCREAMING_SNAKE_CASE ):
def __init__( self : Any , *_lowerCamelCase : Any , **_lowerCamelCas... | 328 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase_ = {
'configuration_efficientnet': [
'EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP',
'EfficientNetC... | 132 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_u... | 199 | 0 |
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_MAPPING,
AutoConfig,
AutoModelForMaskedLM,
... | 704 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is the referenc... | 478 | 0 |
_A = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
''... | 258 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : List[Any] = {
'''microsoft/unispeech-sat-base-100h-libri-ft''': (... | 633 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
# See all PEGASUS models at https://h... | 720 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase_ = {
'''configuration_clip''': [
... | 336 | 0 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 16 |
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
@require_optimum
@s... | 16 | 1 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_... | 701 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""t5-small""": """https://huggingface.co/t5-small/resolve/m... | 152 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is... | 12 |
"""simple docstring"""
import string
def _UpperCamelCase ( A ):
UpperCamelCase_ =""
for i in sequence:
UpperCamelCase_ =ord(A )
if 65 <= extract <= 90:
output += chr(155 - extract )
elif 97 <= extract <= 122:
output += chr(... | 391 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaToken... | 704 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKE... | 446 | 0 |
import os
import sys
import unittest
a__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_bac... | 14 |
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowerCamelCase : Dict =parse(importlib.metadata.version('''torch'''))
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase... | 228 | 0 |
'''simple docstring'''
from __future__ import annotations
def __lowercase ( _A ) -> Optional[int]:
return len(set(lowercase__ ) ) == len(lowercase__ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase__ : str = {"""processing_layoutxlm""": ["""LayoutXL... | 446 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
fr... | 302 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class SCREAMING_SNAKE_CASE_ (a__ ):
... | 278 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
'configuration_jukebox': [
'JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP',
'JukeboxConfig',
'JukeboxPriorConfig',
'Jukeb... | 257 | '''simple docstring'''
from __future__ import annotations
import bisect
def __UpperCAmelCase ( a_: list[int], a_: int, a_: int = 0, a_: int = -1 ):
if hi < 0:
_UpperCAmelCase : int = len(a_ )
while lo < hi:
_UpperCAmelCase :... | 257 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_UpperCamelCase : int = logging.get_logger(__name__)
def __UpperCAmelCase ( A : Union[tf.Tensor, np.ndarray] ) -> List[int]:
if isinst... | 541 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
_UpperCamelCase : Union[str, Any] = 'examples/'
_UpperCamelCase : List[str] = {
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\... | 541 | 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 = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'facebook/x... | 713 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
SCREAMING_SNAKE_CASE = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot ap... | 186 | 0 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import gl... | 565 |
from __future__ import annotations
def _lowerCAmelCase ( lowerCAmelCase_ :int , lowerCAmelCase_ :int )->list[str]:
'''simple docstring'''
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_bytes... | 283 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verb... | 283 | """simple docstring"""
from __future__ import annotations
class _lowerCamelCase :
def __init__( self : Any , lowerCamelCase_ : list[list[int]] ):
"""simple docstring"""
_lowercase : Tuple = TypeError(
'Matrices must be formed ... | 283 | 1 |
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowerCamelCase_ : Any = HUGGINGFACE_HUB_CACHE
lowerCamelCase_ : int = """config.json"""
lowerCamelCase_ : Dict = """diffusion_pytorch_model.bin"""
lowerCamelCase_ ... | 559 | from math import pow, sqrt
def lowerCAmelCase( *__lowerCamelCase ):
__a = len(__lowerCamelCase ) > 0 and all(value > 0.0 for value in values )
return result
def lowerCAmelCase( __lowerCamelCase , __lowerCamelCase ):
return (
round(sqrt(molar_mass_a / mo... | 559 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def __magic_name__( _A ):
'''simple... | 265 |
'''simple docstring'''
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import M... | 265 | 1 |
import argparse
import json
from tqdm import tqdm
def __snake_case ( ):
"""simple docstring"""
A_ = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" ,type=__UpperCamelCase ,default="biencoder-nq-dev.j... | 86 |
from ..utils import DummyObject, requires_backends
class _a ( metaclass=snake_case_ ):
"""simple docstring"""
_lowerCamelCase : Optional[Any] = ['torch', 'transformers', 'onnx']
def __init__( self : str , *UpperCAmelCase ... | 86 | 1 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
def _snake_case ( lowercase , lowercase )... | 719 |
'''simple docstring'''
__SCREAMING_SNAKE_CASE : int = 9.80_665
def _snake_case ( lowercase , lowercase , lowercase = g ) -> float:
if fluid_density <= 0:
raise ValueError("""Impossible fluid density""" )
if volume < 0:
raise V... | 697 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class A ( A_ ):
def __init__(self , lowerCAmelCase , lowerCAmelCase ):
__lowercase= params
__lowercase= np.array(lowerCAmelCase )
__lowercase= ... | 230 |
from math import ceil
def _lowerCamelCase( lowercase__ = 1_0_0_1 ) -> int:
'''simple docstring'''
__lowercase= 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
__lowercase= 2 * i + 1
__lowercase= 2 * i
__lowercase= total + 4 * odd**... | 230 | 1 |
# 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 by applicab... | 405 |
class __magic_name__ ( _a):
pass
class __magic_name__ ( _a):
pass
class __magic_name__ :
def __init__( self : Optional[int] ):
UpperCAmelCase = [
[],
[],
[],
]
def _UpperCAmelCase ( self : Tuple ,__S... | 405 | 1 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCAmelCase = '''\
@inproceedings{kakwani2020indicnlpsuite,
title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Languag... | 119 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 1 |
"""simple docstring"""
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test... | 255 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase =logging.get_logger(__name__)
U... | 255 | 1 |
'''simple docstring'''
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: List[Any] =... | 526 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowercase ( _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : Tuple ):
'''simple docs... | 602 | 0 |
"""simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase__ ( lowercase_ ,lowercase_=7 ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = Non... | 51 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
lowerCamelCase__ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
lowerCamelCase__ = [ord(letter) for letter in string.asci... | 51 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
i... | 383 |
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():
impor... | 383 | 1 |
__a = """Alexander Joslin"""
import operator as op
from .stack import Stack
def UpperCamelCase_ ( a_ ) ->int:
A ={"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
A =Stack()
A =Stack()
for i in equation:
if i.isdigit():
# RULE 1
operand_stack.push(int(a... | 689 |
def UpperCamelCase_ ( a_ = 6008_5147_5143 ) ->int:
try:
A =int(a_ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
raise ValueError("Parameter n must be greater than or equal to one." )
A =2
A =0
if n == 2:
r... | 689 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
Au... | 455 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention,
... | 455 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A_ : Optional[int] = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''MobileNetV2Con... | 32 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : Optional[int] = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''... | 32 | 1 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
UpperCamelCase = get_tests_dir(... | 45 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://e... | 377 | 0 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __a ( __lowerCamelCase : Tuple ,... | 461 | '''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xope... | 461 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import n... | 373 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType... | 581 | 0 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class snake_case__( UpperCAmelCase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : int = (EulerDiscr... | 619 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_xlnet import... | 619 | 1 |
'''simple docstring'''
import re
import string
import numpy as np
import datasets
_a : str = """
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
"""
_a : List[Any] ... | 689 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
impor... | 689 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
Vilt... | 720 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCamelCase : Optional[int] = logging.get_logger(__name__)
__lowerCamelCase : Tuple = {
'''shi-lab... | 501 | 0 |
"""simple docstring"""
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_chann... | 104 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_... | 193 | 0 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class _UpperCAmelCase :
"""simple docstring"""
a_ = 42 # [batch_size x 3]
a_ = 42 # [batch_size x 3]
a_ = 42 # [batch_size x 3]
a_ = ... | 421 |
def a_ ( lowerCAmelCase_ : str, lowerCAmelCase_ : str ):
if not (isinstance(lowerCAmelCase_, lowerCAmelCase_ ) and isinstance(lowerCAmelCase_, lowerCAmelCase_ )):
raise ValueError('longest_common_substring() takes two strings for inputs' )
__lowerCAmelCase ... | 421 | 1 |
import datasets
from .evaluate import evaluate
_a : str = '\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitle={EMNLP},\n year={2016}... | 479 |
import math
import flax.linen as nn
import jax.numpy as jnp
def UpperCamelCase__ ( _A: jnp.ndarray , _A: int , _A: float = 1 , _A: float = 1 , _A: float = 1.0e4 , _A: bool = False , _A: float = 1.0 , ):
'''sim... | 479 | 1 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
__A = logging.getLogger(__name__)
def lowerCamelCase_ ( ) -> Any:
"""simple docstring"""
__lowerCamelCase = argparse.Ar... | 167 |
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuratio... | 167 | 1 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class A__ :
@property
def UpperCamelCase__ ( self ):
return self.ge... | 681 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : int = 10**9):
A_ : Optional[int] = 1
A_ : int = 2
A_ : List[Any] = 0
A_ : Optional[Any] = 0
A_ : str = 0
while perimeter <= max_perimet... | 665 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( UpperCamelCase__ : Any = 1_000 ) -> int:
'''simple docstring'''
_snake_case = 2**power
_snake_case = 0
while n:
_snake_case , _snake_case = r + n % 10, n ... | 703 |
def lowerCamelCase__ ( UpperCamelCase__ : List[Any] , UpperCamelCase__ : Dict , UpperCamelCase__ : str , UpperCamelCase__ : int , UpperCamelCase__ : List[str] , UpperCamelCase__ : str ) -> List[Any]:
... | 541 | 0 |
from manim import *
class lowercase ( snake_case__):
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( self : List[Any] ) -> Union[str, Any]:
UpperCAmelCase_= Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase_= Rectangle(height=0.25 , w... | 593 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ort
... | 593 | 1 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,... | 718 |
from __future__ import annotations
A : List[Any] = 1_0
def __lowerCamelCase ( __a :list[int] ) -> list[int]:
"""simple docstring"""
A__ = 1
A__ = max(__a )
while placement <= max_digit:
#... | 247 | 0 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F... | 480 |
"""simple docstring"""
from math import factorial
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int = 2_0 ):
"""simple docstring"""
snake_case_ : int = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...... | 480 | 1 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _SCREAMING_SNAKE_CASE ( A__ ):
UpperCAmelCase_ :Dict = (CMStochasticIterativeScheduler,)
UpperCAmelCase_... | 256 |
"""simple docstring"""
__UpperCAmelCase = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def _snake_case ( lowercase__ : int ) -> int:
'''simple docstring'''
lowerCAmelCase_ :str = 0
while number:
... | 256 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'... | 60 |
"""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
__UpperCAmelCase =False
class lowerCAmelCase__ ( unittest.TestC... | 337 | 0 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
def snake_case_ (_a : int , _a : int ):
return (
num != den and num % 1_0 == den // 1_0 and (num // 1_0) / (den % 1_0) == num / den
)
def snake_case_ (... | 358 |
'''simple docstring'''
def snake_case_ (_a : list[list[int]] , _a : int , _a : int , _a : list[int] ):
# 1. Validate that path exists between current and next vertices
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
... | 358 | 1 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSeque... | 66 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 664 | 0 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
fro... | 703 |
'''simple docstring'''
import random
from typing import Any
def A_ ( _lowerCAmelCase : list ):
"""simple docstring"""
for _ in range(len(_lowerCAmelCase ) ):
_lowerCamelCase : Any = random.randint(0 , len(_lowerCAmelCase ... | 11 | 0 |
def a (lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
__a = mf_knapsack(i - 1 , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ )
el... | 99 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class a__ ( unittest.TestCase ):
def ... | 507 | 0 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] ) -> Optional[Any]:
"""simple docstring"""
lowerCAmelCase_ : Any = [0] * len(lowerCAmelCase__ )
lowerCAmelCase_ : Dict = []
lowerCAmelCas... | 317 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : int ) -> bool:
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertic... | 317 | 1 |
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ : Optional[int] = logging... | 64 |
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : int | float | str ) -> tuple[int, int]:
try:
SCREAMING_SNAKE_CASE_ : int =float(UpperCAmelCase_ )
except ValueError:
raise ValueError('''Please enter a valid number''' )
SCREAMI... | 443 | 0 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__A : Tuple = '\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Saurav Kadavath\n and Akul Arora\n ... | 75 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class _SCREAMING_SNAKE_CASE ( unittest.TestCase):
... | 75 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Any = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class _lowerCamelCase( _a ):
lowercase_ ... | 89 |
"""simple docstring"""
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->list[str]:
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(_SCREAMING_SNAKE_CASE ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
... | 93 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
__A ={"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}
__A ={
... | 702 |
def a ( _UpperCAmelCase : list[int] , _UpperCAmelCase : list[int] ):
'''simple docstring'''
__UpperCAmelCase : Dict = len(_UpperCAmelCase )
print('''The following activities are selected:''' )
# The first activity is always... | 241 | 0 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ :Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase__ :Any = ... | 355 |
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_docstrings.py
lowercase_ ... | 562 | 0 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ) -> str:
if isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise TypeError('\'float\' object cannot be interpreted as an integer' )
if isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise TypeEr... | 719 |
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KE... | 311 | 0 |
"""simple docstring"""
import argparse
import struct
import unittest
class __magic_name__ :
def __init__( self : List[Any] , snake_case_ : bytes ):
__snake_case = data
# Initialize hash values
__snake_case = ... | 163 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,... | 163 | 1 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case=5 ) -> List[Any]:
'''simple docstring'''
assert masked_input.count("<mask>" ) == 1
U... | 455 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json''',
}
class snake_cas... | 455 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 3 , SCREAMING_SNAKE_CASE__ = 7 , SCREAMING_SNAKE_CASE__ = 100_0000 ) -> int:
'''simple docstring'''
snake_case : str = 0
snake_case : Tuple = 1
for curr... | 638 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
if not is_torch_available... | 711 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class __SCREAMING_SNAKE_CASE :
snake_case : int
snake_case : Node | None = None
... | 548 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE : List[Any] = {
"configuration_trocr": ["TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP", "TrOCR... | 89 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class a__ ( nn.Module ):
_SCREAMING_SNAKE_CASE : int
_SCREAMING_SNAKE_CASE : jnp.dtype = jnp.floataa
def _lowerCamelCase ( self ):
"""simple docstring"""
_lo... | 245 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_A = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechConfig''']}
t... | 711 |
import sys
_A = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"668966489504452445231617318564030987111217223... | 294 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class snake_case__ (A__ ):
"""simple docstring"""
... | 136 |
"""simple docstring"""
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils impor... | 93 | 0 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def lowerCAmelCase_( lowercase_ : Any="ro" , lowercase_ : Optional[int]="en" , lowercase_ : int="wmt16" , lowercase_ : int=None ) -> None:
try:
... | 623 |
"""simple docstring"""
import warnings
from .generation import TFGenerationMixin
class lowerCamelCase_( A__ ):
'''simple docstring'''
warnings.warn(
'Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will '
'be removed i... | 623 | 1 |
"""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_i... | 103 |
"""simple docstring"""
def snake_case ( lowerCAmelCase_ , lowerCAmelCase_ ) -> int:
return 1 if input_a == input_a else 0
def snake_case ( ) -> None:
assert xnor_gate(0 , 0 ) == 1
assert xnor_gate(0 , 1 ) == 0
assert xnor_gate(1 , ... | 103 | 1 |
def snake_case__ ( __lowercase = 5_0 ) -> int:
"""simple docstring"""
A__ : Any = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_le... | 182 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING... | 182 | 1 |
def __A ( _lowercase ):
'''simple docstring'''
_A = [0] * len(_lowercase )
_A = []
_A = [1] * len(_lowercase )
for values in graph.values():
for i in values:
indegree[i] += 1
for i in range(len(_lower... | 484 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def __A ( _lowercase , _lowercase = "cpu" , _lowercase = None ):
'''simple docstring'''
_A = torch.load(_lowercase , map_location=_lowercase )
for k, v in t... | 484 | 1 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_available
... | 705 |
from __future__ import annotations
from typing import Any
def __lowercase( __snake_case : list ) -> int:
if not postfix_notation:
return 0
__snake_case = {'+', '-', '*', '/'}
__snake_case = []
for token in postfix_notation:
... | 345 | 0 |
"""simple docstring"""
def snake_case_ ( A_ : int = 1_00_00_00 ):
'''simple docstring'''
_lowerCamelCase : str = set(range(3, A_, 2 ) )
primes.add(2 )
for p in range(3, A_, 2 ):
if p not in primes:... | 83 |
'''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... | 98 | 0 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
lowerCAmelCase : Optional[int] = [
'Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phon... | 353 |
def A_ ( a ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = 0
while num > 0:
digit_sum += num % 1_0
num //= 1_0
return digit_sum
def A_ ( a = 1_0_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ ... | 353 | 1 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _lowerC... | 678 |
from manim import *
class _lowerCAmelCase ( _lowercase ):
def __magic_name__( self ):
lowerCAmelCase__ : Tuple = Rectangle(height=0.5 , width=0.5 )
lowerCAmelCase__ : Dict = Rectangle(height=0.25 , width=0.25 )
lowerCAmelC... | 678 | 1 |
'''simple docstring'''
def UpperCamelCase__ ( _lowercase : list ) -> float:
__UpperCAmelCase: Union[str, Any] = 0
while len(_lowercase ) > 1:
__UpperCAmelCase: Dict = 0
# Consider two files with minimum cost to be merged
for _ in range(2 ):
__UpperC... | 466 | '''simple docstring'''
def UpperCamelCase__ ( _lowercase : list[int] , _lowercase : list[int] ) -> None:
__UpperCAmelCase: Dict = len(_lowercase )
print("""The following activities are selected:""" )
# The first activity is always selected
__UpperCAmelCase... | 466 | 1 |
UpperCamelCase = range(2, 20 + 1)
UpperCamelCase = [10**k for k in range(ks[-1] + 1)]
UpperCamelCase = {}
def A ( lowercase__ : List[Any] , lowercase__ : Tuple , lowercase__ : str , lowercase__ : Optional[Any] ) -> Any:
UpperCamelCase__ :List[Any] = ... | 45 |
from __future__ import annotations
def A ( lowercase__ : int ) -> list[int]:
UpperCamelCase__ :Union[str, Any] = [True] * limit
UpperCamelCase__ :int = False
UpperCamelCase__ :Optional[Any] = False
UpperCamelCase__ :str = True
for i in range(3 , int... | 45 | 1 |
"""simple docstring"""
def a__ ( __lowercase , __lowercase , __lowercase , __lowercase ) -> str:
# Return True if there is node that has not iterated.
_A = [False] * len(__lowercase )
_A = []
queue.append(__lowercase )
_A = True... | 621 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from ... | 621 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
a = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the refer... | 109 |
def __magic_name__ ( SCREAMING_SNAKE_CASE = 50 ) -> int:
_lowercase : Optional[int] = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in... | 66 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class a ( __SCREAMING_SNAKE_CASE ):
"""simple docstring... | 716 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class a ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def UpperCAmelCase_ ( self : List[str] , lowerCamelCase__ : float ... | 362 | 0 |
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE ( __UpperCamelCase) -> dict:
a = f'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'''
return requests.get(__UpperCamelCase).json()
def SCREAMING_SNAKE_CASE ( __UpperCamelCa... | 515 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : Any = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/m... | 515 | 1 |
_lowercase : List[Any] ={
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax>=0.4.1''',
... | 661 | import math
def A__ ( lowercase: int ) -> list:
A : Optional[Any] =[True] * n
A : Tuple =False
A : List[Any] =False
A : Dict =True
for i in range(3, int(n**0.5 + 1 ), 2 ):
... | 661 | 1 |
def __lowerCAmelCase ( _UpperCamelCase ) -> int:
'''simple docstring'''
lowerCamelCase__: Optional[Any] = hex_num.strip()
if not hex_num:
raise ValueError("""No value was passed to the function""" )
lowerCamelCase__: Lis... | 306 |
_lowercase = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
_lowercase = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def __lowerCAmelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ) -> list[int]:
'''simple docstring'''
... | 306 | 1 |
__UpperCamelCase : List[str] = 0 # The first color of the flag.
__UpperCamelCase : Any = 1 # The second color of the flag.
__UpperCamelCase : Union[str, Any] = 2 # The third color of the flag.
__UpperCamelCase : Union[str, Any] = ... | 718 |
import math
import qiskit
def snake_case_ ( __lowercase = 1 , __lowercase = 1 , __lowercase = 1 ):
if (
isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , _... | 641 | 0 |
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 ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 108 |
'''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 (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_chan... | 314 | 0 |
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class lowerCamelCase__ ( UpperCAmelCase ,unittest.TestCase ):
UpperCamelCase__ =DownBlockaD # noqa ... | 713 | import unittest
from transformers import AutoTokenizer, NystromformerConfig, 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 ..... | 225 | 0 |
'''simple docstring'''
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def lowerCamelCase ( ) ->tuple[list[int], int]:
_SCREAMING_SNAKE_CASE = [randint(-1000 , 1000 ) for i in range(10 )]
_SCRE... | 314 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
lowercase_ = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__( self , *A , **A ) ... | 314 | 1 |
import re
def _snake_case ( __snake_case ):
_UpperCamelCase = re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__snake_case , __snake_case ):
return match.string == phone
return False
if __name__ == "__main__":
print(indian_phone_valida... | 702 | from __future__ import annotations
import math
class lowerCAmelCase_ :
def __init__( self : int , _A : int ):
_UpperCamelCase = size
# approximate the overall size of segment tree with given value
_UpperCamelCase = [0 for i in r... | 71 | 0 |
from __future__ import annotations
_UpperCAmelCase : Union[str, Any] = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _Upper... | 295 |
# 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 required b... | 295 | 1 |
'''simple docstring'''
def _UpperCamelCase ( _a : list , _a : list , _a : int ):
"""simple docstring"""
if len(_a ) != len(_a ):
raise ValueError('The length of profit and weight must be same.' )
if max_weight <= 0:
raise ValueError('max_weight must greater ... | 287 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a= {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerConfig''',
'''BridgeTow... | 287 | 1 |
"""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
... | 602 |
"""simple docstring"""
__A : Optional[int] = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
fro... | 602 | 1 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case = None ,__snake_case = None ,__snake_case = None ,) -> Tup... | 29 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_a = logging.get_logger(__name__)
class __A ( lowerCAmelCase ):
'''simple docstring'''
def __init__( self , *__lowerCAmelCase , **__lowerCAmelCase ... | 29 | 1 |
from math import factorial, pi
def UpperCamelCase_ ( __a , __a = 30 ) -> float:
if not isinstance(__a , (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or float for theta" )
if not isinstance(__a , __a ) or accuracy <= 0... | 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... | 469 | 0 |
def __snake_case ( _UpperCAmelCase ):
"""simple docstring"""
if num < 0:
return False
lowercase = num
lowercase = 0
while num > 0:
lowercase = rev_num * 10 + (num % 10)
num //= 10
retu... | 720 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
__magic_name__ ... | 314 | 0 |
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