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 |
|---|---|---|---|---|
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availa... | 329 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class SCREAMING_SNAKE_CASE :
'''simple docstring'''
__UpperCamelCase = 42
__UpperCamelCase = 4... | 329 | 1 |
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_up_block
@data... | 709 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFXLMRo... | 231 | 0 |
'''simple docstring'''
from __future__ import annotations
def A_ ( __SCREAMING_SNAKE_CASE : list[int] ) -> Union[str, Any]:
if not nums:
return 0
__SCREAMING_SNAKE_CASE : List[str] = nums[0]
__SCREAMING_SNAKE_CASE : Dict ... | 158 |
from PIL import Image
def A__ ( _a : Image , _a : float ):
'''simple docstring'''
def brightness(_a : int ) -> float:
return 128 + level + (c - 128)
if not -2_5_5.0 <= level <= 2_5_5.0:
raise ValueError("""level must be between -255.0 (black) and... | 385 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, Di... | 303 |
def lowercase__( A ):
return " ".join(
''.join(word[::-1] ) if len(A ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('Hey wollef sroirraw'))
| 303 | 1 |
'''simple docstring'''
def _snake_case ( A_ : list ):
"""simple docstring"""
a_ : List[str] = False
while is_sorted is False: # Until all the indices are traversed keep looping
a_ : Dict = True
for i in range(0 , len(A_ ) - 1 , 2 ):... | 577 |
'''simple docstring'''
def _snake_case ( A_ : Optional[int] ):
"""simple docstring"""
a_ : str = len(A_ )
for i in range(length - 1 ):
a_ : List[Any] = i
for k in range(i + 1 , A_ ):
if collection[k] < collection[least]:
... | 577 | 1 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta impo... | 310 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__a = ""
__a = ""
__a = ""
__a = 1 # (0 is vertical, 1 is horizontal)
def A_ ( ):
'''simple docstring'''
... | 310 | 1 |
import cva
import numpy as np
class __A :
"""simple docstring"""
def __init__( self , a__ , a__):
"""simple docstring"""
if k in (0.04, 0.06):
_lowerCamelCase : Optional[Any] = k
... | 114 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , **a__):
... | 114 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_UpperCamelCase : Any = {
"configuration_data2vec_audio": ["DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP", "Data2VecAudioConfig"]... | 721 | """simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import I... | 645 | 0 |
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_channel_dimension_format, to_pil_image
from ...image_utils ... | 85 |
def _lowerCAmelCase ( __lowerCAmelCase , __lowerCAmelCase ) -> List[str]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__lowerCAmelCase , int(b / 2 ) ) * actual_power(__lowerCAmelCase , int(b / 2 ) )
els... | 252 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeries... | 160 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_lowerCAmelCase = datasets.logging.get_logger(__name__)
_lowerCAmelCase = '''\
@InProceedings{moosavi2019m... | 160 | 1 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _snake_case ( _snake_case : int ) -> datetime:
'''simple docstring'''
_A = year % 19
_A = year % 4
_A = year % 7
_A = math.floor(year / 1_00 )
... | 7 | 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, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 0 |
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
fr... | 577 |
import torch
from transformers import AutoModel
class _UpperCamelCase( torch.nn.Module ):
def __init__( self : str , SCREAMING_SNAKE_CASE__ : Tuple="sayef/fsner-bert-base-uncased" ):
'''simple docstring'''
super(SCREAMING_SNAK... | 577 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSemanticSegmentation,
Segfor... | 472 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 472 | 1 |
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
UpperCamelCase_ = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582'
}
... | 709 |
import numpy as np
import qiskit
def _UpperCAmelCase ( UpperCamelCase: int = 8 , UpperCamelCase: int | None = None ):
"""simple docstring"""
__lowerCAmelCase = np.random.default_rng(seed=UpperCamelCase )
# Roughly 25% of the qubits will contribute to the key.
# So... | 376 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
DataC... | 84 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytesserac... | 521 | 0 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bar... | 713 |
lowerCamelCase : int = {str(digit): digit**5 for digit in range(1_0)}
def lowercase__( A ):
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(A ) )
def lowercase__( ):
return sum(
number
for number in range(1_0_0_0 , 1_0_0_0_0_0_0 )
... | 303 | 0 |
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_call... | 146 |
class lowercase :
'''simple docstring'''
def __init__(self , __a ) -> Optional[Any]:
"""simple docstring"""
UpperCAmelCase__ = val
UpperCAmelCase__ = None
UpperCAmelCase__ = None
def ... | 146 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 327 |
"""simple docstring"""
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def lowercase () -> List[Any]:
raise RuntimeError('CUDA out of memory.' ... | 327 | 1 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vision_available
... | 100 | from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowerCAmelCase_ ( lowercase: str = "" ) -> dict[str, float]:
'''simple docstring'''
_UpperCamelCase: Tuple = url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
_UpperCame... | 271 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_lowercase )
class lowerCAmelCase_ ( _lowercase ):
'''simple docstring'''
_lowerCamelCas... | 22 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _snake_case ( snake_case__ : str = "isbn/0140328726" ):
A = olid.strip().strip('/' ) # Remove leading/trailing whitespace & slashes
if new_olid... | 22 | 1 |
"""simple docstring"""
from __future__ import annotations
def _A( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase ):
A__ : str = list(range(len(lowerCAmelCase ) ) )
A__ : Any = [v / w for v, w in zip(lowerCAmelCase , lowerCAmelC... | 363 | """simple docstring"""
import datasets
from .evaluate import evaluate
_UpperCamelCase = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={arXiv prepr... | 363 | 1 |
from ...configuration_utils import PretrainedConfig
class UpperCamelCase__ ( UpperCAmelCase__):
'''simple docstring'''
__a : Optional[int] = """bert-generation"""
def __init__( self , A=5_03_58 , A=10_24 , A=24 , A=16 , A=40_96 ... | 715 |
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 ModelTesterMixin, ids_t... | 433 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/re... | 603 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generation... | 603 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class snake_case_ ( a_ ):
def _... | 370 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
SCREAMING_SNAKE_CASE_ = {
"""config""": [
"""EXTERNAL_DATA_FORMAT_SIZE_LIMIT""",
"""OnnxConfig""",
"""OnnxConfigWithPast""",
"""OnnxSeq2SeqConfigWithPast""",
"""PatchingSpec""",
... | 370 | 1 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def _snake_case ( __snake_case , __snake_case , __snake_case ):
_UpperCamelCase = OmegaConf.load(__snake_case )
_UpperCamelCase = torch.load(_... | 10 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
lowerCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docst... | 692 | 0 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils... | 719 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
"""vocab_file""": """vocab.txt""",
... | 218 | 0 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import... | 25 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__lowercase : List[str] = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE... | 476 | 0 |
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_utils import replicate
from flax.training.common_utils ... | 706 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 81 | 0 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def A(__a: bytes , __a: int ):
lowerCAmelCase_ = F"{sampling_rate}"
lowerCAmelCase_ = "1"
lowerCAmelCase_ = "f32le"
lowerCAmelCase_... | 122 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase__ = {'''configuration_speech_encoder_decoder''': ['''SpeechEncoderDecoderConfig''']}
try:
if not is_torch_available():
raise OptionalDepende... | 122 | 1 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from torch import nn
... | 146 |
from math import ceil
def lowerCAmelCase ( UpperCamelCase__ : Dict , UpperCamelCase__ : Optional[Any] ) -> Union[str, Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: Union[str, Any] = list(range(0 , UpperCamelCase__ ... | 146 | 1 |
'''simple docstring'''
# Algorithm for the pigeonhole sorting
def SCREAMING_SNAKE_CASE ( lowercase_ : Dict ):
lowercase = min(lowercase_ ) # min() finds the minimum value
lowercase = max(lowercase_ ) # max() finds the maximum value
lowercase = ... | 588 |
'''simple docstring'''
import argparse
import os
import re
lowercase_ : Optional[Any] = '''src/transformers'''
# Pattern that looks at the indentation in a line.
lowercase_ : int = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
lowercase... | 588 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase = {
"""configuration_upernet""": ["""UperNetConfig"""],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDepende... | 563 |
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
__lowercase = """\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang, Alex and Singh, Amanpreet a... | 563 | 1 |
"""simple docstring"""
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 _UpperCAmelCase( ... | 19 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_came... | 707 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _snake_case ( UpperCAmelCase_ ):
@staticmethod
@abstractmethod
def lowercase__ ( SCREAMING_SNAKE_CASE_):
'''simple docstring'''
raise NotImplementedError()
@abstractme... | 495 | 0 |
'''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
_lowerCamelCase = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Transl... | 71 |
"""simple docstring"""
def A_ ( lowercase , lowercase ) -> int:
"""simple docstring"""
return number | (1 << position)
def A_ ( lowercase , lowercase ) -> int:
"""simple docstring"""
return number & ~(1 << position... | 470 | 0 |
"""simple docstring"""
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_C... | 717 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class lowerCamelCase__ ( SCREAMIN... | 255 | 0 |
"""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
... | 19 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 677 | 0 |
class lowercase__:
'''simple docstring'''
def __init__( self , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE) -> Union[str, Any]:
"""simple docstring"""
UpperCamelCase__ : str =name
UpperCamelC... | 582 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
__UpperCAmelCase = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for Transfer Learned"""
... | 582 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
a = get_tests_dir('fixtures/test_sentenc... | 169 | def __UpperCamelCase ( A = 10**12 ):
UpperCamelCase__ = 1
UpperCamelCase__ = 0
UpperCamelCase__ = 1
UpperCamelCase__ = 1
while numerator <= 2 * min_total - 1:
prev_numerator += 2 * numerator
numerator += 2 * pre... | 415 | 0 |
# Copyright 2021 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
#
# Unles... | 559 |
import argparse
__a : int = """docs/source/_static/js/custom.js"""
def a_ ( __snake_case ) -> Optional[int]:
'''simple docstring'''
with open(__snake_case , encoding='utf-8' , newline='\n' ) as f:
UpperCamelCase_ = f.readlines... | 559 | 1 |
def UpperCAmelCase_ ( UpperCAmelCase__ , UpperCAmelCase__ ):
lowercase_ = """"""
for word_or_phrase in separated:
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise Exception("""join() accepts only strings to be joined""" )
joi... | 412 |
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.utils import WEIG... | 412 | 1 |
from __future__ import annotations
from collections import deque
class _A :
def __init__( self , _SCREAMING_SNAKE_CASE ):
_UpperCAmelCase = []
self.adlist.append(
{"""value""": """""", """next_states""": [], """fail_state""":... | 175 |
from typing import Dict
from .base import GenericTensor, Pipeline
class _A ( __lowercase ):
def UpperCAmelCase ( self , _SCREAMING_SNAKE_CASE=None , _SCREAMING_SNAKE_CASE=None , _SCREAMING_SNAKE_CASE=None , **_SCREAMING_SNAKE_CASE ):
... | 175 | 1 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def _A ( lowercase__="ro" , lowercase__="en" , lowercase__="wmt16" , lowercase__=None ):
try:
import datasets
except (ModuleNotFoundError, ImportError):
raise ImportError("""... | 325 | '''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def UpperCamelCase__ ( _lowercase : Dict ) -> str:
for param in module.parameters():
__UpperCAmelCase: int = False
def UpperCamelCase__ ( ) ... | 523 | 0 |
"""simple docstring"""
import doctest
from collections import deque
import numpy as np
class A_:
"""simple docstring"""
def __init__( self ):
_lowerCamelCase : Dict = [2, 1, 2, -1]
_lowerCamelCase : str = [1, 2, 3, 4]
def ... | 720 |
"""simple docstring"""
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_... | 349 | 0 |
"""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, TimestepEmbedding, Timest... | 437 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_avail... | 264 | 0 |
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self ):
lowerCamelCase_ : Tuple = {}
def _UpperCamelCase ( self ):
print(self.vertex )
for i in self.vertex:
print(a_ , ... | 711 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
# See all Cvt models at https://hug... | 73 | 0 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..contro... | 71 |
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.utils.testing_utils import i... | 462 | 0 |
'''simple docstring'''
from __future__ import annotations
import time
lowerCAmelCase_ = list[tuple[int, int]]
lowerCAmelCase_ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0,... | 435 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase_ = {
'configuration_roberta_prelayernorm': [
'ROBERTA_PRELAYERNORM_PRETRAINE... | 435 | 1 |
from typing import Dict, List, Optional, Tuple, 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_channel_dimension_format,
)... | 398 | '''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
el... | 209 | 0 |
import requests
from bsa import BeautifulSoup
def SCREAMING_SNAKE_CASE__ ( __lowerCAmelCase = "AAPL" ):
snake_case__ = F"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
snake_case__ = BeautifulSoup(requests.get(__lowerCAmelCase ).text , "html.parser" ... | 530 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import BaseTra... | 530 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json... | 43 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vis... | 43 | 1 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def lowerCAmelCase_ ( SCREAMING_SNAKE_CASE_ ) -> int:
"""simple docstring"""
... | 0 |
'''simple docstring'''
from sklearn.metrics import matthews_corrcoef
import datasets
UpperCamelCase__ : List[str] = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass c... | 0 | 1 |
"""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_channel_dimension_format, to_pil... | 142 |
"""simple docstring"""
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
__lowercase : List[str] = logging.getLogger(__name__)
__l... | 142 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_A: List[Any] = {
"""configuration_mega""": ["""MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegaConfig""", """MegaOnnxConfig"""],
}
t... | 617 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( UpperCAmelCase_ ):
_A : List[Any] = """timm_backbone"""
def __init__( self ,... | 617 | 1 |
from datetime import datetime
import requests
def lowerCAmelCase_ ( A_):
UpperCamelCase__: List[Any] = "https://downloadgram.net/wp-json/wppress/video-downloader/video?url="
UpperCamelCase__: List[Any] = requests.get(base_url + url).json()[0]["urls"][0]["src"]
... | 380 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
A__: Dict = {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'... | 380 | 1 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pi... | 74 |
"""simple docstring"""
def _a ( _snake_case = 10 , _snake_case = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , _snake_case )
UpperCAmelCase = range(1 , _snake_case )
return sum(
1 for power in powers fo... | 74 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"google/bigbird-roberta-base": "https://huggingface.co/goog... | 307 |
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
_snake_case = datasets.load_iris()
_snake_case = np.array(data["data"])
_snake_case = np.array(data["target"])
_snake_case = data["target_names"]
_sna... | 307 | 1 |
"""simple docstring"""
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __A ( SCREAMING_SNAKE_CASE_ ):
@require_torch
def __A ( self ):
... | 707 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_a : int = {
'configuration_altclip': [
'ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AltCLIPConfig',
'AltCLIPTe... | 663 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _lowerCAmelCase ( unittest.T... | 93 |
_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 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCamelCase : int = 2_00 ) -> int:
_lowerCamelCase = [1, 2, 5, 10, 20, 50, 1_00, 2_00]
_lowerCamelCase = [0] * (pence + 1)
_lowerCamelCase = 1 # base case: 1 way to make 0 p... | 700 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 234 | 0 |
def __UpperCAmelCase ( lowerCamelCase_ : int = 3 , lowerCamelCase_ : int = 7 , lowerCamelCase_ : int = 1_00_00_00 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 0
SCREAMING_SNAKE_CASE_ : Any = 1
f... | 105 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 302 | 0 |
"""simple docstring"""
from queue import PriorityQueue
from typing import Any
import numpy as np
def __snake_case ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase_... | 719 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Dict = {
"configuration_megatron_bert": ["MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegatronBertConfig"],
}
try:
if no... | 91 | 0 |
import heapq
import sys
import numpy as np
__a: Dict = tuple[int, int]
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self : Any ) -> str:
"""simple docstring"""
_UpperCAmelCase = []
_UpperCAmelCase ... | 108 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generati... | 330 | 0 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaV... | 711 |
import argparse
import collections
import os
import re
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_table.py
__A : List[Any] = 'src/transformers'
__A : Tuple ... | 75 | 0 |
def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> float:
'''simple docstring'''
UpperCAmelCase__ : int = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
... | 79 |
'''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_effective_axis_d... | 72 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'configuration_blip': [
'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 27 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
__magic_name__ = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
__magic_name__ = reque... | 27 | 1 |
'''simple docstring'''
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 ModelMix... | 310 |
'''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
if is_torch_available():
import ... | 310 | 1 |
UpperCAmelCase_ = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
UpperCAmelCase_ = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> Tuple:
'''simple do... | 718 | 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 fastapi.routing i... | 476 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece... | 40 |
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_extraction_common import SequenceFeatureExtractio... | 40 | 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_availa... | 327 |
"""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/... | 327 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowerCAmelCase_ = {
"""configuration_ernie""": ["""ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieConfig""", """ErnieOnnxConfig"""],
}
try:
... | 678 | from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase__ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_pytorch': 'https://hugg... | 486 | 0 |
'''simple docstring'''
import numpy
class _snake_case :
"""simple docstring"""
def __init__( self : Union[str, Any] , UpperCamelCase_ : numpy.ndarray , UpperCamelCase_ : numpy.ndarray ):
lowerCAmelCase_ : List[str] =input_array
# Rando... | 700 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__lowercase = HfArgumentParser(InitializationArguments)
__lowercase = parser.parse_args()
# Load codeparrot tokenizer tra... | 305 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ = {
'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
'feature_extraction_mctct': ['MCTC... | 560 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __A ( A_ ):
'''simple docstring'''
lowerCAmelCase : Tuple = "SpeechT5FeatureExtractor"
lowerCAmelCase : Optional[Any] = "SpeechT5Toke... | 560 | 1 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf... | 707 |
'''simple docstring'''
from collections import defaultdict
def __magic_name__( _A ):
'''simple docstring'''
UpperCamelCase__ = 1
UpperCamelCase__ = True
for v in tree[start]:
if v not in visited:
ret += dfs(_A )
if... | 265 | 0 |
def UpperCAmelCase_ ( __UpperCamelCase ):
if not isinstance(__SCREAMING_SNAKE_CASE, __SCREAMING_SNAKE_CASE ):
SCREAMING_SNAKE_CASE__ =f"""Input value of [number={number}] must be an integer"""
raise TypeError(__SCREAMING_SNAKE_CASE )
if numbe... | 151 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
'shi-l... | 582 | 0 |
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_utils import On... | 706 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
# See all GLPN models a... | 510 | 0 |
from __future__ import annotations
UpperCamelCase = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class _A :
def __init__( self : List[str] , lowerCamelCase_... | 269 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
A_ = "sshleifer/bart-tiny-random"
A_ = "patrickvonpl... | 393 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class a__ ( a__ ... | 715 |
'''simple docstring'''
def _snake_case ( A , A ) -> bool:
lowerCAmelCase__ = len(A ) + 1
lowerCAmelCase__ = len(A ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i of input_string matches with pr... | 98 | 0 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 50 ) -> int:
'''simple docstring'''
_lowerCamelCase : Any = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in... | 46 |
'''simple docstring'''
from math import isqrt, loga
def lowerCamelCase__ ( a ):
__snake_case = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , a , a ):
... | 356 | 0 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class _SCREAMING_SNAKE_CASE ( lowercase_ ):
def SCREAMING_SNAKE_CASE_( self , lowercase ) -> Union[str, Any]:
return 0.0
def low... | 713 |
from itertools import count
def lowerCamelCase_ ( lowerCamelCase__ = 5_0 ):
lowerCamelCase_ = [1] * min_block_length
for n in count(lowerCamelCase__ ):
fill_count_functions.append(1 )
for block_length in range(lowerCamelCase__ , n + 1 ):
... | 313 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : int = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""Jukeb... | 33 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class a__( lowerCamelCase__ ):
... | 526 | 0 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
A = '<<<<<<< This should probably be modified because it mentions: '
A = '=======\n>>>>>>>\n'
A ... | 46 |
import unittest
from transformers import MraConfig, 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, floats_tensor, ids_tensor, random_attention_mask
if is_torch_a... | 46 | 1 |
from __future__ import annotations
SCREAMING_SNAKE_CASE = list[list[int]]
# assigning initial values to the grid
SCREAMING_SNAKE_CASE = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
... | 99 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
SCREAMING_SNAKE_CASE__:Dict = logging.get_logger(__name__)
class snake_case__ ( snake_case_ ):
def __init__( self , *lowerCamelCase , **lowerCame... | 528 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
fr... | 109 |
"""simple docstring"""
def lowerCAmelCase__ ( lowerCamelCase__ ) -> int:
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
raise ValueError('multiplicative_persistence() only accepts integral values' )
if num < 0:
raise ValueError(... | 109 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {
'''configuration_electra''': ['''ELECTRA_PRETRAINE... | 657 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__magic_name__ = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : Dict = {
"configuration_blenderbot": [
"BLENDERBOT_PRETRAIN... | 604 |
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_barthez import B... | 604 | 1 |
from collections import defaultdict
from math import ceil, sqrt
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ = 1000000 , SCREAMING_SNAKE_CASE__ = 10 ):
snake_case_ = defaultdict(SCREAMING_SNAKE_CASE__ )
for outer_width in range(3 , (t_limit // 4) + 2 ):
... | 39 | import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
a_ = logging.get_logger(__name__)
a_ = {
'post_extract_proj': 'feature_projection.projection',
'encoder.pos_con... | 417 | 0 |
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
a_ : Any = get_tests... | 715 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
AutoTokeni... | 444 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 4 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class lowerCAmelCase_ ( __A ):
'''simple docstring'''
_lowercase = 'Speech2TextFeatureExtractor'
_lowercase = 'Speech2TextTokenizer'
def __init_... | 220 | 0 |
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_get,
ftp_head,
... | 714 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowercase : str = logging.get_logger(__name__)
class __A( __UpperCAmelCase ):
def __init__( self, *A, **A ):
"""simple docstring"""
warning... | 105 | 0 |
import numpy as np
def a (_lowerCAmelCase ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 234 |
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=__UpperCAmelCase):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Optional[Any] = ["flax"]
def __init__( self: Dict , *_lowerCamelCase: Tupl... | 234 | 1 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...imag... | 321 |
_lowerCamelCase = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
def lowerCamelCase ( )-> None:
"""simple docstring"""
a =input("""Enter message: """ )
a =input("""Enter key [alphanumeric]: """ )
a =input("""Encrypt/Decrypt [e/d]: """ )
... | 321 | 1 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Ar... | 631 |
from __future__ import annotations
__magic_name__ = list[list[int]]
# assigning initial values to the grid
__magic_name__ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0, 5],... | 254 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple reposit... | 714 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class _UpperCAmelCase :
'''simple docstring'''
lowercase_ : int
lowercase_ : int
class _Uppe... | 302 | 0 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokeniz... | 52 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def __A ( a_ :Tuple) -> List[str]:
return choice(a_)
def __A ( a_ :list[int] , a_ :int) -> int:
__a : Optional[int] = random_pivot(a... | 52 | 1 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_process... | 413 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
_snake_case = logging.get_logger(__name__)
def lowerCamelCase_ ( A : List[str] , A : Optional[int] ):
"""simple docstring"""
low... | 413 | 1 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModel... | 28 |
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
snake_case : Optional[int] = get_logger(__name__)
snake_case : Union[str, Any] = R"\n Args:\n input_ids (`jnp.ndarray` ... | 124 | 0 |
from __future__ import annotations
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ) -> float:
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError("days_between_payments must be > 0" )
if daily_interest_rate < 0:
rai... | 707 |
"""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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
... | 386 | 0 |
from scipy.stats import spearmanr
import datasets
A : int = '\nThe Spearman rank-order correlation coefficient is a measure of the\nrelationship between two datasets. Like other correlation coefficients,\nthis one varies between -1 and +1 with 0 implying no correlation.\nPositive correlatio... | 15 |
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
... | 14 | 0 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_pa... | 704 |
import math
def _UpperCamelCase (a__ :int ):
"""simple docstring"""
UpperCamelCase__ = [True] * n
UpperCamelCase__ = False
UpperCamelCase__ = False
UpperCamelCase__ = True
for i in range(3 , int(... | 548 | 0 |
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