code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
def a__ ( _UpperCamelCase : list[int] ):
__lowerCamelCase = []
if len(_UpperCamelCase ) == 1:
return [nums.copy()]
for _ in range(len(_UpperCamelCase ) ):
__lowerCamelCase = nums.pop(0 )
__lowerCamelCase = permut... | 330 |
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProcessor
from .modelin... | 330 | 1 |
"""simple docstring"""
import math
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : str = 0
lowerCamelCase__ : Union[str, Any] = 0
while num > 0:
lowerCamelCase__ : Dict = num % 8
lowerCamelCase__ : Optio... | 352 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config impo... | 316 | 0 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_bytes
from... | 118 | 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 TOKEN, USER, get_t... | 118 | 1 |
"""simple docstring"""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_UpperCamelC... | 367 |
"""simple docstring"""
import numpy as np
def _a ( _snake_case ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 234 | 0 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_objects import * # ... | 154 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A : Optional[Any] = {'configuration_fnet': ['FNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FNetConfig']}
try:
i... | 154 | 1 |
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, loggi... | 266 |
from string import ascii_uppercase
_lowercase : str ={char: i for i, char in enumerate(ascii_uppercase)}
_lowercase : Dict =dict(enumerate(ascii_uppercase))
def lowerCAmelCase_ ( _lowercase : str , _lowercase : str) -> str:
... | 266 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase : Optional[Any] = {
"configuration_altclip": [
"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AltCLI... | 42 |
"""simple docstring"""
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
A_ : Dict = HfApi()
A_ : List[str] = {}
# fmt: off
A_ : Dict = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, ... | 165 | 0 |
"""simple docstring"""
import math
import sys
def _lowerCamelCase(__UpperCamelCase ) -> str:
_lowerCAmelCase =""""""
try:
with open(__UpperCamelCase , """rb""" ) as binary_file:
_lowerCAmelCase =binary_file.read()
for dat in data:
_lowerCAmelCase =F'''{d... | 341 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCamelCase__ ( unittest.TestCase ):
'''simple docstring'''
lowerCamelCase = JukeboxTokenizer
lowerCamelCase = {
... | 341 | 1 |
"""simple docstring"""
import numpy as np
def A__ ( UpperCamelCase ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 292 |
"""simple docstring"""
class _UpperCAmelCase :
def __init__( self :List[str] , __UpperCamelCase :Union[str, Any] , __UpperCamelCase :Tuple ):
A = name
A = val
def __str__( self :str ):
return f"{self.__class__.__nam... | 292 | 1 |
import json
import sys
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase ):
with open(__lowerCamelCase , encoding="utf-8" ) as f:
__snake_case : Tuple = json.load(__lowerCamelCase )
__snake_case : Optional[... | 134 |
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
_snake_case : Union[str, Any] = datasets.load_iris()
_snake_case : Tuple = np.array(data["data"])
_snake_case : int = np.array(data["target"])... | 134 | 1 |
import argparse
from collections import defaultdict
def lowerCAmelCase_ ( _lowercase : List[Any] , _lowercase : List[Any] , _lowercase : Dict , _lowercase : Optional[int] , _lowercase : List[str]) -> List[str]:
"""simpl... | 170 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCAmelCase_ ( _lowercase : float , _lowercase : float , _lowercase : bool = False) -> list[float]:
"""sim... | 170 | 1 |
'''simple docstring'''
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 48 |
'''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 _UpperCamelCase ( A ):... | 48 | 1 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
d... | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
UpperCAmelCase__ = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}
... | 0 | 1 |
"""simple docstring"""
def _A (__a ) -> List[Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(__a )
SCREAMING_SNAKE_CASE_ : List[Any] = sum(__a )
SCREAMING_SNAKE_CASE_ : Optional[Any] = [[False f... | 318 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_... | 318 | 1 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def UpperCAmelCase ( a_ , a... | 15 |
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
UpperCAmelCase_ : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase_ : str ... | 32 | 0 |
"""simple docstring"""
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
snake_case_ = """Usage of script: script_name <size_of_canvas:int>"""
snake_case_ = [0] * 100 + [1] * 10
random.shuffle(choice)
... | 355 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowercase_ ):
assert isinstance(lowercase_ , lowercase_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
... | 181 | 0 |
import json
from typing import TYPE_CHECKING, 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_blenderbot import Blen... | 192 |
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 UpperCamelCase (lowercase_: str ) -> Dict:
A__ : int = int(lowercase_ )
A__ , ... | 192 | 1 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMo... | 279 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/config.json''',
# See all BioGPT models at https://huggingface.... | 279 | 1 |
'''simple docstring'''
from __future__ import annotations
import bisect
def UpperCamelCase_ ( A__ : list[int] , A__ : int , A__ : int = 0 , A__ : int = -1 ):
'''simple docstring'''
if hi < 0:
lowerC... | 120 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
a_ = logging.get_logger(__name__)
a_ = {name: getattr(transformers, name + '''Fast''') for name in SLOW_TO_FAST_CONVERTERS}
de... | 340 | 0 |
"""simple docstring"""
import random
def UpperCAmelCase ( UpperCamelCase__ ):
"""simple docstring"""
A__ = num - 1
A__ = 0
while s % 2 == 0:
A__ = s // 2
t += 1... | 154 | """simple docstring"""
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNe... | 154 | 1 |
"""simple docstring"""
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTester... | 160 |
"""simple docstring"""
import os
def _snake_case ( ) -> Dict:
with open(os.path.dirname(lowerCamelCase__ ) + "/p022_names.txt" ) as file:
lowerCamelCase_ : str =str(file.readlines()[0] )
lowerCamelCase_ : Union[str, Any] ... | 144 | 0 |
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, ... | 371 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
_lowerCamelCase : Union[str, Any] = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(i... | 191 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.imp... | 87 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(check_de... | 127 | 0 |
__A = {
0: '''0''',
1: '''1''',
2: '''2''',
3: '''3''',
4: '''4''',
5: '''5''',
6: '''6''',
7: '''7''',
8: '''8''',
9: '''9''',
10: '''a''',
11: '''b''',
12: '''c''',
13: '''d''',
14: '''e''',
15: '''f''',
}
def snake_case_(_UpperCamelC... | 278 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A = {
'''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependenc... | 278 | 1 |
"""simple docstring"""
from __future__ import annotations
def __magic_name__ ( __snake_case : str , __snake_case : list[str] | None = None ) -> list[list[str]]:
lowercase : List[str] = word_bank or []
# create a table
lowercase... | 202 |
"""simple docstring"""
from __future__ import annotations
def __magic_name__ ( __snake_case : list[int] ) -> list[int]:
if len(__snake_case ) == 0:
return array
lowercase , lowercase : Tuple = min(__snake_case ), max(__snake_... | 202 | 1 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{pr... | 326 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ... | 326 | 1 |
"""simple docstring"""
# limitations under the License.
# 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 .pipelines import DiffusionPipeline, ImagePipelineOutput # noq... | 81 |
"""simple docstring"""
import os
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 logging
lowerCamelCase_ : Any = logging.get_... | 81 | 1 |
from collections import defaultdict
from math import gcd
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase = 150_0000 ) -> int:
lowerCamelCase__ : defaultdict = defaultdict(_UpperCAmelCase )
lowerCamelCase__ : Tuple = 2
while 2 * euclid_m * (euclid_m + 1) <= ... | 357 |
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase ) -> str:
if number > 0:
raise ValueError('input must be a negative integer' )
lowerCamelCase__ : str = len(bin(_UpperCAmelCase )[3:] )
lowerCamelCase__ : Dict = bin(abs(_UpperCAmelCase ) - (1 << binary_number_... | 45 | 0 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError("To use the rich extension, install rich with `pip install rich`")
| 101 |
'''simple docstring'''
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 (
... | 297 | 0 |
def lowercase_ ( _lowerCamelCase : List[str]):
lowercase__ : Dict = len(_lowerCamelCase)
lowercase__ : Union[str, Any] = sum(_lowerCamelCase)
lowercase__ : Any = [[False for x in range(s + 1)] for y in range(n + 1)]
for i in range(1 ... | 333 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
... | 333 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def lowercase__( __SCREAMING_SNAKE_CASE : int ... | 213 | """simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.... | 213 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from ... | 87 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
"xlnet-large-cased": "https://huggingfac... | 87 | 1 |
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def _A ( _lowercase , _lowercase=1 ) -> str:
"""simple docstring"""
if n_shave_prefix_segments >= 0:
return ".".join(path.s... | 310 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_en... | 310 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase_ = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
],
"feature_extraction_encodec": ... | 357 |
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis... | 282 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def UpperCamelCase ( snake_case__ : int ) -> Dict:
# A local function to see if a dot lands in the circle.
def is_in_circle(snake_case__ : float , snake_ca... | 119 |
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def UpperCamelCase ( ) -> tuple[list[int], int]:
UpperCamelCase : int = [randint(-1000 , 1000 ) for i in range(10 )]
UpperCamelCase : Dict = randint... | 119 | 1 |
from math import ceil
def _lowerCAmelCase ( A__: Optional[Any] , A__: Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase = list(range(0 , A__ ) )
UpperCAmelCase = [item for sublist in list(device_map.values() ) for it... | 152 |
def _lowerCAmelCase ( A__: list[int] , A__: list[int] ):
'''simple docstring'''
UpperCAmelCase = len(A__ )
print('''The following activities are selected:''' )
# The first activity is always selected
UpperCAmelCase = 0
print... | 152 | 1 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class A__ ( _A ):
... | 325 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for di... | 33 | 0 |
'''simple docstring'''
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common im... | 283 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( a__ ):
lowerCAmelCase :Optional[int] = ''''''
lowerCAmelCase :str ... | 283 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase :Dict = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
... | 206 |
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.utils impo... | 130 | 0 |
'''simple docstring'''
from numpy import exp, pi, sqrt
def _UpperCAmelCase ( _UpperCamelCase : Dict, _UpperCamelCase : float = 0.0, _UpperCamelCase : float = 1.0 ) -> int:
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigm... | 367 | '''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 18 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ : dict ) -> set:
'''simple docstring'''
A__ = set()
# edges = list of graph's edges
A__ = get_edges(SCREAMING_SNAKE_CASE__ )
# While there are still elements in edges list, ... | 7 |
def _snake_case( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , ) -> float:
'''simple docstring'''
A__ ... | 7 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
lowercase =logging.get_logger(__name__)
lowercase ={
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.json',
# Se... | 366 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoen... | 242 | 0 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class a__( lowerCamelCase__ ):
lowercase... | 297 |
'''simple docstring'''
from __future__ import annotations
from math import pi, sqrt
def lowerCamelCase__ ( _A , _A ):
if inductance <= 0:
raise ValueError('Inductance cannot be 0 or negative' )
elif capacitance <= 0:
raise ValueError('Capacitance cannot be 0 or negative... | 297 | 1 |
"""simple docstring"""
import functools
def UpperCamelCase ( __lowercase : str ,__lowercase : str ):
'''simple docstring'''
A_ : List[str] = len(_A )
A_ : List[Any] = len(_A )
@functools.cache
def min_distan... | 355 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
_UpperCAmelCase = logging.get_logger(__name__)
_Uppe... | 192 | 0 |
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''']
snake_c... | 214 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
loggin... | 346 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTe... | 61 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.j... | 61 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase : List[Any] = {
'''configuration_conditional_detr''': [
'''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ConditionalDetr... | 252 |
# 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 applic... | 94 | 0 |
import math
import unittest
def a_ ( lowerCAmelCase_ : int ):
assert isinstance(lowerCAmelCase_, lowerCAmelCase_ ) 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 ... | 353 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDI... | 207 | 0 |
'''simple docstring'''
def __lowerCAmelCase ( UpperCamelCase__ ) -> Union[str, Any]:
if not isinstance(A__ , A__ ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divis... | 67 |
'''simple docstring'''
from sklearn.metrics import recall_score
import datasets
__A : Dict = "\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is... | 120 | 0 |
"""simple docstring"""
def __a ( _SCREAMING_SNAKE_CASE ) ->bool:
a__: Optional[Any] = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 203 | """simple docstring"""
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, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available():
impor... | 203 | 1 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a__ ( ) -> Union[str, Any]:
with offline(OfflineSimulationMode.CONNECTIO... | 291 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : int = logging.get_logger(__name__)
lowerCAmelCase : List[str] = {
"""asapp/sew-d-tiny-100k""": """h... | 291 | 1 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def __A ( _lowercase , _lowercase ):
'''simple docstring'''
_A = args.log_outp... | 75 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
__A = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE ( snake_case ):
"""simple docstring"""
def __init__( self: List[Any] , *__A: Union[str, An... | 75 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class A :
__magic_name__ = field(
metadata={... | 3 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 267 | 0 |
'''simple docstring'''
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : Any ) -> Union[str, Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE ... | 359 |
'''simple docstring'''
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
UpperCAmelCase : Dict = TypeVar('T')
def a__ ( a__ ):
"""simple docstring"""
return (position - 1) // 2
def a__ ( a__ ):
... | 331 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
A__ = TypeVar("""T""")
A__ = TypeVar("""U""")
class __lowerCAmelCase ( Generic[T, U] ):
def __init__( self , _snake_case , _snake_ca... | 82 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
... | 293 | 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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils i... | 360 |
'''simple docstring'''
import random
from .binary_exp_mod import bin_exp_mod
def SCREAMING_SNAKE_CASE__ ( __A , __A=1_000 ) -> str:
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
_snake_case = n - 1
_snake_case ... | 160 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
snake_case__ : Optional[Any] = logging.get_logger(__name__)
class snake_case_( a__ ):
def __init__( self : int , *UpperCamelCase_ : ... | 60 |
'''simple docstring'''
import math
import qiskit
def _lowerCAmelCase ( __snake_case : int = 1 , __snake_case : int = 1 , __snake_case : int = 1 ) -> qiskit.result.counts.Counts:
if (
isinstance(__snake_case , __snake_case )
... | 190 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.... | 356 |
'''simple docstring'''
import os
def a__ ( a__ = "input.txt" ):
"""simple docstring"""
with open(os.path.join(os.path.dirname(a__ ) , a__ ) ) as input_file:
__SCREAMING_SNAKE_CASE = [
[int(a__ ) for element in line.spli... | 331 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import gcd
def lowercase__ ( snake_case_ :int , snake_case_ :int = 2 , snake_case_ :int = 1 , snake_case_ :int = 3 , ):
# A value less than 2 can cause an inf... | 332 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
... | 332 | 1 |
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 o... | 355 |
from collections import defaultdict
from math import ceil, sqrt
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0_0_0_0 , __lowerCAmelCase : int = 1_0 ):
a__ = defaultdict(__lowerCAmelCase )
for outer_width in range(3 , (t_limit // 4) + 2... | 109 | 0 |
'''simple docstring'''
from __future__ import annotations
def __lowerCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) -> Any:
_a : Any = get_failure_array(_lowerCAmelCase )
# 2) Step through text searching for pattern
_a , _a : Any ... | 89 |
"""simple docstring"""
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
... | 320 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> dict[str, float]:
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("""On... | 21 | '''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase ( UpperCAmelCase__ : List[Any] , UpperCAmelCase__ : Op... | 21 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def a__ ( _UpperCamelCase : Optional[Any] ):
__lower... | 330 |
def a__ ( _UpperCamelCase : int ):
if not isinstance(_UpperCamelCase ,_UpperCamelCase ):
__lowerCamelCase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(_UpperCamelCase )
if number < 0:
return False
__lowerCa... | 330 | 1 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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_comm... | 362 |
import copy
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
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE_:Optional[Any] = logging.get_lo... | 115 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, BlipImageProc... | 50 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import require_elasticsearch, re... | 50 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def UpperCAmelCase ( lowerCamelCase_ :Callable , lowerCamelCase_ :float , lowerCamelCase_ :float , lowerCamelCase_ :float , lowerCamelCase_ :float ):
'''simple docstring'''
sn... | 354 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__A : Dict = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_pyto... | 8 | 0 |
import argparse
from collections import defaultdict
import yaml
__lowerCamelCase = """docs/source/en/_toctree.yml"""
def UpperCamelCase ( __lowerCamelCase : Optional[Any] ):
snake_case : Any = defaultdict(__lowerCamelCase )
snake_case ... | 59 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
lowerCAmelCase_ = (
'''4S 3H 2C 7S 5H''',
'''9D 8H 2C 6S 7H''',
'''2D 6D 9D TH 7D''',
'''TC 8C 2S JH 6C''',
'''JH 8S TH AH QH''',
'''TS KS 5S 9S AC''',
'''KD 6... | 279 | 0 |
'''simple docstring'''
from random import randint, random
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = False , _SCREAMING_SNAKE_CASE = False , _SCREAMING_SNAKE_CASE = 5 , ):
_snake_case... | 270 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 270 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a :Dict = logging.get_logger(__name__)
a :int = "▁"
a :Option... | 132 |
"""simple docstring"""
a :dict[tuple[int, int, int], int] = {}
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> int:
# if we are absent twice, or late 3 consecutive days,
# no further prize strings are possible
if late ... | 132 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_a : Optional[int] = logging.get_logger(__name__... | 365 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_a : List[Any] = logging.get_logger(__name__)
class __A ( SCREAMING_SNAKE_CASE_ ,... | 126 | 0 |
import os
import sys
import unittest
UpperCAmelCase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
ge... | 5 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.m... | 25 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ ):
while a != 0:
UpperCAmelCase , UpperCAmelCase = b % a, a
return b
def _lowerCAmelCase ( lowercase_ , lowercase_ ):
if gcd(lowercase_ ... | 181 |
"""simple docstring"""
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
snake_case_ = {
"""facebook/maskforme... | 181 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
'''configuration_upernet''': ['''UperNetConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable(... | 289 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rando... | 94 | 0 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
UpperCAmelCase = get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.mod... | 364 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase = '''\
@misc{chen2021evaluating,
title={Evalu... | 172 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils ... | 71 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
A_ :List[str] = '''\
@misc{chen2021evaluating,
title={Ev... | 71 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
... | 83 |
'''simple docstring'''
import requests
lowercase__ = "" # <-- Put your OpenWeatherMap appid here!
lowercase__ = "https://api.openweathermap.org/data/2.5/"
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "Chicago" , SCREAMING_SNAKE_CASE__ = APPID ) -> dict:
'''sim... | 83 | 1 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
__UpperCamelCase = logging.getLogger(__name__)
class lowerCAmelCase ( lowerCamelCase_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ : O... | 113 |
"""simple docstring"""
def lowercase (SCREAMING_SNAKE_CASE_ : int ) -> str:
SCREAMING_SNAKE_CASE = int(SCREAMING_SNAKE_CASE_ )
if decimal in (0, 1): # Exit cases for the recursion
return str(SCREAMING_SNAKE_CASE_ )
SCREAMING_SNAKE_CAS... | 113 | 1 |
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: F401 # Here ... | 356 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def lowerCamelCase__ (_UpperCAmelCase):
monkeypatch.setattr('datasets.utils.deprecation_utils._emitted_deprecation_warnings' , set())
@pytest.fixture
def lowerCamelCase__ (_UpperCAmelCa... | 327 | 0 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_a... | 31 |
from __future__ import annotations
from cmath import sqrt
def _a ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : int ) -> tuple[complex, complex]:
"""simple docstring"""
if a == 0:
raise ValueError("Coefficient... | 340 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def A_ ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _low... | 356 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class A__ ( __snake_case ):
def _... | 140 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : str = logging.get_logger(__name__)
A_ ... | 165 |
"""simple docstring"""
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
... | 165 | 1 |
"""simple docstring"""
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 ver... | 368 |
"""simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def snake_case__ ( __lowerCamelCase : jnp.ndarray , __lowerCamelCase : int , __lowerCamelCase : float = 1 , __lowerCamelCase : float = 1 , __lowerCamelCase :... | 272 | 0 |
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_chec... | 34 |
'''simple docstring'''
def snake_case_ (_a : str , _a : str ):
UpperCAmelCase = len(_a ) + 1
UpperCAmelCase = len(_a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i of input_string matches with... | 34 | 1 |
"""simple docstring"""
def __a ( __lowerCamelCase, __lowerCamelCase ):
UpperCAmelCase_ : Dict = int(__lowerCamelCase )
# Initialize Result
UpperCAmelCase_ : Any = []
# Traverse through all denomination
for denomination in reversed(__lowerCamelCase ):
# ... | 23 |
"""simple docstring"""
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate... | 23 | 1 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class A_ ( lowerCamelCase__ ):
def __init__(self :Optional[An... | 117 |
'''simple docstring'''
import os
lowerCAmelCase__ = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def _A ( A__ ):
"""simple docstring"""
__lowercase = 0
__lowercase = 0
while index < len(A__ ) - 1:
__... | 104 | 0 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCamelCase ( a_ , a_ , a_ = False ) -> list[float]:
if radian_mode:
return [magnitude * cos(a_ ), magn... | 14 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 14 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is... | 23 |
# 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 app... | 284 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configu... | 338 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Union[str, Any] = logging.get_logger(__name__)
a : ... | 338 | 1 |
'''simple docstring'''
class a__ :
def __init__( self , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
_lowercase : int = None
_lowercase : int = None
_lowercase : Optional[Any] = ... | 250 |
"""simple docstring"""
from itertools import product
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase ) -> list[int]:
lowerCAmelCase__ : Union[str, Any] = sides_number
lowerCAmelCase__ : Optional[int] = max_face_number * dice_number
... | 242 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : int ):
"""simple docstring"""
a :Optional[int] = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
a :List[str] = n - k
... | 281 |
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_available():
from PIL import Image
from ..image_utils impo... | 281 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTok... | 95 |
'''simple docstring'''
import os
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 logging
UpperCamelCase__: Tuple = logging.get_... | 23 | 0 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_dat... | 177 |
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 DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils import logg... | 177 | 1 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class A__:
"""simple docstring"""
_A : List[Any] = None
def UpperCamelCase__ ( self ) -> Any:
a_ : Tuple = self... | 248 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import nightly, slow, to... | 248 | 1 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
lowercase_ = logging.getLogger(__name__)
class _snake_case :
def __init__( self : Optional[Any] ):
lowercas... | 224 |
from pathlib import Path
import fire
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowercase__ = Path(SCREAMING_SNAKE_CASE_ )
lowercase__ = Path(SCREAMING_SNAKE_CASE_ )
dest_dir.mkdir(exist_ok=SCREAMING_SNAK... | 224 | 1 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def lowercase_ (A : Dict[str, torch.Tensor] ):
snake_case__ : List[str] = []
snake_case__ : str = []
snake_case... | 277 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFeat... | 277 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...te... | 290 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ = {
"configuration_deberta": ["DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaConfig", "DebertaOnnxC... | 290 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( ):
return 1
def __SCREAMING_SNAKE_CASE ( A_ ):
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __SCREAMING_SNAKE_CASE ( A_ ):
return 0 if x < 0 else five_pence(x - 5 ) + two_pence(A_ )
def __SCREAMING_SNAKE_CASE ( ... | 106 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCamelCase : Optional[Any] = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
... | 106 | 1 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import Config... | 351 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageI... | 12 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def A ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E_00 and cp <= 0X9F_FF)
or (cp >= 0X34_00 and cp <= 0X4D_BF) #
... | 36 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
... | 36 | 1 |
def A_ ( _lowerCAmelCase ) -> List[str]:
UpperCamelCase : Dict = len(_UpperCAmelCase )
UpperCamelCase : int = sum(_UpperCAmelCase )
UpperCamelCase : Any = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , ... | 351 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__lowerCamelCase : Dict = logging.get_logger("""transformers.models.speecht5""")
def A_ ( _lowerCAmelCase , _lowerCAmelCase ... | 140 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.