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__ ( A_ ):
'''simple docstring'''
__magic_name__ = 0
__magic_name__ = len(A_ )
for i in range(n - 1 ):
for j in range(i + 1, A_ ):
if arr[i] > arr[j]:
num_inversions += 1
return num_inversions
... | 88 |
"""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 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
'''facebook/xlm-roberta-xl''': '''https://h... | 211 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def lowerCamelCase_ ( _a , _a ):
"""simple docstring"""
lowerCAmelCase__ : List[... | 211 | 1 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
lowerCAmelCase : str = """
import os
"""
lowerCAmelCase : Optional[Any] = """
def foo():
import os
return False
"""
lowerCAmelCase : str = """
def foo():
def bar():
... | 13 | """simple docstring"""
import unittest
from transformers import DebertaVaConfig, 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 import ModelTes... | 44 | 0 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
cl... | 369 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : str = 0
__lowerCamelCase : Tuple = len(SCREAMING_SNAKE_CASE__ )
for i in range(n - 1 ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE__ ):
if arr[i] > arr[j]:
num_inversions +=... | 194 | 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
_UpperCamelCase : str = logging.get_logger(__name__)
_UpperCamelCas... | 77 | """simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCAmelCase_ :
def __init__( self , a ) -> List[str]:
if isinstance(a ... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
__A = (3, 9, -11, 0, 7, 5, 1, -1)
__A = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class snake_case :
SCREAMING... | 108 |
"""simple docstring"""
def a__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) -> int:
return int((input_a, input_a).count(0 ) == 0 )
def a__ ( ) -> None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0... | 108 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def UpperCamelCase__ ( lowerCAmelCase ):
"""simple docstring"""
if "model" in orig_key:
_lowerCAmelCase = orig_key.... | 70 |
"""simple docstring"""
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def _SCREAMING_SNAKE_CASE ( _lowercase : List[Any] , _lowercase : int ) ->str:
... | 105 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, require_t... | 305 | import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCamelCase (SCREAMING_SNAKE_CASE__ ):
""... | 305 | 1 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class lowercase ( __a ):
_SCREAMING_SNAKE_CASE = ['''image_processor''', '''tokenizer''']
_SCREAMING_SNAKE_CASE = '''AutoImagePro... | 46 |
from maths.prime_check import is_prime
def snake_case_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : Dict = F"Input value of [number={number}] must be an integer"
raise TypeError(lower... | 233 | 0 |
'''simple docstring'''
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
if not arr:
return None, None, 0
... | 236 |
'''simple docstring'''
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, loggin... | 236 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class a__ :
"""simple docstring"""
__lowerCamelCase = 42
__lowerCamelCase = None
__lowerCamelCas... | 68 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import Re... | 301 | 0 |
def A_ ( A__ , A__ ) -> str:
if not isinstance(A__ , A__ ):
raise ValueError('iterations must be defined as integers' )
if not isinstance(A__ , A__ ) or not number >= 1:
raise ValueError(
'starting number must be\n ... | 225 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
lowercase : Optional[Any] = """"""
lowercase : int = """"""
lowercase : List[Any] = """"""
lowercase : Optional[int] = 1 # (0 is vertical, 1 is horizontal)
def... | 225 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 47 |
'''simple docstring'''
class A__ :
def __init__( self : Union[str, Any] , _a : int ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =size
_SCREAMING_SNAKE_CASE =[0] * size
_SCREAMING_SNAKE_CASE =[0] * ... | 47 | 1 |
_UpperCamelCase: List[str] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_UpperCamelCase: List[Any] = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_UpperCamelCase: Any = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
... | 361 |
"""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, ImageInput, ... | 53 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__( UpperCAmelCase ):
"""simple do... | 30 |
"""simple docstring"""
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCAmelCase_ ( snake_case_ : Dict , snake_case_ : str , snake_case_ : str ,... | 126 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from fl... | 85 | """simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 85 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassific... | 165 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A_ : ... | 165 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
A_ : Tuple = logging.get_logge... | 141 |
from __future__ import annotations
def UpperCamelCase (lowercase_: list[int] , lowercase_: list[int] , lowercase_: int ) -> tuple[float, list[float]]:
A__ : Tuple = list(range(len(lowercase_ ) ) )
A__ : Union[str, Any] = [v / w for v, w in zip(lo... | 141 | 1 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql # noqa F401
f... | 262 |
def lowerCAmelCase ( lowerCAmelCase_ )-> set:
lowerCAmelCase_ : Optional[int] = set()
# edges = list of graph's edges
lowerCAmelCase_ : List[str] = get_edges(lowerCAmelCase_ )
# While there are still elements in edges list, take an arbitrary ed... | 262 | 1 |
"""simple docstring"""
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def snake_case (A_ :List[str] ):
'''simple docstring'''
a : str = {}
a : str = job['started_at']
a : Tuple ... | 186 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_UpperCamelCase : List... | 186 | 1 |
"""simple docstring"""
import os
def UpperCAmelCase ( ) -> Union[str, Any]:
with open(os.path.dirname(UpperCAmelCase ) + '/p022_names.txt' ) as file:
snake_case_ = str(file.readlines()[0] )
snake_case_ = names.replace('"' ... | 69 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
lowerCAmelCase_ = {
'configuration_speecht5': [
'SPEECHT5_PRETRAINED_C... | 16 | 0 |
def _lowercase ( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ ) -> List[str]:
'''simple docstring'''
if index == r:
for j in range(UpperCamelCase_ ):
print(data... | 369 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _lowercase ( UpperCamelCase_ ) -> bool:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = int(number**0.5 )
return number == sq * sq
def _lowercase ... | 169 | 0 |
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def __UpperCamelCase ( _lowerCAmelCase=None ... | 116 |
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
SCREAMING_SNAKE_CASE_:List[Any] = """▁"""
SCREAMING_SNAKE_CASE_:int = {"""vo... | 116 | 1 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __lowerCamelCase ( unittest.TestCase ):
"""simple docstring"""
def a ( self : List[Any] ) -> N... | 221 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
snake_case__ = "Speech2TextFeatureExtractor"
snake_case__ = "Speech2TextTokenizer"
... | 221 | 1 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
_snake_case = pd.read_csv("sample_data.csv", header=None)
_snake_case = df.shape[:1][0]
... | 36 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxMode... | 299 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
SCREAMING_SNAKE_CASE : Optional[Any] = {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_... | 24 |
"""simple docstring"""
def lowercase ( ) ->int:
"""simple docstring"""
return [
a * b * (1_000 - a - b)
for a in range(1 , 999 )
for b in range(_snake_case , 999 )
if (a * a + b * b == (1_000 - a - b) ** 2)
][0]
if __name__ == "__main__":
p... | 24 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCamelCase : str = {
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'PoolFormerConfig',
... | 258 |
'''simple docstring'''
def __a ( UpperCAmelCase , UpperCAmelCase ) ->int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def __a ( ) ->None:
"""simple docstring"""
assert or_gate(0 , 0 ) == 0
assert or_gate(0 ... | 258 | 1 |
import logging
from transformers.configuration_utils import PretrainedConfig
_snake_case = logging.getLogger(__name__)
class lowercase ( lowerCAmelCase_ ):
_a = 'masked_bert'
def __init__( self , _a=3_0522 , _a=768 , _a=12 , _a=12 , _... | 358 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...t... | 343 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
__UpperCAmelCase =logging.getLogger(__name__)
def __lowerCAmelCase ( ) -> int:
__lowerCamelCase = argparse.ArgumentParser(
descri... | 67 |
"""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... | 109 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def a__ ( UpperCAmelCase : list , UpperCAmelCase : list , UpperCAmelCase : list , UpperCAme... | 99 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import ... | 99 | 1 |
"""simple docstring"""
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, ... | 78 |
"""simple docstring"""
import requests
snake_case_ = """""" # <-- Put your OpenWeatherMap appid here!
snake_case_ = """https://api.openweathermap.org/data/2.5/"""
def _lowerCAmelCase ( lowercase_ = "Chicago" , lowercase_ = APPID ):
return requests.ge... | 78 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils i... | 250 |
from __future__ import annotations
from math import pi, sqrt
def _a ( lowerCamelCase: float , lowerCamelCase: float ) -> tuple:
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be ... | 250 | 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
def _SCREAMING_SN... | 186 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""t5-small""": """https://huggingface.co/t5-small/resolve/main/config.json"... | 186 | 1 |
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_camembert import ... | 370 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def lowerCamelCase_ ( lowerCamelCase__ , lowerCamelCase__=False ):
lowerCamelCase_ = OmegaConf.load(lowerCamelCase__ )
if display:
print(yaml.dump(Omega... | 47 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...util... | 15 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 324 | 0 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from... | 367 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in... | 280 | 0 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table imp... | 200 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_ava... | 200 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : Dict = ['image_processor', 'tokenizer']
lowerCamelCase__... | 316 |
"""simple docstring"""
from __future__ import annotations
import queue
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any] = data
lowerCamelCase__ : ... | 316 | 1 |
class _SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__(self : Any , UpperCAmelCase_ : str = "" , UpperCAmelCase_ : bool = False) ->None:
'''simple docstring'''
lowerCamelCase__: dict[str, RadixNode] ={}
# A node will be a leaf ... | 10 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
UpperCamelCase__: Union[str, Any] = "examples/"
UpperCamelCase__: Optional[Any] = {
"examples": (re.compile(r"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_ve... | 23 | 0 |
def __lowerCamelCase ( ):
'''simple docstring'''
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = 1
snake_case_ ... | 370 |
from math import sqrt
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = 0
for i in range(1 , int(sqrt(UpperCamelCase__ ) + 1 ) ):
if n % i == 0 and i != sqrt(UpperCamelCase__ ):
... | 200 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : Dict = logging.get_logger(__name__)
UpperCAmelCase__ : int = {
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrai... | 245 |
import os
import pytest
from attr import dataclass
UpperCAmelCase__ : Optional[int] = """us-east-1""" # defaults region
@dataclass
class a__ :
"""simple docstring"""
UpperCAmelCase__ : str
UpperCAmelCase__ : Union[str, ... | 245 | 1 |
"""simple docstring"""
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 t... | 359 |
"""simple docstring"""
import os
from collections.abc import Iterator
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str = "." ):
for dir_path, dir_names, filenames in os.walk(_UpperCAmelCase ):
lowerCAmelCase = [d for d in dir_names if d != 'scripts' and d[0] not in '._']
for filename in ... | 309 | 0 |
"""simple docstring"""
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_=1024 , UpperCamelCase_=1024 ,... | 100 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class snake_case ( ctypes.Structure ):
'''simple docstring'''
A_ : List[str] = [("... | 266 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
'''configuration_x_clip''': [
'''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XCLIPConfig''',
'''XCLIPTextCo... | 354 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase = logging.get_logge... | 184 | 0 |
"""simple docstring"""
from typing import Dict, Optional
import numpy as np
import datasets
SCREAMING_SNAKE_CASE__ = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binar... | 46 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for... | 46 | 1 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def lowerCAmelCase_ ( snake_case_ : Optional[int] ) -> O... | 371 | '''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditiona... | 106 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json',
}
class __lo... | 160 |
'''simple docstring'''
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase__ : Union[str, Any] = HUGGINGFACE_HUB_CACHE
lowercase__ : int = 'config.json'
lowercase__ : Optional[int] = 'diffusion_pytorch_model.bin'
lowe... | 324 | 0 |
'''simple docstring'''
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def UpperCAmelCase_ (__a : BertModel , __a : str , __a : str ):
"""simple docstring"""
_a : Optional[Any] = ... | 363 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
__lowerCAmelCase = """docs/source/en/_toctree.yml"""
def UpperCAmelCase_ (__a : str ):
"""simple docstring"""
_a : Any = defaultdict(__a )
for doc in model_doc:... | 5 | 0 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
__snake_case = 637_8137.0
__snake_case = 635_6752.31_4245
__snake_case = 6378137
def a ( __a , __a , __a , __a ) -> floa... | 97 | """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, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decode... | 135 | 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 timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 89 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( A__ : int | float | str , A__ : int | float | str ):
'''simple docstring'''
if nth_term == "":
return [""]
lowerCAmelCase_ : str = i... | 89 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class lowerCAmelCase_ :
"""simple docstring"""... | 25 |
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 OptionalDependencyNotAvail... | 262 | 0 |
'''simple docstring'''
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... | 368 |
'''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_to_tf ... | 136 | 0 |
'''simple docstring'''
from graphs.minimum_spanning_tree_kruskal import kruskal
def _A ( ):
"""simple docstring"""
__lowercase =9
__lowercase =[
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
... | 166 |
'''simple docstring'''
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, BlipaProc... | 166 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ : str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 339 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, Fl... | 339 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCamelCase : Tuple = logging.get_logger(__name__)
_lowerCamelCase : An... | 28 | '''simple docstring'''
import math
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
lowercase_ : List[Any] = F'''Input value of [number={number}] must be an integer'''
... | 239 | 0 |
def A ( _UpperCAmelCase : list[int] , _UpperCAmelCase : list[int] ) -> tuple[float, float]:
'''simple docstring'''
# Check if the input is valid
if not len(_UpperCAmelCase ) == len(_UpperCAmelCase ) == 3:
raise ValueError('Please enter a... | 360 |
import argparse
import os
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_task_guides.py
UpperCAmelCase__ = "src/transformers"
UpperCAmelCase__ = "docs/source/en/ta... | 290 | 0 |
'''simple docstring'''
from ....utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
class lowercase_ ( a__ ):
def __init__( self , a , a=None , a=20_48 ):
UpperCamelCase__ = config.__dict__
UpperC... | 80 |
'''simple docstring'''
from math import factorial, pi
def _UpperCamelCase ( __A , __A = 30 ) -> float:
'''simple docstring'''
if not isinstance(__A , (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or float for t... | 80 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
... | 280 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm"... | 280 | 1 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def snake_case ( A__ ):
return getitem, k
def snake_case ( A__ ,A__ ):
return setitem, k, v
def snake_case ( A__ ):
... | 268 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...t... | 301 | 0 |
import os
from math import logaa
def lowerCamelCase__ ( A__ : str = "base_exp.txt" ):
'''simple docstring'''
__lowerCamelCase = 0
__lowerCamelCase = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(A__ ) , A__ ) )... | 29 |
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ ( A__ : str = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
__lowerCamelCase = BeautifulSoup(requests.get(A__ ).text , """html.parser""" )
__lowerCamelCase ... | 29 | 1 |
"""simple docstring"""
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class snake_case ( __snake_case, unittest.TestCase ):
SCREAMING_SNAKE_CASE_ ... | 217 |
"""simple docstring"""
from __future__ import annotations
def a__ ( __SCREAMING_SNAKE_CASE ) -> bool:
__lowerCAmelCase: Tuple = str(__SCREAMING_SNAKE_CASE )
return len(__SCREAMING_SNAKE_CASE ) == 9 and set(__SCREAMING_SNAKE_CASE ) == set("123456789" )
... | 217 | 1 |
"""simple docstring"""
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
__A = logging.get_logger(__name__)
class _snake_case ... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value must be an 'int' type" )
__lowerCamelCase : Dict = 0
... | 64 | 1 |
"""simple docstring"""
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
_a = 50_0000
_a , _a = os.path.split(__file__)
_a = os.path.join(RESULTS_BASEPATH... | 194 |
"""simple docstring"""
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def lowerCamelCase__ ( __snake_case ) -> Tuple:
"""simple ... | 194 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __A ( A_ ):
'''simple docstring'''
lowerCAmelCase : List[Any] = ["image_processor", "tokeni... | 302 |
"""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(... | 302 | 1 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class UpperCAmelCase_ ( unittest.TestCase , _lowercase ):
'''simple docstring'''
def _A ( self ):
'''simple docstring'''
__SCREAMING_SN... | 257 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # n... | 153 | 0 |
'''simple docstring'''
def _a ( _lowercase : str , _lowercase : str ):
'''simple docstring'''
__UpperCAmelCase : int = len(_lowercase )
__UpperCAmelCase : int = len(_lowercase )
__UpperCAmelCas... | 359 |
'''simple docstring'''
from __future__ import annotations
__UpperCAmelCase :Tuple = "Muhammad Umer Farooq"
__UpperCAmelCase :Tuple = "MIT"
__UpperCAmelCase :Union[str, Any] = "1.0.0"
__UpperCAmelCase :Optional[int] = "Muhammad Umer F... | 240 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase : List[Any] = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig""", """Visio... | 20 |
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** ... | 36 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_SCREAMING_SNAKE_CASE )
class a ( _SCREAMING_SNAKE_CASE ):
# `task` is not a Cl... | 104 |
'''simple docstring'''
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 AutoImageProcessor, ViTImageProcessor
from transform... | 104 | 1 |
"""simple docstring"""
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class _SCREAMING_SNAKE_CASE :
def __lowerCAmelCase ( self , __A ) -> int:
raise No... | 84 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCa... | 323 | 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.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # n... | 345 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[str] , Uppe... | 345 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Tuple = [0 for i in range(len(SCREAMING_SNAKE_CASE ) )]
# initialize interval's left pointer and right pointer
__UpperCamelCase , __UpperCamelCase :str = 0, 0
for i in range(1 ... | 43 |
def lowerCamelCase__ ( a ) -> bool:
_A: Dict = [int(a ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(a ) == 4 and all(0 <= int(a ) <= 2_54 for octet in octets )
if __name__ == "__main__":
UpperCAmelCase__ : str = ... | 121 | 0 |
import os
import re
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
a__ = logging.get_logger(__name__)
a__ = {'''vocab_file''': '''spie... | 15 |
from __future__ import annotations
def __UpperCAmelCase ( __a : list ) -> float:
"""simple docstring"""
if not nums:
raise ValueError('''List is empty''' )
return sum(__a ) / len(__a )
if __name__ == "__main__":
import do... | 15 | 1 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
_lowerCAmelCase : int = ... | 218 |
from ... import PretrainedConfig
_lowerCAmelCase : Any = {
"sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class __magic_name__ ( lowerCAmelCase_ ):
SCREAMING_SNAKE_CASE = NEZHA_PRETRAINED_CONFIG_AR... | 218 | 1 |
def UpperCamelCase__( UpperCamelCase__ : dict )->set:
A__ = set()
# edges = list of graph's edges
A__ = get_edges(UpperCamelCase__ )
# While there are still elements in edges list, take an arbitrary edge
# (from_node, to_node) and a... | 39 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a__: Union[str, Any] = False
class SCREAMING_SNAKE_CASE_... | 39 | 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 __snake_case ( a ):
def __init__( self : ... | 51 |
from datetime import datetime
import requests
def A (__A : str ) -> bytes:
"""simple docstring"""
UpperCAmelCase_ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
UpperCAmelCase_ = r... | 51 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
f... | 180 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class a__ ( pl.LightningModule ):
def __init__( self , A ) -> Optional[Any]:
'''simple docstring'''
... | 180 | 1 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class _UpperCamelCase :
"""simple docstring"""
__a : str = field(
metadata={'... | 210 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : str = logging.get_logger(__name__)
__a : int = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
# See all W... | 210 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin... | 370 |
"""simple docstring"""
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class _Up... | 86 | 0 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_swit... | 10 | '''simple docstring'''
def __lowerCAmelCase ( UpperCamelCase__ = 1_00_00_00 ) -> int:
__lowerCamelCase = set(range(3 , UpperCamelCase__ , 2 ) )
primes.add(2 )
for p in range(3 , UpperCamelCase__ , 2 ):
if p not in primes:
continue
pri... | 67 | 0 |
'''simple docstring'''
import argparse
import struct
import unittest
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Any , _lowerCamelCase : bytes ):
"""simple docstring"""
A_ : Dict = ... | 361 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 4 | 0 |
from __future__ import annotations
import requests
lowerCAmelCase__ : Any = set(
'''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_... | 143 | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 143 | 1 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils imp... | 203 | """simple docstring"""
import math
def __a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->Optional[int]:
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(_SCREAMING_SNAKE_CASE )
else:
if x == 0: # 0 ... | 203 | 1 |
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, require... | 281 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : Dict = logging.get_logger(__name__)
snake_case : Union[str, Any] = {
"vocab_file": "vocab.txt",
... | 281 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
resca... | 363 |
"""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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassificatio... | 248 | 0 |
"""simple docstring"""
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
__A = 4
__A = 3
class snake_case ( __sna... | 217 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization... | 217 | 1 |
"""simple docstring"""
import math
def lowercase__ ( _UpperCAmelCase ) -> int:
'''simple docstring'''
if not isinstance(_UpperCAmelCase , _UpperCAmelCase ):
lowercase : Optional[Any] = f'''Input value of [number={n... | 357 |
"""simple docstring"""
def lowercase__ ( _UpperCAmelCase ) -> list:
'''simple docstring'''
lowercase : Dict = len(_UpperCAmelCase )
for i in range(1 , _UpperCAmelCase ):
lowercase : Union[str, Any] = ... | 53 | 0 |
"""simple docstring"""
_a : Tuple = 'Input must be a string of 8 numbers plus letter'
_a : Optional[int] = 'TRWAGMYFPDXBNJZSQVHLCKE'
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : str ) -> bool:
if not isinstance(_lowerCamelCase ,_lowerC... | 44 | """simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertE... | 44 | 1 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is... | 352 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion import Stabl... | 265 | 0 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class __snake_case ( unittest.TestCase , A__ ... | 20 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __UpperCAmelCase ( unittest.TestCase ):
'''simple d... | 258 | 0 |
def _lowerCAmelCase ( A__: int ):
'''simple docstring'''
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def _lowerCAmelCase ( A__: int ):
'''simple docstring'''
UpperCAmelCase = 0
UpperCAmelCase ... | 152 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _lowerCAmelCase ( A__: str , A__: List[str] , A__: str ):
'''simple docstring''... | 152 | 1 |
from __future__ import annotations
def _a ( UpperCAmelCase , UpperCAmelCase ) -> tuple[int, int]:
"""simple docstring"""
if b == 0:
return (1, 0)
((lowerCamelCase__) , (lowerCamelCase__)) : str = extended_euclid(UpperCAmelCase , a... | 142 |
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def _a ( UpperCAmelCase ) -> str:
"""simple docstring"""
lower... | 142 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 143 | from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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, random_attention_mas... | 143 | 1 |
"""simple docstring"""
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__A : str = 299_792_458
# Symbols
__A : Union[str, Any] = symbols('''ct x y z''')
def lowercase ( __snake_case ... | 33 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : Dict = {
"t5-small": "https://huggingface.co/t5-small/resolve... | 114 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a =logging.get_logger(__name__)
a ={
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json""",
# See all AltCLIP models at https://h... | 358 |
# 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 ... | 113 | 0 |
'''simple docstring'''
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.sp... | 166 |
'''simple docstring'''
from datetime import datetime
import requests
def _A ( _lowerCAmelCase ):
"""simple docstring"""
__lowercase ='https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
__lowercase =requests.get(base_url + url ).json()... | 166 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require... | 289 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : int = int(num... | 289 | 1 |
"""simple docstring"""
from math import factorial
_lowercase = {str(d): factorial(d) for d in range(10)}
def _snake_case ( snake_case__ : int ):
return sum(DIGIT_FACTORIAL[d] for d in str(snake_case__ ) )
def _snake_case ( ):
A = 7 * factorial(9... | 74 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax... | 242 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : Tuple = {'configuration_reformer': ['REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 353 |
from __future__ import annotations
import time
import numpy as np
_UpperCAmelCase = [8, 5, 9, 7]
_UpperCAmelCase = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_UpperCAmelCase = [
[3, 2, 1, 4],
[0, 2,... | 232 | 0 |
"""simple docstring"""
def A_ ( _lowercase = 100 ):
'''simple docstring'''
snake_case_ :Dict = set()
snake_case_ :Tuple = 0
snake_case_ :Optional[int] = n + 1 # maximum limit
for a in range(2, _lowercase ):
for b in range(2, _... | 66 |
import argparse
import json
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... | 38 | 0 |
from importlib import import_module
from .logging import get_logger
lowerCamelCase__ = get_logger(__name__)
class A__ :
def __init__( self : Dict , a : Optional[Any] , a : Any=None ):
'''simple docstring'''
... | 356 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
OpenAIG... | 307 | 0 |
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