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 |
|---|---|---|---|---|
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : int = logging.get_logger(__name__)
_lowerCamelCase : str = {
'''google/realm-cc-news-pretrained-embedder''': (
'''https://huggingface.co/google/realm-cc-news-pretrained-em... | 282 |
import numpy as np
def a_ ( __lowercase : np.array ) -> np.array:
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod() | 282 | 1 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_ ): # noqa: E741
while r - l > 1:
_A : List[str] = (l + r) // 2
if v[m] >= key:
_A : Any = m
... | 363 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ort... | 343 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: int = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main... | 276 |
"""simple docstring"""
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... | 249 | 0 |
"""simple docstring"""
import qiskit
def _lowerCamelCase( a , a ):
__a = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantum Circuit acting on the q register
__a = qiskit.QuantumCircuit(lowerCAmelCase__ , lowerCAmelCase__ )
# App... | 366 | """simple docstring"""
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__:Tu... | 268 | 0 |
'''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,
norm... | 276 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class A__ ( UpperCAmelCase__ ):
__UpperCamelCase : str
__UpperCamelCase : int
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> li... | 276 | 1 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 364 |
def lowerCAmelCase_ ( __a ) -> str:
"""simple docstring"""
if isinstance(__a , __a ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(__a , __a ):
raise TypeError("'str' object cannot be interpreted as an integer" )
if ... | 273 | 0 |
'''simple docstring'''
import sys
a_ : Tuple = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043... | 75 | '''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__a = logging.get_logger(__name__)
class A__ ( UpperCamelCase ):
"""simple docstring"""
def __init__( self : Dict , *lo... | 145 | 0 |
"""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 (
... | 253 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingS... | 253 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
'''configuration_whisper''': ['''WHISPER_PRETR... | 97 |
"""simple docstring"""
from __future__ import annotations
__A = tuple[int, int, int]
__A = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
__A = """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""
# -------------------------- default selection -... | 293 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a (_lowerCAmelCase ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = ["image_processor", "tokenizer"]
__UpperCAmelCase : Optional[int] ... | 134 |
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase ):
return x if y == 0 else greatest_common_divisor(__lowerCamelCase , x % y )
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase ):
return (x * y) // greatest_common_divisor... | 134 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
fr... | 85 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from da... | 7 | 0 |
'''simple docstring'''
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils imp... | 357 |
'''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... | 240 | 0 |
'''simple docstring'''
from __future__ import annotations
_UpperCamelCase = 10
def lowercase_ ( lowerCAmelCase__ : Optional[int] ):
"""simple docstring"""
__UpperCAmelCase : Any = 1
__UpperCAmelCase : Optional[int] = max(low... | 254 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> Dict:
"""simple docstring"""
A__ = args.pruning_method
A__ = ar... | 14 | 0 |
import math
import os
import sys
def _UpperCamelCase ( snake_case__ ) -> str:
__UpperCAmelCase : Any = ""
try:
with open(snake_case__, "rb" ) as binary_file:
__UpperCAmelCase : str = ... | 342 | 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 ( _lowercase ):
def __init__( self: Optional[Any] , _... | 342 | 1 |
SCREAMING_SNAKE_CASE :Any = 256
# Modulus to hash a string
SCREAMING_SNAKE_CASE :Union[str, Any] = 100_0003
def UpperCAmelCase ( a_ , a_ ) -> bool:
"""simple docstring"""
__A = len(a_ )
__A = len(a_ )
if p_len > t_len:
... | 15 |
'''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
fr... | 56 | 0 |
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 :Dict = logging... | 329 |
import math
__a :Union[str, Any] = 10
__a :Union[str, Any] = 7
__a :int = BALLS_PER_COLOUR * NUM_COLOURS
def __snake_case ( __UpperCamelCase : int = 20 ):
"""simple docstring"""
A_ = math.comb(__UpperCamelCase ,__UpperCamelCase )
A_ ... | 329 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ :List[str] = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
try:
if not is_tokenizers_ava... | 101 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_comm... | 101 | 1 |
"""simple docstring"""
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa: F401
deprecate(
'stable diffusion controlnet',
'0.22.0',
'Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.... | 357 |
"""simple docstring"""
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from s... | 1 | 0 |
'''simple docstring'''
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_visi... | 93 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def UpperCamelCase_( _snake_case : Union[str, Any] ):
"""simple docstring"""
__a =[
'decoder.version',... | 218 | 0 |
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 FlaxMod... | 356 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
... | 34 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class UpperCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__... | 15 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__:int = logging.get_logger(__name__)
class snake_case__ ( snake_case_ ):
_snake_case : O... | 261 | 0 |
"""simple docstring"""
def snake_case (A_ :Any , A_ :Union[str, Any] , A_ :Any , A_ :Union[str, Any] ):
'''simple docstring'''
a : str = [False] * len(__UpperCAmelCase )
a : Any = []
queue.append(__UpperCAmelC... | 352 |
"""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 | 0 |
"""simple docstring"""
def __lowerCAmelCase (_UpperCamelCase ):
__lowerCAmelCase : Tuple = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def __lowerCAmelCase (_UpperCamelCase = 100 ):
__lowerCAmelCase : Optional[int] = 1
__low... | 86 |
"""simple docstring"""
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers impor... | 86 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
UpperCamelCase_ : List[str] = logging.get_logger(__name__)
class _a ( __lowerCAmelCase ):
def __init__( self ,*_SCREAMING_SNAKE_CAS... | 142 |
'''simple docstring'''
import pprint
import requests
UpperCamelCase_ : Tuple = '''https://zenquotes.io/api'''
def __a ( ) -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + "/today" ).json()
def __a ( ) ... | 142 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCAmelCase : List[str] = logging.get_logger(__name__)
class _A ( __magic_name__ , __magic_nam... | 253 |
import os
import numpy
import onnx
def A_ ( a , a ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = a.name
SCREAMING_SNAKE_CASE_ : Dict = b.name
SCREAMING_SNAKE_CASE_ : Optional[int] = ''
SCREAMING_S... | 253 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class a__ ( unittest.TestCase ):
def __SCREAMIN... | 370 | import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class a__ ( __snake_case ):
def __init__( self , UpperCAmelCase , UpperCAmelCase=None , UpperCA... | 197 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_fl... | 267 |
from __future__ import annotations
def __lowerCamelCase ( snake_case__ ,snake_case__ ) -> list[int]:
"""simple docstring"""
_SCREAMING_SNAKE_CASE = 0
_SCREAMING_SNAKE_CASE = len(snake_case__ ) - 1
while i < j:
... | 306 | 0 |
import warnings
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 = logging.get_logger(__name__)
_UpperCAmelCase = {
'''nv... | 371 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class _UpperCamelCase :
def __init__( self: str ) -> Any:
"""simple docstring"""
UpperCamelCase_ = ""
UpperCamelCase_ = "... | 328 | 0 |
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
_a = {
... | 39 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
_a = get_logger(__name__)
class __lowerCamelCase ( enum.Enum):
"""simple docstring"""
UpperCamelCase__ = ... | 39 | 1 |
"""simple docstring"""
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPP... | 11 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"funnel-transformer/small": "https://huggingface.co/funnel-transformer/small/resolve/main/config.json",
... | 11 | 1 |
'''simple docstring'''
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import dis... | 31 | '''simple docstring'''
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def UpperCamelCase_ ( _UpperCAmelCase : di... | 31 | 1 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
import sql... | 185 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def lowerCAmelCase__ ( a__: NDArray[floataa] , a__: NDArray[floataa] , a__: list[int] , a__: int , ) -> list[float]:
'''simple docstring'''
_Up... | 185 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( lowerCAmelCase__ : list[list[int]] ) -> int:
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first co... | 45 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : Union[str, Any] =["""image_processor""", """t... | 57 | 0 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
return int((input_a, input_a).count(0 ) != 0 )
def _lowercase ( ) -> None:
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ) == 1... | 56 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __a (UpperCamelCas... | 56 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def a ( lowerCamelCase__ ):
'''simple docs... | 206 |
'''simple docstring'''
import torch
from diffusers import StableDiffusionPipeline
lowerCamelCase :Tuple = '''path-to-your-trained-model'''
lowerCamelCase :Optional[int] = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')
lowerCamelC... | 206 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs
... | 355 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def a_ ( lowerCamelCase : str = "AAPL" ):
lowerCAmelCase = f'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
lowerCAmelCase = BeautifulSoup(requests.get(lowerCamelCase ... | 55 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 99 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determini... | 4 | 0 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ = TypeVar("""KEY""")
SCREAMING_SNAKE_CASE__ = TypeVar("""VAL""")
@dataclass(frozen=snake_case_ , slots=snake_case_ )
class __lowerCam... | 369 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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 BackboneTest... | 297 | 0 |
from math import isclose, sqrt
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ) -> tuple[float, float, float]:
__lowerCamelCase : Tuple = point_y / 4 / point_x
__lowerCamelCase : Tuple = 2 * normal_gradient / (1... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE_:str = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
"""tokenization_tr... | 116 | 0 |
"""simple docstring"""
snake_case_ = """Tobias Carryer"""
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Tuple , lowercase_ :Dict , lowercase_ :int , lowercase_ :Any , lowerca... | 363 |
"""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 | 0 |
import numpy
# List of input, output pairs
a_ = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
a_ = (((515, 22, 13), 555), ((61, 35, 49), 150))
a_ = [2, 4, 1, 5]
a_ = len(train_data)
a_ = 0.009
def _... | 340 |
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Im... | 340 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _A ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCas... | 48 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 48 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelera... | 140 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE :List[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 15 | 0 |
import datasets
_snake_case : Tuple = '\\n@InProceedings{conneau2018xnli,\n author = "Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n ... | 207 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
... | 207 | 1 |
"""simple docstring"""
from __future__ import annotations
class A_ :
'''simple docstring'''
def __init__( self , lowercase_ ):
"""simple docstring"""
UpperCAmelCase_ : Optional[Any] = order
# a_{0} ... a_{k}
UpperCAmelCase_ : Tuple = ... | 61 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class __lowerCAmelCase ( lowerCAmelCase_ ):
"""simple docstring"""
A__ : Any = '''EncodecFeatureExtractor'''
A__ : ... | 156 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : Any = {'configuration_mba... | 8 |
'''simple docstring'''
import re
def UpperCAmelCase ( lowerCamelCase_ :str ):
'''simple docstring'''
snake_case_ : List[Any] = re.compile(
R"""^(?:0|94|\+94|0{2}94)""" R"""7(0|1|2|4|5|6|7|8)""" R"""(-| |)""" R"""\d{7}$""" )
return bool(re.search(lowe... | 8 | 1 |
import os
import numpy
import onnx
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ ) -> Any:
_lowercase : Optional[Any] = a.name
_lowercase : Dict = b.name
_lowercase : List[str] = ''
_lowercase : ... | 21 |
import argparse
from collections import defaultdict
import yaml
_snake_case = "docs/source/en/_toctree.yml"
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Dict = defaultdict(_lowerCamelCase )
_lowerCAmelCase : Any ... | 36 | 0 |
from __future__ import annotations
import time
import numpy as np
_lowerCAmelCase : List[str] = [8, 5, 9, 7]
_lowerCAmelCase : List[str] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_lowerCAmelCase : List[Any] ... | 308 |
def UpperCamelCase_( _snake_case : str , _snake_case : int ):
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(_snake_case ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
... | 308 | 1 |
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 216 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : int ):
__a : int = int(number**0.5 )
return number == sq * sq
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCas... | 216 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"tanreinama/GPTSAN-2.8B-spout_is_uniform": (
"https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_u... | 98 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transfo... | 98 | 1 |
'''simple docstring'''
_A : int = 8.3_1_4_4_5_9_8
def UpperCamelCase_ ( snake_case_ : float , snake_case_ : float ) -> float:
'''simple docstring'''
if temperature < 0:
raise Exception("""Temperature cann... | 229 | '''simple docstring'''
def UpperCamelCase_ ( snake_case_ : list[int] , snake_case_ : list[int] ) -> tuple[float, float]:
'''simple docstring'''
if not len(snake_case_ ) == len(snake_case_ ) == 3:
raise ValueError("""Please enter ... | 229 | 1 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __magic_name__ ( a_):
A: List[str] = (UniPCMultistepSc... | 371 |
def _a ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
if principal <= 0:
raise Exception('''Principal borrowed must be > 0''' )
if rate_per_annum < 0:
raise Exception('''Rate of interest m... | 51 | 0 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ,... | 54 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A: str = {
"configuration_distilbert": [
"DISTILBERT_PRETRAI... | 109 | 0 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
_lowerCAmelCase = "\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Saura... | 98 |
'''simple docstring'''
import unittest
import numpy as np
from datasets import load_dataset
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, pre... | 98 | 1 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
__UpperCAmelCase : Optional[Any] = Path(__file__).resolve().parents[3] / "src"
sys.path.insert(1, str(git_repo_path))
import dataclasses ... | 111 |
import math
def A__ ( SCREAMING_SNAKE_CASE__) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number ... | 111 | 1 |
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 _snake_case ( _snake_case ):
SCREAMING_SNAKE_CAS... | 281 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
FEATURE... | 281 | 1 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_vision_available
f... | 101 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@re... | 341 | 0 |
"""simple docstring"""
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase_ = ... | 239 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
"microsoft/xprophetnet-large-wiki100-cased": (
"htt... | 239 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
__UpperCAmelCase = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
try:
if not is_torch_available(... | 299 |
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
UpperCAmelCase_ =["torch", "scipy"]
def __init__( self , *_A , **_A ) -> Tuple:
... | 299 | 1 |
'''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
lowerCAmelCase_ : Optional[int] = ... | 358 |
'''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_rob... | 170 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase_ : List[Any] = {
'google/switch-base-8': 'https://huggingface.co/google/switch-base-8... | 286 |
"""simple docstring"""
from copy import deepcopy
class _UpperCAmelCase :
'''simple docstring'''
def __init__( self , snake_case_ = None , snake_case_ = None ):
"""simple docstring"""
if arr is None and size is not None:
A_ : Union[st... | 286 | 1 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def _lowercase ( ) -> Optional[int]:
SCREAMING_SNAKE_CASE__ : Optional[Any] = [randint(-1000 , 1000 ) for i in range(10 ... | 360 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __a (metaclass=UpperCamelCase_):
'''simple docstring'''
_SCREAMING_SNAKE_CASE :Optional[Any] = ["""transformers""", """torch""", """note_seq"""]
def __init__( self , *_a , **_a ) ... | 56 | 0 |
'''simple docstring'''
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_d... | 272 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class snake_case ( __snake_case ):
# to overwrite at featu... | 217 | 0 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 359 |
'''simple docstring'''
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common... | 3 | 0 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase__ ( UpperCAmelCase__ ):
def __lt__( self : int , lowerCamelCase__ : ... | 234 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.... | 234 | 1 |
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 : Tuple = logging.get_logger(__name__)
__UpperCAmelCase : Any =... | 315 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
__UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
class UpperCAmelCase_ ( _a):
'''simple docstring'''
def __init__( self , ... | 315 | 1 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax i... | 155 |
"""simple docstring"""
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import To... | 155 | 1 |
"""simple docstring"""
def a__ ( __SCREAMING_SNAKE_CASE ) -> str:
__lowerCAmelCase: Tuple = []
__lowerCAmelCase: List[Any] = []
__lowerCAmelCase: List[str] = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
'''%''': 2,
'''+''': ... | 352 |
"""simple docstring"""
from math import ceil
def a__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) -> str:
__lowerCAmelCase: Tuple = list(range(0 , __SCREAMING_SNAKE_CASE ) )
__lowerCAmelCase: Optional[Any] = [item for sublist in list(de... | 108 | 0 |
"""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 LfsCommand... | 45 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowercase ( lowerCAmelCase__ : Namespace ) -> Tuple:
return ConvertCommand(
args.model_type , args.tf_checkpoint ... | 45 | 1 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
UpperCAmelCase__ : int = HfArgumentParser(InitializationArguments)
UpperCAmelCase__ : Union[str, Any] = parser.parse_ar... | 362 |
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCAmelCase__ : Any = '.'
# Internal TensorFlow ops tha... | 301 | 0 |
"""simple docstring"""
import argparse
import os
import re
_lowercase : str = "src/diffusers"
# Pattern that looks at the indentation in a line.
_lowercase : List[Any] = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase : int ... | 238 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
if b == 0:
return (1, 0)
((lowerCamelCase__) , (lowerCamelCase__)) : Any =extended_euclid(__lowerCamelCas... | 238 | 1 |
"""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, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils im... | 77 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class lowerCamelCase__ ( SC... | 77 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
a = logging.get_logger(__name__) # pylint: disable=invalid-name
class SCREAMING_... | 155 |
'''simple docstring'''
import string
def _lowercase ( __A ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__UpperCamelCase = """"""
for symbol in message:
if symbol in string.ascii_uppercase:
__UpperCamelC... | 349 | 0 |
"""simple docstring"""
import math
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : float ,_lowerCamelCase : float ) -> float:
if (
not isinstance(_lowerCamelCase ,(int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError(""... | 126 | """simple docstring"""
from ..utils import DummyObject, requires_backends
class __A ( metaclass=SCREAMING_SNAKE_CASE_ ):
_UpperCamelCase : Optional[Any] = ["sentencepiece"]
def __init__( self , *a__ , **a__ ):
requires_backends(self , ["""se... | 126 | 1 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowercase_ ( ):
SCREAMING_SNAKE_CASE__ : Optional[Any] = ArgumentParser(
... | 25 |
"""simple docstring"""
def lowercase_ ( _snake_case ,_snake_case ):
if not (isinstance(_snake_case ,_snake_case ) and isinstance(_snake_case ,_snake_case )):
raise ValueError("""longest_common_substring() takes two strings for inputs""" )
SCREAM... | 25 | 1 |
def _lowerCAmelCase ( __lowerCAmelCase ) -> bool:
"""simple docstring"""
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
if len(__lowerCAmelCase ) == 0:
raise Va... | 366 |
from sklearn.metrics import mean_squared_error
import datasets
A__ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel, M. and Prettenho... | 44 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/config.json''',
}
class _lowerCamelCase ( _lowercase ):
... | 186 |
'''simple docstring'''
from __future__ import annotations
def lowercase_ ( _lowercase ) -> list[int]: # This function is recursive
'''simple docstring'''
lowerCamelCase_ : Tuple = len(_lowercase )
# If the array contains only one element, we return it (it's the stop c... | 318 | 0 |
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
requi... | 81 | from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDiscreteScheduler... | 81 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.set_verbosity_info()
__lowercase... | 43 | import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
__lowercase = (720, 1280) # Height, Width
__lowercase = (0.4, 0.6) # if height or width lower than this scale, drop it.
__lowercase = 1 / 100
__lowercase ... | 43 | 1 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import T... | 355 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( _lowercase : list[list[int]] ) ->int:
'''simple docstring'''
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessi... | 79 | 0 |
def lowercase__ ( __snake_case : int ):
'''simple docstring'''
if n == 1 or not isinstance(__snake_case , __snake_case ):
return 0
elif n == 2:
return 1
else:
UpperCAmelCase_ : Tuple = ... | 29 |
def _a ( SCREAMING_SNAKE_CASE_ : int = 1_00_00_00 ):
__lowerCAmelCase = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , SCREAMING_S... | 92 | 0 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def UpperCAmelCase__ ... | 371 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
... | 101 | 0 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .datac... | 196 |
import math
def snake_case_ ( snake_case , snake_case ) -> float:
return math.pow(snake_case , 2 ) - a
def snake_case_ ( snake_case ) -> float:
return 2 * x
def snake_case_ ( snake_case ) -> float:
... | 196 | 1 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Dict = logging.get_logger(__name__)
_snake_case : int = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/conf... | 351 |
# 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... | 134 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase__ )
class SCREAMING_SNAKE_CASE__ ( UpperCAmelCase__ ):
# `task` is not a ClassVar since... | 109 |
"""simple docstring"""
from math import isqrt, loga
def _snake_case ( UpperCamelCase : int ):
UpperCAmelCase : Any = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , UpperCamelCase , UpperCamelCase ... | 109 | 1 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import Image... | 60 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE ... | 60 | 1 |
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_configuration_common import ConfigTes... | 20 |
"""simple docstring"""
from __future__ import annotations
from statistics import mean
def lowercase (_lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ):
__lowerCAmelCase = [0] * no_of_processes
__lowerCAmelCase = [0] * no_of_processes
# Initializ... | 301 | 0 |
"""simple docstring"""
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Any , lowercase_ : Union[str, Any] , lowercase_ : int , lowercase_ : Dict):
'''simple docstring'''
SCREAMING... | 367 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 318 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
lowe... | 2 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Tuple = logging.get_logger(__name__)
lowerCamelCase : Dict = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# S... | 2 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transfor... | 174 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCamelCase_ = {
'''configuration_trocr''': ['''TROCR_PRETRAINED_CONFIG_ARCHI... | 174 | 1 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
lowerCamelCase : int = logging.get_logger(... | 204 |
from typing import Any
def lowerCAmelCase_ ( __a , __a , __a , __a , __a , ) -> list:
"""simple docstring"""
_validation(
__a , __a , __a , __a , __a , )
# Creates data structures and fill initial step
lowerCamelCase__: dict ={}... | 10 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : Union[str, Any] ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
UpperCamelCase__ = len(UpperCamelCase__ )
UpperCamelCase__ = ... | 357 | from __future__ import annotations
lowercase = list[list[int]]
# assigning initial values to the grid
lowercase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0, 5... | 35 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : List[str] = logging.get_logger(__name__)
lowercase : int = {
'BridgeTower/bridgetower-base': 'https://h... | 3 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase : Union[str, Any] = logging.get_logger(__name__)
lowercase : str ... | 3 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if not ... | 19 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Any = {'''configuration_xglm''': ['''XGLM_PRETRA... | 19 | 1 |
"""simple docstring"""
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class A_ (unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase__ ( self ):
"""simple docstring"""
U... | 61 |
"""simple docstring"""
def __a ( __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
return round(float(moles / volume ) * nfactor )
def __a ( __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
return round(float((moles * 0.0821 * temperature) / (volume) ) )
def ... | 61 | 1 |
'''simple docstring'''
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logg... | 37 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 37 | 1 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
SCREAMING_SNAKE_CASE__ : str = importlib.util.find_spec("s3fs") is not None
if _has_safs:
from .safilesys... | 270 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCAmelCase__ :
def __init__( self : Any , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> Dict:
... | 270 | 1 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class a ( unittest.TestCase ):
def lowerCAmelCase_ ( self : List[Any] ):
_UpperCAmelCase = 10
def lowerCAme... | 363 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
UpperCAmelCase__ = logging.get_logger(__name__)
class a ( lowerCAmelCase_ ):
_snake_case : List[str] ... | 30 | 0 |
def __magic_name__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ) -> int:
while b:
__lowerCamelCase , __lowerCamelCase = b, a % b
return a
def __magic_name__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ) -> int:
return ... | 270 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
SCREAMING_SNAKE_CASE__ : Union[str, Any] = re.compile(r"\b(a|an|the)\b", re.UNICODE)
SCREAMING_SNAKE_CASE__ : int = None
def __magic_name__ ( ) -> str:
_... | 270 | 1 |
"""simple docstring"""
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteS... | 291 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __snake_ca... | 291 | 1 |
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