code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def _a ( __lowercase = 200_0000 ) -> int:
"""simple docstring"""
__UpperCamelCase = [0 for i in range(n + 1 )]
__UpperCamelCase = 1
__UpperCamelCase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if prima... | 383 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class lowerCAmelCase_ ( _lowercase , _lowercase ):
"""simple docstrin... | 383 | 1 |
from __future__ import annotations
UpperCAmelCase__ = "#"
class __lowerCAmelCase :
def __init__( self : Union[str, Any]) -> None:
"""simple docstring"""
_UpperCAmelCase = {}
def _lowerCamelCase ( self : List[Any] , A :... | 639 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_xlnet impo... | 639 | 1 |
from maths.prime_check import is_prime
def a_ ( __magic_name__ ) -> Optional[Any]:
"""simple docstring"""
if not isinstance(__magic_name__ , __magic_name__ ):
snake_case : Union[str, Any] = F"Input value of [number={number}] m... | 598 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
fro... | 531 | 0 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def lowerCAmelCase_ ( __lowerCamelCase ):
if not is_accelerate_available():
return method
__snake_case : int = versi... | 203 |
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... | 203 | 1 |
def a_ (__A , __A , __A , __A ) -> int:
"""simple docstring"""
__a , __a : Any = len(__A ), len(grid[0] )
if (
min(__A , __A ) < 0
or row == row_length
or col == col_length
... | 351 |
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
fro... | 351 | 1 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, i... | 188 |
_UpperCAmelCase : List[Any] = {
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""zettametre""": """Zm""",
"""yottametre"""... | 188 | 1 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class _lowercase ( nn.Module ):
... | 696 |
import json
import os
import shutil
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 AutoConfig, BertConfig, GPTaConfig
from transformers.configuratio... | 696 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__: Any = logging.get_logger(__name__)
A__: List[str] = {
'''xlm-mlm-en-2048''': '''https:/... | 716 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from... | 506 | 0 |
def __SCREAMING_SNAKE_CASE ( a__ : list ,a__ : list ,a__ : int ,a__ : int ,a__ : int ) -> int:
if index == number_of_items:
return 0
__A : Optional[int] = 0
__A : List[Any] = 0
__A : int = knapsack(a__ ,a__ ,a__ ,a__ ,... | 17 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['torch', 'transformers', 'onnx']
def __init__( self: Union[str, Any]... | 293 | 0 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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 applica... | 701 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_a... | 267 | 0 |
"""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, PreTrained... | 34 |
'''simple docstring'''
from math import pi
def _lowerCAmelCase (_lowercase , _lowercase ):
"""simple docstring"""
return 2 * pi * radius * (angle / 3_60)
if __name__ == "__main__":
print(arc_length(90, 10))
| 331 | 0 |
'''simple docstring'''
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def __UpperCAmelCase ( __magic_name__ )-> Tuple:
"""simple docstring"""
snake_case_ : Union[str, Any] = ar... | 721 |
'''simple docstring'''
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, ... | 656 | 0 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
lowercase_ = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
lowercase_ = "\nArgs:... | 695 |
"""simple docstring"""
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase ( lowerCAmelCase__ : Any , lowerCAmelCase__ : Li... | 695 | 1 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowerCAmelCase ( datasets.BeamBasedBuilder ):
def lowercase ( self ):
return datase... | 709 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGEN... | 29 |
import sys
_a : Any = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'66896648950445244523161... | 598 | 0 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
_a ... | 78 |
"""simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
_a = [
# (stable-diffusion, HF Diffusers)
("""time_embed.0.weight""", "... | 78 | 1 |
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
__a = logging.get_logger(__name__)
__a = {'''vocab_file''': '''sentencepiece.bpe.mode... | 319 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
@require_torch
... | 319 | 1 |
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class __A ( a ):
__A = """MCTCTFeatureExtractor"""
__A = """AutoTokenizer"""
def __init__( self , UpperCAmelCase_ , UpperCAmelCase_ ):
super().... | 269 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
UpperCAmelCase__ : List[Any] =list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
UpperCAmelCase__ : Dict ... | 269 | 1 |
'''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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligne... | 527 |
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_common import OnnxPipelineTe... | 25 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def __magic_name__ ( lowercase ) -> Optional[int]:
"""simple docstring"""
lowercase_ : ... | 721 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase_ = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig"""... | 436 | 0 |
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerT... | 146 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowercase ( _UpperCamelCase , unittest.... | 146 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_a... | 305 |
'''simple docstring'''
import tensorflow as tf
from ...tf_utils import shape_list
class _snake_case ( tf.keras.layers.Layer ):
"""simple docstring"""
def __init__( self : Optional[int] , UpperCamelCase_ : Optional[Any] , UpperCamelCase_ : Any , UpperCamel... | 305 | 1 |
from collections.abc import Callable
class SCREAMING_SNAKE_CASE_ :
'''simple docstring'''
def __init__( self : Tuple , SCREAMING_SNAKE_CASE__ : Callable | None = None ) -> None:
# Stores actual heap items.
A : list =[]
... | 305 | from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class SCREAMING_SNAKE_CASE_ ( nn.Module ):
'''simple docstring'''
def __init__( self : Union[str, Any] , SCREAMING_SNAKE_CASE__ : ... | 305 | 1 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
__UpperCAmelCase : str = "https://www.indeed.co.in/jobs?q=mobile+app+development&l="
def A__ ( SCREAMING_SNAKE_CASE__ = "mumbai") -> Generator[tup... | 707 |
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def A__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__) ... | 155 | 0 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
_snake_case = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, required=True, help="Path t... | 500 |
def A ( _lowerCamelCase ):
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
_lowerCAmelCase : Union[str, Any] = F"Input value of [number={number}] must be an integer"
raise TypeError(_lowerC... | 500 | 1 |
"""simple docstring"""
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowercase__ = datasets.load_iris()
lowercase__ = np.array(data['data'])
lowercase__ = np.array(data['target'])
lowercase__ = data... | 709 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
'facebook/s2t-small-librispeech-asr': (
'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json'
... | 217 | 0 |
from __future__ import annotations
from math import pow, sqrt
def lowerCamelCase_ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueError("One and only one argument must be 0" ... | 463 |
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 ...test_... | 463 | 1 |
"""simple docstring"""
from random import shuffle
import tensorflow as tf
from numpy import array
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase , __lowerCAmelCase ) -> Union[str, Any]:
'''simple docstring'''
lowercase_ = int(__lowerCAmelCase )
... | 712 |
"""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,
)
UpperCAmelCase : Any = {... | 100 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Dict = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
"confi... | 261 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import LEDConfig, 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
from ..... | 261 | 1 |
from collections import deque
def snake_case__ ( lowerCamelCase_ ):
A : Any = len(lowerCamelCase_ )
A : Union[str, Any] = deque()
A : Any = [False for _ in range(lowerCamelCase_ )]
A : Any = [-1 for _ in... | 719 |
def snake_case__ ( lowerCamelCase_ , lowerCamelCase_ ):
A : Optional[int] = len(lowerCamelCase_ )
A : List[Any] = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed by not taking an... | 423 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
_A = logging.get_logger(__name__)
_A... | 431 |
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=UpperCamelCase__ ):
lowerCamelCase__ = ['torch', 'torchsde']
def __init__( self , *snake_case_ , **snake_case_ ) -> Optional[int]:
requires_backends(se... | 258 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase__ : Any = {
"""configuration_roc_bert""": ["""ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RoCBertConfig"""],
"""tokenizati... | 708 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def A_( A , A ):
assert isinstance(A , A )
a... | 486 | 0 |
'''simple docstring'''
UpperCamelCase__ : Any = {
'''Pillow''': '''Pillow<10.0.0''',
'''accelerate''': '''accelerate>=0.20.3''',
'''av''': '''av==9.2.0''',
'''beautifulsoup4''': '''beautifulsoup4''',
'''black''': '''black~=23.1''',
'''codecarbon''': '''codecarbon==1.2.0... | 578 |
'''simple docstring'''
import math
def lowerCAmelCase_ ( _lowerCamelCase: int ):
__SCREAMING_SNAKE_CASE : Dict = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(_lowerCamelCase )
def lowerCAmelCase_ ( _lowerCame... | 578 | 1 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_lowerCAmelCase = False
try:
_lowerCAmel... | 710 |
'''simple docstring'''
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _SCREAMING_SNAKE_CASE ... | 160 | 0 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
__snake_case : Tuple = '''\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitl... | 660 |
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_ = {
"facebook/maskformer-swin-base-ade": (
"https://huggi... | 151 | 0 |
"""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
lowercase__ :int ... | 708 |
"""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_uti... | 374 | 0 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Efficie... | 343 |
import math
import sys
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ) -> str:
'''simple docstring'''
lowerCAmelCase : str = ''
try:
with open(_UpperCAmelCase, 'rb' ) as binary_file:
lowerCAmelCase : Any = bin... | 343 | 1 |
'''simple docstring'''
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__lowerCamelCase : int = ... | 705 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : int = {
'''microsoft/cvt-13''': '''https://huggingface.co/micr... | 656 | 0 |
'''simple docstring'''
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_sentencepiec... | 653 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase : Any = {
'''configuration_longformer... | 653 | 1 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@r... | 705 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_en... | 181 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case_ : str = logging.get_logger(__name__)
snake_case_ : Tuple = {
"... | 195 |
'''simple docstring'''
def UpperCamelCase_( snake_case : Dict , snake_case : str , snake_case : Optional[int] , snake_case : Optional[Any] ):
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
... | 400 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase_ : Optional[Any] = {'''configuration_vit''': ['''VIT_PRETRAINED_CONFIG_ARCHIVE... | 719 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase_ : List[str] = TypeVar('''T''')
lowerCamelCase_ : Optional[int] = TypeVar('''U''')
class _SCREAMING_SNAKE_CASE ( Generic[T, U] ... | 265 | 0 |
'''simple docstring'''
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowercase = 10
def lowerCamelCase__ ( a , a , a , a ):
for i in range(_A ... | 356 | import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
SCREAMING_SNAKE_CASE : Union[str, Any] = namedtuple(
"""_TestComman... | 197 | 0 |
"""simple docstring"""
from __future__ import annotations
__lowercase : List[str] = tuple[int, int, int]
__lowercase : List[Any] = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
__lowercase : int = """ABCDEFGHIJKLM... | 710 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase ( tf.keras.layers.Layer ):
"""simpl... | 66 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCAmelCase__ :Tuple = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
def __init__( self :... | 150 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ :List[str] = logging.get_logger(__name__)
UpperCAmelCase__ :Union[str, Any] = {
"""BAAI/AltCLIP""": """htt... | 150 | 1 |
"""simple docstring"""
from PIL import Image
def snake_case ( UpperCamelCase__ : Image , UpperCamelCase__ : float ) -> Image:
def brightness(UpperCamelCase__ : int ) -> float:
return 128 + level + (c - 128)
if not -2_5_5.0 <= l... | 42 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import ... | 42 | 1 |
'''simple docstring'''
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
A_ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf()... | 42 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 | 0 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
lowerCAmelCase ... | 710 |
"""simple docstring"""
def a__ ( snake_case__ ) -> list:
if n_term == "":
return []
lowerCamelCase = []
for temp in range(int(snake_case__ ) ):
series.append(F'1/{temp + 1}' if series else """1""" )
return series
if __name__ == "_... | 533 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availa... | 337 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
__UpperCAmelCase =logging.get_logger(__name__)
def __a ( A=None , A=None ) -> int:
... | 337 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableU... | 704 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING... | 23 | 0 |
"""simple docstring"""
from math import sqrt
def lowerCAmelCase_ ( lowercase_ : str ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE : Optional[int] = 0
for i in range(1 , int(sqrt(__A ) + 1 ) ):
if n % i == 0 and i != sqrt(__A ):... | 674 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase__ ( ... | 601 | 0 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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 applica... | 708 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...image_uti... | 650 | 0 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def lowerCamelCase_ (UpperCamelCase__ : List[str] , UpperCamelCase__ : List[str]=() ... | 506 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 506 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def A_ ( UpperCAmelCase__ ) -> Optional[... | 707 |
"""simple docstring"""
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSamp... | 509 | 0 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
__a : Dict = logging.getLogger()
@unittest.skip("Temporarily disable the doc tests." )
@requ... | 637 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : Dict = logging.get_logger(__name__)
__a : Dict = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}
class __lowercase ... | 637 | 1 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def UpperCamelCase ( _A : Union[str, Any] )-> Optional[Any]:
"""simple docstring"""
def wrapper(*_A : Tuple , ... | 232 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class UpperCamelCase ( _... | 232 | 1 |
def _lowercase ( a__ : int , a__ : int ) -> Dict:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive" )
_UpperCamelCase = str(bin(snake_case__ ) )[2:] # remove the leading "0b"
_UpperCamelCase =... | 147 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : int , snake_case__ : int ):
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError("""both inputs must be positive integers""" )
_snake_case : Optional[Any] = ... | 609 | 0 |
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_pytorch_model
from transformers.ut... | 268 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils import logging
logging.set_... | 268 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase: Optional[int] = {
"""configuration_convnext""": ["""CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP... | 266 |
def lowerCamelCase__ ( __A :int ,__A :float ,__A :float ):
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def lowerCamelCase__ ( __A :float ,__A :float ,__A :float ):
"""simple docstring"""
... | 268 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transfor... | 702 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def a__ ( snake_case__ ) -> List[str]:
return getitem, k
def a__ ( snake_case__ , snake_case__ ) -> Optional... | 533 | 0 |
"""simple docstring"""
from typing import Dict, Iterable, 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,
... | 52 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMI... | 245 | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowercase ( lowerCamelCase__ , lowerCamelCase__ ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
__UpperCAmelCase : str = int(_... | 712 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : Any = logging.get_logger(__name__)
_a : List[Any] = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt model... | 10 | 0 |
"""simple docstring"""
from manim import *
class _lowerCAmelCase ( lowerCamelCase ):
def _a ( self ) -> List[Any]:
_UpperCAmelCase = Rectangle(height=0.5 , width=0.5 )
_UpperCAmelCase = Rectangle(height=0.46 , width=0.46 ).set_stroke(width=0 )
... | 657 |
"""simple docstring"""
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
def merge(UpperCamelCase__ , UpperCamelCase__ ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
ret... | 657 | 1 |
"""simple docstring"""
from __future__ import annotations
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE ) < 2:
raise ValueError("Monogons and Digons are not polygons in the Euclidean space" )
if ... | 700 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 614 | 0 |
'''simple docstring'''
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from f... | 42 |
'''simple docstring'''
A_ = "Input must be a string of 8 numbers plus letter"
A_ = "TRWAGMYFPDXBNJZSQVHLCKE"
def _UpperCamelCase ( __UpperCamelCase ) -> bool:
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
lowerCamelCase_ = f'''Expected string as input, fou... | 42 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@requir... | 616 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def A ( ):
'''simple docstring'''
with offline(Offline... | 616 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
@flax.struct.datacla... | 635 | from heapq import heappop, heappush
import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.ndarray , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : bool , ):
UpperCamelCase_,UpperCame... | 635 | 1 |
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
_lowercase = models.Sequential()
... | 242 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configurat... | 242 | 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 ConfigTe... | 36 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
snake_case__ : List[str] = TypeVar("""T""")
def _snake_case (__lowercase):
return (position - 1) // 2
def _snake_case (__lowercase):
... | 23 | 0 |
"""simple docstring"""
import qiskit
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : int ):
__a : List[Any] = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
__... | 63 |
"""simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, requi... | 63 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class A_ (lowerCAmelCase__ , unittest.TestCas... | 653 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docst... | 650 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : Tuple = logging.get_logger(__name__)
UpperCAmelCase__ : str = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class ... | 676 |
from __future__ import annotations
class __lowercase :
def __init__( self , lowercase_) -> None:
__snake_case = data
__snake_case = None
__snake_case = None
def A ( snake_case__ : ... | 676 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class ... | 99 |
def lowerCamelCase_ ( __UpperCamelCase ):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
A_ = grid[0]
for r... | 141 | 0 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def _UpperCAmelCase ( UpperCamelCase: Tuple ):
"""simple docstring"""
__lower... | 376 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_bytes
fro... | 376 | 1 |
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 disable_progress_bar, enable... | 184 |
from __future__ import annotations
from statistics import mean
def a ( A__ : list[int] , A__ : list[int] , A__ : int ) -> list[int]:
"""simple docstring"""
_lowercase =[0] * no_of_processes
_lowercase =[0] * no_of_processes
... | 291 | 0 |
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,
rescale,
resize,
to_channel_dimen... | 706 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}
class __UpperCamelCase ( lowerCAme... | 131 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGH... | 465 | """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,
re... | 564 | 0 |
"""simple docstring"""
import re
from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class U... | 708 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musi... | 404 | 0 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _lowerCAmelCase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase=1024 ) -> List[Any]:
"""simple docstring"""
... | 252 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
A__ = logging.get_logger(__name__)
A__ = {'''v... | 252 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ = {
'''con... | 719 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vision_available
fr... | 81 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCam... | 12 | import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _snake_case ( *__snake_case , __snake_case = None , __snake_case=True , __snake_case=2 ):
from .. import __version__
_UpperCamelCase = take_from
_UpperCame... | 10 | 0 |
"""simple docstring"""
import functools
def _snake_case ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] ) -> int:
# Validation
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ) or not all(isinstance(lowerCamelCase__ ... | 244 |
"""simple docstring"""
from datetime import datetime as dt
import os
from github import Github
A__ : int = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def _snake_case ( ) -> List[... | 244 | 1 |
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 ..... | 176 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_model... | 266 | 0 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.p... | 711 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
lowerCAmelCase : Optional[int] ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}... | 693 | 0 |
"""simple docstring"""
import os
import sys
import unittest
UpperCAmelCase__ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_in... | 223 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCAmelCase__ : List[str] = logging.get_logger(__name__)
class lowerCAmelCase_ (a__ ):
"""simple docstring"""
... | 223 | 1 |
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from transformers impor... | 199 |
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def _SCREAMING_SNAKE_CASE ( __lowercase : str ) -> str:
"""simple docstring"""
if "cls_token" in name:
__A ... | 199 | 1 |
'''simple docstring'''
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
__UpperCamelCase = namedtuple... | 26 |
import requests
def lowercase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ) -> None:
_snake_case : Union[str, Any] = {"""Content-Type""": """application/json"""}
_snake_case : Tuple = requests.post... | 477 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class a__ ( __SCREAMING_SNAKE_CASE ):
_A = (DEISMultis... | 706 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : int = logging.get_logger(__name__)
lowercase : Optional[Any] = {
"""google/canine-s""": """https://huggingface.co/google/canine-s/resolve/main/config.json""",
# See all CANINE ... | 584 | 0 |
from functools import lru_cache
@lru_cache
def lowerCamelCase_(lowerCamelCase_ ) -> Optional[Any]:
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest... | 323 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = False
while is_sorted is False: # Until all the indices are traversed keep looping
__lowerCAmelCase = True
for i in range(0 , le... | 636 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
UpperCamelCase_ = datasets.utils.logging.get_logger(__name__)
... | 376 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_bytes
fro... | 376 | 1 |
"""simple docstring"""
def lowerCAmelCase_ ( snake_case_ : int = 1_0 ) ->str:
if not isinstance(snake_case_ , snake_case_ ) or n < 0:
raise ValueError('Invalid input' )
lowerCamelCase__ : List[str] =1_0**n
lowerCamelCase__ : List[Any] ... | 174 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
... | 174 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : str = logging.get_logger(__name__)
__lowe... | 705 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : str = {
... | 459 | 0 |
"""simple docstring"""
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 ... | 535 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy as... | 535 | 1 |
'''simple docstring'''
from collections.abc import Iterable
from typing import Generic, TypeVar
lowercase : Optional[Any] = TypeVar("_T")
class __UpperCAmelCase ( Generic[_T] ):
def __init__( self , lowerCAmelCase_ = None ):
"""simple docstring"... | 713 |
'''simple docstring'''
import unittest
from transformers import 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 Model... | 542 | 0 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_param... | 669 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, 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 im... | 131 | 0 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __snake_case (unittest.TestCase ):
def SCREAMING_SNAKE_CASE ( self : int ) -> List[Any]:
'''simple... | 720 |
from math import loga
def _UpperCAmelCase (UpperCamelCase_ : int ):
'''simple docstring'''
if a < 0:
raise ValueError("""Input value must be a positive integer""" )
elif isinstance(UpperCamelCase_ , UpperCamelCase_ ):
raise TypeError("""Input value ... | 196 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase : Optional[Any] = {'configuration_plbart': ['PLBART_PRETRAINED_CONF... | 476 |
'''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,
rescale,
... | 476 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
def lowerCamelCase__ ( a , a , a ):
__snake_case = namedtuple('result' , 'name value' )
if (voltage, current, power).count(0 ) != 1:
raise ... | 721 |
'''simple docstring'''
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase__ ( a , a , a ):
# ... | 427 | 0 |
'''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
if is_torch_a... | 92 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_avail... | 65 | 0 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def _SCREAMING_SNAKE_CASE ( snake_case_ : int ):
__magic_name__ = prime_factors(snake_case_ )
if is_square_free(snake_case_ ):
return -1 if len(snake_case_ ) % 2 else 1
return... | 678 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urll... | 678 | 1 |
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