code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
... | 435 |
"""simple docstring"""
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase__ : Union[str, Any] ... | 223 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__:Any = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
try:
... | 720 | """simple docstring"""
from __future__ import annotations
def _lowerCamelCase( a , a , a ):
if len(a ) == 0:
raise ValueError("find_max() arg is an empty sequence" )
if (
left >= len(a )
or left < -len(a )
... | 67 | 0 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def a ( UpperCamelCase_ : Union[str, Any] = "https://www.worldometers.info/coronavirus" ) -> dict:
snake_case__ =BeautifulSoup(requests.get(_lowercase ).text , 'html.parser' )
snake_case__ =... | 538 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def lowercase_ ( _lowercase , _lowercase=False ) -> Dict:
'''simple docstring'''
lowerCamelCase_ : Tuple = OmegaConf.load(_lowerca... | 422 | 0 |
'''simple docstring'''
from math import pi
def lowercase (_A , _A ):
"""simple docstring"""
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 716 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 0 |
from datetime import datetime
import requests
def snake_case (UpperCAmelCase__ ) -> bytes:
UpperCamelCase_: Any = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
UpperCamelCase_: int = requests.get(base_url + url ).json()... | 57 |
"""simple docstring"""
from collections import namedtuple
__snake_case : Optional[int] = namedtuple('from_to', 'from_ to')
__snake_case : Union[str, Any] = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.001, 1_000),
'kilolitre': fr... | 571 | 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
__A : str = logging.get_logger(__name__)
__A : Tuple =... | 450 |
import os
import sys
import unittest
__A : 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 check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_bac... | 450 | 1 |
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=UpperCAmelCase_ ):
lowerCamelCase__ : Any =["torch", "transformers", "onnx"]
def __init__( self , *lowerCamelCase , **lowerCamelCase ) -> Tuple:
... | 154 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (... | 51 | 0 |
"""simple docstring"""
def snake_case ( A__ ,A__ ,A__ ):
if principal <= 0:
raise Exception("Principal borrowed must be > 0" )
if rate_per_annum < 0:
raise Exception("Rate of interest must be >= 0" )
if years_to_repay <= 0 or not isinstance(A__ ,A__ ):
raise Exce... | 463 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase_ (metaclass=__A ):
__magic_name__ = ['''onnx''']
def __init__( self : List[Any] , *lowerCAmelCase_ : Dict , **lowerCAmelCase_ : Dict ) -> Dict:
r... | 463 | 1 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( _lowercase : list[float] ) ->bool:
'''simple docstring'''
if len(_lowercase ) < 2:
raise ValueError("Monogons and Digons are not polygons in th... | 633 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple ) ->Optional[Any]:
'''simple docstring'''
a : Any = []
a : List[str] = set({"(", "[", "{"} )
a : int = set({")", "]", "}"} ... | 633 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def UpperCAmelCase ( A__: str , A__: str ) -> str | Literal[False]:
__lowerCamelCase : str = list(A__ )
__lowerCamelCase : O... | 263 |
"""simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttentio... | 263 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCamelCase__ ( _A):
... | 2 |
'''simple docstring'''
def A__ ( A : int , A : int):
'''simple docstring'''
return int((input_a, input_a).count(0) != 0)
def A__ ( ):
'''simple docstring'''
assert nand_gate(0 , 0) == 1
assert nand_gate(0 , 1) == 1
ass... | 173 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.... | 269 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ : str ={'''configuration_fnet''': ['''FNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FNe... | 269 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
lowerCAmelCase : Optional[int] =['''small''', '''medium''', '''large''']
lowerCAmelCase : List[str] ='''lm_head.decoder.weight'''
lowerCAmelCase : Optional[Any] ... | 172 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : Dict =logging.get_logger(__name__)
lowerCAmelCase : List[Any] ... | 172 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 66 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
lowerCamelCase_ ... | 66 | 1 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_t... | 6 |
from copy import deepcopy
class __UpperCamelCase :
def __init__( self : List[str] , lowerCAmelCase : list[int] | None = None , lowerCAmelCase : int | None = None ):
'''simple docstring'''
if arr is None and size is not None:
UpperCAmelCase_ ... | 162 | 0 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 716 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
__UpperCAmelCase : Optional[Any] = 4
__UpperCAmelCase : str = 3
class ... | 155 | 0 |
'''simple docstring'''
class __magic_name__ :
def __init__( self : Optional[Any] ):
_a : dict[str, TrieNode] = {} # Mapping from char to TrieNode
_a : List[Any] = False
def __lowercase ( self : Union[str, Any] ... | 358 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 358 | 1 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a():
'''simple docstring'''
snake_case_ = ArgumentParser(
description=(
'PyTorch TPU distributed training launch '
... | 46 |
from collections import defaultdict
def a(lowercase__ , lowercase__ ):
'''simple docstring'''
snake_case_ = first_str.lower().strip()
snake_case_ = second_str.lower().strip()
# Remove whitespace
snake_case_ = first_str.replace(' ' , '' )
snake_case_ = second_str.replac... | 46 | 1 |
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
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ ... | 622 |
from sklearn.metrics import matthews_corrcoef
import datasets
a__ : Any = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true a... | 622 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase = {
'''configuration_convnext''': ['''CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_M... | 717 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import requ... | 564 | 0 |
from __future__ import annotations
from collections.abc import Callable
__A : int = list[list[float | int]]
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Matrix:
"""simple docstring"""
_A ... | 27 |
from __future__ import annotations
from typing import Any
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : str , __snake_case : int = 6 ) -> None:
'''simple docstring'''
lowerCamelCase ... | 246 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from trans... | 720 |
'''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 (_lowercase, _lowercase, _lowercase ) -> Optional[Any]:
"""... | 483 | 0 |
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)
UpperCAmelCase_ = models.Sequential()
# Step 1 -... | 2 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ... | 146 | 0 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : int , _UpperCamelCase : int ):
'''simple docstring'''
return int((input_a, input_a).count(0 ) != 0 )
def __lowerCamelCase ( ):
'''simple docstring'''
assert nand_gate(0 ... | 710 | '''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowercase__ : Tuple = pytest.mark.integration
@pytest.mark.parametrize('... | 43 | 0 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'''The `image_to_image.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionImg2ImgPipeline` instead.'''
) | 561 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.te... | 561 | 1 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, 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, ra... | 522 | import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import I... | 522 | 1 |
"""simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
... | 83 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 4 | 0 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_... | 714 |
"""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, rando... | 281 | 0 |
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_MAPPING,
AutoConfig,
AutoModelForMaskedL... | 45 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if digit_amount > 0:
return round(number - int(__UpperCamelCase ) , __UpperCamelCase )
return number - int(__UpperCamelCase )
if __name__ == "__main__":
print(decimal_isolate(1.... | 76 | 0 |
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 snake_case_ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
... | 705 |
'''simple docstring'''
import math
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def UpperCamelCase( self , lowerCamelCase , lowerCamelCase ):
_snake_case = 0.0
_snake_case = 0.0
for i in range(len(lowerCamelCase ) ):
... | 368 | 0 |
"""simple docstring"""
def __UpperCamelCase ( snake_case__ ):
if p < 2:
raise ValueError("""p should not be less than 2!""" )
elif p == 2:
return True
A_ : Dict = 4
A_ : int = (1 << p) - 1
for _ in range(p - 2 ):
A_ : Union[str, Any] ... | 180 |
"""simple docstring"""
import math
import os
import sys
def __UpperCamelCase ( snake_case__ ):
A_ : Optional[Any] = """"""
try:
with open(snake_case__ , """rb""" ) as binary_file:
A_ : Union[str, Any] = binary_file.read()
for dat in data:
A_ ... | 180 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__a = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConf... | 710 |
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transformers.models.wavavec... | 300 | 0 |
'''simple docstring'''
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataT... | 38 |
class _lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : int):
'''simple docstring'''
snake_case__ = size
snake_case__ = [0] * size
snake_case__ ... | 654 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json""",
"""RWKV/rwkv-4-430m-pile""": """htt... | 719 |
# 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 by ap... | 648 | 0 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
a : Tuple = '''\
@misc{chen2021evaluat... | 69 |
class __magic_name__ :
'''simple docstring'''
def __init__( self: Optional[int] ):
SCREAMING_SNAKE_CASE_ = {}
def _A ( self: Optional[Any] ):
print(self.vertex )
for i in self.vertex:
print... | 234 | 0 |
import cva
import numpy as np
class _UpperCamelCase :
def __init__( self :Union[str, Any] , lowerCamelCase :float , lowerCamelCase :int ) -> str:
if k in (0.04, 0.06):
UpperCAmelCase__ = k
UpperCAmelCase__ = window_size
... | 364 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoConfig,
... | 364 | 1 |
from collections.abc import Callable
class lowerCAmelCase__ :
def __init__( self , a = None ) -> None:
'''simple docstring'''
_UpperCamelCase = []
# Stores indexes of each item for supporting updates and deletion.
_UpperCa... | 612 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("T")
lowerCamelCase__ = TypeVar("U")
class lowerCAmelCase__ ( Generic[T, U] ):
def __init__( self , a , a ) ... | 612 | 1 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __lowercase ( _UpperCAmelCase ):
UpperCamelCase = (DDPMScheduler,)
def _lowercase ( self : Li... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 0 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import... | 484 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 484 | 1 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( UpperCAmelCase : Any , UpperCAmelCase : int , UpperCAmelCase : int , UpperCAmelCase : Any=1_024 )... | 709 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( UpperCAmelCase : Any , UpperCAmelCase : int , UpperCAmelCase : int , UpperCAmelCase : Any=1_024 )... | 458 | 0 |
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
UpperCamelCase : Union[str, Any] ... | 37 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if ... | 575 | 0 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokeniz... | 705 |
"""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
fro... | 51 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin,... | 342 |
__a :Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_0000)]
def __snake_case ( __UpperCamelCase : int ):
"""simple docstring"""
A_ = 0
while number:
# Increased Speed Slightly by checking every 5 digits toget... | 86 | 0 |
def snake_case (UpperCamelCase : List[Any] ):
'''simple docstring'''
lowerCamelCase__ = [0] * len(UpperCamelCase )
lowerCamelCase__ = []
lowerCamelCase__ = [1] * len(UpperCamelCase )
for values in graph.values():
for i in values:
indegree... | 235 |
def snake_case (UpperCamelCase : int = 50 ):
'''simple docstring'''
lowerCamelCase__ = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_leng... | 235 | 1 |
'''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
SCREAMING_SNAKE_CASE__ = pytest.mark.integration
... | 267 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class snake_case (UpperCamelCase , UpperCamelCase ):
@reg... | 267 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musi... | 296 | """simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class _lowercase :
"""simple docstring"""
def __init__( self : Tuple , UpperCamelCase__ : int ) -> List[str]:
'''s... | 296 | 1 |
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 snake_case ( __snake_case ):
"""simple docstring"""
... | 321 | import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.modelin... | 321 | 1 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _UpperCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def _lowerCAmelCase ( self ):
'''si... | 460 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _UpperCAmelCase ( unittest.TestCase ):
"""simple docstr... | 460 | 1 |
"""simple docstring"""
UpperCamelCase = """Tobias Carryer"""
from time import time
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ... | 104 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def __magic_name__ ( __lowerCAmelCase : Any ) ... | 298 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPConfig""",
""... | 351 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
... | 351 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase: List[Any] = {
'''configuration_tapas''': ['''TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TapasConfig'''],
'''tokenization_tapas''': ['''TapasTokenizer'''... | 192 | 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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from transformer... | 192 | 1 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ..... | 129 |
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 129 | 1 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a =... | 19 |
def UpperCAmelCase__ ( lowerCamelCase_ : list[int] , lowerCamelCase_ : list[int] ):
# Check if the input is valid
if not len(lowerCamelCase_ ) == len(lowerCamelCase_ ) == 3:
raise ValueError('Please enter a valid equation.' )
if equa... | 47 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_ima... | 65 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
lowercase_ = logging.get_logger(__name__)
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self , _a=Non... | 65 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
__SCREAMING_SNAKE_CASE =TypeVar("T")
__SCREAMING_SNAKE_CASE =TypeVar("U")
class UpperCamelCase ( Generic[T, U] ):
def __init__( ... | 425 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils im... | 95 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A : Any = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 595 | """simple docstring"""
from __future__ import annotations
__A : Union[str, Any] = []
def lowercase ( UpperCamelCase : list[list[int]] , UpperCamelCase : int , UpperCamelCase : int ):
"""simple docstring"""
for i in range(len(UpperC... | 595 | 1 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging... | 103 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def __lowerCamelCase ( UpperCAmelCase_ : int = 8 ):
"""simple docstring"""
a :Optional[int] = ascii_letters + digits + punctuation
... | 445 | 0 |
'''simple docstring'''
def _a ( _lowercase : Any ): # noqa: E741
'''simple docstring'''
__UpperCAmelCase : Any = len(lowerCAmelCase__ )
__UpperCAmelCase : Tuple = 0
__UpperCAmelCase : Any = [0] * n
... | 706 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCAmelCase :Optional[Any] = {
"configuration_layoutlm... | 266 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : int = {
'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main... | 139 |
"""simple docstring"""
def lowerCamelCase ( _UpperCamelCase : int = 1_0_0_0_0_0_0 ) -> int:
'''simple docstring'''
__UpperCAmelCase : List[str] = 1
__UpperCAmelCase : Union[str, Any] = 1
__UpperCAmelCase : Optional[Any] = {1: 1}
... | 139 | 1 |
'''simple docstring'''
import os
from pathlib import Path
def _UpperCamelCase ( ):
"""simple docstring"""
from torch.utils.cpp_extension import load
__UpperCamelCase : Optional[int] = Path(_a ).resolve().parent.parent.parent / 'kernels' / 'deformable_detr'
__UpperCamelCase : ... | 720 | '''simple docstring'''
a= '''0.21.0'''
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .la... | 287 | 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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageResam... | 31 |
def _A ( SCREAMING_SNAKE_CASE : list[int] , SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
a__ : List[str] =len(SCREAMING_SNAKE_CASE )
a__ : Optional[int] =[[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr ... | 563 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require... | 710 |
'''simple docstring'''
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be check... | 13 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}
class _lowerCAmelCase ( __... | 282 |
from functools import lru_cache
@lru_cache
def __lowerCamelCase ( _lowercase ) -> int:
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
doctes... | 282 | 1 |
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 TFCamembertModel
@req... | 59 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCamelCase = logging.getLogger(__name__)
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description="""Pr... | 59 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelFo... | 94 |
import tensorflow as tf
from ...tf_utils import shape_list
class a ( tf.keras.layers.Layer ):
def __init__( self :Tuple ,__lowercase :Optional[int] ,__lowercase :List[Any] ,__lowercase :int ,__lowercase :str ,__lowercase :List[str]=1 ,__lowercase :Optional[Any]=False ,**__l... | 252 | 0 |
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __magic_name__ :
lowercase : Tuple =42
lowercase : Any =None
lowercase : List[Any] =None
def lowerCamelCase_(lowerCamelCase_ ) -> List[Any]:
... | 714 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
fr... | 457 | 0 |
"""simple docstring"""
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
A_ : List[str] =collections.namedtuple("""_Data... | 650 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class __a ( lowerCAmelCase__ ):
def __init__( self , a__ , a__=None , a__=True , a__=None , ... | 650 | 1 |
'''simple docstring'''
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
Pixa... | 357 |
'''simple docstring'''
def lowercase_ ( _lowercase , _lowercase ) -> Dict:
'''simple docstring'''
lowerCamelCase_ : List[Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def lowercase_ ( _... | 357 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
UpperCAmelCase_ = (3, 9, -1_1, 0, 7, 5, 1, -1)
UpperCAmelCase_ = (4, 6, 2, 0, 8, 1_0, 3, -2)
@dataclass
class lowerCAmelCase_ :
''... | 603 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __lt__( self : List[Any] , _Upper... | 603 | 1 |
from __future__ import annotations
from typing import Any
class UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCamelCase_ ):
lowercase_ :List[str] = num_of_nodes
lowercase_ :list[list[int]] ... | 441 |
def UpperCamelCase ( _a , _a , _a ) -> int:
'''simple docstring'''
def count_of_possible_combinations(_a ) -> int:
if target < 0:
return 0
if target == 0:
return 1
return sum(count_of_possi... | 441 | 1 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
a_ : List[str] = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
... | 623 |
"""simple docstring"""
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class snake_case_ ( low... | 34 | 0 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
A... | 419 |
'''simple docstring'''
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def UpperCamelCase__ ( __magic_name__ : Union[str, Any] , __magic_name__ : str , __magic_name__ : Any ) -> Optional[Any]:
... | 419 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, Bi... | 36 |
"""simple docstring"""
def A__ ( A__ ) -> list[int]:
'''simple docstring'''
if length <= 0 or not isinstance(A__ , A__ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(A__ )]
if __name__ == "__main__":
print(hexagonal_n... | 426 | 0 |
'''simple docstring'''
from collections import deque
class __SCREAMING_SNAKE_CASE :
def __init__( self , lowerCamelCase , lowerCamelCase , lowerCamelCase ) ->None:
'''simple docstring'''
__a = process_name # process name
__a ... | 718 |
'''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,
... | 270 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
... | 489 |
'''simple docstring'''
def _lowerCamelCase (__lowerCamelCase : list[int] , __lowerCamelCase : list[int] , __lowerCamelCase : int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__lowerCamelCase ) )
... | 489 | 1 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from torch import nn
f... | 719 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase ( _lowerCamelCase ,unittest.TestCase ):
... | 501 | 0 |
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : float = 0 ) -> None:
... | 570 |
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=lowercase__ ):
snake_case__ : List[str] = ['''onnx''']
def __init__( self : List[Any] , *SCREAMING_SNAKE_CASE__ : Dict , **SCREAMING_SNAKE_CASE__ : ... | 570 | 1 |
'''simple docstring'''
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 493 |
'''simple docstring'''
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import v... | 493 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : int = {
"""configuration_upernet""": ["""UperNetConfig"""],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvail... | 257 |
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 ( SCREAMING_SNAKE_CASE : List[str] ):
... | 563 | 0 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase ):
"""simple docstring"""
lowerCAmelCase__ : ... | 160 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase ):
"""simple docstring"""
while a != 0:
lowerCAmelCase__ , lowerCAmelCase__ : Optional[Any] = b % a, a
return b
def _SCREAMING_SNAKE_CASE ... | 160 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowerCAmelCase : List[str] ... | 440 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _SCREAMING_SNAKE_CASE ( __a ):
__SCREAMING_SNAKE_CASE :Optional[int] = """ClapFeatureExtractor"""
__SCREAMING_SNAKE_CASE :List[Any] = ("""Robe... | 432 | 0 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class __A :
"""simple docstring"""
UpperCamelCase__ : str =None
def __lowercase ( self ):
... | 721 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def A ( a_ = "" ) -> dict[str, float]:
__UpperCamelCase : Tuple =url or 'https://www.imdb.com/chart/top/?ref_=nv_mv_250'
__UpperCamelCase : Optional[int... | 154 | 0 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from tr... | 217 |
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase_ = get_tests_dir('fixtures/spiec... | 217 | 1 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowercase__( unittest.TestCase ):
'''simple docstring'''
def __lowerCAmelCase ( self :int ) -> Tuple:
'''simple docstring'''
SCREAMING_SNAK... | 18 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def __A ( a_ : float , a_ : float , a_ : bool = False )-> list[float]:
'''simple docstring'''
if radian_... | 18 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...utils im... | 524 |
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,
require_tim... | 35 | 0 |
from torch import nn
class UpperCamelCase_ ( nn.Module ):
'''simple docstring'''
def __init__( self , _UpperCAmelCase , _UpperCAmelCase):
super().__init__()
lowerCAmelCase_ = class_size
lowerCAmelCase_ = ... | 413 |
def lowerCamelCase_ ( ):
"""simple docstring"""
return [
a * b * (10_00 - a - b)
for a in range(1 , 9_99 )
for b in range(A , 9_99 )
if (a * a + b * b == (10_00 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(f'''{solutio... | 413 | 1 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
__A : Tuple ... | 27 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def __UpperCAmelCase( lowercase_ ):
# vision encoder
if "img_encoder.pos_embed" in name:
_lowerCamelCase : Tuple = name.replace(... | 114 | 0 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : int):
if not isinstance(lowerCamelCase , lowerCamelCase):
raise ValueError("""check_bouncy() accepts only integer arguments""")
A_ : List[str] = str(lowerCamelCase)
A_ : ... | 27 |
'''simple docstring'''
import baseaa
def lowerCamelCase ( lowerCamelCase : str):
return baseaa.aaaencode(string.encode("""utf-8"""))
def lowerCamelCase ( lowerCamelCase : bytes):
return baseaa.aaadecode(lowerCamelCase).decode("""utf-8""")
if __name__ ==... | 27 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
imp... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : List[Any] = {
"configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}
try:
if not is_torch_available():
ra... | 289 | 1 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __lowerCa... | 171 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
snake_case__ : int = logging.get_logger(__name__)
snake_case__ : List[str] = {
'Visual-Attention-Network/van-base': (
'https://huggingface.co/Visual-Attention-Network/van-base/blob/ma... | 171 | 1 |
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 import FlaxTimestepEmbedding, F... | 488 |
class snake_case_ :
'''simple docstring'''
def __init__( self : Tuple , __magic_name__ : Any , __magic_name__ : int , __magic_name__ : List[Any] ) -> Union[str, Any]:
lowerCamelCase_ : Any ... | 488 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__a : str = logging.get_logger(__name__)
__a : Tuple = {
... | 716 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def snake_case_ ( *SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ = None ,SCREAMING_SNAKE_CASE_=True ,SCREAMING_SNAKE_CASE_=2 ) -> Dict:
from .. import __... | 298 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
... | 22 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] , SCREAMING_SNAKE_CASE :Dict , SCREAMING_SNAKE_CASE :Any , SCREAMING_SNAKE_CASE :List[str] ) -> List[str]:
'''simple docstring'''
_a : ... | 694 | 0 |
"""simple docstring"""
from math import pow, sqrt
def lowerCAmelCase__ ( *_UpperCamelCase : List[str] ) -> Tuple:
"""simple docstring"""
snake_case = len(lowerCAmelCase_ ) > 0 and all(value > 0.0 for value in values )
re... | 703 | """simple docstring"""
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def lowerCAmelCase__ ( _UpperCamelCase : Dict[str, torch.Tensor] ) -> Dict[str, torch.Tensor]:
... | 104 | 0 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from transformer... | 221 | import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
SCREAMING_SNAKE_CASE : List[Any] = get_logger(__name__)
class A_ ( enum.Enum ):
_SCREAMING_SNAKE_CASE = """all_checks"""
_SCREAMING_... | 197 | 0 |
lowercase_ = tuple[float, float, float]
lowercase_ = tuple[float, float, float]
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowercase__ = end_pointa[0] - end_pointa[0]
lowercase__ = end_pointa[1] - end_pointa[1]
lowercase__ ... | 37 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowercase__ = {
"en": "Machine learning is great, isn't it?",
"ru": "Машинное обучение - это здоро... | 37 | 1 |
'''simple docstring'''
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermar... | 349 |
'''simple docstring'''
import math
import qiskit
def _a ( lowerCamelCase_ = 1 , lowerCamelCase_ = 1 , lowerCamelCase_ = 1 ):
if (
isinstance(lowerCamelCase_ , lowerCamelCase_ )
or isinstance(lowerCamelCase_ , lowerCamelCase_ )
or isinstance(lowerCamelCase_ ,... | 349 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : ... | 157 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _a ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ) -> str | Literal[False]:
'''simple docstring'''
SCREAM... | 157 | 1 |
class _a :
"""simple docstring"""
def __init__( self : Union[str, Any] , UpperCAmelCase : int , UpperCAmelCase : Any , UpperCAmelCase : Dict ):
A_ = None
A_ = None
A_ ... | 86 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available... | 114 | 0 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
__SCREAMING_SNAKE_CASE : Any = TypeVar('''T''')
__SCREAMING_SNAKE_CASE : Any = Union[List[T], Tuple[T, ...]]
__SCREAMING_SNAKE_CASE : str = Union[T, List[T], Dict[str, T]]
__SCREAMING_SNAKE_CASE : ... | 149 |
def snake_case_ ( lowercase__ : int ):
'''simple docstring'''
_lowerCAmelCase =n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 149 | 1 |
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