code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from cva import destroyAllWindows, imread, imshow, waitKey
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for i in range(a_ ):
... | 362 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def __A ( a_ :Tuple) -> List[str]:
return choice(a_)
def __A ( a_ :list[int] , a_ :int) -> int:
__a : Optional[int] = random_pivot(a... | 52 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
UpperCAmelCase__ = ... | 277 |
"""simple docstring"""
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAM... | 52 | 0 |
def SCREAMING_SNAKE_CASE__ ( lowerCAmelCase_ : list[int] ,lowerCAmelCase_ : list[int] ) -> tuple[float, float]:
"""simple docstring"""
if not len(a_ ) == len(a_ ) == 3:
raise ValueError('Please enter a valid equation.' )
i... | 220 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask... | 52 | 0 |
import sys
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 checked before tokeni... | 17 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A = logging.get_logger(__name__)
A ... | 52 | 0 |
def _a ( __UpperCamelCase : int ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 233 |
"""simple docstring"""
def __A ( a_ :Tuple , a_ :Union[str, Any] , a_ :int=False) -> List[str]:
if isinstance(a_ , a_) and isinstance(a_ , a_):
__a : List[str] = len(set_a.intersection(a_))
if alternative... | 52 | 0 |
"""simple docstring"""
def lowercase_ ( _lowercase : int ):
'''simple docstring'''
if bit_count < 0:
raise ValueError("The given input must be positive" )
# get the generated string sequence
UpperCAmelCase : Optional[int] = gray_code... | 595 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
A = tuple[int, int]
class __lowercase :
'''simple docstring'''
def __init__( self , _UpperCAmelCase , ... | 52 | 0 |
'''simple docstring'''
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
lowerCAmelCase = """<<<<<<< This should probably be modified because it mentions: """
lower... | 525 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main... | 52 | 0 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def lowerCamelCase__ ( A_="ro" , A_="en" , A_="wmt16" , A_=None ):
try:
import datasets
except (ModuleNotFoundError, ImportError):
raise ImportError("run pip install datasets" ... | 660 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def __A ( a_ :Union[str, Any] , a_ :Union[str, Any] , a_ :Optional[Any] , a_ :Optional[int]=5) -> List[Any]:
# Adapted from https://github... | 52 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
... | 250 |
"""simple docstring"""
import unittest
from knapsack import greedy_knapsack as kp
class __lowercase ( unittest.TestCase ):
'''simple docstring'''
def _lowerCamelCase ( self ):
__a : Optional[int] ... | 52 | 0 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _lowercase ( _UpperCamelCase , unittest.TestCase ):
"""simple docstring"""
lowerC... | 398 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {}
class __lowercase ( _UpperCamelCase ):
'''simple docstring'''
__l... | 52 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase =logging.get_logger(__name__)
__UpperCAmelCase ={}
class a__ ( _UpperCamelCase ):
lowerCamelCase : Optional[int] ="llama"
lowerCamelCase : int =["... | 546 |
"""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, p... | 52 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_UpperCAmelCase : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
... | 362 |
"""simple docstring"""
from __future__ import annotations
def __A ( a_ :list[int]) -> int:
if not nums:
return 0
__a : Any = nums[0]
__a : Optional[Any] = 0
for num in nums[1:]:
__a , __a : ... | 52 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
UpperCAmelCase__ = logging.get_logger(__name__)
class a ( _UpperCamelCase ):
def __init__( self : List[Any] , *__lowerCAmelCase : Dict , **__l... | 277 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokeniz... | 52 | 0 |
from __future__ import annotations
from random import choice
def SCREAMING_SNAKE_CASE__ ( lowerCAmelCase_ : Tuple ) -> List[str]:
"""simple docstring"""
return choice(a_ )
def SCREAMING_SNAKE_CASE__ ( lowerCAmelCase_ : list[int] ,lowerCAmelCase_ :... | 220 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A = logging.get_logger(__name__)
A = {
'''facebook/convnextv... | 52 | 0 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __SCREAMING_SNAKE_CASE ( a__ : bytes ,a__ : int ) -> np.array:
__A : str = f"""{sampling_rate}"""
__A : Tuple = '''1'''
__A : Optional[int] ... | 17 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __lowercase ( _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = (DDPMScheduler,)
... | 52 | 0 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
renew_... | 233 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_to... | 52 | 0 |
"""simple docstring"""
from collections import defaultdict
def lowercase_ ( _lowercase : str , _lowercase : str ):
'''simple docstring'''
UpperCAmelCase : List[Any] = first_str.lower().strip()
UpperCAmelCase : str = second_str.l... | 595 |
"""simple docstring"""
from __future__ import annotations
class __lowercase :
'''simple docstring'''
def __init__( self , _UpperCAmelCase , _UpperCAmelCase ):
__a , __a : List[Any] =... | 52 | 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():
... | 525 |
"""simple docstring"""
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
A = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(... | 52 | 0 |
'''simple docstring'''
from __future__ import annotations
__snake_case : Optional[Any] = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],... | 660 |
"""simple docstring"""
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_s... | 52 | 0 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unit... | 250 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A = {
'''configuration_tapas''': ['''TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TapasConfig'''],
'''tokenizatio... | 52 | 0 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class _UpperCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def lowercase ( self ... | 53 |
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,
AutoModelForMaskedLM... | 53 | 1 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_snake_case : str = logging.get_logger(__name__)
class _UpperCAmelCase ( _UpperCamelCase ):
"""simple docstring"""
def __init__( self : Opti... | 53 |
def a_ ( lowerCAmelCase_ : int = 200_0000 ):
__lowerCAmelCase = [0 for i in range(n + 1 )]
__lowerCAmelCase = 1
__lowerCAmelCase = 1
for i in range(2, int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
for... | 53 | 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... | 53 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
log... | 53 | 1 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
_snake_c... | 53 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_com... | 53 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_deter... | 53 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 53 | 1 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 53 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
__lowerCAmelCase = ArgumentParser(
description=(
'PyTorch TPU distributed training launch '
... | 53 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
_snake_case : List[Any] = {
'configuration_speecht5': [
'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SPEEC... | 53 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_availab... | 53 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_snake_case : Tuple = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftF... | 53 |
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_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : Optio... | 53 | 1 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class _UpperCAmelCase ... | 53 |
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
_sn... | 53 | 1 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoModelWithLMHead,
... | 53 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _UpperCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : Union[str, Any] ) -> List[str]:
__lowerCAmelCase = ... | 53 | 1 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class _UpperCAmelCase :
"""simple docstring"""
def lowercase ( self : Dict , lowerCAmelCase_ : Tuple ) -> str:
... | 53 |
import math
def a_ ( lowerCAmelCase_ : list, lowerCAmelCase_ : int ):
__lowerCAmelCase = len(lowerCAmelCase_ )
__lowerCAmelCase = int(math.floor(math.sqrt(lowerCAmelCase_ ) ) )
__lowerCAmelCase = 0
while arr... | 53 | 1 |
import numpy
# List of input, output pairs
_snake_case : Optional[int] = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
_snake_case : List[str] = (((515, 22, 13), 555), ((61, 35, 49), 150))
_snake_case :... | 53 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : List[Any], lowerCAmelCase_ : str ... | 53 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snak... | 53 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import logg... | 53 | 1 |
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils i... | 53 |
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 import... | 53 | 1 |
def a_ ( lowerCAmelCase_ : float, lowerCAmelCase_ : float ):
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) = }""")
| 53 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
_snake_case : Any = logging.get_logger(__name__)
_sn... | 53 | 1 |
from __future__ import annotations
def a_ ( lowerCAmelCase_ : list[int], lowerCAmelCase_ : int, lowerCAmelCase_ : int, lowerCAmelCase_ : int ):
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[indexa] < array[indexa]
... | 53 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_pr... | 53 | 1 |
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_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : Optio... | 53 |
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,
rescale,
resize,
to_channel_dimension_... | 53 | 1 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
r... | 53 |
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_tor... | 53 | 1 |
import re
def a_ ( lowerCAmelCase_ : str ):
__lowerCAmelCase = re.compile(R'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' )
if match := re.search(lowerCAmelCase_, lowerCAmelCase_ ):
return match.string == phone
return False
if __name__ == "__main__":
... | 53 |
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.utils import W... | 53 | 1 |
def a_ ( lowerCAmelCase_ : int, lowerCAmelCase_ : int ):
return "\n".join(
F"""{number} * {i} = {number * i}""" for i in range(1, number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_table(number=5, number_of_terms=10))
| 53 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 53 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..... | 53 |
from __future__ import annotations
def a_ ( lowerCAmelCase_ : list[float] ):
if len(lowerCAmelCase_ ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
if any(i <= 0 for i in nums ):
raise ValueError('All values must be g... | 53 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_snake_case : Optional[Any] = {
'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
'configuration_mas... | 53 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Fla... | 53 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Optional[Any] = logging.get_logger(__name__)
_snake_case : Dict = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/res... | 53 |
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,
AutoModelForMaskedLM... | 53 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Tuple = logging.get_logger(__name__)
_snake_case : List[Any] = {
'microsoft/git-base': 'https://huggingface.co/microsoft/git... | 53 |
def a_ ( lowerCAmelCase_ : int = 200_0000 ):
__lowerCAmelCase = [0 for i in range(n + 1 )]
__lowerCAmelCase = 1
__lowerCAmelCase = 1
for i in range(2, int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
for... | 53 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case : Optional[int] = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
... | 53 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
log... | 53 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case : List[str] = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor'],
}
try:
... | 53 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_com... | 53 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def a_ ( lowerCAmelCase_ : int, lowerCAmelCase_ : int, lowerCAmelCase_ : int, lowerCAmelCase_ : int, lowerCAmelCase_ : int, lowerCAmelCase_ : int ... | 53 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 53 | 1 |
from sklearn.metrics import recall_score
import datasets
_snake_case : Dict = '\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives and FN is the... | 53 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
__lowerCAmelCase = ArgumentParser(
description=(
'PyTorch TPU distributed training launch '
... | 53 | 1 |
from __future__ import annotations
def a_ ( lowerCAmelCase_ : list[float], lowerCAmelCase_ : int ):
print(F"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(lowerCAmelCase_ ):
print(F"""{i}\t\t{d}""" )
def a_ ( lowe... | 53 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_availab... | 53 | 1 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class _UpperCAmelCase :
"""simple docstring"""
def __init__( self : Dict , lowerCAmelCase_ : list[tuple[float, float]] ) -> Any:
__lowerCAmelCase = list_of_... | 53 |
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_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : Optio... | 53 | 1 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_snake_case : int = logging.get_logger(__name__)
def a_ ( lowerCAmelCase_ : Optional[Any], lo... | 53 |
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
_sn... | 53 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_snake_case : Tuple = get_tests_d... | 53 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _UpperCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : Union[str, Any] ) -> List[str]:
__lowerCAmelCase = ... | 53 | 1 |
import os
import time
import numpy as np
import onnxruntime as ort
_snake_case : Dict = '1'
_snake_case : str = '0'
_snake_case : Optional[Any] = '1'
_snake_case : int = ort.SessionOptions()
_snake_case : Optional[Any] ... | 53 |
import math
def a_ ( lowerCAmelCase_ : list, lowerCAmelCase_ : int ):
__lowerCAmelCase = len(lowerCAmelCase_ )
__lowerCAmelCase = int(math.floor(math.sqrt(lowerCAmelCase_ ) ) )
__lowerCAmelCase = 0
while arr... | 53 | 1 |
class _UpperCAmelCase :
"""simple docstring"""
def __init__( self : List[str] , lowerCAmelCase_ : int ) -> None:
__lowerCAmelCase = size
__lowerCAmelCase = [0] * size
__lowerCAmelCase = [0] * size
... | 53 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : List[Any], lowerCAmelCase_ : str ... | 53 | 1 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
_snake_case : Dict = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
'KD 6S 9D TH A... | 53 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import logg... | 53 | 1 |
import math
from datetime import datetime, timedelta
def a_ ( lowerCAmelCase_ : int ):
__lowerCAmelCase = year % 19
__lowerCAmelCase = year % 4
__lowerCAmelCase = year % 7
__lowerCAmelCase = math.floor(year / 100 )
... | 53 |
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 import... | 53 | 1 |
import math
def a_ ( lowerCAmelCase_ : list, lowerCAmelCase_ : int ):
__lowerCAmelCase = len(lowerCAmelCase_ )
__lowerCAmelCase = int(math.floor(math.sqrt(lowerCAmelCase_ ) ) )
__lowerCAmelCase = 0
while arr... | 53 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
_snake_case : Any = logging.get_logger(__name__)
_sn... | 53 | 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
_snake_case : str = logging.get_logger(__name__)
_sna... | 53 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_pr... | 53 | 1 |
import inspect
import unittest
from transformers import MobileViTConfig
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_configuration_common import ConfigTester
from ...t... | 53 |
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,
rescale,
resize,
to_channel_dimension_... | 53 | 1 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTe... | 53 |
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_tor... | 53 | 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, Stabl... | 53 |
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.utils import W... | 53 | 1 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : List[Any], lowerCAmelCase_ : str ... | 53 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 53 | 1 |
def a_ ( lowerCAmelCase_ : float, lowerCAmelCase_ : int ):
if digit_amount > 0:
return round(number - int(lowerCAmelCase_ ), lowerCAmelCase_ )
return number - int(lowerCAmelCase_ )
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
... | 53 |
from __future__ import annotations
def a_ ( lowerCAmelCase_ : list[float] ):
if len(lowerCAmelCase_ ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
if any(i <= 0 for i in nums ):
raise ValueError('All values must be g... | 53 | 1 |
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
from torch.utils.data import Dat... | 53 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Fla... | 53 | 1 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def a_ ( lowerCAmelCase_ : int, lowerCAmelCase_ : int, lowerCAmelCase_ : float = 1 / sqrt(2 ) ):
__lowerCAmelCase = tau * frequency / samplerate
__lowerCAmelCase ... | 53 |
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,
AutoModelForMaskedLM... | 53 | 1 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files', [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos.json'],
['dataset... | 53 |
def a_ ( lowerCAmelCase_ : int = 200_0000 ):
__lowerCAmelCase = [0 for i in range(n + 1 )]
__lowerCAmelCase = 1
__lowerCAmelCase = 1
for i in range(2, int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
for... | 53 | 1 |
import unittest
import numpy as np
from transformers import DistilBertConfig, 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.numpy as jnp
... | 53 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
log... | 53 | 1 |
import math
class _UpperCAmelCase :
"""simple docstring"""
def lowercase ( self : Union[str, Any] , lowerCAmelCase_ : list[list[float]] , lowerCAmelCase_ : list[int] ) -> int:
__lowerCAmelCase = 0.0
__lowerCA... | 53 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_com... | 53 | 1 |
def a_ ( lowerCAmelCase_ : str ):
return credit_card_number.startswith(('34', '35', '37', '4', '5', '6') )
def a_ ( lowerCAmelCase_ : str ):
__lowerCAmelCase = credit_card_number
__lowerCAmelCase = 0
__lowerCAmelCase ... | 53 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 53 | 1 |
from manim import *
class _UpperCAmelCase ( _UpperCamelCase ):
"""simple docstring"""
def lowercase ( self : int ) -> Union[str, Any]:
__lowerCAmelCase = Rectangle(height=0.5 , width=0.5 )
__lowerCAmelCase = ... | 53 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
__lowerCAmelCase = ArgumentParser(
description=(
'PyTorch TPU distributed training launch '
... | 53 | 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 import... | 53 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_availab... | 53 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, t... | 53 |
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_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : Optio... | 53 | 1 |
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
_snake_case : Optional[Any] = logging.get_logger(__name__)
class _UpperCAmelCase ( _UpperCam... | 53 |
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
_sn... | 53 | 1 |
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... | 53 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _UpperCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : Union[str, Any] ) -> List[str]:
__lowerCAmelCase = ... | 53 | 1 |
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case : List[str] = logging.get_logger(__name... | 53 |
import math
def a_ ( lowerCAmelCase_ : list, lowerCAmelCase_ : int ):
__lowerCAmelCase = len(lowerCAmelCase_ )
__lowerCAmelCase = int(math.floor(math.sqrt(lowerCAmelCase_ ) ) )
__lowerCAmelCase = 0
while arr... | 53 | 1 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
_snake_case : str = logging.get_logger(__name__)
def a_ ( lowerCAmelCase_ : Union[str, Any] ):
__lowerCAmelCas... | 53 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : List[Any], lowerCAmelCase_ : str ... | 53 | 1 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _i... | 53 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import logg... | 53 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator,... | 53 |
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 import... | 53 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 53 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
_snake_case : Any = logging.get_logger(__name__)
_sn... | 53 | 1 |
import math
import qiskit
def a_ ( lowerCAmelCase_ : int = 1, lowerCAmelCase_ : int = 1, lowerCAmelCase_ : int = 1 ):
if (
isinstance(lowerCAmelCase_, lowerCAmelCase_ )
or isinstance(lowerCAmelCase_, lowerCAmelCase_ )
or isinst... | 53 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_pr... | 53 | 1 |
def a_ ( lowerCAmelCase_ : int = 10 ):
if not isinstance(lowerCAmelCase_, lowerCAmelCase_ ) or n < 0:
raise ValueError('Invalid input' )
__lowerCAmelCase = 10**n
__lowerCAmelCase = 2_8433 * (pow(2, 783_0457, lowerCAmelCase_... | 53 |
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,
rescale,
resize,
to_channel_dimension_... | 53 | 1 |
def a_ ( lowerCAmelCase_ : str ):
__lowerCAmelCase = [0 for i in range(len(lowerCAmelCase_ ) )]
# initialize interval's left pointer and right pointer
__lowerCAmelCase , __lowerCAmelCase = 0, 0
for i in range(1, len(lowerCAm... | 53 |
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_tor... | 53 | 1 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('socket.socket' )
@patch('builtins.open' )
def a_ ( lowerCAmelCase_ : List[str], lowerCAmelCase_ : str ):
# ===== initialization =====
__lowerCAmelCase = Mock(... | 53 |
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.utils import W... | 53 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_snake_case : List[str] = {'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}
try:
if not is_vision... | 53 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 53 | 1 |
def a_ ( lowerCAmelCase_ : Union[str, Any], lowerCAmelCase_ : List[str] ):
__lowerCAmelCase = ''
for i in table:
res += inp[i - 1]
return res
def a_ ( lowerCAmelCase_ : Union[str, Any] ):
return data[1:] + data[0]
def a_ ... | 53 |
from __future__ import annotations
def a_ ( lowerCAmelCase_ : list[float] ):
if len(lowerCAmelCase_ ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
if any(i <= 0 for i in nums ):
raise ValueError('All values must be g... | 53 | 1 |
import itertools
import math
def a_ ( lowerCAmelCase_ : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
#... | 53 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Fla... | 53 | 1 |
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
_snake_case : str = datasets.logging.get_logger(__name__)
_snake_case : Union[str, Any] = '\\n@inproceedings{bleurt,\n title={BLEURT: Learning Robust Metrics... | 53 |
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,
AutoModelForMaskedLM... | 53 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_pr... | 53 |
def a_ ( lowerCAmelCase_ : int = 200_0000 ):
__lowerCAmelCase = [0 for i in range(n + 1 )]
__lowerCAmelCase = 1
__lowerCAmelCase = 1
for i in range(2, int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
for... | 53 | 1 |
import torch
from diffusers import StableDiffusionPipeline
_snake_case : str = 'path-to-your-trained-model'
_snake_case : List[str] = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('cuda')
_snake_case : List[str] = 'A... | 53 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
log... | 53 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_snake_case : Union[str, Any] = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not is_t... | 53 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_com... | 53 | 1 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 53 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 53 | 1 |
from __future__ import annotations
def a_ ( lowerCAmelCase_ : list[int] ):
if not nums:
return 0
__lowerCAmelCase = nums[0]
__lowerCAmelCase = 0
for num in nums[1:]:
__lowerCAmelCase , __lowerCAmelCase = (
... | 53 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
__lowerCAmelCase = ArgumentParser(
description=(
'PyTorch TPU distributed training launch '
... | 53 | 1 |
# Function to print upper half of diamond (pyramid)
def a_ ( lowerCAmelCase_ : Optional[int] ):
for i in range(0, lowerCAmelCase_ ):
for _ in range(0, n - i - 1 ): # printing spaces
print(' ', end='' )
for _ in range(0, i + 1 ... | 53 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_availab... | 53 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_snake_case : Optional[int] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvaila... | 53 |
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_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : Optio... | 53 | 1 |
def a_ ( lowerCAmelCase_ : int = 100_0000 ):
__lowerCAmelCase = limit + 1
__lowerCAmelCase = [0] * limit
for first_term in range(1, lowerCAmelCase_ ):
for n in range(lowerCAmelCase_, lowerCAmelCase_, lowerCAmelCase_ ):
... | 53 |
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
_sn... | 53 | 1 |
_snake_case : int = {
'a': 'AAAAA',
'b': 'AAAAB',
'c': 'AAABA',
'd': 'AAABB',
'e': 'AABAA',
'f': 'AABAB',
'g': 'AABBA',
'h': 'AABBB',
'i': 'ABAAA',
'j': 'BBBAA',
'k': 'ABAAB',
'l': 'ABABA',
'm': 'ABABB',
'n': 'ABBAA',
'o': 'ABBAB',
... | 53 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _UpperCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : Union[str, Any] ) -> List[str]:
__lowerCAmelCase = ... | 53 | 1 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRe... | 53 |
import math
def a_ ( lowerCAmelCase_ : list, lowerCAmelCase_ : int ):
__lowerCAmelCase = len(lowerCAmelCase_ )
__lowerCAmelCase = int(math.floor(math.sqrt(lowerCAmelCase_ ) ) )
__lowerCAmelCase = 0
while arr... | 53 | 1 |
_snake_case : dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.60_93_44,
"knot": 1.8_52,
}
_snake_case : dict[str, float] = {
"km/h": 1.0,
"m/s": 0.2_77_77_77_78,
"mph": 0.6_21_37_11_92,
"knot": 0.5_39_95_68_03,
}
def a_ ( ... | 53 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : List[Any], lowerCAmelCase_ : str ... | 53 | 1 |
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_configuration_common... | 53 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import logg... | 53 | 1 |
def a_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_, lowerCAmelCase_ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
__lowerCAmelCase = str(lowerCAmelCase_ )
__lowerCAmelCase = ''.join(sorte... | 53 |
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 import... | 53 | 1 |
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