code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def snake_case_ ( lowerCAmelCase_ : Optional[int] ):
__lowercase : int = {}
__lowercase ... | 233 |
from maths.prime_check import is_prime
def snake_case_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : Dict = F"Input value of [number={number}] must be an integer"
raise TypeError(lower... | 233 | 1 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : Any = logging.get_logger(__name__)
lowerCamelCase : Union[str, Any] = {
... | 233 |
# flake8: noqa
# Lint as: python3
lowerCamelCase : Optional[Any] = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .log... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCase_ : int ):
if principal <= 0:
raise Exception("""Principal borrowed must be > 0""" )
if rate_per_annum < 0:
raise Exception("""Rate of interest... | 233 |
lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e''']
def snake_case_ ( lowerCAmelCase_ : Optional[int] , low... | 233 | 1 |
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.testing_utils import D... | 233 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generatio... | 233 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCamelCase : int = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenizatio... | 233 |
# 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 ... | 233 | 1 |
import random
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : float , lowerCAmelCase_ : bool = False ):
__lowercase : dict = {i: [] for i in range(lowerCAmelCase_ )}
# if probability is greater or equal than 1, then generate a c... | 233 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCa... | 233 | 1 |
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 transformers.testing_utils im... | 233 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : int = 1000000 ):
__lowercase : List[Any] = 1
__lowercase : List[Any] = 1
__lowercase : List[Any] = {1: 1}
for inputa in range(2 , lowerCAmelCase_ ):
__lowercase ... | 233 |
def snake_case_ ( lowerCAmelCase_ : list ):
if len(lowerCAmelCase_ ) <= 1:
return [tuple(lowerCAmelCase_ )]
__lowercase : Any = []
def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ):
if k ==... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : int = 1000 ):
__lowercase : Tuple = 3
__lowercase : Any = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result... | 233 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
raise ValueError(""... | 233 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusion.modeling_roberta_series impo... | 233 |
from math import pi
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10)) | 233 | 1 |
from collections import defaultdict
def snake_case_ ( lowerCAmelCase_ : int ):
__lowercase : Tuple = 1
__lowercase : Tuple = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCAmelCase_ )
... | 233 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_devi... | 233 | 1 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : list[int | str] ):
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def snake_case_ ( lowerCAmelCase_ : list[int | str] ... | 233 |
import math
def snake_case_ ( 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
... | 233 | 1 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase : Optional[int] = logging.get_logger(__name__)
lowerCamelCase : int = [
... | 233 |
from __future__ import annotations
import math
lowerCamelCase : List[Any] = '''2020.9.26'''
lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila'''
def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas... | 233 | 1 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
lowerCamelCase : str = logging.get_logger(__name__)
lowerCamelCase : Optional[Any] = r'''
Args... | 233 |
from itertools import permutations
def snake_case_ ( lowerCAmelCase_ : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__lowercase : ... | 233 | 1 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : list[int] , lowerCAmelCase_ : int ):
if len(lowerCAmelCase_ ) == 0:
return False
__lowercase : List[Any] = len(lowerCAmelCase_ ) // 2
if a_list[midpoint] =... | 233 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : int = '''▁'''
lowerCamelCase : Optional[int] = ... | 233 | 1 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversatio... | 233 |
lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
def snake_case_ ( ):
__lowercase : List[str] = input("""Enter message: """ )
__lowercase : int = input("""Enter key [alphanumeric]: """ )
__lowercase : ... | 233 | 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 Da... | 233 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def snake_case_ ( lowerCAmelCase_ : int = 8 ):
__lowercase : str = ascii_letters + digits + punctuation
return "".join(secrets.choice(l... | 233 | 1 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, O... | 233 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_inf... | 233 | 1 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNet... | 233 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : str ):
__lowercase : Union[str, Any] = 0
__lowercase : List[Any] = len(lowerCAmelCase_ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase_ ):
... | 233 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from diffus... | 233 | 1 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import C... | 233 |
import math
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1
"""simple docstring"""
__lowercase : Any = n
__lowercase : ... | 233 | 1 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 233 |
lowerCamelCase : Dict = '''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 s... | 233 | 1 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCamelCase : int = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
... | 233 |
from maths.prime_check import is_prime
def snake_case_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : Dict = F"Input value of [number={number}] must be an integer"
raise TypeError(lower... | 233 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase : Union[str, Any] = {
'''configuration_upernet''': ['''UperNetConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable(... | 233 |
# flake8: noqa
# Lint as: python3
lowerCamelCase : Optional[Any] = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .log... | 233 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add_start_docstri... | 233 |
lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e''']
def snake_case_ ( lowerCAmelCase_ : Optional[int] , low... | 233 | 1 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
lowerCamelCase : Dict = '''\
'''
lowerCamelCase : Optional[Any] = '''
Perplexity (PPL) i... | 233 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generatio... | 233 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet import F... | 233 |
# 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 ... | 233 | 1 |
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowerCAmelCase ( __a ... | 233 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCa... | 233 | 1 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def snake_case_ ( lowerCAmelCase_ : NDArray[floataa] , lowerCAmelCase_ : NDArray[floataa] , lowerCAmelCase_ : list[int] , lowerCAmelCase_ : int , )... | 233 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ... | 233 | 1 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import C... | 233 |
def snake_case_ ( lowerCAmelCase_ : list ):
if len(lowerCAmelCase_ ) <= 1:
return [tuple(lowerCAmelCase_ )]
__lowercase : Any = []
def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ):
if k ==... | 233 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase : int = {
'''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GraphormerConfig'''],
}
try:
i... | 233 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
raise ValueError(""... | 233 | 1 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def snake_case_ ( lowerCAmelCase_ : bool = True , *lowerCAmelCase_ : Any , **lowerCAmelCase_ : str ):
if not is_tqdm_available():
... | 233 |
from math import pi
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10)) | 233 | 1 |
import os
import numpy
import onnx
def snake_case_ ( lowerCAmelCase_ : Union[str, Any] , lowerCAmelCase_ : List[Any] ):
__lowercase : Dict = a.name
__lowercase : Dict = b.name
__lowercase : int = """"""
__lowerc... | 233 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_devi... | 233 | 1 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
'''huggingface/informer-tourism-monthly''': (
... | 233 |
import math
def snake_case_ ( 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
... | 233 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCamelCase : List[Any] = {
'''configuration_trocr''': ['''TROCR_PRETRAINED_CONFIG_ARCHIV... | 233 |
from __future__ import annotations
import math
lowerCamelCase : List[Any] = '''2020.9.26'''
lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila'''
def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas... | 233 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase : List[str] = {
'''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
'''tokenizat... | 233 |
from itertools import permutations
def snake_case_ ( lowerCAmelCase_ : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__lowercase : ... | 233 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
lowerCamelCa... | 233 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : int = '''▁'''
lowerCamelCase : Optional[int] = ... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : list[int] ):
__lowercase : Any = len(lowerCAmelCase_ )
for i in range(lowerCAmelCase_ ):
for j in range(i + 1 , lowerCAmelCase_ ):
if numbers[j] < numbers[i]:
... | 233 |
lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
def snake_case_ ( ):
__lowercase : List[str] = input("""Enter message: """ )
__lowercase : int = input("""Enter key [alphanumeric]: """ )
__lowercase : ... | 233 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Optional[int] = logging.get_logger(__name__)
class lowerCAmelCase ( __a ):
'''simple docstring'''
_A : Dict = '''timm_backbone'''
def __init__( ... | 233 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def snake_case_ ( lowerCAmelCase_ : int = 8 ):
__lowercase : str = ascii_letters + digits + punctuation
return "".join(secrets.choice(l... | 233 | 1 |
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertL... | 233 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_inf... | 233 | 1 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ... | 233 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso... | 233 | 1 |
from torch import nn
class lowerCAmelCase ( nn.Module ):
'''simple docstring'''
def __init__( self : List[Any] , __a : List[Any] , __a : Optional[Any] ) -> Union[str, Any]:
"""simple docstring"""
super().__init__()
_... | 233 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from diffus... | 233 | 1 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, va... | 233 |
import math
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1
"""simple docstring"""
__lowercase : Any = n
__lowercase : ... | 233 | 1 |
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,
AdamW,
get_constant_schedule,
get_constant_schedul... | 233 |
lowerCamelCase : Dict = '''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 s... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : float ):
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("""Length must be a positive.""" )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def snake_case_ ... | 233 |
from maths.prime_check import is_prime
def snake_case_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : Dict = F"Input value of [number={number}] must be an integer"
raise TypeError(lower... | 233 | 1 |
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def snake_case_ ( lowerCAmelCase_ : np.ndarray , lowerCAmelCase_ : np.ndarray , lowerCAmelCase_ : np.ndarray , lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
... | 233 |
# flake8: noqa
# Lint as: python3
lowerCamelCase : Optional[Any] = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .log... | 233 | 1 |
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import write_b... | 233 |
lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e''']
def snake_case_ ( lowerCAmelCase_ : Optional[int] , low... | 233 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso... | 233 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generatio... | 233 | 1 |
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... | 233 |
# 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 ... | 233 | 1 |
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def snake_case_ ( *lowerCAmelCase_ : List[Any] ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : int = list(lower... | 233 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCa... | 233 | 1 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl import CORPU... | 233 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ... | 233 | 1 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble,... | 233 |
def snake_case_ ( lowerCAmelCase_ : list ):
if len(lowerCAmelCase_ ) <= 1:
return [tuple(lowerCAmelCase_ )]
__lowercase : Any = []
def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ):
if k ==... | 233 | 1 |
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 (
center_crop,
ge... | 233 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
raise ValueError(""... | 233 | 1 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowerCamelCase : Tuple = datasets.logging.get_logger(__name__)
lowerCamelCase : Any = '''\
@InProce... | 233 |
from math import pi
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10)) | 233 | 1 |
from collections.abc import Iterable
from typing import Generic, TypeVar
lowerCamelCase : Any = TypeVar('''_T''')
class lowerCAmelCase ( Generic[_T] ):
'''simple docstring'''
def __init__( self : List[Any] , __a : Iterable[_T] | None = None ) -... | 233 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_devi... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : Tuple ):
__lowercase : List[Any] = []
__lowercase : Optional[int] = set({"""(""", """[""", """{"""} )
__lowercase : Any = set({""")""", """]""", """}"""} )
__lowercase : ... | 233 |
import math
def snake_case_ ( 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
... | 233 | 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
lowerCamelCase : Tuple = logging.get_logger(__name__)
lowerCamelCase : ... | 233 |
from __future__ import annotations
import math
lowerCamelCase : List[Any] = '''2020.9.26'''
lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila'''
def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas... | 233 | 1 |
def snake_case_ ( 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)) | 233 |
from itertools import permutations
def snake_case_ ( lowerCAmelCase_ : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__lowercase : ... | 233 | 1 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...ut... | 233 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : int = '''▁'''
lowerCamelCase : Optional[int] = ... | 233 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers.utils import... | 233 |
lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
def snake_case_ ( ):
__lowercase : List[str] = input("""Enter message: """ )
__lowercase : int = input("""Enter key [alphanumeric]: """ )
__lowercase : ... | 233 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase : Tuple = {... | 233 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def snake_case_ ( lowerCAmelCase_ : int = 8 ):
__lowercase : str = ascii_letters + digits + punctuation
return "".join(secrets.choice(l... | 233 | 1 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart... | 233 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_inf... | 233 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Optional[int] = logging.get_logger(__name__)
lowerCamelCase : Dict = {
'''microsoft/git-base''': '''https://huggingf... | 233 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso... | 233 | 1 |
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditionalGeneration, BartToke... | 233 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from diffus... | 233 | 1 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def snake_case_ ( lowerCAmelCase_ : str , lowerCAmelCase_ : str = "cpu" , lowerCAmelCase_ : Union[str, None] = None ):
__lowercase : List[Any] = torch.load(lowerCAmelCase_ , ... | 233 |
import math
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1
"""simple docstring"""
__lowercase : Any = n
__lowercase : ... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : list[int] ):
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__lowercase : str = sum(lowerCAmelCase_ ) / len(lowerCAmelCase_ ) # Calculate the average
... | 233 |
lowerCamelCase : Dict = '''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 s... | 233 | 1 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : List[Any] , __a : Any ) -> Any:
"""simple docstring"""
__lowercase : ... | 233 |
from maths.prime_check import is_prime
def snake_case_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : Dict = F"Input value of [number={number}] must be an integer"
raise TypeError(lower... | 233 | 1 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""" , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("""input_in_memory_max_size""" , ["""default""", 0, 100 * 2**20, 900 * 2**20] )
def snake... | 233 |
# flake8: noqa
# Lint as: python3
lowerCamelCase : Optional[Any] = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .log... | 233 | 1 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDi... | 233 |
lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e''']
def snake_case_ ( lowerCAmelCase_ : Optional[int] , low... | 233 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : Union[str, Any] = {
'''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/config... | 233 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generatio... | 233 | 1 |
import numpy as np
def snake_case_ ( lowerCAmelCase_ : np.array ):
return 1 / (1 + np.exp(-vector ))
def snake_case_ ( lowerCAmelCase_ : np.array ):
return vector * sigmoid(1.702 * vector )
if __name__ == "__main__":
import doctest
doctest.testmo... | 233 |
# 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 ... | 233 | 1 |
from math import factorial
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
... | 233 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCa... | 233 | 1 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
lowerCamelCase : Any = logging.getLogg... | 233 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ... | 233 | 1 |
lowerCamelCase : Dict = '''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 s... | 233 |
def snake_case_ ( lowerCAmelCase_ : list ):
if len(lowerCAmelCase_ ) <= 1:
return [tuple(lowerCAmelCase_ )]
__lowercase : Any = []
def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ):
if k ==... | 233 | 1 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessi... | 233 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
raise ValueError(""... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int , lowerCAmelCase_ : Optional[Any] , lowerCAmelCase_ : int , lowerCAmelCase_ : int , lowerCAmelCase_ : Union[str, Any] ):
if index == r:
for j in range(lowerCA... | 233 |
from math import pi
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10)) | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : int = 50000000 ):
__lowercase : Union[str, Any] = set()
__lowercase : Union[str, Any] = int((limit - 24) ** (1 / 2) )
__lowercase : List[str] = set(range(3 , prime_square_limit + 1 ... | 233 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_devi... | 233 | 1 |
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int , lowerCAmelCase_ : Optional... | 233 |
import math
def snake_case_ ( 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
... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : str , lowerCAmelCase_ : str ):
__lowercase : int = len(lowerCAmelCase_ )
__lowercase : List[Any] = len(lowerCAmelCase_ )
__lowercase : int = [[False for _ in range(m + 1 )]... | 233 |
from __future__ import annotations
import math
lowerCamelCase : List[Any] = '''2020.9.26'''
lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila'''
def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas... | 233 | 1 |
lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e''']
def snake_case_ ( lowerCAmelCase_ : Optional[int] , low... | 233 |
from itertools import permutations
def snake_case_ ( lowerCAmelCase_ : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__lowercase : ... | 233 | 1 |
import math
def snake_case_ ( lowerCAmelCase_ : list , lowerCAmelCase_ : int ):
__lowercase : List[str] = len(lowerCAmelCase_ )
__lowercase : Any = int(math.floor(math.sqrt(lowerCAmelCase_ ) ) )
__lowercase : ... | 233 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : int = '''▁'''
lowerCamelCase : Optional[int] = ... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : int ):
if number < 0:
raise ValueError("""number must not be negative""" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod() | 233 |
lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
def snake_case_ ( ):
__lowercase : List[str] = input("""Enter message: """ )
__lowercase : int = input("""Enter key [alphanumeric]: """ )
__lowercase : ... | 233 | 1 |
import logging
import os
from .state import PartialState
class lowerCAmelCase ( logging.LoggerAdapter ):
'''simple docstring'''
@staticmethod
def lowerCAmelCase ( __a : List[str] ) -> List[Any]:
"""simple docstring"""
__lowercase ... | 233 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def snake_case_ ( lowerCAmelCase_ : int = 8 ):
__lowercase : str = ascii_letters + digits + punctuation
return "".join(secrets.choice(l... | 233 | 1 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : Union[str, Any] , __a : int ) -> None:
"""simple docstring"""
__lowercase : Optional[int] ... | 233 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_inf... | 233 | 1 |
def snake_case_ ( lowerCAmelCase_ : int ):
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def snake_case_ ( lowerCAmelCase_ : int ):
__lowercase : Tuple = 0
__lowercase : Optional[int] = number
w... | 233 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso... | 233 | 1 |
from maths.prime_check import is_prime
def snake_case_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : Dict = F"Input value of [number={number}] must be an integer"
raise TypeError(lower... | 233 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from diffus... | 233 | 1 |
from collections.abc import Sequence
def snake_case_ ( lowerCAmelCase_ : Sequence[int] | None = None ):
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__lowercase : Any = nums[0]
for i in range(1 ... | 233 |
import math
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1
"""simple docstring"""
__lowercase : Any = n
__lowercase : ... | 233 | 1 |
import math
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1
"""simple docstring"""
__lowercase : Any = n
__lowercase : ... | 233 |
lowerCamelCase : Dict = '''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 s... | 233 | 1 |
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTeacher,
EfficientForm... | 233 |
from maths.prime_check import is_prime
def snake_case_ ( lowerCAmelCase_ : int ):
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__lowercase : Dict = F"Input value of [number={number}] must be an integer"
raise TypeError(lower... | 233 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase : Tuple = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Re... | 233 |
# flake8: noqa
# Lint as: python3
lowerCamelCase : Optional[Any] = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .log... | 233 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ..... | 233 |
lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e''']
def snake_case_ ( lowerCAmelCase_ : Optional[int] , low... | 233 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : Any = logging.get_logger(__name__)
lowerCamelCase ... | 233 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generatio... | 233 | 1 |
import sys
lowerCamelCase : Tuple = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
'''6... | 233 |
# 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 ... | 233 | 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
lowerCamelCase : Optional[int] = logging.get_logger(__name__)
lowerCamelCase ... | 233 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCa... | 233 | 1 |
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowerCamelCase : List[Any] = argparse.ArgumentParser()
parser.add_argument(
'''--checkpoint_path''', default=No... | 233 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ... | 233 | 1 |
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa: F401
deprecate... | 233 |
def snake_case_ ( lowerCAmelCase_ : list ):
if len(lowerCAmelCase_ ) <= 1:
return [tuple(lowerCAmelCase_ )]
__lowercase : Any = []
def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ):
if k ==... | 233 | 1 |
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCAmelCase :
'''simple docstring'''
pass | 233 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
raise ValueError(""... | 233 | 1 |
from __future__ import annotations
from typing import Any
class lowerCAmelCase ( __a ):
'''simple docstring'''
pass
class lowerCAmelCase :
'''simple docstring'''
def __init__( self : List[Any] , __a : Any ) -> None:
"""si... | 233 |
from math import pi
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10)) | 233 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassification,
D... | 233 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_devi... | 233 | 1 |
from __future__ import annotations
from typing import Any
def snake_case_ ( lowerCAmelCase_ : list ):
if not postfix_notation:
return 0
__lowercase : Dict = {"""+""", """-""", """*""", """/"""}
__lowercase : list[Any] = []
... | 233 |
import math
def snake_case_ ( 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
... | 233 | 1 |
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