code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ )-> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(SCREAMING_SNAKE... | 356 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diff... | 60 | 0 |
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
SCREAMING_SNAKE_CASE :Optional[Any] = logging.get_logger(__name__)
SCREAMING_... | 357 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_... | 60 | 0 |
from __future__ import annotations
import math
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negativ... | 358 |
from ...processing_utils import ProcessorMixin
class __magic_name__ ( snake_case ):
UpperCamelCase_ :str = """SpeechT5FeatureExtractor"""
UpperCamelCase_ :Optional[int] = """SpeechT5Tokenizer"""
def __init__( self , ... | 60 | 0 |
import itertools
import string
from collections.abc import Generator, Iterable
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ )-> Generator[tuple[str, ...], None, None]:
"""simple docstring"""
UpperCamelCase_ = iter(SCREAMING_SNAKE_CASE_ )
... | 359 |
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... | 60 | 0 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall... | 360 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> list:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE_ ) <= 1:
return lst
UpperCamelCase_ = 1
while i < len(SCREAMING_SNAKE_CASE_ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
... | 60 | 0 |
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... | 361 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE :Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE :Union[str, Any] = {
"""BridgeTower/bridgetow... | 60 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from... | 362 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokeniz... | 60 | 0 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderK... | 363 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE ... | 60 | 0 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 364 |
# 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 requ... | 60 | 0 |
SCREAMING_SNAKE_CASE :Tuple = {str(digit): digit**5 for digit in range(10)}
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(SCREAMING_SNAKE_CASE_ ) )
def lowerCAmelCa... | 365 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 60 | 0 |
"""simple docstring"""
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
... | 366 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ = 1_0_0 )-> int:
"""simple docstring"""
UpperCamelCase_ = (n * (n + 1) // 2) ** 2
UpperCamelCase_ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(F'''{solutio... | 60 | 0 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
SCREAMING_SNAKE_CASE :Optional[int] = """\
@inproceedings{snover-etal-2006-study,
title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",
author = \"Snover, Matthew... | 367 |
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 impor... | 60 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __magic_name__ ( snake_case ):
Upper... | 368 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
SCREAMING_SNAKE_CASE :List[str] = logging.getLogger(__name__)
def lowerCAmelCase( )-> Union[str, Any]:
"""simple docstring"""
... | 60 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import l... | 369 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_availab... | 60 | 0 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> list:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE_ ) <= 1:
return lst
UpperCamelCase_ = 1
while i < len(SCREAMING_SNAKE_CASE_ ):
if lst[i - 1] <= lst[i]:
i += 1
... | 370 |
import unittest
import numpy as np
from transformers import AlbertConfig, 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
... | 60 | 0 |
import os
import sys
import unittest
SCREAMING_SNAKE_CASE :Tuple = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get... | 371 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = False )-> str:
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
UpperCamelCase_ = f"Expected string as input, found {type(SCREAMING_SNAKE_CASE_ )}"
... | 60 | 0 |
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 impor... | 350 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, lo... | 60 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...u... | 351 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
i... | 60 | 0 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> int:
"""simple docstring"""
UpperCamelCase_ = len(SCREAMING_SNAKE_CASE_ )
UpperCamelCase_ = len(matrix[0] )
UpperCamelCase_ = min(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ )
for row in range... | 352 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
... | 60 | 0 |
"""simple docstring"""
#
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc_per_n... | 353 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_util... | 60 | 0 |
from ...processing_utils import ProcessorMixin
class __magic_name__ ( snake_case ):
UpperCamelCase_ :str = """SpeechT5FeatureExtractor"""
UpperCamelCase_ :Optional[int] = """SpeechT5Tokenizer"""
def __init__( self ... | 354 |
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 accelerat... | 60 | 0 |
from math import pi, sqrt, tan
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> float:
"""simple docstring"""
if side_length < 0:
raise ValueError("surface_area_cube() only accepts non-negative values" )
return 6 * side_length**2
def lowerCAmel... | 355 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
SCREAMING_SNAKE_CASE :Optional[int] = """\
@inproceedings{snover-etal-2006-study,
title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",
author = \"Snover, Matthew... | 60 | 0 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Da... | 356 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diff... | 60 | 0 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproces... | 357 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_... | 60 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging... | 358 |
from ...processing_utils import ProcessorMixin
class __magic_name__ ( snake_case ):
UpperCamelCase_ :str = """SpeechT5FeatureExtractor"""
UpperCamelCase_ :Optional[int] = """SpeechT5Tokenizer"""
def __init__( self , ... | 60 | 0 |
import math
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ )-> int:
"""simple docstring"""
UpperCamelCase_ = len(SCREAMING_SNAKE_CASE_ )
UpperCamelCase_ = int(math.floor(math.sqrt(SCREAMING_SNAKE_CASE_ ) ) )
UpperCamelCase_ ... | 359 |
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... | 60 | 0 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __magic_name__ ( unittest.TestCase ):
def UpperCAmelCase_ ( ... | 360 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> list:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE_ ) <= 1:
return lst
UpperCamelCase_ = 1
while i < len(SCREAMING_SNAKE_CASE_ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
... | 60 | 0 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import Image... | 361 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE :Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE :Union[str, Any] = {
"""BridgeTower/bridgetow... | 60 | 0 |
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 Tokeniz... | 362 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokeniz... | 60 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE :Optional[Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_AR... | 363 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE ... | 60 | 0 |
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
SCREAMING_SNAKE_CASE :Union[str, Any] = logging.get_logger(__name__)
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> List[int]:
"""simple docstring"""
... | 364 |
# 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 requ... | 60 | 0 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_util... | 365 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 60 | 0 |
"""simple docstring"""
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ )-> List[str]:
"""simple docstring"""
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
... | 366 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ = 1_0_0 )-> int:
"""simple docstring"""
UpperCamelCase_ = (n * (n + 1) // 2) ** 2
UpperCamelCase_ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(F'''{solutio... | 60 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE :str = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
try... | 367 |
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 impor... | 60 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...token... | 368 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
SCREAMING_SNAKE_CASE :List[str] = logging.getLogger(__name__)
def lowerCAmelCase( )-> Union[str, Any]:
"""simple docstring"""
... | 60 | 0 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
... | 369 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_availab... | 60 | 0 |
import math
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> list:
"""simple docstring"""
UpperCamelCase_ = [True] * n
UpperCamelCase_ = False
UpperCamelCase_ = False
UpperCamelCase_ = True
for i in range(3 , int(n*... | 370 |
import unittest
import numpy as np
from transformers import AlbertConfig, 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
... | 60 | 0 |
import requests
from bsa import BeautifulSoup
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ = "https://www.worldometers.info/coronavirus" )-> dict:
"""simple docstring"""
UpperCamelCase_ = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE_ ).text , "html.parser" )
... | 371 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = False )-> str:
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
UpperCamelCase_ = f"Expected string as input, found {type(SCREAMING_SNAKE_CASE_ )}"
... | 60 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
... | 61 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https... | 61 | 1 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError... | 61 |
'''simple docstring'''
# 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 ... | 61 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase_ = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch_avail... | 61 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.j... | 61 | 1 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCAmelCase_ = logging.get_logger('transformers.models.speecht5')
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : L... | 61 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTe... | 61 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if i... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : bool = False ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
UpperCAmelCase__ = F'''Expected string as input, ... | 61 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
'feature_extraction_mctct': ['MCTCTFeatureExtractor']... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCamelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gate:""" )
print("... | 61 | 1 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
UpperCAmelCase_ = logging.getLogger(__name__)
if __name__ == "__... | 61 |
'''simple docstring'''
# 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
... | 61 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
Condi... | 61 |
'''simple docstring'''
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors ... | 61 | 1 |
'''simple docstring'''
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def _UpperCamelCase ( ... | 61 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ ... | 61 | 1 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _UpperCamelCase ( ):
'''simple docstring'''
UpperCAmelCase__ = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
UpperCAmelCase__ ... | 61 |
'''simple docstring'''
UpperCAmelCase_ = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
UpperCAmelCase__ = 0
while number:
# Increased Speed Slightly by checking ... | 61 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
Up... | 61 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 61 | 1 |
'''simple docstring'''
import requests
UpperCAmelCase_ = '' # <-- Put your OpenWeatherMap appid here!
UpperCAmelCase_ = 'https://api.openweathermap.org/data/2.5/'
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "Chicago" , SCREAMING_SNAKE_CASE__ : str = APPID ):
'''sim... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : list[list[int]] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : set ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ = ... | 61 | 1 |
'''simple docstring'''
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Con... | 61 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
UpperCAmelCase_ = logging.get_logger(__name__)
... | 61 | 1 |
'''simple docstring'''
import enum
import shutil
import sys
UpperCAmelCase_ , UpperCAmelCase_ = shutil.get_terminal_size()
UpperCAmelCase_ = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class lowerCAmelCase_ ( enum.Enum ):
'''simple docstring'''
lowerCAme... | 61 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/goog... | 61 | 1 |
'''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, to... | 61 |
'''simple docstring'''
import os
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : Any ):
'''simple docstring'''
UpperCAmelCase__ = len(grid[0] )
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ = 0
UpperCAmelCase__ ... | 61 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : bool = False ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
UpperCAmelCase__ = F'''Expected string as input, ... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : list[list[int]] ):
'''simple docstring'''
def update_area_of_max_square(SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int... | 61 | 1 |
'''simple docstring'''
from __future__ import annotations
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : List[str] , _UpperCAmelCase : int ):
"""simple docstring"""
UpperCAmelCase__ = order
# a_{0} ... a_{k}
... | 61 |
'''simple docstring'''
import enum
import shutil
import sys
UpperCAmelCase_ , UpperCAmelCase_ = shutil.get_terminal_size()
UpperCAmelCase_ = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class lowerCAmelCase_ ( enum.Enum ):
'''simple docstring'''
lowerCAme... | 61 | 1 |
'''simple docstring'''
from __future__ import annotations
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Dict , _UpperCAmelCase : int = 0 ):
"""simple docstring"""
UpperCAmelCase__ = key
def SCREAMING_S... | 61 |
'''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
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {... | 61 | 1 |
'''simple docstring'''
# Imports
import numpy as np
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Tuple , _UpperCAmelCase : List[str]=None , _UpperCAmelCase : int=None , _UpperCAmelCase : Dict=None , _UpperCAmelCase ... | 61 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
Uppe... | 61 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
while b:
UpperCAmelCase__ , UpperCAmelCase__ = b, a % b
return a
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : ... | 61 | 1 |
'''simple docstring'''
import os
UpperCAmelCase_ = {'I': 1, 'V': 5, 'X': 1_0, 'L': 5_0, 'C': 1_0_0, 'D': 5_0_0, 'M': 1_0_0_0}
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
UpperCAmelCase__ = 0
UpperCAmelCase__ = 0
whi... | 61 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProc... | 61 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase_ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 61 |
'''simple docstring'''
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'nielsr/canine-s': 2_0_4_8,
}
# Unicode defines 1,114,112 total ... | 61 | 1 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCAmelCase_ = [
'good first issue',
'feature request',
'wip',
]
def _UpperCamelCase ( ):
'''simple docstring'''
UpperCAmelCase__ = Github(os.environ["""GITHUB_TO... | 61 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https... | 61 | 1 |
'''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config im... | 61 |
'''simple docstring'''
# 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 ... | 61 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCAmelCase_ = {'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
UpperCA... | 61 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.j... | 61 | 1 |
'''simple docstring'''
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
UpperCAmelCase_ = datasets.logging.get_logger(__name__)
UpperCAmelCase_ = '\\n@InProceedings{moosavi2019mi... | 61 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTe... | 61 | 1 |
'''simple docstring'''
# 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
... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : bool = False ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
UpperCAmelCase__ = F'''Expected string as input, ... | 61 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
try:
if not... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCamelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gate:""" )
print("... | 61 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f"{price_plus_tax(1_0_0, 0.25) = }")
print(f"{price_plus_tax(125.50, 0.05) ... | 61 |
'''simple docstring'''
# 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
... | 61 | 1 |
'''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCAmelCase_ :
'''simple docstring'''
pass
| 61 |
'''simple docstring'''
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors ... | 61 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = '▁'
... | 61 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ ... | 61 | 1 |
'''simple docstring'''
UpperCAmelCase_ = '\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
UpperCAmelCase_ = [{'type': 'code', 'content': INSTALL_CONTENT}]
Uppe... | 61 |
'''simple docstring'''
UpperCAmelCase_ = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
UpperCAmelCase__ = 0
while number:
# Increased Speed Slightly by checking ... | 61 | 1 |
'''simple docstring'''
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors ... | 61 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 61 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
if not all(x.isalpha() for x in string ):
raise ValueError("""String must only contain alphabetic characters.""" )
UpperCAmelCase__ = sorted(string.lower() )
ret... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : list[list[int]] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : set ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ = ... | 61 | 1 |
'''simple docstring'''
import string
from math import logaa
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
UpperCAmelCase__ = document.translate(
str.maketrans("""""" , """""" , string.punctua... | 61 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
UpperCAmelCase_ = logging.get_logger(__name__)
... | 61 | 1 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 61 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/goog... | 61 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from tr... | 61 |
'''simple docstring'''
import os
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : Any ):
'''simple docstring'''
UpperCAmelCase__ = len(grid[0] )
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ = 0
UpperCAmelCase__ ... | 61 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class lowerCAmelCase_ :
'''simple docstring'''
lowerCAm... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : list[list[int]] ):
'''simple docstring'''
def update_area_of_max_square(SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int... | 61 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cac... | 61 |
'''simple docstring'''
import enum
import shutil
import sys
UpperCAmelCase_ , UpperCAmelCase_ = shutil.get_terminal_size()
UpperCAmelCase_ = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class lowerCAmelCase_ ( enum.Enum ):
'''simple docstring'''
lowerCAme... | 61 | 1 |
'''simple docstring'''
UpperCAmelCase_ = [
'Audio',
'Array2D',
'Array3D',
'Array4D',
'Array5D',
'ClassLabel',
'Features',
'Sequence',
'Value',
'Image',
'Translation',
'TranslationVariableLanguages',
]
from .audio import Audio
from .features import ArrayaD, ... | 61 |
'''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
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {... | 61 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : list[str] ):
'''simple docstring'''
UpperCAmelCase__ = """"""
for word_or_phrase in separated:
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE_... | 61 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
Uppe... | 61 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json',
}
class lowe... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
while b:
UpperCAmelCase__ , UpperCAmelCase__ = b, a % b
return a
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : ... | 61 | 1 |
'''simple docstring'''
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
... | 61 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProc... | 61 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, p... | 61 |
'''simple docstring'''
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'nielsr/canine-s': 2_0_4_8,
}
# Unicode defines 1,114,112 total ... | 61 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'BAAI/AltCLIP': 'https://huggingface.co/BAAI/AltCLIP/resolve/main/config.... | 61 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https... | 61 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
UpperCAmelCase_ = logging.get... | 61 |
'''simple docstring'''
# 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 ... | 61 | 1 |
'''simple docstring'''
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers im... | 61 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.j... | 61 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_roformer': ['ROFORMER_PRETRAINED... | 61 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTe... | 61 | 1 |
'''simple docstring'''
from __future__ import annotations
UpperCAmelCase_ = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class lowerCAmelCase_ :
'''simple docstring'''
d... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : bool = False ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
UpperCAmelCase__ = F'''Expected string as input, ... | 61 | 1 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
UpperCAmelCase__ = []... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCamelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gate:""" )
print("... | 61 | 1 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_a... | 61 |
'''simple docstring'''
# 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
... | 61 | 1 |
'''simple docstring'''
def _UpperCamelCase ( ):
'''simple docstring'''
UpperCAmelCase__ = []
UpperCAmelCase__ = 1
while len(SCREAMING_SNAKE_CASE__ ) < 1e6:
constant.append(str(SCREAMING_SNAKE_CASE__ ) )
i += 1
UpperCAmelCase__ = """... | 61 |
'''simple docstring'''
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors ... | 61 | 1 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self : Union[str, Any] , _UpperCAmelCase ... | 61 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ ... | 61 | 1 |
'''simple docstring'''
import numpy as np
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[Any] ):
"""simple docstring"""
UpperCAmelCase__ = (0, 0)
UpperCAmelCase__ = None
UpperCAmelCase__ ... | 61 |
'''simple docstring'''
UpperCAmelCase_ = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
UpperCAmelCase__ = 0
while number:
# Increased Speed Slightly by checking ... | 61 | 1 |
'''simple docstring'''
import os
import numpy
import onnx
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : Any , SCREAMING_SNAKE_CASE__ : List[str] ):
'''simple docstring'''
UpperCAmelCase__ = a.name
UpperCAmelCase__ = b.name
UpperCAmelCase__ ... | 61 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 61 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : List[str] )... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : list[list[int]] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : set ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ = ... | 61 | 1 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
Uppe... | 61 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
UpperCAmelCase_ = logging.get_logger(__name__)
... | 61 | 1 |
'''simple docstring'''
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
Uppe... | 61 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/goog... | 61 | 1 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
UpperCAmelCase_ = pd.read_csv('sample_data.csv', header=None)
Upp... | 61 |
'''simple docstring'''
import os
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : Any ):
'''simple docstring'''
UpperCAmelCase__ = len(grid[0] )
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ = 0
UpperCAmelCase__ ... | 61 | 1 |
'''simple docstring'''
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
UpperCAmelCase_ ... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : list[list[int]] ):
'''simple docstring'''
def update_area_of_max_square(SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int... | 61 | 1 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
lowerCAmelCase_ : Optional[int] = (DDIMParallelScheduler,)
lowerCAmelCa... | 61 |
'''simple docstring'''
import enum
import shutil
import sys
UpperCAmelCase_ , UpperCAmelCase_ = shutil.get_terminal_size()
UpperCAmelCase_ = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class lowerCAmelCase_ ( enum.Enum ):
'''simple docstring'''
lowerCAme... | 61 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-cc-news-pretrained-embedder/re... | 61 |
'''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
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {... | 61 | 1 |
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