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 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : List[Any] = logging.get_logger(__name__)
def a__ ( lowercase : Tuple ) ... | 370 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : Tuple ) -> int:
'''simple d... | 287 | 0 |
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from transformers.utils imp... | 371 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 287 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, log... | 350 |
'''simple docstring'''
import math
def a__ ( lowercase : float, lowercase : float ) -> float:
"""simple docstring"""
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of init... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : str ) -> str:
"""simple docstring"""
return " ".join(
''''''.join(word[::-1] ) if len(lowercase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
pri... | 351 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Optional[Any] = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
if not isinstance(lowercase, lowercase ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
... | 352 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowercase : int, lowercase : int ) -> int:
# BASE CASE
if row >= rows or col >= cols... | 287 | 0 |
'''simple docstring'''
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_comm... | 353 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgume... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 354 |
'''simple docstring'''
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
if not isinstance(lowercase, lowercase ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : int = 1000000 ) -> int:
"""simple docstring"""
_UpperCamelCase = set(range(3, lowercase, 2 ) )
primes.add(2 )
for p in range(3, lowercase, 2 ):
if p not in primes:
continue
... | 355 |
'''simple docstring'''
import random
class __lowerCAmelCase :
"""simple docstring"""
@staticmethod
def snake_case__ ( lowerCAmelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
_UpperCamelCase ... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : list[int], lowercase : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(lowercase : int ) -> int:
if target < 0:
return 0
if target == 0:
... | 356 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(lowercase, x % y )
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstrin... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configurat... | 357 |
'''simple docstring'''
import argparse
import os
# New Code #
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... | 287 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 358 |
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_cas... | 287 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
cl... | 359 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as ... | 287 | 0 |
'''simple docstring'''
from collections import deque
def a__ ( lowercase : Optional[Any] ) -> Any:
"""simple docstring"""
_UpperCamelCase = len(lowercase )
_UpperCamelCase = deque()
_UpperCamelCase = [False for _ in range(lowercase )]
... | 360 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
lowercase__ : Optional[Any] = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def __ini... | 287 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ : str = 50_00_00
lowercase__ : List[Any] = os.path.split(__file__)
lowercase__ : Optional[Any] = os.pat... | 361 |
'''simple docstring'''
from math import isclose, sqrt
def a__ ( lowercase : float, lowercase : float, lowercase : float ) -> tuple[float, float, float]:
"""simple docstring"""
_UpperCamelCase = point_y / 4 / point_x
_UpperCamelCase = 2 * normal_grad... | 287 | 0 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowercas... | 362 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Tuple = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwr... | 287 | 0 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test... | 363 |
'''simple docstring'''
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 TokenizerTes... | 287 | 0 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def a__ ( lowercase : float, lowercase : float, lowercase : int ) -> float:
"""simple docstring"""
_UpperCamelCase = x
_UpperCamelCase = y
for step in range(lowercase ... | 364 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list[int], lowercase : list[int], lowercase : int ) -> tuple[float, list[float]]:
"""simple docstring"""
_UpperCamelCase = list(range(len(lowercase ) ) )
_UpperCamelC... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : Tuple , lowerCAmelCase__ : list[tuple[float, float]] ) -> List[str]:
... | 365 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : List[Any] = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
... | 287 | 0 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceCl... | 366 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowercase__ : List[Any] = parse(importlib.metadata.version('torch'))
def a__ ( lowercase : Union[str, Version], lo... | 287 | 0 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgume... | 367 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def a__ ( lowercase : Tuple ) -> Dict:
"""simple docstring"""
_U... | 287 | 0 |
'''simple docstring'''
import argparse
import os
from accelerate.test_utils import execute_subprocess_async
def a__ ( lowercase : Any=None ) -> List[Any]:
"""simple docstring"""
if subparsers is not None:
_UpperCamelCase = subparsers.add_parser('''test''' ... | 368 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def a__ ( lowercase : str ) -> Optional[int]:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase = img.shape[0], img.shape[1]
# converting each pixel's color to its nega... | 287 | 0 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransfo... | 369 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available()... | 287 | 0 |
'''simple docstring'''
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accele... | 370 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : Tuple ) -> int:
'''simple d... | 287 | 0 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( lowercase : str ) -> Any:
"""simple docstring"""
_UpperCamelCase = {}
_UpperCam... | 371 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 287 | 0 |
'''simple docstring'''
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffus... | 350 |
'''simple docstring'''
import math
def a__ ( lowercase : float, lowercase : float ) -> float:
"""simple docstring"""
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of init... | 287 | 0 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
_snake_case : Tuple = (DDIMParallelScheduler,)
_snake_case... | 351 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Optional[Any] = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 287 | 0 |
'''simple docstring'''
import json
import sys
def a__ ( lowercase : List[Any], lowercase : Union[str, Any] ) -> str:
"""simple docstring"""
with open(lowercase, encoding='''utf-8''' ) as f:
_UpperCamelCase = json.load(lowerca... | 352 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowercase : int, lowercase : int ) -> int:
# BASE CASE
if row >= rows or col >= cols... | 287 | 0 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
_UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
_UpperCAmelCase : ... | 353 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgume... | 287 | 0 |
'''simple docstring'''
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : Union[str, Any] , lowerCAmelCase__ : int ) -> None:
'''simple docstring'''
_UpperCamelCase = size
_UpperCamel... | 354 |
'''simple docstring'''
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
if not isinstance(lowercase, lowercase ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import gcd
def a__ ( lowercase : int, lowercase : int = 2, lowercase : int = 1, lowercase : int = 3, ) -> int | None:
"""simple docstring"""
if num < 2:
raise ValueError('''The input val... | 355 |
'''simple docstring'''
import random
class __lowerCAmelCase :
"""simple docstring"""
@staticmethod
def snake_case__ ( lowerCAmelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
_UpperCamelCase ... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : int ) -> list:
"""simple docstring"""
if bit_count < 0:
raise ValueError('''The given input must be positive''' )
# get the generated string sequence
_UpperCamelCase = gray_code_sequence_string(lowercase ... | 356 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(lowercase, x % y )
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstrin... | 287 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ : Union[str, Any] = {
'co... | 357 |
'''simple docstring'''
import argparse
import os
# New Code #
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... | 287 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
lowercase__ : Any = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def __init__( ... | 358 |
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_cas... | 287 | 0 |
'''simple docstring'''
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
lowercase__ : Dict = logging.getLogger()
@unittest.skip('Temporarily di... | 359 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as ... | 287 | 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,
BertTokenizer,
... | 360 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
lowercase__ : Optional[Any] = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def __ini... | 287 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase__ : Dict = lo... | 361 |
'''simple docstring'''
from math import isclose, sqrt
def a__ ( lowercase : float, lowercase : float, lowercase : float ) -> tuple[float, float, float]:
"""simple docstring"""
_UpperCamelCase = point_y / 4 / point_x
_UpperCamelCase = 2 * normal_grad... | 287 | 0 |
from __future__ import annotations
import os
from typing import Any
import requests
lowercase__ : Optional[int] = 'https://api.github.com'
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase__ : Optional[int] = BASE_URL + '/user... | 362 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Tuple = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwr... | 287 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
lowercase__ : List[Any] = loggin... | 363 |
'''simple docstring'''
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 TokenizerTes... | 287 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : str = {
'Visual-Attention-Network/van-base': (
'https://huggingface.co/Visual-Attention-Network/v... | 364 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list[int], lowercase : list[int], lowercase : int ) -> tuple[float, list[float]]:
"""simple docstring"""
_UpperCamelCase = list(range(len(lowercase ) ) )
_UpperCamelC... | 287 | 0 |
'''simple docstring'''
from scipy.stats import pearsonr
import datasets
lowercase__ : Any = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies... | 365 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : List[Any] = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
... | 287 | 0 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
... | 366 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowercase__ : List[Any] = parse(importlib.metadata.version('torch'))
def a__ ( lowercase : Union[str, Version], lo... | 287 | 0 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def a__ ( lowercase : Tuple ) -> Dict:
"""simple docstring"""
_U... | 367 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def a__ ( lowercase : Tuple ) -> Dict:
"""simple docstring"""
_U... | 287 | 0 |
'''simple docstring'''
import random
class __lowerCAmelCase :
"""simple docstring"""
@staticmethod
def snake_case__ ( lowerCAmelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
_UpperCamelCase ... | 368 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def a__ ( lowercase : str ) -> Optional[int]:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase = img.shape[0], img.shape[1]
# converting each pixel's color to its nega... | 287 | 0 |
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_cas... | 369 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available()... | 287 | 0 |
'''simple docstring'''
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : int ) -> Tuple:
'''simple docstring'''
_UpperCamelCase = ''''''
_UpperCamelCase = ''''''
_UpperCamel... | 370 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : Tuple ) -> int:
'''simple d... | 287 | 0 |
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoModelForMaskedLM... | 371 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : float, lowercase : float, lowercase : float ) -> dict[str, float]:
"""simple docstring"""
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('''One and only ... | 350 |
'''simple docstring'''
import math
def a__ ( lowercase : float, lowercase : float ) -> float:
"""simple docstring"""
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of init... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowercase : int, lowercase : int ) -> int:
# BASE CASE
if row >= rows or col >= cols... | 351 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Optional[Any] = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 287 | 0 |
'''simple docstring'''
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
... | 352 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowercase : int, lowercase : int ) -> int:
# BASE CASE
if row >= rows or col >= cols... | 287 | 0 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
_UpperCAmelCase ... | 353 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgume... | 287 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available()... | 354 |
'''simple docstring'''
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
if not isinstance(lowercase, lowercase ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
... | 287 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Padding... | 355 |
'''simple docstring'''
import random
class __lowerCAmelCase :
"""simple docstring"""
@staticmethod
def snake_case__ ( lowerCAmelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
_UpperCamelCase ... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(lowercase, x % y )
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstrin... | 356 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(lowercase, x % y )
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstrin... | 287 | 0 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowercase__ : Dict = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
... | 357 |
'''simple docstring'''
import argparse
import os
# New Code #
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... | 287 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : List[str] = {
... | 358 |
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_cas... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list[int], lowercase : list[int], lowercase : int ) -> tuple[float, list[float]]:
"""simple docstring"""
_UpperCamelCase = list(range(len(lowercase ) ) )
_UpperCamelC... | 359 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as ... | 287 | 0 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __lowerCAmelCase ( yaml.SafeLoader ):
"""simple docstring"""
def snake_case__ ( self : Union[str, Any] , lowerCAmelCase__ ... | 360 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
lowercase__ : Optional[Any] = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def __ini... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[str] , lowerCAmelCase__ : Collec... | 361 |
'''simple docstring'''
from math import isclose, sqrt
def a__ ( lowercase : float, lowercase : float, lowercase : float ) -> tuple[float, float, float]:
"""simple docstring"""
_UpperCamelCase = point_y / 4 / point_x
_UpperCamelCase = 2 * normal_grad... | 287 | 0 |
lowercase__ : Optional[Any] = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
def a__ ( lowercase : dict, lowercase : Union[str, Any], lowercase : int ) -> list[s... | 362 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Tuple = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwr... | 287 | 0 |
from math import factorial
def a__ ( lowercase : int = 100 ) -> int:
"""simple docstring"""
return sum(map(lowercase, str(factorial(lowercase ) ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
| 363 |
'''simple docstring'''
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 TokenizerTes... | 287 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNo... | 364 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list[int], lowercase : list[int], lowercase : int ) -> tuple[float, list[float]]:
"""simple docstring"""
_UpperCamelCase = list(range(len(lowercase ) ) )
_UpperCamelC... | 287 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=__magic_name__ )
class __lowerCAmelCase ( __magic_name__ ):
"""simple docst... | 365 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : List[Any] = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
... | 287 | 0 |
'''simple docstring'''
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def a__ ( lowercase : Optional[Any], lowercase : Any,... | 366 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowercase__ : List[Any] = parse(importlib.metadata.version('torch'))
def a__ ( lowercase : Union[str, Version], lo... | 287 | 0 |
'''simple docstring'''
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def a__ ( ... | 367 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def a__ ( lowercase : Tuple ) -> Dict:
"""simple docstring"""
_U... | 287 | 0 |
'''simple docstring'''
import json
import os
from ...utils.constants import SAGEMAKER_PARALLEL_EC2_INSTANCES, TORCH_DYNAMO_MODES
from ...utils.dataclasses import ComputeEnvironment, SageMakerDistributedType
from ...utils.imports import is_botoa_available
from .config_args import SageMakerConfig
from .config_uti... | 368 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def a__ ( lowercase : str ) -> Optional[int]:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase = img.shape[0], img.shape[1]
# converting each pixel's color to its nega... | 287 | 0 |
'''simple docstring'''
import argparse
import struct
import unittest
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : Optional[int] , lowerCAmelCase__ : bytes ) -> None:
'''simple docstring'''
_Upper... | 369 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available()... | 287 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ : Tuple = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeBer... | 370 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : Tuple ) -> int:
'''simple d... | 287 | 0 |
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.u... | 371 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 287 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : List[Any] = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
... | 350 |
'''simple docstring'''
import math
def a__ ( lowercase : float, lowercase : float ) -> float:
"""simple docstring"""
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of init... | 287 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_uti... | 351 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Optional[Any] = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 287 | 0 |
'''simple docstring'''
import math
def a__ ( lowercase : int ) -> bool:
"""simple docstring"""
_UpperCamelCase = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(lowercase )
def... | 352 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowercase : int, lowercase : int ) -> int:
# BASE CASE
if row >= rows or col >= cols... | 287 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : int = {
'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'],
'processing_mgp_str': ['MgpstrProcesso... | 353 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgume... | 287 | 0 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowercase__ : List[Any] = parse(importlib.metadata.version('torch'))
def a__ ( lowercase : Union[str, Version], lo... | 354 |
'''simple docstring'''
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
if not isinstance(lowercase, lowercase ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
... | 287 | 0 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
lowercase__ : List[str] = [int(0.5 * n * (n + 1)) for n in range(1, 1_01)]
def a__ ( ) -> Optional[Any]:
"""simple docstring"""
_UpperCamelCase = os.path.dirname(os.path.... | 355 |
'''simple docstring'''
import random
class __lowerCAmelCase :
"""simple docstring"""
@staticmethod
def snake_case__ ( lowerCAmelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
_UpperCamelCase ... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : int ) -> bool:
"""simple docstring"""
if p < 2:
raise ValueError('''p should not be less than 2!''' )
elif p == 2:
return True
_UpperCamelCase = 4
_UpperCamelCase = (1 << p) - 1
fo... | 356 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(lowercase, x % y )
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstrin... | 287 | 0 |
'''simple docstring'''
import math
def a__ ( lowercase : int ) -> 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:
# Negatives, 0, 1, all even numbers, ... | 357 |
'''simple docstring'''
import argparse
import os
# New Code #
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... | 287 | 0 |
'''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[Any] , ... | 358 |
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_cas... | 287 | 0 |
'''simple docstring'''
import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : ... | 359 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as ... | 287 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .t... | 360 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
lowercase__ : Optional[Any] = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def __ini... | 287 | 0 |
'''simple docstring'''
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def a__ ( lowercase : List[str], lowercase : Any ) -> List[str]:
"""simple docstring"""
... | 361 |
'''simple docstring'''
from math import isclose, sqrt
def a__ ( lowercase : float, lowercase : float, lowercase : float ) -> tuple[float, float, float]:
"""simple docstring"""
_UpperCamelCase = point_y / 4 / point_x
_UpperCamelCase = 2 * normal_grad... | 287 | 0 |
import math
def a__ ( lowercase : int = 100 ) -> int:
"""simple docstring"""
_UpperCamelCase = sum(i * i for i in range(1, n + 1 ) )
_UpperCamelCase = int(math.pow(sum(range(1, n + 1 ) ), 2 ) )
return square_of_sum - sum_of_squares
i... | 362 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Tuple = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwr... | 287 | 0 |
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class __lowerCAmelCase ( __magic_name__ , unittest.TestCase ):
"""simple docstring"""
_snake_cas... | 363 |
'''simple docstring'''
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 TokenizerTes... | 287 | 0 |
'''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.utils... | 364 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list[int], lowercase : list[int], lowercase : int ) -> tuple[float, list[float]]:
"""simple docstring"""
_UpperCamelCase = list(range(len(lowercase ) ) )
_UpperCamelC... | 287 | 0 |
'''simple docstring'''
lowercase__ : int = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
_UpperCamelCase = 0
while number:
# Increased Speed Slightly by check... | 365 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : List[Any] = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
... | 287 | 0 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int ) -> str:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
_UpperCamelCase = str(bin(lowercase ) )[2:] # remove the leading ... | 366 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowercase__ : List[Any] = parse(importlib.metadata.version('torch'))
def a__ ( lowercase : Union[str, Version], lo... | 287 | 0 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
def a__ ( lowercase : Optional[int], lowercase : int )... | 367 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def a__ ( lowercase : Tuple ) -> Dict:
"""simple docstring"""
_U... | 287 | 0 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .... | 368 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def a__ ( lowercase : str ) -> Optional[int]:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase = img.shape[0], img.shape[1]
# converting each pixel's color to its nega... | 287 | 0 |
'''simple docstring'''
import warnings
from .generation import TFGenerationMixin
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
warnings.warn(
'Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will '
... | 369 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available()... | 287 | 0 |
'''simple docstring'''
import os
import pytest
from attr import dataclass
lowercase__ : Optional[Any] = 'us-east-1' # defaults region
@dataclass
class __lowerCAmelCase :
"""simple docstring"""
_snake_case : str
_snake_case : Any = 'ar... | 370 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : Tuple ) -> int:
'''simple d... | 287 | 0 |
import argparse
import os
# New Code #
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... | 371 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,... | 287 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_chan... | 350 |
'''simple docstring'''
import math
def a__ ( lowercase : float, lowercase : float ) -> float:
"""simple docstring"""
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of init... | 287 | 0 |
'''simple docstring'''
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 TokenizerTes... | 351 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Optional[Any] = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 287 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : Any = {
'BridgeTower/bridgetower-bas... | 352 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowercase : int, lowercase : int ) -> int:
# BASE CASE
if row >= rows or col >= cols... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
_UpperCAmelCase : Tuple = [True] * 1_00_00_01
_UpperCAmelCase : List[str] = 2
while i * i <= 1_00_00_00:
if seive[i]:
for j in range(i * i, 1_00_00_01, i):
_UpperCAmelCase : Any = False
i += 1
... | 353 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgume... | 287 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as ... | 354 |
'''simple docstring'''
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
if not isinstance(lowercase, lowercase ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
... | 287 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 355 |
'''simple docstring'''
import random
class __lowerCAmelCase :
"""simple docstring"""
@staticmethod
def snake_case__ ( lowerCAmelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
_UpperCamelCase ... | 287 | 0 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list[int | float], lowercase : int, lowercase : int ) -> int | float:
"""simple docstring"""
if len(lowercase ) == 0:
raise ValueError('''find_max() arg is an empty sequence... | 356 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstring"""
return x if y == 0 else greatest_common_divisor(lowercase, x % y )
def a__ ( lowercase : int, lowercase : int ) -> int:
"""simple docstrin... | 287 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
lowercase__ : Optional[int] = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def __init_... | 357 |
'''simple docstring'''
import argparse
import os
# New Code #
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... | 287 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : str = logging.get_logger(__name__)
lowercase__ : Optional[Any] = {
... | 358 |
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_cas... | 287 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : Dict = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_C... | 359 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as ... | 287 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.