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'''
from numpy import exp, pi, sqrt
def _UpperCAmelCase ( _UpperCamelCase : Dict, _UpperCamelCase : float = 0.0, _UpperCamelCase : float = 1.0 ) -> int:
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigm... | 367 | '''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
#
# U... | 18 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simpli... | 368 | '''simple docstring'''
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F4... | 18 | 0 |
'''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
__snake_case : Any = logging.get_logger(__name__)
__snake_case ... | 369 | '''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModel... | 370 | '''simple docstring'''
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules i... | 18 | 0 |
'''simple docstring'''
import math
import tensorflow as tf
from packaging import version
def _UpperCAmelCase ( _UpperCamelCase : Optional[Any] ) -> Any:
A_ = tf.convert_to_tensor(lowerCamelCase__ )
A_ = 0.5 * (1.0 + tf.math.erf(x / tf.c... | 371 | '''simple docstring'''
from statistics import mean, stdev
def _UpperCAmelCase ( _UpperCamelCase : list, _UpperCamelCase : int = 3 ) -> list:
A_ = min(_UpperCamelCase )
A_ = max(_UpperCamelCase )
# normalize data
... | 18 | 0 |
'''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Union[str, Any] = logging.get_logger(__name__)
__snake_case : Optional[int] = {
'facebook/data2vec-base-960h': 'https://huggingface.co/facebo... | 350 | '''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
... | 18 | 0 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
__snake_case : Any ... | 351 | '''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 is_fla... | 18 | 0 |
'''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils imp... | 352 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : Union[str, Any] ) -> Dict:
A_ = 1
A_ = 2
while i * i <= n:
A_ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisor... | 18 | 0 |
'''simple docstring'''
import warnings
from ..trainer import Trainer
from ..utils import logging
__snake_case : int = logging.get_logger(__name__)
class __UpperCAmelCase ( lowerCamelCase__ ):
'''simple docstring'''
def __init__( self , _S... | 353 | '''simple docstring'''
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... | 18 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def _UpperCAmelCase ( _UpperCamelCase : Optional[Any] ) ... | 354 | '''simple docstring'''
import math
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : float ) -> float:
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values... | 18 | 0 |
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : List[Any], _UpperCamelCase : int, _UpperCamelCase : int ) -> tuple[float, list[float]]:
A_ = list(range(len(__UpperCAmelCase ) ) )
A_ = ... | 355 | '''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()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 18 | 0 |
'''simple docstring'''
from typing import Any
class __UpperCAmelCase :
'''simple docstring'''
def __init__( self , _SCREAMING_SNAKE_CASE ) -> int:
A_ = data
A_ = None
class __Upper... | 356 | '''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case : Any = logging.get_logger(__name__)
def _UpperCAmelCase ( _UpperCamelCas... | 18 | 0 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
__snake_case : Union[str, Any] =... | 357 | '''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__snake_case : Optional[Any] = logging.get_logger(__name__)
__snake_case : Tup... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def _UpperCAmelCase ( ) -> Optional[int]:
A_ = [randint(-10_00, 10_00 ) for i in range(10 )]
A_ ... | 358 | '''simple docstring'''
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 18 | 0 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def _UpperCAmelCase ( ) -> List[str]:
raise RuntimeError('''CUDA out of memory.''' ... | 359 | '''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availabl... | 18 | 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,
)
__snake_case : Any = {
'configuration_whisper': ['WHISP... | 360 | '''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : int = logging.get_logger(__name__)
__snake_case : str = {
'microsoft/xprophetnet-large-wiki100-cased': (
... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : List[str], _UpperCamelCase : Dict, _UpperCamelCase : Optional[int], ) -> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
... | 361 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : list[float] ) -> float:
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows ... | 18 | 0 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_... | 362 | '''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : int | str ) -> bool:
A_ = str(_UpperCamelCase )
return n == n[::-1]
def _UpperCAmelCase ( _UpperCamelCase : int = 1_00_00_00 ... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : int ) -> "list[int]":
if upper_limit < 0:
raise ValueError('''Limit for the Catalan sequence must be ≥ 0''' )
A_ = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
A_ ... | 363 | '''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( _UpperCamelCase : Tuple, _UpperCamelCase : Tuple, _UpperCamelCase : List[str] ) -> int:
A_ = {
'''en''': '''... | 18 | 0 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel,... | 364 | '''simple docstring'''
from collections import defaultdict
def _UpperCAmelCase ( _UpperCamelCase : int ) -> int:
A_ = 1
A_ = True
for v in tree[start]:
if v not in visited:
ret += dfs(_UpperCamelCase )
if ret ... | 18 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Tuple, 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_... | 365 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : List[str] = logging.get_logger(__name__)
__snake_case : Union[str, Any] = {
'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base... | 18 | 0 |
'''simple docstring'''
import argparse
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 A... | 366 | '''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __UpperCAmelCase :
'''simple docstring'''
pass
| 18 | 0 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
__snake_case : List[Any] = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth.... | 367 | '''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
#
# U... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def _UpperCAmelCase ( _UpperCamelCase : list[float] ) -> List[Any]:
return np.maximum(0, __UpperCamelCase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0... | 368 | '''simple docstring'''
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F4... | 18 | 0 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__snake_case : Tuple = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.sel... | 369 | '''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)... | 18 | 0 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def _UpperCAmelCase ( _UpperCamelCase : Union[dict, list... | 370 | '''simple docstring'''
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules i... | 18 | 0 |
'''simple docstring'''
from math import factorial
def _UpperCAmelCase ( _UpperCamelCase : Optional[Any], _UpperCamelCase : Dict ) -> Union[str, Any]:
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative... | 371 | '''simple docstring'''
from statistics import mean, stdev
def _UpperCAmelCase ( _UpperCamelCase : list, _UpperCamelCase : int = 3 ) -> list:
A_ = min(_UpperCamelCase )
A_ = max(_UpperCamelCase )
# normalize data
... | 18 | 0 |
'''simple docstring'''
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.ut... | 350 | '''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
... | 18 | 0 |
'''simple docstring'''
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizer... | 351 | '''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 is_fla... | 18 | 0 |
'''simple docstring'''
import torch
from accelerate import PartialState
from accelerate.utils.operations import broadcast, gather, gather_object, pad_across_processes, reduce
def _UpperCAmelCase ( _UpperCamelCase : List[str] ) -> Tuple:
return (torch.arange(state.num_proces... | 352 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : Union[str, Any] ) -> Dict:
A_ = 1
A_ = 2
while i * i <= n:
A_ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisor... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : list[int], _UpperCamelCase : int ) -> List[Any]:
A_ = len(_UpperCamelCase )
A_ = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for ea... | 353 | '''simple docstring'''
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... | 18 | 0 |
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
__snake_case : int = yaml.safe_load(
'\\nname: ""\nallow_empty: false\nallow_empty_text: true\nsubsections:\n - name: "Datas... | 354 | '''simple docstring'''
import math
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : float ) -> float:
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values... | 18 | 0 |
import string
import numpy
def _UpperCAmelCase ( _UpperCamelCase : int, _UpperCamelCase : int ) -> List[str]:
return b if a == 0 else greatest_common_divisor(b % a, lowerCamelCase_ )
class __UpperCAmelCase :
'''simple docstring'''... | 355 | '''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()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 18 | 0 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
... | 356 | '''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case : Any = logging.get_logger(__name__)
def _UpperCAmelCase ( _UpperCamelCas... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFI... | 357 | '''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__snake_case : Optional[Any] = logging.get_logger(__name__)
__snake_case : Tup... | 18 | 0 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def _UpperCAmelCase ( _UpperCamelCase : Optional[Any], _UpperCamelCase : Tuple ) -> Tuple:
A_ = math.sqrt(lowerCAmelCase__ )
A_ = 1 / (sigma *... | 358 | '''simple docstring'''
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 18 | 0 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transform... | 359 | '''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availabl... | 18 | 0 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'The `image_to_image.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionImg2ImgPipeline` instead.'
)
| 360 | '''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : int = logging.get_logger(__name__)
__snake_case : str = {
'microsoft/xprophetnet-large-wiki100-cased': (
... | 18 | 0 |
'''simple docstring'''
__snake_case : List[str] = [0, 2, 4, 6, 8]
__snake_case : int = [1, 3, 5, 7, 9]
def _UpperCAmelCase ( _UpperCamelCase : Any, _UpperCamelCase : Any, _UpperCamelCase : Dict, _UpperCamelCase : Dict ... | 361 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : list[float] ) -> float:
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows ... | 18 | 0 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _UpperCAmelCase ( _UpperCamelCase : List[str], _UpperCamelCase : List[Any], _UpperCamelCase : str ) -> List[Any]:
A_ = 0
if ... | 362 | '''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : int | str ) -> bool:
A_ = str(_UpperCamelCase )
return n == n[::-1]
def _UpperCAmelCase ( _UpperCamelCase : int = 1_00_00_00 ... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : list[list[int]], _UpperCamelCase : int, _UpperCamelCase : int, _UpperCamelCase : set ) -> Any:
A_ ,A_ = len(SCREAMING_SNAKE_CASE_ ), len(grid[0] )
... | 363 | '''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( _UpperCamelCase : Tuple, _UpperCamelCase : Tuple, _UpperCamelCase : List[str] ) -> int:
A_ = {
'''en''': '''... | 18 | 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_channel... | 364 | '''simple docstring'''
from collections import defaultdict
def _UpperCAmelCase ( _UpperCamelCase : int ) -> int:
A_ = 1
A_ = True
for v in tree[start]:
if v not in visited:
ret += dfs(_UpperCamelCase )
if ret ... | 18 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCAmelCase ( _SCREAMING_SNAKE_CASE ):
__lowercase : List[str] = ['image_processor', 'tokenizer']
__lowercase : Any = 'AutoIm... | 365 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : List[str] = logging.get_logger(__name__)
__snake_case : Union[str, Any] = {
'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : Optional[Any], _UpperCamelCase : Any ) -> Tuple:
assert x is not None
assert y is not None
A_ = len(_UpperCamelCase )
A_ = len(_UpperCamelCase )
# ... | 366 | '''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __UpperCAmelCase :
'''simple docstring'''
pass
| 18 | 0 |
'''simple docstring'''
import argparse
import json
import os
import re
from collections import OrderedDict
from os.path import basename, dirname
import fairseq
import torch
from fairseq import hub_utils
from fairseq.data.dictionary import Dictionary
from transformers import FSMTConfig, FSMTForConditionalGenera... | 367 | '''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
#
# U... | 18 | 0 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
__snake_case : List[Any] = {
'facebook/maskform... | 368 | '''simple docstring'''
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F4... | 18 | 0 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attent... | 369 | '''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)... | 18 | 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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
re... | 370 | '''simple docstring'''
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules i... | 18 | 0 |
'''simple docstring'''
class __UpperCAmelCase :
'''simple docstring'''
def __init__( self ) -> Any:
A_ = ''''''
A_ = ''''''
A_ = []
def __A ( self , _SCREAMING_SNAKE_CASE , _SCR... | 371 | '''simple docstring'''
from statistics import mean, stdev
def _UpperCAmelCase ( _UpperCamelCase : list, _UpperCamelCase : int = 3 ) -> list:
A_ = min(_UpperCamelCase )
A_ = max(_UpperCamelCase )
# normalize data
... | 18 | 0 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class __... | 350 | '''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
... | 18 | 0 |
'''simple docstring'''
from math import factorial
class __UpperCAmelCase :
'''simple docstring'''
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str]:
A_ = real
if isinstance(_SCREAMING_SNAKE_... | 351 | '''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 is_fla... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : int, _UpperCamelCase : int ) -> int:
while b:
A_ ,A_ = b, a % b
return a
def _UpperCAmelCase ( _UpperCamelCase : int, _UpperCamelCase : i... | 352 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : Union[str, Any] ) -> Dict:
A_ = 1
A_ = 2
while i * i <= n:
A_ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisor... | 18 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs
if is_tor... | 353 | '''simple docstring'''
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... | 18 | 0 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
__snake_case : str = logging.get_logger(__name__)
def _UpperCAmelCase ( _UpperCamelCase : Optional[Any] ) -> ... | 354 | '''simple docstring'''
import math
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : float ) -> float:
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values... | 18 | 0 |
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _UpperCAmelCase ( _UpperCamelCase : List[str], _UpperCamelCase : str, _UpperCamelCase : Union[str, Any], _UpperCamelCase : int ) -> ... | 355 | '''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()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : int ) -> bool:
return sum(i for i in range(1, number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('Program to check whether a number is a Perfect number or... | 356 | '''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case : Any = logging.get_logger(__name__)
def _UpperCAmelCase ( _UpperCamelCas... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
__snake_case : Optional[Any] = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
__snake_case : List[Any] = typing.Union[np.fl... | 357 | '''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__snake_case : Optional[Any] = logging.get_logger(__name__)
__snake_case : Tup... | 18 | 0 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipel... | 358 | '''simple docstring'''
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : list[float] ) -> float:
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows ... | 359 | '''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availabl... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__snake_case : int = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-... | 360 | '''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : int = logging.get_logger(__name__)
__snake_case : str = {
'microsoft/xprophetnet-large-wiki100-cased': (
... | 18 | 0 |
'''simple docstring'''
import argparse
import os
import re
__snake_case : List[str] = 'src/diffusers'
# Pattern that looks at the indentation in a line.
__snake_case : Tuple = re.compile(R'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
__snake_case ... | 361 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : list[float] ) -> float:
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows ... | 18 | 0 |
'''simple docstring'''
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
__snake_case : Optional[int] = HfApi()
__snake_case : Tuple = {}
# fmt: off
__snake_case : Dict = torch.tensor([
-0.7_515, -1.6_883, 0.... | 362 | '''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : int | str ) -> bool:
A_ = str(_UpperCamelCase )
return n == n[::-1]
def _UpperCAmelCase ( _UpperCamelCase : int = 1_00_00_00 ... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import pi, sqrt
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : float ) -> tuple:
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
... | 363 | '''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( _UpperCamelCase : Tuple, _UpperCamelCase : Tuple, _UpperCamelCase : List[str] ) -> int:
A_ = {
'''en''': '''... | 18 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
... | 364 | '''simple docstring'''
from collections import defaultdict
def _UpperCAmelCase ( _UpperCamelCase : int ) -> int:
A_ = 1
A_ = True
for v in tree[start]:
if v not in visited:
ret += dfs(_UpperCamelCase )
if ret ... | 18 | 0 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class __UpperCAmelCase :
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Tuple:
if dst_width < 0 or dst_heig... | 365 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : List[str] = logging.get_logger(__name__)
__snake_case : Union[str, Any] = {
'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : list[list[int]] ) -> bool:
A_ = len(_UpperCamelCase )
# We need to create solution object to save path.
A_ = [[0 for _ in range(_UpperC... | 366 | '''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __UpperCAmelCase :
'''simple docstring'''
pass
| 18 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__snake_case : Optional[int] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 367 | '''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
#
# U... | 18 | 0 |
'''simple docstring'''
class __UpperCAmelCase :
'''simple docstring'''
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str]:
A_ = None
A_ = None
... | 368 | '''simple docstring'''
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F4... | 18 | 0 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFI... | 369 | '''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)... | 18 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : Dict = {
'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}
try:... | 370 | '''simple docstring'''
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules i... | 18 | 0 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _UpperCAmelCase ( _UpperCamelCase : str, _UpperCamelCase : str, **_UpperCamelCase : List[str] ) -> Union[str, Any]:
A_ = Au... | 371 | '''simple docstring'''
from statistics import mean, stdev
def _UpperCAmelCase ( _UpperCamelCase : list, _UpperCamelCase : int = 3 ) -> list:
A_ = min(_UpperCamelCase )
A_ = max(_UpperCamelCase )
# normalize data
... | 18 | 0 |
'''simple docstring'''
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel... | 350 | '''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
... | 18 | 0 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _UpperCAmelCase ( _UpperCamelCase : str, ... | 351 | '''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 is_fla... | 18 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
... | 352 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : Union[str, Any] ) -> Dict:
A_ = 1
A_ = 2
while i * i <= n:
A_ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisor... | 18 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_... | 353 | '''simple docstring'''
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... | 18 | 0 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __UpperCAmelCase ( yaml.SafeLoader ):
'''simple docstring'''
def __A ( self , _SCREAMING_SNAKE_CASE ) -> List[Any]:
A_ = [self... | 354 | '''simple docstring'''
import math
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : float ) -> float:
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values... | 18 | 0 |
__snake_case : Optional[Any] = {
0: '0',
1: '1',
2: '2',
3: '3',
4: '4',
5: '5',
6: '6',
7: '7',
8: '8',
9: '9',
10: 'a',
11: 'b',
12: 'c',
13: 'd',
14: 'e',
15: 'f',
}
def _UpperCAmelCase ( _UpperCamelCase : float... | 355 | '''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()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 18 | 0 |
'''simple docstring'''
from math import sqrt
def _UpperCAmelCase ( _UpperCamelCase : int ) -> bool:
assert isinstance(_UpperCamelCase, _UpperCamelCase ) and (
number >= 0
), "'number' must been an int and positive"
A_ = ... | 356 | '''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case : Any = logging.get_logger(__name__)
def _UpperCAmelCase ( _UpperCamelCas... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : list ) -> list:
A_ = len(_UpperCamelCase )
for i in range(1, _UpperCamelCase ):
A_ = collection[i]
A_ = 0
A_ = i -... | 357 | '''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__snake_case : Optional[Any] = logging.get_logger(__name__)
__snake_case : Tup... | 18 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_g... | 358 | '''simple docstring'''
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 18 | 0 |
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
__snake_case : Optional[Any] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
__snake_case : int = None
def _UpperCAmelCase ( ) ... | 359 | '''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availabl... | 18 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
... | 360 | '''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : int = logging.get_logger(__name__)
__snake_case : str = {
'microsoft/xprophetnet-large-wiki100-cased': (
... | 18 | 0 |
'''simple docstring'''
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
__snake_case : str = logging.getLogger(__name__)
if is_to... | 361 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : list[float] ) -> float:
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows ... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : int = 3, _UpperCamelCase : int = 7, _UpperCamelCase : int = 1_00_00_00 ) -> int:
A_ = 0
A_ = 1
for current_denominator in range(1, limit + 1 ):
... | 362 | '''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : int | str ) -> bool:
A_ = str(_UpperCamelCase )
return n == n[::-1]
def _UpperCAmelCase ( _UpperCamelCase : int = 1_00_00_00 ... | 18 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : Optional[Any] ) -> Union[str, Any]:
A_ = len(_UpperCamelCase )
while cur > 1:
# Find the maximum number in arr
A_ = arr.index(max(arr[0:cur] ) )
... | 363 | '''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( _UpperCamelCase : Tuple, _UpperCamelCase : Tuple, _UpperCamelCase : List[str] ) -> int:
A_ = {
'''en''': '''... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import T... | 364 | '''simple docstring'''
from collections import defaultdict
def _UpperCAmelCase ( _UpperCamelCase : int ) -> int:
A_ = 1
A_ = True
for v in tree[start]:
if v not in visited:
ret += dfs(_UpperCamelCase )
if ret ... | 18 | 0 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def _UpperCAmelCase ( _UpperC... | 365 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : List[str] = logging.get_logger(__name__)
__snake_case : Union[str, Any] = {
'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base... | 18 | 0 |
'''simple docstring'''
from collections import defaultdict
from math import ceil, sqrt
def _UpperCAmelCase ( _UpperCamelCase : int = 1_00_00_00, _UpperCamelCase : int = 10 ) -> int:
A_ = defaultdict(_UpperCamelCase )
for outer_width in ra... | 366 | '''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __UpperCAmelCase :
'''simple docstring'''
pass
| 18 | 0 |
'''simple docstring'''
import csv
import tweepy
# Twitter API credentials
__snake_case : Union[str, Any] = ''
__snake_case : Any = ''
__snake_case : int = ''
__snake_case : int = ''
def _UpperCAmelCase ( _UpperCamelCase ... | 367 | '''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
#
# U... | 18 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_u... | 368 | '''simple docstring'''
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F4... | 18 | 0 |
'''simple docstring'''
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 369 | '''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)... | 18 | 0 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( _UpperCamelCase : Optional[Any] ) -> List[str]:
return getitem, k
def _UpperCAmelCase ( _UpperCa... | 370 | '''simple docstring'''
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules i... | 18 | 0 |
'''simple docstring'''
import random
from typing import Any
def _UpperCAmelCase ( _UpperCamelCase : list ) -> list[Any]:
for _ in range(len(_UpperCamelCase ) ):
A_ = random.randint(0, len(_UpperCamelCase ) - 1 )
A_ ... | 371 | '''simple docstring'''
from statistics import mean, stdev
def _UpperCAmelCase ( _UpperCamelCase : list, _UpperCamelCase : int = 3 ) -> list:
A_ = min(_UpperCamelCase )
A_ = max(_UpperCamelCase )
# normalize data
... | 18 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _UpperCAmelCase ( _UpperCamelCase : str, _UpperCamelCase : str, _UpperCamelCase : str, ... | 350 | '''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
... | 18 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPrio... | 351 | '''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 is_fla... | 18 | 0 |
'''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : int = logging.get_logger(__name__)
__snake_case : str = {
'microsoft/xprophetnet-large-wiki100-cased': (
... | 352 | '''simple docstring'''
def _UpperCAmelCase ( _UpperCamelCase : Union[str, Any] ) -> Dict:
A_ = 1
A_ = 2
while i * i <= n:
A_ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisor... | 18 | 0 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serializatio... | 353 | '''simple docstring'''
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... | 18 | 0 |
def _UpperCAmelCase ( _UpperCamelCase : int = 1_00 ) -> int:
A_ = n * (n + 1) * (2 * n + 1) / 6
A_ = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 354 | '''simple docstring'''
import math
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : float ) -> float:
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values... | 18 | 0 |
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : Any, _UpperCamelCase : Union[str, Any], _UpperCamelCase : Optional[Any], _UpperCamelCase : List[Any] ) -> Any: # noqa: E741
while r - l > 1:
A_ = ... | 355 | '''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()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 18 | 0 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common... | 356 | '''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case : Any = logging.get_logger(__name__)
def _UpperCAmelCase ( _UpperCamelCas... | 18 | 0 |
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