code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
def __UpperCAmelCase ( __lowerCamelCase , __lowerCamelCase ) -> int:
if len(__A ) != len(__A ):
raise ValueError('''String lengths must match!''' )
lowercase__ : List[Any] = 0
for chara, chara in zip(__A... | 560 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers... | 418 | 0 |
def A_ ( __a : str = "The quick brown fox jumps over the lazy dog" , ):
"""simple docstring"""
a__ = set()
# Replace all the whitespace in our sentence
a__ = input_str.replace(""" """ , """""" )
for alpha in input_str:
if "a" <= alpha.l... | 351 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def A_ ( __a : str = "laptop" ):
"""simple docstring"""
a__ = F'''https://www.amazon.in/laptop/s?k={product}'''
a__ = {
"""User-Agent... | 351 | 1 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
__magic_name__ : List[str] = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": o... | 102 |
"""simple docstring"""
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import float... | 506 | 0 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
a__ : Optional[Any] = TypeVar("""T""")
def A__ ( __lowerCamelCase ):
"""simple docstring"""
return (position - 1) // 2
def A__ ( __lowerCamelCase ):
... | 703 |
"""simple docstring"""
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils imp... | 309 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transform... | 35 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ :List[str] = {
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'GroupViTConfig',
'GroupViTOnnxConfig',
'Grou... | 35 | 1 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> bool:
if not all(x.isalpha() for x in string ):
raise ValueError("""String must only contain alphabetic characters.""" )
SCREAMING_SNAKE_CASE__ : Any = sorted(string.lower() ... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE__ : List[Any] = 1
SCREAMING_SNAKE_CASE__ : int = 1
while repunit:
SCREAMING_SNA... | 12 | 1 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE_ = TypeVar('KEY')
SCREAMING_SNAKE_CASE_ = TypeVar('VAL')
@dataclass(frozen=__lowerCAmelCase , slots=__lowerCAmelCase ... | 523 | '''simple docstring'''
from math import pi
def UpperCamelCase__ ( _lowercase : int , _lowercase : int ) -> float:
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10)) | 523 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase : int = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2FormerCo... | 542 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase : int = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2FormerCo... | 542 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
... | 542 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __lowercase ( ... | 542 | 1 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
__lowerCamelCase = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def UpperCAmelCase__... | 667 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A__ ( _snake_case ):
lowercase = "ClapFeatureExtractor"
lowercase = ("RobertaTokenizer", "RobertaTokenizerFast")
def __init__( self ... | 667 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
a__ : Tuple = {"""vocab_file""": """vocab.txt""", """token... | 589 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from... | 325 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ : Tuple = logging.get_logger(__name__)
lowerCAmelCase_ : List[str]... | 378 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Any = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/... | 378 | 1 |
from ...processing_utils import ProcessorMixin
class snake_case ( UpperCamelCase_ ):
lowercase_ = ['image_processor', 'feature_extractor']
lowercase_ = 'TvltImageProcessor'
lowercase_ = 'TvltFeatureExtractor'
def __init__( self : int , a_ : List[str] ... | 85 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : Optional[Any] = {"configuration_fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE... | 85 | 1 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : int = 1_0_0_0 ):
'''simple docstring'''
lowerCAmelCase : Union[str, Any] = 2**power
lowerCAmelCase : Dict = str(SCREAMING_SNAKE_CASE )
lowerCAmelCase : Optional[int] = list... | 681 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ = {
'''configuration_efficientformer''': [
'''EFFICIENTFORMER... | 681 | 1 |
from heapq import heappop, heappush
import numpy as np
def _a ( lowercase__ : np.ndarray , lowercase__ : tuple[int, int] , lowercase__ : tuple[int, int] , lowercase__ : bool , ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ... | 85 |
"""simple docstring"""
def A_ ( __lowercase , __lowercase , __lowercase ):
if len(__lowercase ) != len(__lowercase ):
raise ValueError('The length of profit and weight must be same.' )
if max_weight <= 0:
raise ValueError('max_weight must greater than zero.' )
if any(p < 0 for p in pro... | 357 | 0 |
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
... | 716 | """simple docstring"""
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
imp... | 477 | 0 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import ... | 21 |
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class __A ( tf.keras.layers.Layer ):
def __init__( self ... | 21 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuratio... | 709 |
'''simple docstring'''
def __snake_case ( _UpperCAmelCase : Optional[int]):
UpperCamelCase = []
UpperCamelCase = []
UpperCamelCase = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
'''%''': 2,
'''+''': 1,
'''-''': 1,
} ... | 350 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__a: Tuple = {
"""configuration_vision_text_dual_encoder""": ["""VisionTextDualEncoderConfig"""],
... | 152 | '''simple docstring'''
from collections.abc import Sequence
def __UpperCamelCase ( UpperCAmelCase , UpperCAmelCase = False ):
if not arr:
return 0
lowercase__ : Tuple = 0 if allow_empty_subarrays else float('''-inf''' )
lowercase__ : int = 0.0
for num i... | 152 | 1 |
'''simple docstring'''
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
SCREAMING_SNAKE... | 719 | '''simple docstring'''
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
SCREAMING_SNAKE_CASE_: Optional[Any] =2_99_79_24_58
# Symbols
SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_: Option... | 415 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ : int = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
i... | 223 |
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str , __lowerCAmelCase : Optional[str] = None ):
"""simple docs... | 290 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ : Any = {
'configuration_xlm_roberta': [
... | 678 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class SCREAMING_SNAKE_CASE_ :
"""simple docstring"""
def __init__( self , A ) -> Tuple:
'''simple docstring'''
__magic_name__ = list_of_points
# Degree det... | 678 | 1 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_snake_case : List[str] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : List[str] , *lowe... | 81 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->Optional[int]:
# Checks if the entire collection has been sorted
if len(lowerCAmelCase_ ) <= 1 or n <= 1:
return
insert_next(lowerCAmelCase_ , n - 1 )
rec_insertion_sort(lowerC... | 377 | 0 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
__A : Optional[Any] = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint... | 714 |
'''simple docstring'''
# Copyright (c) 2021-, NVIDIA CORPORATION. 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... | 267 | 0 |
import random
def lowerCamelCase__ ( snake_case_ : List[Any] , snake_case_ : Union[str, Any] , snake_case_ : Optional[Any] ) -> List[str]:
__snake_case = a[left_index]
__snake_case = left_index + 1
for j in range(left_index ... | 592 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class lowerCamelCase_ ( lowerCamelCase ... | 0 | 0 |
def lowercase ( _a ) -> list:
UpperCAmelCase_: Optional[Any] = len(_a )
for i in range(1 ,_a ):
UpperCAmelCase_: List[str] = collection[i]
UpperCAmelCase_: List[str] = 0
UpperCAmelCase_: Optional[Any] = i - 1
while low <= h... | 306 |
import os
def lowercase ( _a = "matrix.txt" ) -> int:
with open(os.path.join(os.path.dirname(_a ) ,_a ) ) as in_file:
UpperCAmelCase_: str = in_file.read()
UpperCAmelCase_: Union[str, Any] = [[int(_a ) for cell in row.split("," )] for row in d... | 306 | 1 |
"""simple docstring"""
def snake_case_ ( A_ : List[str] ):
'''simple docstring'''
_lowerCamelCase : Tuple = 0
_lowerCamelCase : Union[str, Any] = len(A_ )
for i in range(n - 1 ):
for j in range(i + 1,... | 83 |
"""simple docstring"""
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import ... | 535 | 0 |
import torch
from diffusers import DiffusionPipeline
class a_ ( a ):
def __init__( self : Optional[Any] , UpperCAmelCase__ : Tuple , UpperCAmelCase__ : List[Any] ):
"""simple docstring"""
super().__init__()
se... | 84 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler... | 84 | 1 |
"""simple docstring"""
import requests
A__ : Tuple = '''''' # <-- Put your OpenWeatherMap appid here!
A__ : Optional[Any] = '''https://api.openweathermap.org/data/2.5/'''
def _snake_case ( lowerCamelCase__ : int = "Chicago" , lowerCamelCase__ ... | 153 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_torch
... | 428 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import Batc... | 716 | """simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ... | 283 | 0 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
imp... | 661 |
"""simple docstring"""
from __future__ import annotations
__SCREAMING_SNAKE_CASE : Dict = 1.6_0_2_1e-1_9 # units = C
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : float , ) -> tuple[str, float]:
if (conductivity, electron_con... | 661 | 1 |
'''simple docstring'''
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def _A (lowerCAmelCase__ :str ) -> Optional[int]:
'''simple docstring'''
_a = {}
_a = job... | 532 |
'''simple docstring'''
def _A (lowerCAmelCase__ :Union[str, Any] ) -> List[str]:
'''simple docstring'''
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
... | 532 | 1 |
import requests
from bsa import BeautifulSoup
def __A ( _lowercase = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
_A = BeautifulSoup(requests.get(_lowercase ).text , '''html.parser''' )
_A = soup.findAll('''h1''' ... | 484 |
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def __A ( _lowercase ):
'''simple docstring'''
return sum(param.float().sum() if '''en... | 484 | 1 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def UpperCAmelCase_ ( lowercase__ ):
'''simple docstring'''
def decorator(lowercase__ ):
a_ =getattr(lowercase__ , "handle_key"... | 41 |
'''simple docstring'''
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def UpperCAmelCase_ ( lowercase__ , lowercase__ , lowercase__ , lowercase__=5 ):
'''simple docstring'''
assert masked_input.cou... | 41 | 1 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE : List[Any] = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.c... | 141 |
def lowerCamelCase_ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__UpperCamelCase , n - 1 , __UpperCamelCase ) * a) % mod
else:
A_ = binary_exponenti... | 141 | 1 |
"""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
__lowercase = logging.getLogger(__name__)
if is_torch_tpu_availab... | 719 | """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 lowerCAmelCase ():
"""simple docstring"""
raise RuntimeError('''CUDA out of... | 296 | 0 |
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import... | 106 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get... | 709 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 0 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licens... | 430 |
'''simple docstring'''
import argparse
import os
import re
_lowerCamelCase : int = "src/transformers/models/auto"
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
_lowerCamelCase : Union... | 430 | 1 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import tor... | 619 |
import math
import qiskit
def lowerCAmelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 )-> qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCas... | 619 | 1 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as P... | 149 |
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 149 | 1 |
'''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, _concaten... | 717 |
'''simple docstring'''
def __snake_case ( SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ) -> int:
"""simple docstring"""
if exponent == 1:
return base
if exponent % 2 == 0:
UpperCAmelCase =... | 570 | 0 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def __UpperCAmelCase ( _UpperCAmelCase : int = 3 ) -> qiskit.result.counts.Counts:
if isinstance(_UpperCAmelCase , _U... | 69 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
fro... | 39 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
A = TypeVar('T')
class UpperCAmelCase__ ( Generic[T] ):
def __init__( self : Union[str, Any] , snake_case : T ) -> None:
'''simple docstri... | 109 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 109 | 1 |
from __future__ import annotations
def _snake_case ( __snake_case ):
return [ord(__snake_case ) - 96 for elem in plain]
def _snake_case ( __snake_case ):
return "".join(chr(elem + 96 ) for elem in encoded )
def _snake_case ( ):
_UpperCamelCase = encod... | 10 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 62 | 0 |
def a_ ( lowerCamelCase : List[Any] ):
lowerCAmelCase = len(__snake_case )
for i in range(length - 1 ):
lowerCAmelCase = i
for k in range(i + 1 , __snake_case ):
if collection[k] < collection[least]:
lowerCAmelCase = ... | 705 |
'''simple docstring'''
from __future__ import annotations
def a_ ( lowerCamelCase : list , lowerCamelCase : int ):
# Checks if the entire collection has been sorted
if len(lowerCamelCase ) <= 1 or n <= 1:
return
insert_next(lowerCamelCase ... | 513 | 0 |
import re
def __magic_name__ ( lowerCAmelCase_):
'''simple docstring'''
if len(re.findall("[ATCG]" , lowerCAmelCase_)) != len(lowerCAmelCase_):
raise ValueError("Invalid Strand")
return dna.translate(dna.maketrans("ATCG" , "TAGC"))
if __name__ == "__main__"... | 250 |
import warnings
warnings.warn(
'''memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '''
'''`from accelerate import find_executable_batch_size` to avoid this warning.''',
FutureWarning,
)
| 250 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_UpperCAmelCase : str = {
"configuration_swiftformer": [
"SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SwiftFormerConfig",
"SwiftFormer... | 288 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class lowerCAmelCase_ ( unittest.TestCase ):
def __snake_case ( self ... | 288 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[int] , _a : int , _a : MutableSequence[float] ... | 459 |
'''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
fr... | 459 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
... | 159 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules imp... | 159 | 1 |
import torch
from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool
if is_datasets_available():
from datasets import load_dataset
class lowerCamelCase__ ( lowerCamelCase_):
... | 2 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
__UpperCamelCase = '''\
@inproceedings{popovic-2015-chrf,
title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",
author = "Popovi{\'c}, Maja",
... | 247 | 0 |
"""simple docstring"""
def __lowercase ( a : List[str] , a : Union[str, Any] ) -> Optional[int]:
__snake_case : Optional[int] =''''''
for i in table:
res += inp[i - 1]
return res
def __lowercase ( a : List[str] ) ... | 497 |
"""simple docstring"""
def __lowercase ( a : int , a : int ) -> int:
return x if y == 0 else greatest_common_divisor(a , x % y )
def __lowercase ( a : int , a : int ) -> int:
return (x * y) // greatest_common_divisor(a ... | 497 | 1 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...te... | 262 | '''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_availab... | 262 | 1 |
def UpperCAmelCase_ ( _A ):
'''simple docstring'''
if not isinstance(_A , _A ):
raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
if len(_A ) == 0:
raise ValueError('''Input list must be a non ... | 713 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class UpperCAmelCase__ :
"""simple docstring"""
a = field(
default="codeparrot/codeparrot" , metadata={"help": "Model name or path of model to be trained."} )
a = field(
default="./" ,... | 472 | 0 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.confi... | 522 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ :Union[str, Any] = argparse.ArgumentParser('Stable Diffusion script with intel optimizat... | 522 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase__ )
class _lowercase ( UpperCAmelCase__ ):
'''simple docstr... | 330 | '''simple docstring'''
from collections import defaultdict
class _lowercase :
'''simple docstring'''
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Tuple ) -> Optional[Any]:
... | 330 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,... | 578 |
'''simple docstring'''
def lowerCAmelCase_ ( _lowerCamelCase: list ):
if len(_lowerCamelCase ) <= 1:
return [tuple(_lowerCamelCase )]
__SCREAMING_SNAKE_CASE : Optional[int] = []
def generate(_lowerCamelCase: int , _lowerCamelCase: list ):
__SCREAMI... | 578 | 1 |
"""simple docstring"""
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowerCamelCase__ ( A ):
"""simple docstring"""
... | 721 |
"""simple docstring"""
def lowerCamelCase ( _UpperCamelCase : str , _UpperCamelCase : str ) -> str:
'''simple docstring'''
if not (isinstance(_UpperCamelCase , _UpperCamelCase ) and isinstance(_UpperCamelCase , _UpperCamelCase )):
raise ValueErr... | 299 | 0 |
'''simple docstring'''
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditio... | 405 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_commo... | 405 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils i... | 721 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
__lowerCamelCase : Union[str, Any] = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.... | 25 | 0 |
'''simple docstring'''
from math import factorial, pi
def __UpperCamelCase ( UpperCAmelCase , UpperCAmelCase = 30 ):
if not isinstance(UpperCAmelCase , (int, float) ):
raise ValueError('''maclaurin_sin() requires either an int or float for theta''' )
if not isinstance(UpperCAmelCase , Uppe... | 152 | '''simple docstring'''
def __UpperCamelCase ( UpperCAmelCase ):
lowercase__ : Optional[int] = 0
lowercase__ : int = len(UpperCAmelCase )
for i in range(n - 1 ):
for j in range(i + 1 , UpperCAmelCase ):
if arr[i] > arr[j]:
num_inversions += 1
ret... | 152 | 1 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase_ ):
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
A : List[Any] = F'Input value of [number={number}] must be an integer'
raise TypeError(_lowerCAmelCase )
... | 701 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
lowercase : Dict = logging.getLogger(__name__)
class __lowercase :
"""simple docs... | 423 | 0 |
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> int: # noqa: E741
"""simple docstring"""
_A = len(_SCREAMING_SNAKE_CASE )
_A = 0
_A = [0] * n
_A = [False] * n
_A = [False] * n
def d... | 27 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline... | 461 | 0 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class lowerCamelCase (a__ ):
_lowercase : Optional[int] = """MCTCTFeatureExtractor"""
_lowercase : str = """AutoTokenizer"""
def _... | 717 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 47 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Dict = {
"co... | 131 |
'''simple docstring'''
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet imp... | 131 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowerCAmelCase : Optional[int] =TypeVar("T")
class __snake_case ( Generic[T] ):
'''simple docstring'''
def __init__( self : Tuple ... | 15 | from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
... | 15 | 1 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
... | 455 |
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase__ = 50_0000
lowerCamelCase__ , lowerCamelCase__ = os.path.split(__file__)
lowerCamelCase__ = os.path.join(RES... | 455 | 1 |
'''simple docstring'''
from math import pi, sqrt, tan
def lowerCamelCase__ ( a ):
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def lowerCamelCase__ ( a , a , a ... | 710 |
'''simple docstring'''
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be check... | 427 | 0 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from tr... | 94 |
"""simple docstring"""
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def A__ ( A__ , A__ , **A__ ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(A__ , **A__ )
_UpperC... | 426 | 0 |
'''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_... | 474 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__( lowerCamelCase, lowerCamelCase):
__lowerCAmelCase = BeautifulSoup(requests.get(lowerCamelCase, params=lowerCamelCase).content, '''html.parser''')
__lowerCAmelCase ... | 474 | 1 |
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 accelerate.test_utils import Reg... | 40 |
def UpperCamelCase ( snake_case__ : int ) -> str:
if isinstance(snake_case__ , snake_case__ ):
raise TypeError('\'float\' object cannot be interpreted as an integer' )
if isinstance(snake_case__ , snake_case__ ):
raise TypeError('\'str\' object can... | 40 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/co... | 710 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase : List[str] = {
'configuration_pix2struct': [
'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 343 | 0 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGen... | 23 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class lowercase_ (lowerCamelCase__ ):
"""simple docstring"""
def __init__( self : List[Any] ,*low... | 41 | 0 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCAmelCase__ = version.parse(importlib_metadata.version("""nltk"""))
if NLTK_VERSION >= version.Version("""3.6.4"""):
from nltk import word_tokenize
lowerCAmelCase__ = """... | 717 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: list[list[str]] , SCREAMING_SNAKE_CASE_: int , ) -> ... | 626 | 0 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def A_ ( _lowerCAmelCase : Optional[Any] ):
... | 44 |
from __future__ import annotations
from math import pow, sqrt
def __lowercase( UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ ):
"""simple docstring"""
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueError("One and only one argume... | 623 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase_ = {
"configuration_data2vec_audio": ["DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP", "Data2VecAudioConfig"],
"co... | 714 |
'''simple docstring'''
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('''repo_id''' , ['''canonical_dataset_name''', '''org-name/dataset-name'''] )
@pytest.mark.parametrize('''path''' , ['''filename.csv''', '''filename with blanks.cs... | 599 | 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 impor... | 496 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Effic... | 496 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForS... | 707 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelT... | 124 | 0 |
import re
def UpperCamelCase_( lowerCamelCase_ ) -> bool:
_lowercase : List[Any] = re.compile(
R'^(?:0|94|\+94|0{2}94)' R'7(0|1|2|4|5|6|7|8)' R'(-| |)' R'\d{7}$' )
return bool(re.search(lowerCamelCase_ , lowerCamelCase_ ) )
if __name__ == "__... | 89 |
"""simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_... | 179 | 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_utils ... | 706 |
'''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_utils ... | 454 | 0 |
'''simple docstring'''
def __a ( A__ , A__ , A__ ) -> Tuple:
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(A__ , n - 1 , A__ ) * a) % mod
else:
lowerCAmelCase = binary_exponentia... | 649 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : List[str] = logging.get_logger(__name__)
lowercase : Any = {
'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.js... | 649 | 1 |
'''simple docstring'''
def _snake_case ( lowercase ) -> list:
if len(lowercase ) < 2:
return collection
def circle_sort_util(lowercase , lowercase , lowercase ) -> bool:
__a : Optional[int] = False
if low == high:
... | 697 |
'''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_d... | 697 | 1 |
"""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
fro... | 510 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCAmelCase = {
'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Wav2Vec2Co... | 585 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kineti... | 312 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__ = 8.9_88e9 # units = N * m^s * C^-2
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> dict[str, float]:
UpperCAmelCase_... | 312 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torc... | 14 |
'''simple docstring'''
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> Dict:
"""simple docstring"""
... | 653 | 0 |
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __lowerCamelCase ( __UpperCAmelCase ):
"""simple docstring"""
... | 712 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
snake_case__ = ["image_processor", "tokenizer"]
snake_case__ =... | 125 | 0 |
'''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
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 ImageProc... | 350 |
'''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class a_ :
pass
| 350 | 1 |
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ : int = logging.get_logger(__name__)
class UpperCamelCase ( _UpperCAmelCase ):
lowerCAmelCase : ... | 232 |
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - generate model_cards - us... | 232 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceCla... | 468 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def __A ( __lowerCamelCase , __lowerCamelCase=None ) -> Tuple:
a = None
if token is not None:
a ... | 468 | 1 |
def UpperCAmelCase_ ( _A , _A ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
SCREAMING_SNAKE_CASE__ = str(bin(_A ) )[2:] # remove the leading "0b"
SCREAMING_SNAKE_CAS... | 472 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils import... | 472 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from tr... | 430 |
'''simple docstring'''
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
... | 430 | 1 |
"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a__ ( SCREAMING_SNAKE_CASE : bytes , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
lowerCAmelCase : List... | 681 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .sche... | 681 | 1 |
'''simple docstring'''
_snake_case : Any = 9.8_0665
def snake_case_ (UpperCamelCase : float , UpperCamelCase : float , UpperCamelCase : float = g ):
'''simple docstring'''
if fluid_density <= 0:
raise ValueError(... | 22 | import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, U... | 403 | 0 |
class _UpperCamelCase :
def __init__( self: Dict ) -> Tuple:
"""simple docstring"""
UpperCamelCase_ = 0
UpperCamelCase_ = 0
UpperCamelCase_ = {}
def lowercase ( self: Optional[Any] ,... | 371 |
import random
from typing import Any
def lowerCAmelCase_ ( UpperCamelCase_ ) -> list[Any]:
for _ in range(len(UpperCamelCase_ ) ):
UpperCamelCase_ = random.randint(0 , len(UpperCamelCase_ ) - 1 )
UpperCamelCase_ = random.randint(0 ... | 371 | 1 |
'''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 PreTrainedTokeniz... | 667 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase :Optional[Any] = logging.get_logger(__name__)
lowerCamelCase :Tuple = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-st... | 667 | 1 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simpl... | 715 |
'''simple docstring'''
import math
class lowercase :
def __init__( self , _snake_case=0) -> Union[str, Any]: # a graph with Node 0,1,...,N-1
UpperCAmelCase_ : Tuple = n
UpperCAmelCase_ : Optional[Any] = [
... | 471 | 0 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_... | 43 | '''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_image_inputs
if is_torch_availab... | 660 | 0 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=snake_case__ )
class lowerCAmelCase ( snake_case__ ):
'''... | 304 | """simple docstring"""
def snake_case__ ( _snake_case : str ):
"""simple docstring"""
UpperCamelCase__ = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase__ = ""
UpperCamelCase__ = ""
# app... | 304 | 1 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
UpperCAmelCase_ = TypeVar("""KEY""")
UpperCAmelCase_ = TypeVar("""VAL""")
@dataclass(frozen=lowerCamelCase__ , slots=lowerCamelCase__ )
class UpperCa... | 458 |
from __future__ import annotations
from math import gcd
def __magic_name__ ( lowercase , lowercase = 2 , lowercase = 1 , lowercase = 3 , ) -> int | None:
"""simple docstring"""
if num < 2:
raise ValueError("""Th... | 458 | 1 |
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 : Union[str, Any] ... | 717 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : List[str] = logging.get_logger(__name__)
lowercase : Optional[Any] = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt mod... | 423 | 0 |
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