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 |
|---|---|---|---|---|
import math
import qiskit
def lowerCAmelCase_ (lowercase__ : int = 1 , lowercase__ : int = 1 , lowercase__ : int = 1 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
if (
isinstance(lowerCamelCase__ , lowerCamel... | 668 |
"""simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_... | 572 | 0 |
"""simple docstring"""
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
_UpperCamelCase = {
# 1536-bit
5: {
"pr... | 717 |
"""simple docstring"""
def _a ( _snake_case = 10 , _snake_case = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , _snake_case )
UpperCAmelCase = range(1 , _snake_case )
return sum(
1 for power in powers fo... | 74 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( __a ):
'''simple docstring'''
__UpperCamelCase = (DDPMParallelScheduler,)
def _UpperCamelCa... | 329 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_ava... | 451 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ = 0 , lowercase_ = 0 ) -> Union[str, Any]:
"""simple docstring"""
A__ = right or len(lowercase_ ) - 1
if left > right:
return -1
elif list_dat... | 721 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassification,
Au... | 177 | 0 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
a :Any = logging.get_log... | 680 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configur... | 680 | 1 |
"""simple docstring"""
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipelin... | 359 |
"""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
A: List[An... | 359 | 1 |
'''simple docstring'''
from __future__ import annotations
from cmath import sqrt
def UpperCamelCase ( lowercase_ : Any , lowercase_ : Optional[Any] , lowercase_ : Optional[int] ) -> tuple[complex, complex]:
'''simple docstring'''
if a == 0:
raise V... | 72 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
__UpperCAmelCase ="""us-east-1""" # defaults region
@dataclass
class lowerCAmelCase__ :
lowercase__ : str
lowercase__ : List[Any] = """arn:aws:iam::558105141721:role/sagemaker_execution_role"""
lower... | 337 | 0 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
snake_case_ : Union[str, Any] = '\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n ... | 350 |
'''simple docstring'''
def __snake_case ( _UpperCAmelCase : list[list[float]]):
UpperCamelCase = []
for data in source_data:
for i, el in enumerate(_UpperCAmelCase):
if len(_UpperCAmelCase) < i + 1:
data_lists.append([])
data_lists[i].appen... | 350 | 1 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
UpperCAmelCase_ : Union[str, Any] = '''\
'''
UpperCAmelCase_ : int = '''
Perplexity ... | 24 |
'''simple docstring'''
class UpperCAmelCase :
def __init__( self : List[str] , __snake_case : str ) -> Union[str, Any]:
_lowerCAmelCase = val
_lowerCAmelCase = None
_lowerCAmelCase ... | 207 | 0 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ ):
__SCREAMING_SNAKE_CASE = """"""
__SCREAMING_S... | 721 |
'''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_devic... | 680 | 0 |
"""simple docstring"""
def lowerCamelCase_ (UpperCamelCase__ : Any ):
stooge(UpperCamelCase__ , 0 , len(UpperCamelCase__ ) - 1 )
return arr
def lowerCamelCase_ (UpperCamelCase__ : List[Any] , UpperCamelCase__ : List[Any] , UpperCamelCase__ ... | 506 |
"""simple docstring"""
import qiskit
def lowerCamelCase_ (UpperCamelCase__ : int , UpperCamelCase__ : int ):
_UpperCAmelCase : Any = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
_UpperCAmelC... | 506 | 1 |
"""simple docstring"""
import numpy as np
def UpperCAmelCase ( snake_case : np.ndarray ):
return 1 / (1 + np.exp(-vector ))
def UpperCAmelCase ( snake_case : np.ndarray ):
return vector * sigmoid(snake_case )
if __name__ == "__main__":
impor... | 700 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils i... | 439 | 0 |
"""simple docstring"""
import os
from pathlib import Path
def __A () ->List[str]:
"""simple docstring"""
from torch.utils.cpp_extension import load
lowerCAmelCase__ :List[Any] = Path(_SCREAMING_SNAKE_CASE ).resolve().parent.parent.parent / 'kernels' / 'deformable_de... | 93 |
import qiskit
def lowercase ( SCREAMING_SNAKE_CASE = 2 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
SCREAMING_SNAKE_CASE_ = qubits
# Using Aer's simulator
SCREAMING_SNAKE_CASE_ = qiskit.Aer.get_backend('aer_simulator' )
# Creating a Quantum... | 205 | 0 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class __UpperCAmelCase ( __A ):
"""simple docstring"""
def __init__( self ... | 209 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE = {'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}
try:
if not is_vision... | 209 | 1 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
UpperCAmelCase__ : List[str] = len(A__ )
UpperCAmelCase__ : Union[str, Any] = len(matrix[0] )
UpperCAmelCase__ : Optional[int] = ... | 65 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( A__ : list , A__ : int , A__ : int , A__ : int ):
'''simple docstring'''
lowerCAmelCase_ : int = []
lowerCAmelCase_, ... | 275 | 0 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lower... | 471 |
'''simple docstring'''
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def SCREAMING_SNAKE_CASE( UpperCamelCase ,UpperCamelCase ,UpperCamelCase ,UpperCamelCase ,UpperCamelCase ) -> Tuple:
# load bas... | 471 | 1 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def lowerCAmelCase__(__snake_case ,__snake_case ) -> np.array:
'''simple docstring'''
lowerCamelCase__ = F'{sampling_rate}'
lowerCamelCase__ ... | 481 |
from math import factorial
_a = {str(digit): factorial(digit) for digit in range(10)}
def lowerCAmelCase__(__snake_case ) -> int:
'''simple docstring'''
if not isinstance(__snake_case ,__snake_case ):
raise TypeError('''Parameter number must be int''' )
if number <... | 481 | 1 |
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.csv'] )
@pytest.... | 676 |
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.csv'] )
@pytest.... | 676 | 1 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 571 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case : ... | 571 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.t... | 227 | """simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from... | 227 | 1 |
'''simple docstring'''
import math
def UpperCAmelCase ( A : int ):
SCREAMING_SNAKE_CASE : Tuple = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(A )
def UpperCAmelCase ( A : float = 1... | 527 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : Dict = {
'configuration_encodec': [
'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 527 | 1 |
"""simple docstring"""
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import GradientAcc... | 614 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __magic_name__ :
_SCREAMING_SNAKE_CASE : float
_SCREAMING_SNAKE_CASE : TreeNode | None = None
_SCREAMING_SNAKE_CASE : TreeNode... | 614 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A = {
'''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GraphormerConfig'''],
}
try:
if not is_torch_available():
... | 593 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase = {
"""configuration_ro... | 259 | 0 |
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_dimension_format,
)... | 710 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class ... | 154 | 0 |
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 TFModelTesterMixin, ... | 39 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_... | 385 | 0 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __UpperCAmelCase( lowercase_ ):
return (data["data"],... | 613 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from ... | 613 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowercase_ ( __A : str ) -> None:
"""simple docstring"""
lowercase , lowercase : Any =analyze_text(__A )
l... | 94 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
_snake_case = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["export", "validate_model_out... | 500 | 0 |
def lowercase ( a = 1000 ):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ :Union[str, Any] = 2**power
SCREAMING_SNAKE_CASE_ :Optional[int] = str(a )
SCREAMING_SNAKE_CASE_ :Union[str, Any] = list(a )
SCREAMING_SNAKE_CASE_ :List[An... | 720 |
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,
)
SCREAMING_SNAKE_CASE__ = {
"configuration_albert": ["ALBERT_PRE... | 140 | 0 |
'''simple docstring'''
from math import pi
def UpperCamelCase__ ( __magic_name__ : int , __magic_name__ : int ) -> float:
'''simple docstring'''
return 2 * pi * radius * (angle / 3_60)
if __name__ == "__main__":
print(arc_length(90, 10))
| 38 |
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 (
... | 556 | 0 |
'''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
... | 711 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A__: Optional[int] = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig... | 506 | 0 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowerCAmelCase : Optional[int] = datasets.logging.get_logger(__name__)
lowerCAmelCase : List[str] = """\
@inprocee... | 444 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = ["torch", "torchsde"]
def __init__( sel... | 444 | 1 |
'''simple docstring'''
def a ( __a ) -> bool:
'''simple docstring'''
UpperCamelCase__ :set[int] = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
UpperCamelCase__ :set[int] = set()
ret... | 718 |
'''simple docstring'''
import json
import sys
def a ( __a , __a ) -> str:
'''simple docstring'''
with open(__a , encoding='''utf-8''' ) as f:
UpperCamelCase__ :List[str] = json.load(__a )
UpperCamelCase__ :int ... | 280 | 0 |
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def UpperCamelCase_( lowerCamelCase_ ) -> Dict:
_lowercase : List[... | 89 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassification,
DataC... | 89 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json',
}
class lowerCAmelCase__( __lower... | 381 |
def lowerCamelCase__ (__lowerCamelCase = 10**9 ):
_SCREAMING_SNAKE_CASE : List[str] = 1
_SCREAMING_SNAKE_CASE : Any = 2
_SCREAMING_SNAKE_CASE : List[Any] = 0
_SCREAMING_SNAKE_CASE : Dict = 0
_SCREAM... | 381 | 1 |
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
def __init__( self ,__snake_case ,__snake_case ):
"""simple docstring"""
... | 188 |
from __future__ import annotations
def UpperCAmelCase_ ( _UpperCAmelCase :list[float] , _UpperCAmelCase :list[float] ) -> float:
'''simple docstring'''
A_ = sorted(numsa + numsa )
A_ , A_ = divmod(len(_UpperCAmelCase ) ... | 188 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
__lowerCAmelCase : Optional[Any] ... | 704 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def __snake_case ( UpperCamelCase ) -> float:
"""simple docstring"""
return np.dot(UpperCamelCase , UpperCamelCase )
class SCREAMING_SNAKE_CASE ... | 158 | 0 |
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
def _UpperCamelCase (a__ :Union[tf.Tensor, np.ndarray] ):
"""simple docstring"""
if isinstance(lo... | 619 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def lowercase__ ( lowerCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[int]:
'... | 642 | 0 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCAmelCase ( nn.Module ):
lowercase = 42
lowercase = 42
lowercase = 0.0... | 181 |
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 transformers.utils import loggin... | 181 | 1 |
'''simple docstring'''
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_ut... | 370 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowercase = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfi... | 370 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import fl... | 705 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json''',
#... | 452 | 0 |
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 ...test_modeling_common impor... | 291 |
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requ... | 291 | 1 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNet... | 596 |
from pathlib import Path
import fire
from tqdm import tqdm
def snake_case( __magic_name__="ro" , __magic_name__="en" , __magic_name__="wmt16" , __magic_name__=None ) -> None:
'''simple docstring'''
try:
import datasets
... | 596 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common... | 580 |
"""simple docstring"""
__lowerCamelCase = {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
__lowerCamelCase = ["a", "b", "c", "d", "e"]
def lowercase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> int:
__magic_name__ = start
# add curren... | 490 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"google/canine-s": "https://huggingface.co/google/canine-s/resolve/main/config.json",
# See all CANINE models at https://huggingface.co/models?filter=canine
}... | 706 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_A = "▁"
_A = {"vocab_file": "spiece.model"}
_A = {
... | 294 | 0 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 283 |
from __future__ import annotations
def _lowerCAmelCase ( lowerCAmelCase_ :int , lowerCAmelCase_ :int )->list[str]:
'''simple docstring'''
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_bytes... | 283 | 1 |
'''simple docstring'''
from math import factorial
def lowerCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase ) ->float:
"""simple docstring"""
if successes > trials:
raise ValueError('''successes must be lowe... | 703 |
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,
)
... | 336 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json''',
# ... | 84 |
from __future__ import annotations
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
lowercase = str(__SCREAMING_SNAKE_CASE )
return n == n[::-1]
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE = 100_0000 ):
lowercase = 0
for i in range(1 , __SCRE... | 84 | 1 |
"""simple docstring"""
from __future__ import annotations
import pandas as pd
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = [0] * no_of_processes
UpperCAmelCase = ... | 378 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = 0
UpperCAmelCase = len(lowerCAmelCase )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase ):
... | 378 | 1 |
from PIL import Image
def _snake_case ( lowerCAmelCase : Image ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = image.size
SCREAMING_SNAKE_CASE_ : Optional[Any] = 0
SCREAMING_SNAKE_CASE_ : Union[str, Any] = im... | 216 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class _UpperCAmelCase ( datasets.BeamBasedBuilder):
... | 238 | 0 |
'''simple docstring'''
from manim import *
class SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def snake_case__ ( self : Any ) ->Optional[Any]:
'''simple docstring'''
_Up... | 204 | '''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_ : Tuple = {
"""huggingface/time-series-transformer-tou... | 204 | 1 |
'''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
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_C... | 523 |
'''simple docstring'''
lowerCAmelCase : Optional[Any] = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
def A_( A : dict , A : str , A :... | 3 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase : str = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""Gro... | 712 |
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 OptionalDependencyNotAvailable:
from ...utils.du... | 25 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_devi... | 314 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
lowercase_ = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__( self , *A , **A ) ... | 314 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determin... | 709 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"YituTech/conv-bert-base": "https... | 276 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMix... | 435 | import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A... | 486 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
... | 720 |
"""simple docstring"""
import numpy as np
def lowerCAmelCase_( lowercase_ : np.ndarray , lowercase_ : np.ndarray , lowercase_ : float = 1e-12 , lowercase_ : int = 1_00 , ) -> tuple[float, np.ndarray]:
assert np.shape(lowercase... | 623 | 0 |
'''simple docstring'''
from collections.abc import Sequence
def lowerCAmelCase_ ( snake_case_ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
Up... | 78 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ = {
'''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''GitVisionConfig'''],
'''processing_git'''... | 227 | 0 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_av... | 9 |
'''simple docstring'''
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.proces... | 9 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def lowerCamelCase_( _lowe... | 46 |
"""simple docstring"""
_UpperCamelCase = {
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""zettametre""": """Zm""",
"""yotta... | 341 | 0 |
'''simple docstring'''
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class UpperCamelCase ... | 708 | '''simple docstring'''
import os
def SCREAMING_SNAKE_CASE__ ( ) -> List[Any]:
"""simple docstring"""
a : List[str] = os.path.join(os.path.dirname(snake_case ) , 'num.txt' )
with open(snake_case ) as file_hand:
return str... | 610 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase :Optional[int] = logging.get_logger(__name__)
lowerCamelCase :str = {
'''nielsr/canine-s''': 2... | 667 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
Aut... | 667 | 1 |
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
fr... | 714 |
"""simple docstring"""
def lowercase__(A ) ->list[int]:
"""simple docstring"""
lowercase__ : List[str]= len(A )
for i in range(A ):
for j in range(i + 1 , A ):
if numbers[j] < numbers[i]:
... | 85 | 0 |
from maths.prime_factors import prime_factors
def snake_case__ ( __SCREAMING_SNAKE_CASE ) -> List[Any]:
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
UpperCAmelCase_ = f'''Input value of [number={number}] must be an integer'''
raise TypeError(UpperCamel... | 579 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def lowerCamelCase_ (UpperCamelCase__ : list , UpperCamelCase__ : list , UpperCamelCase__ ... | 506 | 0 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class low... | 713 |
"""simple docstring"""
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, torc... | 22 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class SCREAMING_SNAKE_CASE ( _lowerCamelCase )... | 225 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : str = {'configuration_unispeech': ['UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechC... | 265 | 0 |
from random import shuffle
import tensorflow as tf
from numpy import array
def UpperCamelCase__( UpperCamelCase__ : int , UpperCamelCase__ : str )->Optional[Any]:
A__ = int(UpperCamelCase__ )
assert noofclusters < len(UpperCamelCase__ )
... | 714 |
def UpperCamelCase__( UpperCamelCase__ : Optional[int] , UpperCamelCase__ : List[Any] )->List[str]:
A__ = [1]
for i in range(2 , UpperCamelCase__ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k ou... | 212 | 0 |
from __future__ import annotations
def __UpperCamelCase ( A ): # This function is recursive
UpperCamelCase__ = len(A )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if array_length <= 1:
return... | 415 | import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
__magic_name__ =logging.get_logger(__name__)
__magic_name__ =r'''
Args:
input_ids (`torch.LongTensor` of shape `(... | 415 | 1 |
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 ):
"""simple docstring"""
def __A ( sel... | 707 | import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
A : List[str] = False
class lowerCamelCase (unittest.TestCase ):
... | 356 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
Wav... | 293 |
import pytest
import datasets
# Import fixture modules as plugins
__snake_case = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def _A ( _lowercase , _lowercase ) -> Tuple:
"""simple docstring"""
for item in ... | 1 | 0 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def snake_case__ ( _SCREAMING_SNAKE_CASE = 3 ) ->qiskit.result.counts.Counts:
if isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_... | 713 |
"""simple docstring"""
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accele... | 422 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase =logging.get_logger(__name__)
_lowerCamelCase ={
"""facebook/wav2vec2-base-960h""": """https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/config.json""",
# ... | 681 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase =logging.get_logger(__name__)
_lowerCamelCase ={
"""edbeeching/decision-transformer-gym-hopper-medium""": (
"""https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/co... | 681 | 1 |
'''simple docstring'''
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowerCAmelCase_ ( lowerCamelCase , lowerCamelCase=7 ):
__magic_name__ : List[Any] =None
if token is not None:
... | 715 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
UpperCAmelCase_ : Dict = 637_8137.0
UpperCAmelCase_ : List[Any] = 635_6752.31_4245
UpperCAmelCase_ : List[str] = 6378137
def lowerCAmelCase_ ( l... | 367 | 0 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import Ba... | 100 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
a = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
]... | 7 | 0 |
"""simple docstring"""
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
... | 712 |
"""simple docstring"""
import random
from .binary_exp_mod import bin_exp_mod
def UpperCamelCase_ ( SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_=1_0_0_0 ):
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
SCREAMING... | 406 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available():
import torch
... | 68 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import... | 303 | 0 |
'''simple docstring'''
from __future__ import annotations
from cmath import sqrt
def _SCREAMING_SNAKE_CASE ( lowercase : Dict , lowercase : Optional[Any] , lowercase : Optional[Any] ):
'''simple docstring'''
if a == 0:
r... | 717 |
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
lowerCamelCase : List[Any] = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
... | 651 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_UpperCAmelCase : Any = logging.get_logger(__name__)
class lowercase_ ( _UpperCamelCase ):
"""simple docstring"""
def __init__( sel... | 107 | '''simple docstring'''
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( __snake_case : int | str ):
_A = str(__snake_case )
return n == n[::-1]
def _SCREAMING_SNAKE_CASE ( __snake_case : int = 1_0_0_0_0_0_0 ):
_A = 0
f... | 107 | 1 |
from __future__ import annotations
_lowercase : Tuple =1.6_0_2_1E-1_9 # units = C
def A__ ( lowercase: float, lowercase: float, lowercase: float, ) -> tuple[str, float]:
if (conductivity, electron_conc, mobility).count(0 ) != 1:
raise Va... | 661 | import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test... | 661 | 1 |
'''simple docstring'''
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class SCREAMING_SNAKE_CASE__ ( _UpperCamelCase ):
... | 69 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from tr... | 536 | 0 |
'''simple docstring'''
from importlib import import_module
from .logging import get_logger
__UpperCAmelCase :int = get_logger(__name__)
class a :
"""simple docstring"""
def __init__( self : Optional[int] , snake_case : Tu... | 266 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _a ( _lowercase : int ):
'''simple docstring'''
__UpperCAmelCase : int = int(number**0.5 )
... | 266 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__magic_name__ : Any = {"""processing_wav2vec2_with_lm""": ["""Wav2Vec2ProcessorWithLM"""]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:... | 102 |
"""simple docstring"""
import argparse
a = '''docs/source/_static/js/custom.js'''
def _snake_case ( _snake_case : Dict ) -> Any:
'''simple docstring'''
with open(_snake_case , encoding='utf-8' , newline='\n' ) as f:
_... | 7 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
'kssteven/i... | 201 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE_ = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowerConf... | 201 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, 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 impo... | 168 | '''simple docstring'''
import os
import sys
import unittest
_a : Optional[int] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402... | 168 | 1 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A : str = logging.get_logger(__name__)
A : Union[str, Any] = {
"vocab_file": "vocab.txt",
"merg... | 700 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, ... | 5 | 0 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: int | str ):
"""simple docstring"""
UpperCAmelCase_: Optional[int] = str(lowerCAmelCase__ )
return n == n[::-1]
def lowerCAmelCase_ (lowerCAmelCase__: int = 1_... | 556 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mas... | 556 | 1 |
def A_ ( lowercase_ ) ->Union[str, Any]:
"""simple docstring"""
assert column_title.isupper()
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = len(_lowerCAmelCase ) - 1
SCREAMING_SNAKE_CASE = 0
while index >= 0:
SCREAMING_SNAKE_CASE = (o... | 711 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDepen... | 259 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowercase )
class lowercase__ ( lowercase ):
# `task` is not a ClassVar since we wan... | 195 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ ):
return int((input_a, input_a).count(0 ) != 0 )
def A__ ( ):
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ) == 1
assert nand_gate(1 , 0 ) == 1
assert... | 195 | 1 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class _A ( pl.LightningModule ):
def __init__( self , _SCREAMING_SNAKE_CASE ):
super().__init__()
_UpperCA... | 711 |
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_up_block
... | 175 | 0 |
"""simple docstring"""
def lowercase_ ( _lowercase : int , _lowercase : Tuple ):
'''simple docstring'''
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(A__ , int(b / 2 ) ) * actual_power(A__ , int(b / 2 ... | 595 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils im... | 426 | 0 |
'''simple docstring'''
from __future__ import annotations
def __lowerCamelCase ( __lowerCAmelCase : list[int] ) -> int:
snake_case = len(__lowerCAmelCase ) // 2
# choose the middle 3 elements
snake_case = lst[m - 1 : m + 2]
# if mi... | 517 |
'''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _lowerCAmelCase ( ctypes.Structure ):
"""simple docstring"""
snake_case_ = [(... | 517 | 1 |
from __future__ import annotations
def _a ( UpperCamelCase_ : list , UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : int ) -> list:
"""simple docstring"""
lowerCAmelCase__ = []
lowerCAmelCase__ , ... | 339 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''YituTech/conv-bert-base''': '''https://huggingface.co/YituTech/conv-bert... | 339 | 1 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
lowerCamelCase__ = 0
while number:
... | 9 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def A__ ( __lowerCAmelCase : Union[str, Any] ):
lowerCamelCase__ = [
"""encoder.version""",
"""decoder.vers... | 9 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''xlm-roberta-base''': '''https://huggingface.co/xlm-robert... | 157 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
A_ = (7_20, 12_80) # Height, Width
A_ = (0.4, 0.6) # if height or width lower than this scale, drop it.
A_ =... | 609 | 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.configuration_pegasus imp... | 521 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ : Dict = logging.get_logger(__name__)
lowerCAmelCase_ : Any ... | 521 | 1 |
"""simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase ( lowerCAmelCase__ : Any , lowerCAmelCase__ : List[str]=7 ) -> Union[str, Any]:
__a = None
if toke... | 695 |
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
from di... | 253 | 0 |
'''simple docstring'''
def __A ( _SCREAMING_SNAKE_CASE : Any ):
"""simple docstring"""
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
... | 564 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base impo... | 564 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diff... | 516 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
snake_case_ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ):
def __init__( self ,... | 421 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _a ( _SCREAMING_SNAKE_CASE = "AAPL" ) -> str:
snake_case_ = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
snake_case_ = BeautifulSoup(requests.get(_SCREAMING_SNAK... | 2 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
... | 2 | 1 |
a__: Tuple = 256
# Modulus to hash a string
a__: Dict = 1_000_003
def UpperCamelCase__( UpperCamelCase__ : str , UpperCamelCase__ : List[str] )->Optional[Any]:
A__ = len(__lowercase )
A__ = len(__lowercase )
... | 190 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
while second != 0:
lowerCamelCase__ = first & second
first ^= second
lowerCamelCase__ = c << 1
return first
... | 129 | 0 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
lowerCamelCase : List[str] = Mapping[str, np.ndarray]
lowerCamelCase : Any = Mapping[str, Any] # Is a nes... | 704 |
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 TFModelTesterMixin, ids_ten... | 649 | 0 |
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