code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.uti... | 162 |
'''simple docstring'''
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__( ... | 162 | 1 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_... | 338 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
a : List[Any] = logging.get_log... | 338 | 1 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common im... | 141 |
'''simple docstring'''
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 75 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Tuple = ["image_processor", "tokenizer"]
S... | 357 |
"""simple docstring"""
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowerCamelCase__ = "%20".join(argv[1:]) if len(argv) > 1 else quote(str(input("Search... | 310 | 0 |
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
UpperCAmelCase : Tuple = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
'''text-classifica... | 280 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ ... | 153 | 0 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _SCREAMING_SNAKE_CASE ( _lowercase : List[Any] , _lowercas... | 79 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.util... | 79 | 1 |
"""simple docstring"""
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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
#
# Un... | 109 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .toke... | 223 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( lowerCamelCase : Optional[Any] , lowerCamelCa... | 371 |
'''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common i... | 55 | 0 |
from __future__ import annotations
import math
def a__ ( A_, A_, A_, A_, A_ ):
'''simple docstring'''
if depth < 0:
raise ValueError("""Depth cannot be less than 0""" )
if not scores:
raise ValueError("""Scores cannot be empty""" )
... | 88 |
"""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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils impor... | 109 | 0 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
raise ValueErro... | 135 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForS... | 135 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def UpperCAmelCase__ ( lowerCAmelCase__ :Any , lowerCAmelCase__ :str , lowerCAmelCase__ :str , lowerCAmelCase__ :Union[s... | 197 | """simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : List[Any] =logging.get... | 197 | 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
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : Optional[Any] ... | 354 |
def lowerCAmelCase_ ( _snake_case : int , _snake_case : Optional[int] ) -> List[Any]:
'''simple docstring'''
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowerCAmelCase_ ( _snake_case : List[Any] , _snake_case : Option... | 41 | 0 |
"""simple docstring"""
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase , **_UpperCamelCase ):
__lowerCAmelCase : List[Any] = AutoConfig.from_pretrained(_UpperCamelCase ... | 86 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( __lowercase ):
"""simple docstring"""
UpperCAmelCase__ : List[Any] = (DDPMScheduler,)
def __lowercase ( sel... | 235 | 0 |
'''simple docstring'''
__a = 8.3_1_4_4_5_9_8
def __UpperCAmelCase ( a_: float, a_: float ):
if temperature < 0:
raise Exception("Temperature cannot be less than 0 K" )
if molar_mass <= 0:
raise Exception("Molar mass cannot be less than or equal to 0 kg/mol... | 17 | '''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@requi... | 17 | 1 |
def __lowerCamelCase ( snake_case__ ) -> bool:
"""simple docstring"""
_SCREAMING_SNAKE_CASE = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def __lowerCamelCase ( snake_case__ = 50_00 ) -> int:
... | 306 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | 306 | 1 |
'''simple docstring'''
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transfo... | 364 |
'''simple docstring'''
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 A_ ... | 280 | 0 |
"""simple docstring"""
import math
def lowercase ( A_ , A_ = 0 , A_ = 0 )-> list:
'''simple docstring'''
a : Optional[Any] = end or len(A_ )
for i in range(A_ , A_ ):
a : Optional[Any] =... | 40 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : str = {}
class __snake_case ( a ):
UpperCAmelCase__ : str = '''llama'''
UpperCAmelCase__ : ... | 51 | 0 |
'''simple docstring'''
def _a ( _lowerCamelCase , _lowerCamelCase ) -> list[str]:
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(_lowerCamelCase ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testm... | 357 |
'''simple docstring'''
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import Squ... | 13 | 0 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
TrainingArgument... | 337 |
def __lowercase ( a__ ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or not...''')
lowerCAmelCase__ : Optional[Any] =int(input(''... | 257 | 0 |
"""simple docstring"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def __A ( a_ :Optional[int]) -> int:
return 1 / (1 + np.exp(-z))
def __A ( a_ :Optional[Any] , a_ :int) -> Dict:
return (-... | 356 |
"""simple docstring"""
import os
import string
import sys
A = 1 << 8
A = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 27,
'''up''': 65 + ARROW_KEY_FLAG,
'''down''': 66 + ARROW_KEY_FLAG,
'''right''': 67 + ARROW_KEY... | 188 | 0 |
def lowerCAmelCase__ ( ):
'''simple docstring'''
return [list(range(1000 - i ,-1000 - i ,-1)) for i in range(1000)]
__snake_case : Any =generate_large_matrix()
__snake_case : str =(
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[... | 129 |
def lowerCAmelCase__ ( lowerCamelCase_ : list[list[float]]):
'''simple docstring'''
lowerCAmelCase__ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(lowerCamelCase_):
if len(lowerCamelCase_) < i + 1:
data_lis... | 129 | 1 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...tes... | 306 |
def snake_case_ ( lowerCAmelCase_ : int ):
__lowercase : int = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def snake_case_ ( lowerCAmelCase_ : int = 5000 ):
__lowercase : Optional[int] = [(i * (3 * i - 1)) // 2 for ... | 306 | 1 |
'''simple docstring'''
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__a: Any = logging.get_logger(__name__)
def __UpperCamelCase ( UpperCAmelCase , UpperCAmelCa... | 198 |
'''simple docstring'''
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def a ( lowerCamelCase_... | 206 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_to... | 352 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_lowercase : Union[str, Any] =logging.get_logger(__name__)
class snake_case__ (A__ ):
"""simple docstring"""
def __init__( self... | 266 | 0 |
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=A__ ):
lowerCAmelCase__ : str = ["torch"]
def __init__( self : Any , *_UpperCAmelCase : Union[str, Any] , **_UpperCAmelCase : List[Any] ) -> Dict:
"""simple d... | 325 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import... | 126 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : Optional[Any] ):
lowercase_ : Any = current_set.copy()
for row_index, row in enumerate(SCREAMING_SNAKE_CASE__ ):
lowercase_ : Optional[int] = row[0]
for column_index... | 366 | '''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_av... | 21 | 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,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta... | 59 |
'''simple docstring'''
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow... | 344 | 0 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class __lowercase :
'''simple docstring'''
def __init__( self : ... | 35 | def lowerCamelCase_ ( UpperCamelCase__ : list[int], UpperCamelCase__ : list[int], UpperCamelCase__ : int ):
'''simple docstring'''
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(UpperCamel... | 35 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : Dict =logging.get_logger(__name__)
A__ : Dict ={
'''SCUT-DLVCLab/lilt-roberta-en-base''': (
'''https://huggingface.co/SCUT-DLVCLab/lilt-robert... | 70 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
A__ : Any =logging.g... | 70 | 1 |
'''simple docstring'''
import math
class lowerCAmelCase_:
'''simple docstring'''
def __init__( self ,__UpperCAmelCase=0 ) -> int: # a graph with Node 0,1,...,N-1
lowerCAmelCase__ : List[str] = n
lowerCAmelCase__ : int = [
[math.inf for j ... | 352 |
'''simple docstring'''
class lowerCAmelCase_:
'''simple docstring'''
def __init__( self ,__UpperCAmelCase ) -> Tuple:
lowerCAmelCase__ : Union[str, Any] = n
lowerCAmelCase__ : int = [None] * self.n
lowerCAmelCase__ : Union[str, Any] = 0... | 184 | 0 |
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
__UpperCAmelCase : str = logging.getLogger()
def A__ ( ... | 111 |
def A__ ( SCREAMING_SNAKE_CASE__) -> Union[str, Any]:
__snake_case: List[Any] = []
__snake_case: List[str] = []
__snake_case: List[str] = {
"""^""": 3,
"""*""": 2,
"""/""": 2,
"""%""": 2,
"""+""": 1,
"""-""": 1,
} # ... | 111 | 1 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _lowerCamelCase(__UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> Optional[int]:
_lowerCAmelCase =0
if start < end:
_lowerCAmelCase =randint(_Upper... | 365 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__A = logging.get_l... | 341 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a : Union[str, Any] = {
'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}
try:
... | 265 |
'''simple docstring'''
class lowercase__ :
'''simple docstring'''
def __init__( self , __snake_case = "" , __snake_case = False ):
# Mapping from the first character of the prefix of the node
_SCREAMING_SNAKE_CASE : dict[str, RadixNode] ... | 200 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCAmelCase__ :Optional[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Dict = {
"... | 364 |
from __future__ import annotations
from PIL import Image
# Define glider example
lowerCAmelCase__ :str = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0... | 185 | 0 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_UpperCAmelCase : int = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
rai... | 222 |
from __future__ import annotations
import os
from collections.abc import Mapping
_UpperCAmelCase : Tuple = tuple[int, int]
class lowercase :
def __init__( self , A_ , A_ ) -> None:
"""simple docstring"""
UpperCamelCase = vertices
UpperCamelCas... | 222 | 1 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase: List[str] = logging.get_logger(__name__)
_lowercase: Optional[Any] = {
"kakaobrain/align-base"... | 71 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowercase ( lowerCAmelCase ):
"""simple docstring"""
__A = ["image_processor", "tokenizer"]
__A = "ViTImageProcessor"
__A ... | 71 | 1 |
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="session" )
def UpperCamelCase ( ):
sn... | 59 |
from __future__ import annotations
__lowerCamelCase = list[list[int]]
# assigning initial values to the grid
__lowerCamelCase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, ... | 59 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str ):
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = [0] * len(lowerCamelCase_ )
for i in range(1 , len(lowerCamelCase_ ) ):
# use last results f... | 274 | '''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
def _UpperCamelCase ( self ):
'''simple docstring'''
UpperCAmelCase_ : Dict = Rectangle(height=0.5 , width=0.5 ... | 274 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowerCAmelCase (lowercase_ , unittest.TestCase ):
'''simple docstring... | 2 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
lowerCamelCase : Any = re.compile(R'([A-Z]+)([A-Z][a-z])')
lowerCamelCase : str = re.compile(R'([a-z\d])([A-Z])')
lowerCamelCase : Optional[int] = re.compile(R'(?<!_)_(?!_)')
lowerCamelCase... | 2 | 1 |
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE_ = 100 ):
lowercase__ = (n * (n + 1) // 2) ** 2
lowercase__ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(F'{solution() = }')
| 224 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional import Inte... | 224 | 1 |
import math
import sys
def lowerCamelCase_ ( _a : str ):
'''simple docstring'''
UpperCAmelCase_ : str = ''''''
try:
with open(_lowercase , """rb""" ) as binary_file:
UpperCAmelCase_ : Union[str, Any] = binary_file.read()
... | 345 | import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 182 | 0 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
__SCREAMING_SNAKE_CAS... | 353 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Any = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abej... | 73 | 0 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class _UpperCAmelCase ( A__ ):
"""sim... | 207 |
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 _UpperCAmelCase ( ... | 207 | 1 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__A =argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_argument('--dpm'... | 358 |
'''simple docstring'''
import numpy
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase):
UpperCAmelCase__ : Dict = input_array
# Random initial weights are assigned where first argument is t... | 283 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
"""configuration_roberta""": ["""ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """R... | 176 |
def _lowercase ( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ ) -> int:
'''simple docstring'''
def update_area_of_max_square(UpperCamelCase_ , UpperCamelCase_ ) -> int:
# BASE CASE
if row >= rows or col >= cols:
return 0
SCREAMING_SN... | 176 | 1 |
"""simple docstring"""
import os
import numpy
import onnx
def _A ( lowercase , lowercase ):
"""simple docstring"""
a =a.name
a =b.name
a =''''''
a =''''''
a =a == b
a =name_a
a =name_b
r... | 215 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
norm... | 215 | 1 |
from __future__ import annotations
def A__ ( __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('''One and only one argument must be 0''' )
if resistance < 0:
raise ValueError('''Resistance cannot be n... | 299 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
def _SCREAMING_SNAKE... | 37 | 0 |
'''simple docstring'''
from datetime import datetime
import requests
def _lowerCAmelCase ( _UpperCamelCase : str ) -> bytes:
"""simple docstring"""
_SCREAMING_SNAKE_CASE ='https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
_SCREAMING_SNAKE_CA... | 355 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCamelCase : List[str] = {"UserAgent": UserAgent().random}
def _lowerCAmelCase ( _UpperCamelCase : str ) -> dict:
... | 114 | 0 |
import cva
import numpy as np
class a__ :
def __init__( self : Any,_A : float,_A : int ):
"""simple docstring"""
if k in (0.04, 0.06):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = k
SCREAMING_SNAKE_CASE_ :... | 18 | import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : str , lowerCAmelCase : str , lowerCAmelCase : Path , lowe... | 18 | 1 |
from math import sqrt
def lowercase__ ( __snake_case : int = 1_000_000 ):
'''simple docstring'''
UpperCAmelCase_ : int = 0
UpperCAmelCase_ : int = 0
UpperCAmelCase_ : int
while num_cuboids <= limit:
... | 353 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( __snake_case : Optional[Any] , __snake_case : Any , _... | 145 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : Dict = logging.get_logger(__name__)
A__ : int = {
"unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json",
}
class __snake_case ( ... | 103 |
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 (
AutoTokeni... | 227 | 0 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='''session''' )
def lowerCamelCase__ ( )... | 362 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.ut... | 91 | 0 |
'''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 di... | 28 |
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def UpperCamelCase ( ) -> tuple[list[int], int]:
UpperCamelCase : int = [randint(-1000 , 1000 ) for i in range(10 )]
UpperCamelCase : Dict = randint... | 119 | 0 |
'''simple docstring'''
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
_snake_case = [
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight', 'time_embedding.linear_1.... | 199 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = '▁'
_snake_case = {'vocab_file': 'spiece.model'}
_snake_... | 199 | 1 |
_a = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.60_93_44,
"knot": 1.8_52,
}
_a = {
"km/h": 1.0,
"m/s": 0.2_77_77_77_78,
"mph": 0.6_21_37_11_92,
"knot": 0.5_39_95_68_03,
}
def __A ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )->... | 39 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
_a = get_logger(__name__)
class __lowerCamelCase ( enum.Enum):
"""simple docstring"""
UpperCamelCase__ = ... | 39 | 1 |
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_configuration_common import ConfigTester
from ...t... | 63 | import inspect
import unittest
from transformers import DecisionTransformerConfig, 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 i... | 63 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ = 100 ):
'''simple docstring'''
A : List[str] = 0
A : List[str] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
ret... | 3 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowercase : Union[str, Any] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'a... | 3 | 1 |
import math
import unittest
def lowerCamelCase_ ( UpperCamelCase__ : int ) -> List[Any]:
"""simple docstring"""
assert isinstance(_a , _a ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:... | 365 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@... | 348 | 0 |
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,
MusicgenProcessor,
... | 275 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class _UpperCAmelCase :
def __init__( self : Union[str, Any] , _lowercase : Optional[Any] ):
__UpperCAmelCase = str(id_ )
__UpperCAmelCase = None
... | 332 | 0 |
'''simple docstring'''
class lowercase_ :
"""simple docstring"""
def __init__( self : Any ,lowercase__ : list ):
__lowercase = set_counts
__lowercase = max(lowercase__ )
__lowercase = len(lowercase__ )
__lowerc... | 52 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class lowercase_ (lowerCamelCase__ ):
"""simple docstring"""
def __init__( self : Lis... | 52 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWith... | 22 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import T... | 22 | 1 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 359 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusion.modeling_roberta_series... | 60 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DUM... | 14 | import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
lowerCAmelCase__ : str = (
'''4S 3H 2C 7S 5H''',
'''9D 8H 2C 6S 7H''',
'''2D 6D 9D TH 7D''',
'''TC 8C 2S JH 6C''',
'''JH 8S TH AH QH''',
'''TS KS 5S 9S ... | 143 | 0 |
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import PreTrai... | 223 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase_ : Optional[int] = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class _UpperCamelCase ( _A ):
... | 223 | 1 |
'''simple docstring'''
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
lowercase__ : Any = logging.get_logger(__name__)
lowercase__ : Tupl... | 190 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : List[str] = logging.get_logger(__name__)
lowercase__ :... | 190 | 1 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
) | 270 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
) | 270 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase : Any = {'''configuration_glpn''': ['''GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GLPNConfig''']}
try:
if not is_vision_available():
... | 280 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase : Any = {
'''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''],
}
try:
if not is_torch_available(... | 280 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pow, sqrt
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
"""simple docstring"""
if (resistance, reactance, impedance).count(... | 154 | """simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ ):
"""simple docstring"""
if inductance <= 0:
raise ValueError('Inductance cannot b... | 154 | 1 |
"""simple docstring"""
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def A__ ( UpperCamelCase ):
return x + 2
class _UpperCAmelCase ( unittest.TestCase ):
def lowerCamelCase (... | 292 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_com... | 311 | 0 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : str = logging.get_logger(__name__)
snake_case : List[str] ... | 371 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : List[str] ... | 281 | 0 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( __UpperCamelCase : list , __UpperCamelCase : int , __UpperCamelCase : int , __UpperCamelCase : int ) -> list:
"""simple docstring"""
SCREAMING_SNAKE_CASE__... | 219 | from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_... | 219 | 1 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
f... | 283 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .... | 283 | 1 |
"""simple docstring"""
def _A (__a , __a ) -> int:
"""simple docstring"""
while a != 0:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Optional[int] = b % a, a
return b
def _A (__a , __a ) -> int:
"... | 91 |
"""simple docstring"""
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
UpperCAmelCase_ : Optional[Any] = datasets.logging.get_logger(__name__)
UpperCAmelCase_ : List[str] ... | 91 | 1 |
import argparse
import os
import re
import packaging.version
UpperCAmelCase_ = """examples/"""
UpperCAmelCase_ = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compile(R"""^__ve... | 361 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase_ = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui W... | 295 | 0 |
"""simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
... | 221 | """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 ... | 221 | 1 |
'''simple docstring'''
def UpperCamelCase_( snake_case : list[list[int]] , snake_case : int , snake_case : int , snake_case : list[int] ):
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
retu... | 92 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
_SCREAMING_SNAKE_CASE : Any = False
class _snake_case ... | 92 | 1 |
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
import ja... | 11 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from ... | 75 | 0 |
lowerCamelCase : Tuple = {str(digit): digit**5 for digit in range(1_0)}
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> int:
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(SCREAMING_SNAKE_CASE_ ) )
def SCREAMING_SNAKE_CASE__ ( ) -> int:
return sum(
... | 366 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import loggi... | 176 | 0 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A__ : str = logging.get_logger(__name__)
A__ : List[str] = {'''vocab_file''... | 103 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
A__ : Union[str, Any] = {
'''n_samples''': 64,
'''horizon''': 32,
'''num_inference_steps''': 20,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, does not use value network
... | 103 | 1 |
import math
class __magic_name__ :
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( self :Optional[Any] , snake_case :list[list[float]] , snake_case :list[int] ):
'''simple docstring'''
A_ : List[Any] = 0.0
... | 70 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
_lowerCAmelCase : Any = (3, 9, -11, 0, 7, 5, 1, -1)
_lowerCAmelCase : Any = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __magic_name__ :
"""simple docstrin... | 70 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 5 |
'''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 transformers.utils ... | 56 | 0 |
def a_ ( lowerCAmelCase_ : list[int] ):
if not numbers:
return 0
if not isinstance(lowerCAmelCase_, (list, tuple) ) or not all(
isinstance(lowerCAmelCase_, lowerCAmelCase_ ) for number in numbers ):
raise ValueError('numbers must be an iterable of in... | 207 |
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi.routing import ... | 207 | 1 |
"""simple docstring"""
__magic_name__ = "Tobias Carryer"
from time import time
class SCREAMING_SNAKE_CASE_ :
"""simple docstring"""
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__=int(time())): # noqa: B008... | 100 |
"""simple docstring"""
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class ... | 105 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_comm... | 362 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_ut... | 159 | 0 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"kwargs, expected" , [
({"num_shards": 0, "max_num_jobs": 1}, []),
({"num_shards": 10, "max_num_jobs": 1}, [range... | 250 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a__ ( unittest.TestCase ):... | 250 | 1 |
"""simple docstring"""
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 ={
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingfac... | 364 | """simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 321 | 0 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_A : Any = False
... | 202 | import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied f... | 65 | 0 |
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 __snake_case ( snake_case_ ):
... | 350 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json""",
#... | 291 | 0 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowerCAmelCase__( lowercase : List[str] ) -> Optional[int]:
return getitem, k
def lowerCAmelCase__( lowercase : Tuple , lowercase : Opti... | 326 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
_UpperCamelCase = 4
_UpperCamelCase = 3
class _lowerCamelCase ( a ):
"""s... | 326 | 1 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
c... | 215 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
norm... | 215 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
'microsoft/unispeech-large-1500h-cv': (
'https://huggingface.co/microsoft/unispeech-large-1500h-cv/resolve/main/config.j... | 62 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
OpenAIGPTDoubleHeadsM... | 62 | 1 |
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision.transform... | 211 |
class _a :
def __init__( self : str , _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : Optional[int] , _SCREAMING_SNAKE_CASE : List[Any] )-> Tuple:
lowerCAmelCase__ : List[Any] = None
lowerCAmelCase__ : int = None
lo... | 211 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,... | 46 | """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 transforme... | 289 | 0 |
"""simple docstring"""
def __UpperCAmelCase ( __lowerCamelCase = 10_00 ) -> int:
return sum(e for e in range(3 , __lowerCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F'''{solution() = }''')
| 302 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 302 | 1 |
"""simple docstring"""
import operator
def UpperCAmelCase__ ( lowerCAmelCase__ :list , lowerCAmelCase__ :bool = False , lowerCAmelCase__ :list | None = None ) -> list:
'''simple docstring'''
lowercase = operator.lt if reverse else op... | 197 | """simple docstring"""
from scipy.stats import pearsonr
import datasets
__lowerCAmelCase : List[Any] ="""
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calcula... | 197 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwri... | 133 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class SCREAMING_SNAKE_CASE__ ( lowercase ... | 133 | 1 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoMode... | 110 |
"""simple docstring"""
from PIL import Image
def _snake_case ( lowercase__ : Image , lowercase__ : float ) -> Image:
'''simple docstring'''
def brightness(lowercase__ : int ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if n... | 84 | 0 |
'''simple docstring'''
import requests
UpperCAmelCase_ = '' # <-- Put your OpenWeatherMap appid here!
UpperCAmelCase_ = 'https://api.openweathermap.org/data/2.5/'
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "Chicago" , SCREAMING_SNAKE_CASE__ : str = APPID ):
'''sim... | 61 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : list[list[int]] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : set ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ = ... | 61 | 1 |
"""simple docstring"""
import unittest
from transformers import 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,
... | 61 |
'''simple docstring'''
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
__UpperCAmelCase = 0
__UpperCAmelCase = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0... | 323 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from trans... | 359 |
from ....utils import logging
_A = logging.get_logger(__name__)
class lowerCamelCase ( A_ ):
def __init__(self : Tuple , _A : Optional[int] , _A : Tuple=None , _A : Union[str, Any]=2_0_4_8 ) -> List[Any]:
snak... | 137 | 0 |
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