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 |
|---|---|---|---|---|
import string
from math import logaa
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ ) -> int:
__lowerCamelCase : Tuple = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , '' )
__lowerCamelCase : i... | 73 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokeni... | 304 | 0 |
"""simple docstring"""
from collections import deque
def _A ( lowercase ):
"""simple docstring"""
a =len(lowercase )
a =deque()
a =[False for _ in range(lowercase )]
a =[-1 for _ in range(lowercase )]
a =index_of[:]
... | 215 |
"""simple docstring"""
import inspect
import unittest
from transformers import YolosConfig
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_configura... | 215 | 1 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase_ :
def __init__( self, __a):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = list_of_points
# Degree determines the f... | 36 |
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 _lowerCAmelCase ( __a , unittest.TestCase ):
_lo... | 231 | 0 |
"""simple docstring"""
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_d... | 362 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : int = 50 ) ->int:
'''simple docstring'''
a : Any = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for ... | 79 | 0 |
"""simple docstring"""
from __future__ import annotations
lowercase__ : Dict = 1_0
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : int = 1
lowerCAmelCase_ ... | 224 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
... | 224 | 1 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_SCREAMING_SNAKE_CASE : Optional[Any] = {
"configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJa... | 213 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor... | 213 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise TypeError('''only integers accepted as input''' )
else:
A : int = ... | 3 |
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCase__ = get_tests_dir("""fixtures/spiece.mod... | 212 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_gra... | 369 | """simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Config... | 2 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : Union[str, Any] = {
"EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b... | 136 |
"""simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
UpperCAmelCase : Union[str, Any] = "__DUMMY_TRANSFORMERS_USER__"
UpperCAmelCase : Dict = "Dummy... | 136 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_availabl... | 355 |
'''simple docstring'''
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.... | 299 | 0 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowerCamelCase__ ) , ... | 82 |
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback, get_ear... | 82 | 1 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class lowerCamelCase__ ( logging.LoggerAdapter ):
'''simple docstring'''
@staticmethod
def UpperCamelCase__ ( lowerCamelCase_ ) -> str:
A = ... | 357 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from .... | 77 | 0 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowercase : Dict = None
try:
import msvcrt
except ImportError:
lowercase : Optional[int] = None
try:
import fcntl
except ImportError:
lowercase : Dict = ... | 20 |
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 _snake_case ( unittest.TestCase ):
'''simple docstring'''
def A__... | 345 | 0 |
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 accelerate import ... | 225 |
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 GradientAccumulator, create_... | 225 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnl... | 294 |
'''simple docstring'''
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
lowerCamelCase :str = TypeVar('''T''')
class _lowerCAmelCase (... | 206 | 0 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class UpperCAmelCase_ ( lowerCamelCase__ ):
'''simple docstring'''
... | 357 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAme... | 36 | 0 |
'''simple docstring'''
import numpy
class lowercase :
"""simple docstring"""
def __init__( self ,a_ ,a_ ) -> None:
_UpperCAmelCase : Optional[Any] = input_array
# Random initial weights are assigned where first argument is the
# numb... | 215 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from tr... | 215 | 1 |
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.processors import TemplateProcessing
cla... | 110 |
import logging
import os
from .state import PartialState
class lowercase ( logging.LoggerAdapter ):
@staticmethod
def __UpperCamelCase ( A_ ) -> Optional[Any]:
"""simple docstring"""
UpperCamelCase = PartialState()
return not main_process_only or (main_process_only an... | 110 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowerCAmelCase ( snake_case_ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = ['image_processor', 'tokenizer']
_SCREAMING_SN... | 159 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase_ = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
''... | 79 | 0 |
def __UpperCAmelCase ( __a : int ,__a : int ) -> Optional[Any]:
"""simple docstring"""
while second != 0:
_a : Tuple = first & second
first ^= second
_a : int = c << 1
return first
... | 365 |
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
a__ = yaml.safe_load(
'''\
name: ""
allow_empty: false
allow_empty_text: true
subsections:
- name: "Dataset Card for X"... | 15 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE ={
"asapp/sew-d-tiny-100k": "https://huggingface.co/asapp/sew-d-tiny-100k/resolve/ma... | 213 | """simple docstring"""
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassif... | 213 | 1 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def lowercase (SCREAMING_SNAKE_CASE_ : int ) -> bool:
SCREAMING_SNAKE_CASE = int(number**0.5 )
return number == sq * sq
def ... | 38 |
"""simple docstring"""
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... | 38 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : float ):
"""simple docstring"""
return 10 - x * x
def UpperCAmelCase__ (snake_case__ : float , snake_case__ : float ):
"""simple docstring"""
if equation(snake_cas... | 64 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import Ta... | 2 | 0 |
def _UpperCamelCase ():
"""simple docstring"""
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
UpperCamelCase__ = generate_large_matrix()
UpperCamelCase__ = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -... | 361 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
Up... | 87 | 0 |
"""simple docstring"""
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.swit... | 293 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
... | 293 | 1 |
'''simple docstring'''
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... | 346 |
'''simple docstring'''
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available()... | 346 | 1 |
import math
import tensorflow as tf
from packaging import version
def UpperCAmelCase_ ( __snake_case ) -> Optional[Any]:
"""simple docstring"""
_lowercase =tf.convert_to_tensor(_lowerCAmelCase )
_lowercase =0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqr... | 5 | """simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingSt... | 77 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
snake_case_ = R"""
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control... | 358 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
snake_case_ = 3
def _lowerCAmelCase ( lowercase_ ):
print('Generating primitive root of p' )
while True:
Up... | 181 | 0 |
import os
import pytest
from attr import dataclass
lowerCamelCase__ : Any = 'us-east-1' # defaults region
@dataclass
class lowerCamelCase_ :
'''simple docstring'''
lowercase_ = 42
lowercase_ = "arn:aws:iam::558105141721:role/sagemaker_execution_role... | 225 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tr... | 225 | 1 |
'''simple docstring'''
from math import ceil
def lowercase__ ( __UpperCamelCase = 1001 )-> int:
UpperCamelCase = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
UpperCamelCase = 2 * i + 1
UpperCamelCase = 2 * i... | 183 |
'''simple docstring'''
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing imp... | 183 | 1 |
def _A ( SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
a__ : Optional[Any] =[0] * len(SCREAMING_SNAKE_CASE )
for i in range(1 , len(SCREAMING_SNAKE_CASE ) ):
# use last results for better performance - dyna... | 95 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"facebook/wav2vec2-base-960h": "https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/config.json",
# See all Wav2Vec... | 36 | 0 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, Partial... | 119 | import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAme... | 119 | 1 |
import functools
def _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or not all(isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) for day in days ):
... | 110 |
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_mod... | 110 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE_ = {
"""configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
"""tokenization_tapas""": ... | 361 |
import json
import sys
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
'''simple docstring'''
with open(_SCREAMING_SNAKE_CASE , encoding="""utf-8""" ) as f:
SCREAMING_SNAKE_CASE = json.lo... | 193 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
A__ = logging.get_logger(__name__)
A__ = {"""voc... | 82 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Optiona... | 15 | 0 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import... | 363 |
"""simple docstring"""
def __lowercase ( ) ->Tuple:
'''simple docstring'''
__A : str = []
__A : List[Any] = 1
while len(snake_case_ ) < 1e6:
constant.append(str(snake_case_ ) )
i += 1
__A : ... | 291 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow,... | 38 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class _SCREAMING_SNAKE_CASE ( _a ):
def __init__( self : List[Any] , __lowerCamelCase : Callable , __low... | 38 | 1 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
l... | 353 |
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 Inter... | 117 | 0 |
'''simple docstring'''
def a_ ( __snake_case : Any , __snake_case : List[str] ) -> str:
"""simple docstring"""
lowerCamelCase_ =''''''
for i in table:
res += inp[i - 1]
return res
def a_ ( ... | 75 | from PIL import Image
def lowercase_ ( _lowerCamelCase : Image , _lowerCamelCase : int):
lowercase__ : List[str] = (259 * (level + 255)) / (255 * (259 - level))
def contrast(_lowerCamelCase : int) -> int:
return int(128 + factor * (c - 12... | 87 | 0 |
"""simple docstring"""
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,
Trai... | 132 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A_ = {
'''configuration_maskformer''': ['''MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MaskFormerConfig'''],
'''c... | 132 | 1 |
'''simple docstring'''
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_ava... | 346 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class lowerCAmelCase_ ( lowerCamelCase_ ... | 346 | 1 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE_ = {
'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
'scale_grad_by_s... | 371 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = [
['attention', 'attn'],
['enco... | 189 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ = {
"""configuration_layoutlmv3""": [
"""LAYOUTLMV3_PRETRAINED_CO... | 92 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowerCamelCase_ ( unittest.TestCase ):
def lowercase_ ( self : Tuple ):
''... | 181 | 0 |
"""simple docstring"""
def lowercase_ ( __UpperCAmelCase ) -> Union[str, Any]:
if len(lowercase__ ) < 2:
return collection
def circle_sort_util(__UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> bool:
lowerCAmelCase__ : int = ... | 363 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowercase_ ( __UpperCAmelCase ) -> None:
lowerCAmelCase__ , lowerCAmelCase__ : int = analyze_text(__UpperCAmelCase )
lowerCAm... | 212 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE : str = {
'''configura... | 183 |
"""simple docstring"""
from typing import Any
class a :
def __init__( self : Tuple , __SCREAMING_SNAKE_CASE : Any ) -> List[Any]:
lowerCamelCase_ = data
lowerCamelCase_ = ... | 183 | 1 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def __lowerCAmelCase ()-> Union[str, Any]:
"""simple docstring"""
snake_case_ = ArgumentParser(
description=(
... | 365 |
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, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor, loa... | 267 | 0 |
from ...processing_utils import ProcessorMixin
class lowerCAmelCase_ ( a__ ):
UpperCAmelCase__ : List[Any] = ["image_processor", "feature_extractor"]
UpperCAmelCase__ : Union[str, Any] = "TvltImageProcessor"
UpperCAmelCase__ : int = "T... | 119 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Effic... | 119 | 1 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _snake_case( SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : int , **SCREAMING_SNAKE_CASE__ : Tuple ) -> List[Any]:
'''simple ... | 359 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
lowercase_ = Path(__file__).resolve().parents[3] / "src"
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # noqa
import i... | 282 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ : int = 1000000 ) -> int:
'''simple docstring'''
A__ = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i... | 7 |
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=UpperCamelCase__ ):
__SCREAMING_SNAKE_CASE = ['''keras_nlp''']
def __init__( self,*__lowerCamelCase,**__lowerCamelCase ):
requires_backends(self,['''keras_... | 193 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between... | 367 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowercase : Optional[int] = get_tests_dir('fix... | 151 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT... | 110 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
lowerCAmelCase : Any = """
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is ... | 291 | 0 |
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_accelerate_available,
is_accele... | 364 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 68 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Any ) -> List[Any]: # noqa: E741
_lowerCAmelCase : Optional[int] = len(_lowerCamelCase )
_lowerCAmelCase : str = 0
_lowerCAmelCase : Any = [0] * n
... | 44 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 117 | 0 |
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load_datase... | 138 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onn... | 138 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowercase ( __lowerCAmelCase ) -> int:
if not nums:
return 0
SCREAMING_SNAKE_CASE__ : Dict = nums[0]
SCREAMING_SNAKE_CASE__ : int = 0
for num in nums[1:... | 132 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mod... | 132 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices... | 211 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/confi... | 211 | 1 |
A__ : List[Any] = [
(10_00, '''M'''),
(9_00, '''CM'''),
(5_00, '''D'''),
(4_00, '''CD'''),
(1_00, '''C'''),
(90, '''XC'''),
(50, '''L'''),
(40, '''XL'''),
(10, '''X'''),
(9, '''IX'''),
(5, '''V'''),
(4, '''IV'''),
(1, '''I'''),
]
def a ( l... | 207 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
lowerCamelCase : int =TypeVar('''T''')
class __a ( Generic[T] ):
_lowerCAmelCase : deque[T] # Cache store of keys
_lowerCAmelCase ... | 189 | 0 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( _A : Optional[int] , _A ... | 368 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
__A : List[Any] = logging.get_logger(__name__)
__A : List[Any] = [
['attention', 'attn'],
['encoder_attention'... | 49 | 0 |
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncode... | 52 |
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_available():
from PIL import Image
from ..i... | 212 | 0 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _SCREAMING_SNAKE_CASE( A ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = (DDPMScheduler,)
def _UpperCamelCase ... | 239 |
"""simple docstring"""
def __lowerCamelCase ( a_ : str ) -> list:
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(a_ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__("do... | 239 | 1 |
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def lowerCamelCase__ ( ) -> Dict:
raise RuntimeError('''CUDA out of memory.''' )
... | 24 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
UpperCAmelCase : Optional[Any] = None
try:
import msvcrt
except ImportError:
UpperCAmelCase : List[Any] = None
try:
import fcntl
except ImportError:
Up... | 267 | 0 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( lowerCamelCase__ : Tuple , lowerCamelCase__ : List[str] , lowerCamelCase__ ... | 66 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : str =... | 66 | 1 |
"""simple docstring"""
from PIL import Image
def __UpperCAmelCase ( UpperCAmelCase_ : Union[str, Any] , UpperCAmelCase_ : str ) -> Image:
'''simple docstring'''
__snake_case : Union[str, Any] = (2_59 * (level + 2_55)) / (2_55 * (2_59 - ... | 172 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase = 2000000 )-> int:
UpperCamelCase = [0 for i in range(n + 1 )]
UpperCamelCase = 1
UpperCamelCase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if prima... | 321 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler,... | 21 | '''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
lowercase_ : Any = prime_factors(UpperCAmelCase__ )
if is_square_free(UpperCAmelCase__ ... | 21 | 1 |
"""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
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCRE... | 102 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 151 | 0 |
"""simple docstring"""
def _A ( _SCREAMING_SNAKE_CASE ) -> list:
if len(_SCREAMING_SNAKE_CASE ) <= 1:
return [tuple(_SCREAMING_SNAKE_CASE )]
snake_case_ = []
def generate(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
if k == 1:... | 356 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = 0 ) -> list:
snake_case_ = length or len(_SCREAMING_SNAKE_CASE )
snake_case_ = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
... | 233 | 0 |
import os
import numpy
import onnx
def a ( A__ : str , A__ : int ) -> Optional[int]:
"""simple docstring"""
_lowercase =a.name
_lowercase =b.name
_lowercase =''
_lowercase =''
_lowercase... | 205 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxCon... | 68 | 0 |
'''simple docstring'''
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 tr... | 89 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __snake_case ( unittest.TestCase):
"""simple docstring"""
def __lowercase ( self : Tuple ) -> Dict:
... | 89 | 1 |
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ) -> int:
'''simple docstring'''
assert column_title.isupper()
lowerCAmelCase : List[str] = 0
lowerCAmelCase : Tuple = len(_UpperCAmelCase ) - 1
lowerCAmelCase : Optional[Any] = 0
while index >= 0:... | 138 |
__A : dict[tuple[int, int, int], int] = {}
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ) -> int:
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not failed any... | 138 | 1 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowerCamelCase : Any... | 208 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( lowercase : dict , lowercase : str ):
'''simple docstring'''
lowerCamelCase_ , lowerCamelCase_ = set(lowercase ), [start]
while stack:
lower... | 208 | 1 |
'''simple docstring'''
import math
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''')
# handling of negative values of initial intensity
if angle < 0 or angle > 360:
... | 211 |
'''simple docstring'''
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokeni... | 211 | 1 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def lowerCamelCase__ ... | 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 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, ... | 25 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Effic... | 49 | 0 |
'''simple docstring'''
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def UpperCamelCase ( a , a , a ) -> Union[str, Any]:
'''simple docstring'''
__magic_name__ = ("""dense.we... | 356 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
def UpperCamelCase ( a , a ) -> bool:
'''simple docstring'''
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def Up... | 98 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Tuple = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BridgeTowerConfi... | 239 | '''simple docstring'''
from itertools import product
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int ) -> list[int]:
lowercase_ : List[Any] = sides_number
lowercase_ : Dict = max_face_nu... | 239 | 1 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
UpperCAmelCase_ = '.'
if __name__ == "__main__":
UpperCAmelCase_ = os.path.join(REPO_PATH, 'utils/documentation_tes... | 61 |
'''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
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {... | 61 | 1 |
"""simple docstring"""
import pprint
import requests
__a = "https://zenquotes.io/api"
def A_ ( ):
'''simple docstring'''
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def A_ ( ):
'''simple docstring'''
return requests.get(API_ENDPOINT_UR... | 66 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__a = pd.read_csv("sample_data.csv", header=None)
__a = ... | 66 | 1 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
UpperCAmelCase__ : Tuple = ... | 369 |
def lowerCamelCase__ ( a = 10**9 ) -> int:
_A: Dict = 1
_A: Union[str, Any] = 2
_A: List[str] = 0
_A: List[Any] = 0
_A: int = 0
while perimeter <= max_perimeter:
perimeters_sum += perimeter
prev_value += 2 * value
value +... | 301 | 0 |
from collections import deque
class _lowerCamelCase:
def __init__( self, lowerCamelCase, lowerCamelCase, lowerCamelCase) -> None:
"""simple docstring"""
_lowercase : Optional[Any] = process_name # process name
_lowerca... | 21 |
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 21 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
A : Optional[Any] = len(lowerCamelCase_ )
A : str = len(lowerCamelCase_ )
A : Union[str, Any] = [[False for _ in ... | 356 |
'''simple docstring'''
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class A ( __snake_case ):
def __init__( self , SCREAMING_SNAKE_CAS... | 311 | 0 |
def __lowercase ( a__ ) -> str:
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase_ ):
if arr[i] > arr[j]:
... | 257 |
def snake_case_ ( lowerCAmelCase_ : list ):
if len(lowerCAmelCase_ ) <= 1:
return [tuple(lowerCAmelCase_ )]
__lowercase : Any = []
def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ):
if k ==... | 233 | 0 |
from collections.abc import Sequence
def UpperCAmelCase__ ( lowerCamelCase, lowerCamelCase = False ):
if not arr:
return 0
lowercase :Optional[Any] = 0 if allow_empty_subarrays else float("-inf" )
lowercase :Union[str, Any] = 0.0
for num in arr:
lowercase ... | 158 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __lowerCAmelCase ( lowerCAmelCase):
def __init__( self: Any , _lowerCAmelCase: int , _lowerCAmelCase: str , _lowerCAmelCase: U... | 158 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
# See all Cvt m... | 89 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__lowerCAmelCase = logging.... | 89 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TF... | 360 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, 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 .tokeniza... | 172 | 0 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def a_ ( *_lowerCAmelCase ,_lowerCAmelCase = None ,_lowerCAmelCase=True ,_lowerCAmelCase=2 ) -> List[str]:
fr... | 208 |
'''simple docstring'''
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a_ ( _lowerCAmelCase ,_lowerCAmelCase ) -> np.array:
__lowerCamelCase : Any = F'{sampling_... | 208 | 1 |
'''simple docstring'''
from torch import nn
def __a ( UpperCAmelCase ) ->List[str]:
"""simple docstring"""
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f"""Unsuppo... | 337 |
'''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
_lowerCamelCase : List[Any] = logging.get_logger(__name__)
_lower... | 337 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
UpperCAmelCase__ : ... | 25 |
from math import isqrt
def _lowerCamelCase( lowercase__ ) -> bool:
'''simple docstring'''
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowercase__ ) + 1 ) )
def _lowerCamelCase( lowercase__ = 1_0**6 ) -> int:
'''simple docstring'''
__... | 295 | 0 |
'''simple docstring'''
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_available():
from PIL import Image
from... | 365 |
'''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __lowerCamelCase ( __snake_case : int ) -> int:
"""simple docstring"""
A__ : List[Any] =prime_factors(__snake_case )
if is_squar... | 136 | 0 |
class lowercase :
def __init__( self ) -> List[str]:
_A : List[Any] = {}
def a__ ( self ) -> None:
print(self.vertex )
for i in self.vertex:
print(_a , """ -> """ , """ -> """.... | 26 | """simple docstring"""
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Optional[int] = logging.get_logger(__name__)
class snake_case ( __UpperCAmelCase ):
... | 98 | 0 |
'''simple docstring'''
import random
def __lowerCamelCase ( lowerCAmelCase_ ) -> int:
_a : Any = num - 1
_a : List[Any] = 0
while s % 2 == 0:
_a : Dict = s // 2
t += 1
for _ in range(5 ):
_a : Tuple = r... | 361 |
'''simple docstring'''
from math import sqrt
def __lowerCamelCase ( lowerCAmelCase_ ) -> int:
_a : Dict = 0
for i in range(1 , int(sqrt(lowerCAmelCase_ ) + 1 ) ):
if n % i == 0 and i != sqrt(lowerCAmelCase_ ):
total += i + n // i
elif i == sqr... | 107 | 0 |
"""simple docstring"""
import numpy as np
import datasets
_a = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was intro... | 61 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
_a = 'src/diffusers'
# Matches is_xxx_available()
_a = re.compile(R'is\_([a-z_]*)_avai... | 61 | 1 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for ... | 356 |
from __future__ import annotations
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> list[int]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = len(_SCREAMING_SNAKE_CASE ) - 1
... | 193 | 0 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMi... | 42 |
"""simple docstring"""
import os
from pathlib import Path
def lowercase ():
from torch.utils.cpp_extension import load
__lowerCAmelCase = Path(_lowerCAmelCase ).resolve().parent.parent.parent / """kernels""" / """deformable_detr"""
__lowerCAmelCase = [
... | 301 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_e... | 311 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowercase : Tuple = argparse.ArgumentParser()
parser.add_argument(
... | 311 | 1 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 50 ):
"""simple docstring"""
a :str = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_s... | 94 |
'''simple docstring'''
def lowercase ( __magic_name__ ):
'''simple docstring'''
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 311 | 0 |
from __future__ import annotations
import pandas as pd
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = [0] * no_of_processes
snake_case_ = [0] * no_of_p... | 200 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDependencyNotAvailable... | 200 | 1 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
_SCRE... | 158 |
'''simple docstring'''
from __future__ import annotations
def __a(SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float ):
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError("days_betwe... | 158 | 1 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase ):
'''simple docstring'''
for e in env_keys:
UpperCAmelCase = int(os.environ.get(lowerCAmelCase , -1 ) )
... | 352 |
"""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, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionMod... | 248 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}
cl... | 166 | """simple docstring"""
def __UpperCAmelCase ( UpperCAmelCase_ : Tuple ) -> Optional[int]:
'''simple docstring'''
__snake_case : List[str] = []
__snake_case : Optional[Any] = set({'(', '[', '{'} )
__snake_case : Union[str, A... | 172 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jn... | 364 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
_a , _a : Dict = len(UpperCamelCase__ ), len(grid[0] )
if (
min... | 324 | 0 |
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