code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class A_ :
_UpperCAmelCase : float
_UpperCAmelCase : TreeNode | None = None
_UpperCAmelCase : TreeNode | None = None
def SCREAMING_SNAKE_CASE... | 652 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
a =logging.getLogger()
@unittest.skip('''Temporarily disable the doc tests.''' ... | 652 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
'https://huggingface.co/microsoft/unis... | 380 |
import math
import tensorflow as tf
from packaging import version
def a ( A__ : Tuple ) -> List[Any]:
"""simple docstring"""
_lowercase =tf.convert_to_tensor(A__ )
_lowercase =0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0 ) , x.dtype ) ... | 380 | 1 |
'''simple docstring'''
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__( ... | 418 |
"""simple docstring"""
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
a__ : List[Any] = log... | 589 | 0 |
"""simple docstring"""
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
lowercase = ... | 700 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, 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 .attention_processor import Att... | 468 | 0 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase_ )
class snake_case_ ( lowerCamelCase_ ):
"""simple docstring"... | 34 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
impo... | 351 | 0 |
'''simple docstring'''
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
fro... | 323 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
... | 323 | 1 |
def __SCREAMING_SNAKE_CASE ( ) -> int:
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(SCREAMING_SNAKE_CASE , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(f'''{solution() = }''')
| 345 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> ... | 345 | 1 |
'''simple docstring'''
import doctest
from collections import deque
import numpy as np
class a :
"""simple docstring"""
def __init__( self : str ):
'''simple docstring'''
snake_case__ : Union[str, Any] = [2, 1, 2, -1]
... | 502 |
'''simple docstring'''
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def __init__( self : Dict... | 502 | 1 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
__lowerCamelCase = logging.getLogger()
@unittest.skip("""Temporarily d... | 608 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common... | 443 | 0 |
"""simple docstring"""
import re
import subprocess
import sys
_A = subprocess.check_output("git merge-base main HEAD".split()).decode("utf-8")
_A = subprocess.check_output(f"""git diff --name-only {fork_point_sha}""".split()).decode("utf-8").split()
_A = "|".join(sys.argv[1:])
_A ... | 714 |
"""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 ..... | 228 | 0 |
'''simple docstring'''
class lowercase__ :
def __init__( self : int ,lowerCamelCase__ : Union[str, Any] ,lowerCamelCase__ : List[Any] ):
'''simple docstring'''
_UpperCamelCase : List[Any] = name
_UpperCamelCase :... | 195 |
'''simple docstring'''
from typing import List
import numpy as np
def A__ ( UpperCAmelCase_ ):
_UpperCamelCase : Any = {key: len(UpperCAmelCase_ ) for key, value in gen_kwargs.items() if isinstance(UpperCAmelCase_ , UpperCAmelCase_ )}
if len(set(lists_lengt... | 195 | 1 |
"""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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTI... | 713 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from... | 598 | 0 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import GenerationTes... | 35 |
"""simple docstring"""
from collections.abc import Sequence
def _lowerCAmelCase(a : Sequence[float] , a : float ) -> float:
return sum(c * (x**i) for i, c in enumerate(a ) )
def _lowerCAmelCase(a : Sequence[float] , a : float ) -> ... | 255 | 0 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
snake_case = logging.get_logger(__name__)
class A_ ( UpperCAmelCase ):
"""simple docstring"""
def __init__( self : Dict ,*__A :... | 705 |
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_neuroncore... | 535 | 0 |
def lowerCAmelCase__ ( _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
__a = len(_SCREAMING_SNAKE_CASE )
__a = len(_SCREAMING_SNAKE_CASE )
__a = [[False for _ in range(m + 1 )] for _ in range(n + 1 ... | 225 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils impor... | 225 | 1 |
def UpperCAmelCase ( UpperCamelCase__ ) -> float:
'''simple docstring'''
if edge <= 0 or not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise ValueError("""Length must be a positive.""" )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)... | 334 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__A : Optional[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__A : Tuple ... | 334 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.mode... | 102 |
"""simple docstring"""
import math
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return math.pow(SCREAMING_SNAKE_CASE , 2 ) - a
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
return 2 * x
def UpperCamelC... | 102 | 1 |
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 A... | 185 |
def UpperCamelCase_( _A :int , _A :int )-> str:
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers" )
UpperCamelCase__ = str(bin(_A ) )
binary_number += "0" * shift_amount
return binary_number
def UpperCamelCase_( ... | 185 | 1 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .... | 44 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE : List[Any] = {
"configuration_funnel": ["FUNNEL_PRETRAINED... | 400 | 0 |
'''simple docstring'''
import random
class __UpperCAmelCase :
@staticmethod
def lowerCamelCase ( lowerCAmelCase_ ):
"""simple docstring"""
_snake_case = [ord(lowerCAmelCase_ ) for i in text]
_snake_case = []
_snake_... | 542 |
'''simple docstring'''
lowercase : Tuple = {
"a": "AAAAA",
"b": "AAAAB",
"c": "AAABA",
"d": "AAABB",
"e": "AABAA",
"f": "AABAB",
"g": "AABBA",
"h": "AABBB",
"i": "ABAAA",
"j": "BBBAA",
"k": "ABAAB",
"l": "ABABA",
"m": "ABABB",
"n": "ABBAA"... | 542 | 1 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCAmelCase ( unittest.TestCase ):
'''simple docstring'''
snake_case_ = JukeboxTokenizer
snake_case_ = {
"artist": "Zac Brown Band",
"genres": ... | 55 | '''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICE... | 251 | 0 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class A_ ( pl.LightningModule ):
def __init__( self : List[Any] ,SCREAMING_SNAKE_CASE... | 714 |
from ..utils import DummyObject, requires_backends
class A_ ( metaclass=SCREAMING_SNAKE_CASE ):
_UpperCAmelCase : List[Any] = ['''sentencepiece''']
def __init__( self : Any ,*SCREAMING_SNAKE_CASE__ : List[str] ,**SCREAMING_SNAKE_CASE__ : str):
... | 337 | 0 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=A ):
'''simple docstring'''
a_ : Tuple = ["note_seq"]
def __init__( self : List[Any] , *_lowerCamelCase : Any , **_lowerCamelCase : Any ):
... | 519 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : int = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
r... | 519 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
... | 718 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__lowerCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
__lowercase : Union[str, Any] ... | 335 | 0 |
import re
from filelock import FileLock
try:
import nltk
A_ : Union[str, Any] = True
except (ImportError, ModuleNotFoundError):
A_ : Union[str, Any] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punk... | 303 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class A_ ( _a ):
'''simple docstring'''
a__ = CustomTokenizer
pass
| 303 | 1 |
"""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__ : Any= """src/diffusers"""
# Matches is_xxx_available()
A__ : Tuple= re.c... | 20 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimensio... | 20 | 1 |
"""simple docstring"""
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
_lowercase = re.compile(r'''^(?P<major>\d+)''' r'''\.(?P<minor>\d+)''' r'''\.(?P<patch>\d+)$''')
@total_ordering
@dataclass... | 91 |
'''simple docstring'''
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
__lowerCAmelCase =numpy.array([0, 0])
__lowerCAmelCase =numpy.array([0.5, 0.866_0254])
__lowerCAmelCase =numpy.array([1, 0])
__lowerCAmelCase =... | 697 | 0 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenizerFast,
XLMRoberta... | 86 |
def __magic_name__ ( __a : int = 50 ):
'''simple docstring'''
UpperCamelCase__ = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
... | 86 | 1 |
"""simple docstring"""
from math import isqrt
def _SCREAMING_SNAKE_CASE ( UpperCamelCase : int ):
A__ = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , Upper... | 574 |
"""simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
lowerCamelCase__ = [
# (stable-diffusion, HF Diffusers)
("time_embed.... | 574 | 1 |
def lowerCamelCase_ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
for i in range(len(SCREAMING_SNAKE_CASE ) - 1 , 0 , -1 ):
SCREAMING_SNAKE_CASE = False
for j in range(SCREAMING_SNAKE_CASE , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]... | 719 |
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import tensorflow as tf
from tokenizers import pre... | 450 | 0 |
"""simple docstring"""
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 low... | 82 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 0 |
'''simple docstring'''
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorS... | 92 |
'''simple docstring'''
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
a_ = logging.get_logger(__name__)
def UpperCamelCase_ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring""... | 92 | 1 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class lowerCAmelCase__ ( __lowerCamelCase ):
"""simple docstring"""
def __init__( self , a_ , a_ ):
lowerCamelCase_ : Dict ... | 250 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
class lowerCAmelCase__ ( __lowerCamelCase ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = '''tim... | 250 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prep... | 65 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json",
... | 65 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.ut... | 7 | '''simple docstring'''
import os
import sys
import unittest
_a : int = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, creat... | 168 | 0 |
'''simple docstring'''
def UpperCamelCase_ ( a_ ) ->List[Any]:
A =0
A =len(snake_case__ )
for i in range(n - 1 ):
for j in range(i + 1 , snake_case__ ):
if arr[i] > arr[j]:
num_inversions += 1
return num_inversions
def UpperCamelCase_ ( a_ ) ... | 717 |
def UpperCamelCase_ ( a_ , a_ ) ->int:
return int((input_a, input_a).count(0 ) != 0 )
def UpperCamelCase_ ( ) ->None:
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ) == 1
assert nand_gate(1 , 0 ) == 1
assert nand_gate(1 , ... | 689 | 0 |
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def lowercase__ ( _UpperCamelCase) -... | 280 |
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
__magic_name__ : Optional[int] = ... | 280 | 1 |
'''simple docstring'''
import os
import jsonlines
import numpy as np
from tqdm import tqdm
lowercase__ : Dict = 2048
lowercase__ : Dict = 4096
lowercase__ : List[Any] = 42
lowercase__ : List[str] = os.environ.pop("PROCESS_TRAIN", "false")
lowercase_... | 43 | '''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require... | 43 | 1 |
'''simple docstring'''
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 ... | 109 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import Ima... | 283 | 0 |
def lowerCAmelCase__ ( a__ ) ->int:
'''simple docstring'''
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def lowerCAmelCase__ ( a__ ) ->bool:
'''simple docstring'''
_UpperCamelCase = 0
_UpperCamelCase = number
while duplica... | 704 | from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCamelCase__ = input('''Enter image url: ''').strip()
print(F"Downloading image from {url} ...")
lowerCamelCase__ = BeautifulSoup(requests.get(url).content, '''html.parser''')
# The ima... | 82 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( SCREAMING_SNAKE_CASE : int ):
UpperCAmelCase = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def lowerCamelCase__ ( SCREAMING_SNAKE_CASE : int = 100 ):
UpperCAmelCase = 1
UpperCAm... | 447 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
_a : List[Any] = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
_a : Dict = re... | 447 | 1 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def __UpperCamelCase (_SCREAMING_SNAKE_CASE ) -> Dict:
lowercase__ = FileLock(str(tmpdir / 'foo.lock' ) )
lowercase__ = FileLock(str(tmpdir / 'foo.lock' ) ... | 45 |
def __UpperCamelCase (_SCREAMING_SNAKE_CASE ) -> bool:
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(_SCREAMING_SNAKE_CASE ) == 0:
raise ValueError('Input list must be a n... | 45 | 1 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def __A ( a_ :int) -> Dict:
__a : Tuple = {}
... | 52 |
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (
BarkCoarseConfig,
... | 269 | 0 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : str = logging.get_logger(__name__)
_a : Any = {
'''facebook/encodec_24khz''': '''https://huggingface.co/facebook/encodec_24khz... | 706 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import Ba... | 571 | 0 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 85 | import os
import pytest
from attr import dataclass
SCREAMING_SNAKE_CASE__ : int = "us-east-1" # defaults region
@dataclass
class snake_case :
lowercase_ = 42
lowercase_ = 'arn:aws:iam::558105141721:role/sagemaker_execution_role'
lowercase_ = {
'... | 85 | 1 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_mo... | 98 |
'''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docs... | 98 | 1 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipel... | 290 |
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class _lowerCAmelCase ( __a ):
_lowercase =4... | 290 | 1 |
class lowerCAmelCase :
def __init__( self : str , UpperCAmelCase : Optional[Any] , UpperCAmelCase : str , UpperCAmelCase : Dict ) -> Optional[int]:
lowerCamelCase__ : Optional[int] = name
lowerCamelCase__ : Tuple ... | 188 |
from collections import defaultdict
from math import ceil, sqrt
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase = 100_0000 , _UpperCAmelCase = 10 ) -> int:
lowerCamelCase__ : defaultdict = defaultdict(_UpperCAmelCase )
for outer_width in range(3 , (t_limit // 4) + 2 ):
... | 188 | 1 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
... | 311 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noq... | 664 | 0 |
"""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 _lowerCamelCase ... | 714 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgument... | 128 | 0 |
'''simple docstring'''
import sys
from collections import defaultdict
class _UpperCAmelCase :
"""simple docstring"""
def __init__( self ):
'''simple docstring'''
a_ : Tuple = []
def _lowerCAmelCase ( self , lowerCAmelCase_ ):
... | 577 |
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.utils import load_numpy, s... | 205 | 0 |
from __future__ import annotations
lowerCamelCase__ : List[str] = list[list[int]]
# assigning initial values to the grid
lowerCamelCase__ : Matrix = [
[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... | 717 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
lowerCamelCase__ : Dict = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author... | 495 | 0 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( UpperCAmelCase ):
__UpperCAmelCase =(CMStochasticIterativeScheduler,)
__UpperCAmelCase =10
... | 292 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/... | 292 | 1 |
'''simple docstring'''
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from... | 708 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
A ... | 163 | 0 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class A:
'''simple docstring'''
UpperCamelCase = 42 # [batch_size x 3]
UpperCamelCase = 42 # [batch_size x 3]
UpperCamelCase = 42 # [batch_size x 3]
... | 70 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import Confi... | 335 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase_ ( SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ ):
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[indexa] < array... | 711 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCamelCase_ ( SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING... | 406 | 0 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested... | 22 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase : Tuple = {
'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
... | 50 | 0 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
a = "<<<<<<< This should probably be modified because it mentions: "
a = "=======\n>>>>... | 701 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _SCR... | 175 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=lowercase_ ):
"""simple docstring"""
_lowerCamelCase = ["""torch""", """transformers""", """onnx"""]
def __init__( self , *__lowerCamelCase , **__lowerCamelC... | 177 |
'''simple docstring'''
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
__UpperCAmelCase = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (... | 379 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils i... | 199 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__a : List[str] = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["... | 199 | 1 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
snake_case__ = {
"""tiny.en""": """https://openaipublic.azureedge.net/main/whisper/models/... | 583 |
'''simple docstring'''
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCa... | 358 | 0 |
import sys
A = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121722383113"... | 277 |
class lowercase__ :
def __init__( self : List[str] , _lowercase : list ):
"""simple docstring"""
UpperCAmelCase__ = set_counts
UpperCAmelCase__ = max(_lowercase )
UpperCAmelCase_... | 277 | 1 |
from importlib import import_module
from .logging import get_logger
SCREAMING_SNAKE_CASE__ : Union[str, Any] = get_logger(__name__)
class UpperCAmelCase_ :
def __init__( self , _lowerCAmelCase , _lowerCAmelCase=None ):
UpperC... | 79 |
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.t... | 79 | 1 |
"""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 : List[Any] ):
deb... | 718 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class lowerCAmelCase__ :
__a = 42
__a... | 430 | 0 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class UpperCAmelCase_ :
"""simple docstring""... | 94 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str] = logging.get_logger(__name__)
# TODO Update this
A__ : Tuple = {
"""facebook/esm-1b""": "... | 13 | 0 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
__lowerCamelCase : Tuple = False
__lowerCamelCase : str = True
__lowerCamelCase : Tuple = False
if __na... | 271 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available... | 271 | 1 |
'''simple docstring'''
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_m... | 41 |
import unittest
import numpy as np
from transformers import RobertaConfig, 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():
from transformers.mod... | 307 | 0 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def a_ ( __snake_case = True , *__snake_case , **__snake_case ) -> Union[str, Any]:
'''simple docstring'''
if not is_tqd... | 716 |
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 a... | 559 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.... | 292 |
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class UpperCamelCase_ ( __UpperCamelCase ,__UpperCamelCase ):
"""simple docstring"""
@re... | 479 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
"configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
... | 362 |
import tensorflow as tf
from ...tf_utils import shape_list
class a ( tf.keras.layers.Layer ):
"""simple docstring"""
def __init__( self : int , lowerCamelCase__ : Union[str, Any] , lowerCamelCase__ : Tuple , lowerCamelCase__ : List[Any] , ... | 362 | 1 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
lo... | 62 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_confi... | 436 | 0 |
from maths.prime_check import is_prime
def __lowerCAmelCase ( A_ : int ) -> int:
if not isinstance(A_ , A_ ):
__UpperCAmelCase = F'''Input value of [number={number}] must be an integer'''
raise TypeError(A_ )
if is_prime(A_ ) and is_prime(number ... | 286 | 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_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we had to include /home/niels/p... | 286 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import ... | 400 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 505 | 0 |
"""simple docstring"""
SCREAMING_SNAKE_CASE = frozenset(
[
'prompt',
'height',
'width',
'guidance_scale',
'negative_prompt',
'prompt_embeds',
'negative_prompt_embeds',
'cross_attention_kwargs',
]
)
SCREAMING_SNAKE_CASE ... | 283 | """simple docstring"""
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
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_... | 283 | 1 |
def UpperCamelCase ( _A : list[int] , _A : str )-> list[int]:
"""simple docstring"""
A__ = int(_A )
# Initialize Result
A__ = []
# Traverse through all denomination
for denomination in reversed(_A ):
# Find ... | 491 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__) # pylint: disable=invalid-name
class UpperCa... | 491 | 1 |
_lowerCamelCase = [0, 2, 4, 6, 8]
_lowerCamelCase = [1, 3, 5, 7, 9]
def _lowerCAmelCase ( __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : list[int] , __lowerCamelCase : int ):
"""simple docstring"""
if remaining_length ... | 447 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...image_ut... | 447 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attentio... | 107 | '''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, ... | 107 | 1 |
from pathlib import Path
import numpy as np
from PIL import Image
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase , lowerCamelCase , lowerCamelCase : int = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2989 * ... | 231 |
import unittest
from transformers import DonutProcessor
_snake_case = '''naver-clova-ix/donut-base'''
class UpperCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
def _snake_case ( self ):
"""simple docstring"""
lowerC... | 231 | 1 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {'''vocab_file''': '''vocab.json'''}
__UpperCAmelCase = {
'''vocab_file''': {
... | 40 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _A ( __lowercase ):
lowercase__: Any = ['''image_processor''', '''tokenizer''']
lowercase__: Any = ''... | 26 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( lowercase : int , lowercase : int , lowercase : int ) ->int:
"""simple docstring"""
if exponent == 1:
return base
if exponent % 2 == 0:
lowercase__ = _mo... | 318 |
'''simple docstring'''
def _lowerCAmelCase ( lowercase : int ) ->int:
"""simple docstring"""
if not isinstance(lowercase , lowercase ):
raise ValueError('''multiplicative_persistence() only accepts integral values''' )
if num < 0:
... | 318 | 1 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
__a: List[str] = namedtuple('''covid_data''', '''cases deaths recovered''')
def _SCREAMING_SNAKE_CASE ( __snake_case = "https://www.worldometers.info/coronavirus/" ) -> covid_data:
... | 108 | from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class _UpperCamelCase ( _UpperCAmelCa... | 534 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ = {
"configuration_whisper": ["WHISPER_P... | 718 |
"""simple docstring"""
import os
import sys
import unittest
lowerCAmelCase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_file... | 598 | 0 |
"""simple docstring"""
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 ...... | 532 |
"""simple docstring"""
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
SCREAMING_SNAK... | 532 | 1 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfi... | 700 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class lowercase :
def __init__( self , lowercase , lowercase , lowercase = 0 ) -> None:
lowerCAmelCase , lowerCAmelCase = row, column
lowerCAmelCase = [[defa... | 393 | 0 |
from collections import deque
def lowercase_ ( SCREAMING_SNAKE_CASE : List[str] ):
"""simple docstring"""
snake_case__ : Union[str, Any] =len(SCREAMING_SNAKE_CASE )
snake_case__ : str =deque()
snake_case__ : str =[False for _ in rang... | 381 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowercase_ ( SCREAMING_SNAKE_CASE : str = "laptop" ):
"""simple docstring"""
snake_case__ : Tuple =F'''https://www.amazon.in/laptop/s?k={pr... | 381 | 1 |
'''simple docstring'''
def lowerCamelCase__ ( _A ):
assert column_title.isupper()
a : str = 0
a : Optional[int] = len(_lowerCamelCase ) - 1
a : int = 0
while index >= 0:
a : Optional[Any] = (ord(column_title[index] ) - 64)... | 700 |
'''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
lowerCAmelCase: Tuple = 'sr... | 195 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCamelCase_ :
def __init__( self , snake_case__=2 , snake_case__=3 , snake_case__=64 , snake_case__=None ) ... | 673 |
'''simple docstring'''
import re
def _snake_case ( A ) -> bool:
lowerCAmelCase__ = re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(A , A ):
return match.string == phone
return False
if _... | 90 | 0 |
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
lowerCamelCase__ = logging.get_logger(_... | 720 | import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase__ = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
and... | 82 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( __A : list ):
a_ : List[str] = len(__A )
for i in range(1 , __A ):
a_ : str = collection[i]
a_ : List[str] = 0
a_ : Any = i - 1
while lo... | 466 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def _UpperCAmelCase ( __A : int ):
a_ : Optional[Any] = FileLock(str(tmpdir / '''foo.lock''' ) )
a_ : Union[str, Any] ... | 466 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_C... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : bool = False ):
"""simple docstring"""
snake_case_ : dict = {i: [] for i in range(SCREAMING... | 48 | 1 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('''Googling.....''')
snake_case_ : List[Any] = '''https://www.google.com/search?q=''' + ''' '''.join(sys.argv[1:])
snake_case_ :... | 691 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impor... | 691 | 1 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_ava... | 40 |
'''simple docstring'''
def __lowerCAmelCase ():
_UpperCAmelCase : str = 0
for i in range(1 , 1_001 ):
total += i**i
return str(__lowerCAmelCase )[-10:]
if __name__ == "__main__":
print(solution())
| 40 | 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
snake_case = logging.get_logger(__name__)
snake_case = {
"""kakaobrain/align-ba... | 67 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = {
"""google/bigbird-roberta-base"... | 67 | 1 |
'''simple docstring'''
import numpy as np
from transformers import Pipeline
def __UpperCamelCase( _A : Dict ):
'''simple docstring'''
UpperCAmelCase__ : Union[str, Any] = np.max(_A , axis=-1 , keepdims=_A )
UpperCAmelCase__ : Dict = np.exp(outputs -... | 496 | '''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : List[Any] = logging.get_logger(__name__)
UpperCamelCase__ : Optional[Any] = {
'huggingface/time-series-transformer-tourism-monthl... | 496 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 156 |
"""simple docstring"""
class __lowerCamelCase :
def __init__(self , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase = val
_lowerCAmelCase = None
_lowerCAmelCase = None
def A__ (self , ... | 156 | 1 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,) -> float | int:
"""simple docstring"""
for nxt, d in graph[v]:
... | 702 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2FormerConfig",
... | 51 | 0 |
import heapq
import sys
import numpy as np
A_ : Any = tuple[int, int]
class _lowerCAmelCase:
"""simple docstring"""
def __init__( self ):
UpperCamelCase_: List[Any] = []
UpperCam... | 57 | import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
_lowerCamelCase : int = logging.get_logger(__name__)
class lowercase ( a ):
def __init__( self : Optional[int] , *_UpperCamelCase : ... | 403 | 0 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_A : Tuple = argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_argument('--dpm', action=... | 130 |
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 logg... | 130 | 1 |
"""simple docstring"""
_a : Dict = [
(1_000, 'M'),
(900, 'CM'),
(500, 'D'),
(400, 'CD'),
(100, 'C'),
(90, 'XC'),
(50, 'L'),
(40, 'XL'),
(10, 'X'),
(9, 'IX'),
(5, 'V'),
(4, 'IV'),
(1, 'I'),
]
def SCREAMING_SNAKE_CASE ( _lowerCamelCase :... | 213 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a : Optional[int] = logging.get_logger(__name__)
_a : int = {
'google/bigbird-r... | 213 | 1 |
"""simple docstring"""
import numpy as np
from PIL import Image
def A_ ( __UpperCamelCase : np.ndarray , __UpperCamelCase : int , __UpperCamelCase : int ):
lowercase = np.array(__UpperCamelCase )
if arr.shape[0] != arr.shape[1]:
raise... | 705 |
"""simple docstring"""
import numpy as np
from PIL import Image
def A_ ( __UpperCamelCase : np.ndarray , __UpperCamelCase : int , __UpperCamelCase : int ):
lowercase = np.array(__UpperCamelCase )
if arr.shape[0] != arr.shape[1]:
raise... | 396 | 0 |
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