code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import operator as op
lowercase__ :Union[str, Any] = "scaler.pt"
lowercase__ :Tuple = "pytorch_model"
lowercase__ :Union[str, Any] = "random_states"
lowercase__ :List[Any] = "optimizer"
lowercase__ :Any = "scheduler"
lowercase__ :Optional[Any] = "pytorch_model.bin"
lowercase__ :O... | 101 |
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
lowercase_ = get_tests_dir("fixtures/spiece.model")
... | 7 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : str = {
"""sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/ma... | 102 |
from typing import Dict
from .base import GenericTensor, Pipeline
class A ( _UpperCAmelCase ):
"""simple docstring"""
def snake_case__ ( self : int,lowercase_ : Dict=None,lowercase_ : Tuple=None,lowercase_ : List[Any]=None,... | 7 | 0 |
import requests
from bsa import BeautifulSoup
def UpperCamelCase( __UpperCamelCase : str = "AAPL" ):
lowerCAmelCase_ : Optional[Any] = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
lowerCAmelCase_ : Any = BeautifulSoup(requests.get(__UpperCamelCase ).text... | 103 |
from timeit import timeit
def _snake_case( SCREAMING_SNAKE_CASE__ : int ) -> int:
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
A__ = 0
while number:
number &=... | 7 | 0 |
'''simple docstring'''
def _A ( A__ ):
"""simple docstring"""
__lowercase = 0
while len(A__ ) > 1:
__lowercase = 0
# Consider two files with minimum cost to be merged
for _ in range(2 ):
__lowercase = files.index(min(A__ ) )
temp ... | 104 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def _snake_case( SCREAMING_SNAKE_CASE__ : Any ) -> ... | 7 | 0 |
"""simple docstring"""
import numpy as np
class __UpperCamelCase :
def __init__( self ) -> int:
a : Tuple = (0, 0)
a : Any = None
a : int = 0
a : Optional[int] = 0
a : Li... | 105 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from... | 7 | 0 |
"""simple docstring"""
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from tran... | 106 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : Union[str, Any] ) -> Tuple:
'''simple docstring'''
A__ = 0
A__ = len(SCREAMING_SNAKE_CASE__ ) - 1
while left <= right:
... | 7 | 0 |
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... | 107 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from da... | 7 | 0 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 108 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import Confi... | 7 | 0 |
"""simple docstring"""
import re
def _snake_case ( UpperCamelCase : str ):
UpperCAmelCase : Optional[int] = re.compile(
R"""^(?:0|94|\+94|0{2}94)""" R"""7(0|1|2|4|5|6|7|8)""" R"""(-| |)""" R"""\d{7}$""" )
return bool(re.search(UpperCamelCase , UpperCamelCase ) ... | 109 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common... | 7 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCAmelCase = {'UserAgent': UserAgent().random}
def _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowercase__ ... | 110 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class A ( _UpperCAmelCase ):
... | 7 | 0 |
"""simple docstring"""
from timeit import timeit
def __lowerCamelCase ( a_ : int ) -> int:
if number < 0:
raise ValueError('''the value of input must not be negative''' )
__SCREAMING_SNAKE_CASE :List[str] = 0
... | 191 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _snake_case( SCREAMING_SNAKE... | 7 | 0 |
def lowerCAmelCase ( _lowerCAmelCase : int = 100_0000 ):
"""simple docstring"""
UpperCAmelCase__ = [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 , limit + 1 , SCREAMING_SNA... | 169 |
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_tokenization_common import Toke... | 7 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, s... | 156 |
def _snake_case( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , ) -> float:
'''simple docstring'''
A__ ... | 7 | 0 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __magic_name__ ( ctypes.Structure ):
'''simple docstring'''
__UpperCamelCase = ... | 291 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def _snake_case( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str = "cpu" , SCREAMING_SNAKE_CASE__ : Union[str, None] = None ) -> None:
'''simple docstring'''
... | 7 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attenti... | 34 |
import os
# Precomputes a list of the 100 first triangular numbers
lowercase_ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def _snake_case( ) -> int:
'''simple docstring'''
A__ = os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE__... | 7 | 0 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowercase__ ( unittest.TestCase ):
'''simple docstring'''
def U... | 201 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy,... | 7 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a__ : List[str] = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFI... | 54 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowercase_ = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def _snake_case( SCREAMING_SNAKE_CA... | 7 | 0 |
"""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.skipUnless(os.path.exists(_UpperCA... | 179 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A ( _UpperCAmelCase ):
"""simple... | 7 | 0 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStruc... | 187 |
class A :
"""simple docstring"""
def __init__( self : Any,lowercase_ : Tuple,lowercase_ : Any,lowercase_ : List[str] )-> List[Any]:
'''simple docstring'''
A__ = name
A__ = ... | 7 | 0 |
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = 0
while len(SCREAMING_SNAKE_CASE__ ) > 1:
snake_case_ = 0
# Consider two files with minimum cost to be merged
for _ in range(2 ... | 285 |
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
... | 7 | 0 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
a_ = logging.get_logger(__name__)
def __lowercase ( lowerCamelCase : Union[str, Any] , ... | 175 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"t5-small": "https://huggingface.co/t5-small/resolve/main/config.json... | 7 | 0 |
"""simple docstring"""
class _SCREAMING_SNAKE_CASE:
def __init__( self ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ) -> List[Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE :Dict ... | 191 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Any ) -> Optional[int]:
'''simple docstring'''
global f # a global dp tabl... | 7 | 0 |
def lowerCAmelCase ( _lowerCAmelCase : Optional[Any] , _lowerCAmelCase : Union[str, Any] ):
"""simple docstring"""
UpperCAmelCase__ = 0
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ ) - 1
while left <= right:
# avoid divided b... | 169 |
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
lowercase_ = get_tests_dir("fixtures/spiece.model")
... | 7 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
__lowerCAmelCase : List[str] = {
"google/switch-base-8": "https://huggingface.co/google/switch-base-8/blob/main/config.json",
}
... | 156 |
from typing import Dict
from .base import GenericTensor, Pipeline
class A ( _UpperCAmelCase ):
"""simple docstring"""
def snake_case__ ( self : int,lowercase_ : Dict=None,lowercase_ : Tuple=None,lowercase_ : List[Any]=None,... | 7 | 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, random_a... | 291 |
from timeit import timeit
def _snake_case( SCREAMING_SNAKE_CASE__ : int ) -> int:
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
A__ = 0
while number:
number &=... | 7 | 0 |
'''simple docstring'''
def snake_case_ (_a : int = 1_0_0_0 ):
UpperCAmelCase = -1
UpperCAmelCase = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
UpperCAmelCase = (n ... | 34 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def _snake_case( SCREAMING_SNAKE_CASE__ : Any ) -> ... | 7 | 0 |
import math
def lowerCAmelCase_ ( __UpperCAmelCase: int ) -> list:
UpperCamelCase__ : Tuple = [True] * n
UpperCamelCase__ : Optional[Any] = False
UpperCamelCase__ : int = False
UpperCamelCase_... | 201 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from... | 7 | 0 |
"""simple docstring"""
from collections import deque
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : str , UpperCAmelCase__ : str , UpperCAmelCase__ : int , UpperCAmelCase__ : int ) -> None:
__SCREAMING_SNAKE_CASE = proc... | 54 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : Union[str, Any] ) -> Tuple:
'''simple docstring'''
A__ = 0
A__ = len(SCREAMING_SNAKE_CASE__ ) - 1
while left <= right:
... | 7 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test impor... | 179 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from da... | 7 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : List[Any] = {"configuration_fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 187 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import Confi... | 7 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLImgaImgPipeline,
UNetaDCon... | 285 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common... | 7 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __lowercase ( lowerCamelCase : Any ):
UpperCamelCase_ ... | 175 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class A ( _UpperCAmelCase ):
... | 7 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
lowerCamelCase_ = {
"google/tapas-base-finetuned-sqa": (
"https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"
),
"google/tapas-base-finetuned-wtq": (
"https:... | 191 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _snake_case( SCREAMING_SNAKE... | 7 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available():
import torch
from ... | 169 |
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_tokenization_common import Toke... | 7 | 0 |
import comet # From: unbabel-comet
import torch
import datasets
__lowerCAmelCase : Dict = datasets.logging.get_logger(__name__)
__lowerCAmelCase : Any = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alo... | 156 |
def _snake_case( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , ) -> float:
'''simple docstring'''
A__ ... | 7 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
lowerCAmelCase : Any = {
"""google/fnet-base""": """https://huggingface.co/google/fnet... | 291 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def _snake_case( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str = "cpu" , SCREAMING_SNAKE_CASE__ : Union[str, None] = None ) -> None:
'''simple docstring'''
... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class _a :
def __init__( self : Tuple , lowercase : list[tuple[float, float]] ):
'''simple docstring'''
UpperCAmelCase = list_of_points... | 34 |
import os
# Precomputes a list of the 100 first triangular numbers
lowercase_ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def _snake_case( ) -> int:
'''simple docstring'''
A__ = os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE__... | 7 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingf... | 201 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy,... | 7 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 0
# if input_string is "aba" than new_input_string become "a|b|a"
__SCREAMING_SNAKE_CASE = ""
__SCREAMING_SNAKE_CASE = ""
... | 54 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowercase_ = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def _snake_case( SCREAMING_SNAKE_CA... | 7 | 0 |
"""simple docstring"""
from math import pow, sqrt
def __lowercase ( *snake_case_ : float ) ->bool:
'''simple docstring'''
__A : List[Any] = len(SCREAMING_SNAKE_CASE__ ) > 0 and all(value > 0.0 for value in values )
return result
d... | 179 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A ( _UpperCAmelCase ):
"""simple... | 7 | 0 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import Toke... | 187 |
class A :
"""simple docstring"""
def __init__( self : Any,lowercase_ : Tuple,lowercase_ : Any,lowercase_ : List[str] )-> List[Any]:
'''simple docstring'''
A__ = name
A__ = ... | 7 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCAmelCase : str = {
"""configuration_resnet""": ["""RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ResNetConfig... | 285 |
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
... | 7 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'configuration_xlm_roberta': [
'XLM_ROBERTA_... | 175 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"t5-small": "https://huggingface.co/t5-small/resolve/main/config.json... | 7 | 0 |
"""simple docstring"""
def __lowerCamelCase ( a_ : int , a_ : int ) -> int:
return int((input_a, input_a).count(0 ) != 0 )
def __lowerCamelCase ( ) -> None:
assert nand_gate(0 , 0 ) == 1
assert nand_ga... | 191 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Any ) -> Optional[int]:
'''simple docstring'''
global f # a global dp tabl... | 7 | 0 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
_lowerCAmelCase : List[str] = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
_lowerCAmelCase : Optional[int] ... | 169 |
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
lowercase_ = get_tests_dir("fixtures/spiece.model")
... | 7 | 0 |
def UpperCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
assert x is not None
assert y is not None
__lowercase : Dict = len(SCREAMING_SNAKE_CASE__ )
__lowercase : List[Any] = len(SCREAMING_SNAKE_CASE__ )
# declaring the array for st... | 156 |
from typing import Dict
from .base import GenericTensor, Pipeline
class A ( _UpperCAmelCase ):
"""simple docstring"""
def snake_case__ ( self : int,lowercase_ : Dict=None,lowercase_ : Tuple=None,lowercase_ : List[Any]=None,... | 7 | 0 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
lowerCAmelCase : Dict ... | 291 |
from timeit import timeit
def _snake_case( SCREAMING_SNAKE_CASE__ : int ) -> int:
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
A__ = 0
while number:
number &=... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
import requests
A =set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories creat... | 34 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def _snake_case( SCREAMING_SNAKE_CASE__ : Any ) -> ... | 7 | 0 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
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_config_docstri... | 201 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from... | 7 | 0 |
"""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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feat... | 54 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : Union[str, Any] ) -> Tuple:
'''simple docstring'''
A__ = 0
A__ = len(SCREAMING_SNAKE_CASE__ ) - 1
while left <= right:
... | 7 | 0 |
"""simple docstring"""
from math import factorial, pi
def __lowercase ( snake_case_ : float ,snake_case_ : int = 30 ) ->float:
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE__ ,(int, float) ):
raise ValueError('''maclaurin_sin() requ... | 179 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from da... | 7 | 0 |
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
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lower... | 187 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import Confi... | 7 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType
_U... | 285 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common... | 7 | 0 |
def __lowercase ( lowerCamelCase : str ):
UpperCamelCase_ : int = []
UpperCamelCase_ : List[Any] = []
UpperCamelCase_ : Any = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priority of each operator
UpperCamelCase_ ... | 175 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class A ( _UpperCAmelCase ):
... | 7 | 0 |
"""simple docstring"""
def __lowerCamelCase ( a_ : float , a_ : float , a_ : float , a_ : float , a_ : float , ) -> float:
__SCREAMING_SNAKE_CASE :Dict = [redshift, radiation_density, matter_density, dark_energy]
if any(p < 0 for ... | 191 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _snake_case( SCREAMING_SNAKE... | 7 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.... | 169 |
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_tokenization_common import Toke... | 7 | 0 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProce... | 156 |
def _snake_case( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , ) -> float:
'''simple docstring'''
A__ ... | 7 | 0 |
"""simple docstring"""
def a__ ( snake_case__ = 60_08_51_47_51_43 ) -> int:
try:
lowerCamelCase = int(SCREAMING_SNAKE_CASE__ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable to int.""" )
if n <= 0:
rai... | 291 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def _snake_case( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str = "cpu" , SCREAMING_SNAKE_CASE__ : Union[str, None] = None ) -> None:
'''simple docstring'''
... | 7 | 0 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vis... | 34 |
import os
# Precomputes a list of the 100 first triangular numbers
lowercase_ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def _snake_case( ) -> int:
'''simple docstring'''
A__ = os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE__... | 7 | 0 |
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,
MobileViTImageProc... | 201 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy,... | 7 | 0 |
"""simple docstring"""
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def UpperCAmelCase__ (*lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_=True , lowerCAmelCase_=2 ):
'''simple docstring'''
... | 54 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowercase_ = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def _snake_case( SCREAMING_SNAKE_CA... | 7 | 0 |
"""simple docstring"""
import math
import os
import unittest
from transformers import MegatronBertConfig, 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_configu... | 179 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A ( _UpperCAmelCase ):
"""simple... | 7 | 0 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowercase__ : List[str] = HfApi()
lowercase__ : Any = {}
# fmt: off
lowercase__ : List[str] = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, 0.63... | 187 |
class A :
"""simple docstring"""
def __init__( self : Any,lowercase_ : Tuple,lowercase_ : Any,lowercase_ : List[str] )-> List[Any]:
'''simple docstring'''
A__ = name
A__ = ... | 7 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : List[str] = logging.get_logger(__name__)
_UpperCAmelCase : Union[str, An... | 285 |
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
... | 7 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _lowercase ( _Upper... | 175 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"t5-small": "https://huggingface.co/t5-small/resolve/main/config.json... | 7 | 0 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@re... | 191 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Any ) -> Optional[int]:
'''simple docstring'''
global f # a global dp tabl... | 7 | 0 |
_lowerCAmelCase : List[str] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.6_0_9_3_4_4,
"knot": 1.8_5_2,
}
_lowerCAmelCase : Optional[Any] = {
"km/h": 1.0,
"m/s": 0.2_7_7_7_7_7_7_7_8,
"mph": 0.6_2_1_3_7_1_1_9_2,
"knot": 0.5_3_9_9_5_6_8_0_3,
}
def lowerCA... | 169 |
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
lowercase_ = get_tests_dir("fixtures/spiece.model")
... | 7 | 0 |
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
__lowerCAmelCase : Optional[Any] ... | 156 |
from typing import Dict
from .base import GenericTensor, Pipeline
class A ( _UpperCAmelCase ):
"""simple docstring"""
def snake_case__ ( self : int,lowercase_ : Dict=None,lowercase_ : Tuple=None,lowercase_ : List[Any]=None,... | 7 | 0 |
"""simple docstring"""
import argparse
import json
import subprocess
def a__ ( snake_case__ , snake_case__ ) -> List[Any]:
lowerCamelCase = []
lowerCamelCase = (
F'curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'... | 291 |
from timeit import timeit
def _snake_case( SCREAMING_SNAKE_CASE__ : int ) -> int:
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
A__ = 0
while number:
number &=... | 7 | 0 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team and The OpenBMB 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.o... | 34 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def _snake_case( SCREAMING_SNAKE_CASE__ : Any ) -> ... | 7 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNex... | 201 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from... | 7 | 0 |
"""simple docstring"""
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.t... | 54 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : Union[str, Any] ) -> Tuple:
'''simple docstring'''
A__ = 0
A__ = len(SCREAMING_SNAKE_CASE__ ) - 1
while left <= right:
... | 7 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig... | 179 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from da... | 7 | 0 |
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, loggi... | 187 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import Confi... | 7 | 0 |
from maths.prime_factors import prime_factors
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
snake_case_ = F'''Input value of [number={number}] must be ... | 285 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common... | 7 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class _lowercase ( _UpperCAmelCase ):
lowe... | 175 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class A ( _UpperCAmelCase ):
... | 7 | 0 |
"""simple docstring"""
def __lowerCamelCase ( a_ : int = 4_00_00_00 ) -> int:
__SCREAMING_SNAKE_CASE :Any = [0, 1]
__SCREAMING_SNAKE_CASE :Optional[Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
... | 191 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _snake_case( SCREAMING_SNAKE... | 7 | 0 |
from torch import nn
class _UpperCamelCase ( nn.Module ):
def __init__( self :str , lowerCamelCase :List[Any] , lowerCamelCase :List[Any] ) -> Optional[Any]:
super().__init__()
UpperCAmelCase__ = class_size
UpperCAmelCase__... | 169 |
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_tokenization_common import Toke... | 7 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__lowerCAmelCase : Tuple = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except Option... | 156 |
def _snake_case( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , ) -> float:
'''simple docstring'''
A__ ... | 7 | 0 |
"""simple docstring"""
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils i... | 291 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def _snake_case( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str = "cpu" , SCREAMING_SNAKE_CASE__ : Union[str, None] = None ) -> None:
'''simple docstring'''
... | 7 | 0 |
'''simple docstring'''
import string
import numpy
def snake_case_ (_a : int , _a : int ):
return b if a == 0 else greatest_common_divisor(b % a , SCREAMING_SNAKE_CASE__ )
class _a :
__a : List[Any] = string.ascii_uppercase + s... | 34 |
import os
# Precomputes a list of the 100 first triangular numbers
lowercase_ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def _snake_case( ) -> int:
'''simple docstring'''
A__ = os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE__... | 7 | 0 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class lowercase__ ... | 201 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy,... | 7 | 0 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 54 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowercase_ = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def _snake_case( SCREAMING_SNAKE_CA... | 7 | 0 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 179 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A ( _UpperCAmelCase ):
"""simple... | 7 | 0 |
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also ... | 187 |
class A :
"""simple docstring"""
def __init__( self : Any,lowercase_ : Tuple,lowercase_ : Any,lowercase_ : List[str] )-> List[Any]:
'''simple docstring'''
A__ = name
A__ = ... | 7 | 0 |
from __future__ import annotations
import time
_UpperCAmelCase : Optional[int] = list[tuple[int, int]]
_UpperCAmelCase : Dict = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, ... | 285 |
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
... | 7 | 0 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_available():
... | 175 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"t5-small": "https://huggingface.co/t5-small/resolve/main/config.json... | 7 | 0 |
"""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_availabl... | 191 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : Any ) -> Optional[int]:
'''simple docstring'''
global f # a global dp tabl... | 7 | 0 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
_lowerCAmelCase : List[str] = (3, 9, -1_1, 0, 7, 5, 1, -1)
_lowerCAmelCase : Optional[int] = (4, 6, 2, 0, 8, 1_0, 3, -2)
@dataclass
class _UpperCamelCase :
... | 169 |
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
lowercase_ = get_tests_dir("fixtures/spiece.model")
... | 7 | 0 |
import os
# Precomputes a list of the 100 first triangular numbers
__lowerCAmelCase : List[Any] = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def UpperCAmelCase_ ( ) -> int:
__lowercase : Optional[int] = os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE__ ... | 156 |
from typing import Dict
from .base import GenericTensor, Pipeline
class A ( _UpperCAmelCase ):
"""simple docstring"""
def snake_case__ ( self : int,lowercase_ : Dict=None,lowercase_ : Tuple=None,lowercase_ : List[Any]=None,... | 7 | 0 |
"""simple docstring"""
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 impo... | 291 |
from timeit import timeit
def _snake_case( SCREAMING_SNAKE_CASE__ : int ) -> int:
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
A__ = 0
while number:
number &=... | 7 | 0 |
'''simple docstring'''
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
A =logging.get_logger(__name__)
class _a ( _UpperCAmelCase ):
__a : str = CLIPCon... | 34 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def _snake_case( SCREAMING_SNAKE_CASE__ : Any ) -> ... | 7 | 0 |
def lowerCAmelCase_ ( __UpperCAmelCase: int , __UpperCAmelCase: int ) -> str:
return "\n".join(
f"{number} * {i} = {number * i}" for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_table(number=5, number_of_term... | 201 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from... | 7 | 0 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requ... | 54 |
def _snake_case( SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : Union[str, Any] ) -> Tuple:
'''simple docstring'''
A__ = 0
A__ = len(SCREAMING_SNAKE_CASE__ ) - 1
while left <= right:
... | 7 | 0 |
"""simple docstring"""
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class __snake_case :
"""simple docstring"""
_lowerCamelCase = None
_lowerCamelCase = False
_lowerCamelCase = ... | 179 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from da... | 7 | 0 |
from collections import defaultdict
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : List[Any] , __lowercase : str , __lowercase : str ):
"""simple docstring"""
... | 187 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import Confi... | 7 | 0 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class lowercase ( unittest.TestCase ):
def a ( self ):
snake_case_ = 10
def a ( ... | 285 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common... | 7 | 0 |
from pathlib import Path
import fire
def __lowercase ( lowerCamelCase : str , lowerCamelCase : str , lowerCamelCase : int ):
UpperCamelCase_ : List[str] = Path(SCREAMING_SNAKE_CASE__ )
UpperCamelCase_ : List[str] = Path(SCREAMING_SNAKE_CASE__ )
... | 175 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class A ( _UpperCAmelCase ):
... | 7 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_co... | 191 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _snake_case( SCREAMING_SNAKE... | 7 | 0 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _UpperCamelCase ( _UpperCAmelCase ):
UpperCAmelCase_... | 169 |
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_tokenization_common import Toke... | 7 | 0 |
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