code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
'configuration_bigbird_pegasus': [
'BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BigBirdPegasusConfig',
'BigBirdP... | 27 |
'''simple docstring'''
import baseaa
def lowerCamelCase ( lowerCamelCase : str):
return baseaa.aaaencode(string.encode("""utf-8"""))
def lowerCamelCase ( lowerCamelCase : bytes):
return baseaa.aaadecode(lowerCamelCase).decode("""utf-8""")
if __name__ ==... | 27 | 1 |
'''simple docstring'''
from __future__ import annotations
__magic_name__ = '#'
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self : str ):
'''simple docstring'''
A_ : dict = {}
def _a ( self : ... | 27 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowerCamelCase ( lowerCamelCase : Optional[Any]):
# This defines a "chinese character" as anything in the CJK Unico... | 27 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__magic_name__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 27 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( ... | 27 | 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_mode... | 27 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = ["""torch""", """torchsde"""]
def __init__( self : Any ,*_a : Union[str, Any] ,**_a : ... | 27 | 1 |
'''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = 'T5Config'
class __lowerCAmelCase ( __SCR... | 27 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data ... | 27 | 1 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_ten... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {}
try:
if not is_sentencepiece_available():
raise Op... | 27 | 1 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,... | 27 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, ... | 27 | 1 |
'''simple docstring'''
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 __lowerCAmelCase ( __SCREAMING_SNA... | 27 |
'''simple docstring'''
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, PreTrainedToke... | 27 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'configuration_blip': [
'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 27 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
__magic_name__ = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
__magic_name__ = reque... | 27 | 1 |
'''simple docstring'''
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 27 |
'''simple docstring'''
from ... import PretrainedConfig
__magic_name__ = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = NEZHA_PRE... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : list[int]):
if not numbers:
return 0
if not isinstance(lowerCamelCase , (list, tuple)) or not all(
isinstance(lowerCamelCase , lowerCamelCase) for number in numbers):
... | 27 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( lowerCamelCase : dict , lowerCamelCase : str):
A_ , A_ : List[Any] = set(lowerCamelCase), [start]
while stack:
A_ : Optional[Any] =... | 27 | 1 |
'''simple docstring'''
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def lowerCamelCase ( lowerCamelCase : Optional[int] , lowerCamelCase : int , lowerCamelCase : Dict , lower... | 27 |
'''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,
MobileViTImageP... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : int = 100):
A_ : Any = n * (n + 1) * (2 * n + 1) / 6
A_ : str = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares)
if __name__ == "__main__":
print(f"""{solut... | 27 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
r... | 27 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datase... | 27 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : ... | 27 | 1 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixi... | 27 |
'''simple docstring'''
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def lowerCamelCase ( lowerCamelCase : str , lowerCamelCase : complex , lowerCamelCase : str = "x" , lowerCamelCase : float = 10**-1... | 27 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decode... | 27 |
'''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
__magic_name__ = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 27 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {
'configuration_blenderbot': [
'BLENDERBOT_P... | 27 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( lowerCamelCase : int):
if num <= 0:
A_ : List[Any] = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(lowerCamelCase)
... | 27 | 1 |
'''simple docstring'''
import numpy as np
def lowerCamelCase ( lowerCamelCase : np.ndarray , lowerCamelCase : np.ndarray , lowerCamelCase : float = 1E-12 , lowerCamelCase : int = 100 , ):
assert np.shape(lowerCamelCase)[0] ... | 27 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datase... | 27 | 1 |
'''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.conversationa... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNext... | 27 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __lowerCAmelCase ( __SCREAMING_SNAKE... | 27 |
'''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 PretrainedConfig
fr... | 27 | 1 |
'''simple docstring'''
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
f... | 27 |
'''simple docstring'''
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 BatchFe... | 27 | 1 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 27 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 27 | 1 |
'''simple docstring'''
from ... import PretrainedConfig
__magic_name__ = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = NEZHA_PRE... | 27 |
'''simple docstring'''
import baseaa
def lowerCamelCase ( lowerCamelCase : str):
return baseaa.aaaencode(string.encode("""utf-8"""))
def lowerCamelCase ( lowerCamelCase : bytes):
return baseaa.aaadecode(lowerCamelCase).decode("""utf-8""")
if __name__ ==... | 27 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( lowerCamelCase : list[int]):
A_ : int = len(lowerCamelCase) // 2
# choose the middle 3 elements
A_ : Tuple = lst[m - 1 : m + 2]
# if middle element is... | 27 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowerCamelCase ( lowerCamelCase : Optional[Any]):
# This defines a "chinese character" as anything in the CJK Unico... | 27 | 1 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="""session""")
def lowerCamelCase ( ... | 27 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( ... | 27 | 1 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self : str ,_a : Any ):
'''simple docstring'''
A_ : Optional[int] =... | 27 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = ["""torch""", """torchsde"""]
def __init__( self : Any ,*_a : Union[str, Any] ,**_a : ... | 27 | 1 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data ... | 27 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data ... | 27 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__magic_name__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {}
try:
if not is_sentencepiece_available():
raise Op... | 27 | 1 |
'''simple docstring'''
import os
import string
import sys
__magic_name__ = 1 << 8
__magic_name__ = {
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,
'left': 68 + ARROW_KEY_FLAG,
... | 27 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, ... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : float , lowerCamelCase : float):
if density <= 0:
raise ValueError("""Impossible fluid density""")
if bulk_modulus <= 0:
raise ValueError("""Impossible bulk modulus""")
retu... | 27 |
'''simple docstring'''
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, PreTrainedToke... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : Dict):
A_ : Tuple = 0
A_ : Union[str, Any] = len(lowerCamelCase)
for i in range(n - 1):
for j in range(i + 1 , lowerCamelCase):
if arr[i] ... | 27 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
__magic_name__ = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
__magic_name__ = reque... | 27 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@re... | 27 |
'''simple docstring'''
from ... import PretrainedConfig
__magic_name__ = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = NEZHA_PRE... | 27 | 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,
MobileViTImageP... | 27 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( lowerCamelCase : dict , lowerCamelCase : str):
A_ , A_ : List[Any] = set(lowerCamelCase), [start]
while stack:
A_ : Optional[Any] =... | 27 | 1 |
'''simple docstring'''
from collections import defaultdict
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self : Optional[Any] ,_a : List[str] ,_a : Optional[int] ):
'''simple docstring'''
A_ : Optional[int] = total # ... | 27 |
'''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,
MobileViTImageP... | 27 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torc... | 27 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
r... | 27 | 1 |
'''simple docstring'''
from itertools import permutations
def lowerCamelCase ( lowerCamelCase : tuple):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
A_ ... | 27 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : ... | 27 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCamelCase ( lowerCamelCase : int = 200_0000):
A_ : list[int] = [0]
A_ : int
for idx in range(1 , ceil(sqrt(target * 2) * 1.1)):
... | 27 |
'''simple docstring'''
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def lowerCamelCase ( lowerCamelCase : str , lowerCamelCase : complex , lowerCamelCase : str = "x" , lowerCamelCase : float = 10**-1... | 27 | 1 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
__magic_name__ = 'examples/'
__magic_name__ = {
'examples': (re.compile(r'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(r'^__version__\s+=\s+"([^"... | 27 |
'''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
__magic_name__ = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : int = 400_0000):
A_ : Dict = [0, 1]
A_ : str = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1])
if fib[i + 2] > n:
break
i... | 27 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( lowerCamelCase : int):
if num <= 0:
A_ : List[Any] = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(lowerCamelCase)
... | 27 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __lowerCAmelCase ( unitte... | 27 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datase... | 27 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = ["""onnx"""]
def __init__( self : Any ,*_a : int ,**_a : Optional[Any] ):
... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNext... | 27 | 1 |
'''simple docstring'''
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision... | 27 |
'''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 PretrainedConfig
fr... | 27 | 1 |
'''simple docstring'''
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = """M-CLIP"""
def __init__( self : int ,_a : str=1024 ,_a : ... | 27 |
'''simple docstring'''
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 BatchFe... | 27 | 1 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
)
| 27 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 27 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorTy... | 27 |
'''simple docstring'''
import baseaa
def lowerCamelCase ( lowerCamelCase : str):
return baseaa.aaaencode(string.encode("""utf-8"""))
def lowerCamelCase ( lowerCamelCase : bytes):
return baseaa.aaadecode(lowerCamelCase).decode("""utf-8""")
if __name__ ==... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : int):
A_ : Optional[Any] = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def lowerCamelCase ( lowerCamelCase : int = 100):
... | 27 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowerCamelCase ( lowerCamelCase : Optional[Any]):
# This defines a "chinese character" as anything in the CJK Unico... | 27 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, id... | 27 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( ... | 27 | 1 |
'''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 .t... | 27 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = ["""torch""", """torchsde"""]
def __init__( self : Any ,*_a : Union[str, Any] ,**_a : ... | 27 | 1 |
'''simple docstring'''
from math import ceil, sqrt
def lowerCamelCase ( lowerCamelCase : int = 100_0000):
A_ : Tuple = 0
for outer_width in range(3 , (limit // 4) + 2):
if outer_width**2 > limit:
A_ : List[str] ... | 27 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data ... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : List[Any]): # noqa: E741
A_ : Optional[int] = len(lowerCamelCase)
A_ : Tuple = 0
A_ : Tuple = [0] * n
A_ : Dict = [False] * n
A_ ... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {}
try:
if not is_sentencepiece_available():
raise Op... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : float , lowerCamelCase : float):
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f"""{price_plus_tax(100, 0.2_5) = }""")
print(f"""{price_plus_tax(1_2_5.5_0, 0.0_5) = }""")
| 27 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, ... | 27 | 1 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
__magic_name__ = 6_3_7_8_1_3_7.0
__magic_name__ = 6_3_5_6_7_5_2.3_1_4_2_4_5
__magic_name__ = 6_378_137
def lowerCamelCase ( lowerCamelCase : float , lowerCamelCase : float... | 27 |
'''simple docstring'''
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, PreTrainedToke... | 27 | 1 |
'''simple docstring'''
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils imp... | 27 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
__magic_name__ = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
__magic_name__ = reque... | 27 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__magic_name__ = {'tokenization_herbert': ['HerbertTokenizer']}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
e... | 27 |
'''simple docstring'''
from ... import PretrainedConfig
__magic_name__ = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = NEZHA_PRE... | 27 | 1 |
'''simple docstring'''
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 (
... | 27 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( lowerCamelCase : dict , lowerCamelCase : str):
A_ , A_ : List[Any] = set(lowerCamelCase), [start]
while stack:
A_ : Optional[Any] =... | 27 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = ["""note_seq"""]
def __init__( self : int ,*_a : Optional[int] ,**_a : Any ):
... | 27 |
'''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,
MobileViTImageP... | 27 | 1 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.ut... | 27 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
r... | 27 | 1 |
'''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
__magic_name__ = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 27 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : ... | 27 | 1 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class __lowerCAmelCase ( __SCR... | 27 |
'''simple docstring'''
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def lowerCamelCase ( lowerCamelCase : str , lowerCamelCase : complex , lowerCamelCase : str = "x" , lowerCamelCase : float = 10**-1... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : Dict , lowerCamelCase : Union[str, Any]):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
A_ : List[Any] = (boundary[1] - boundary[0]) / steps
A_ : ... | 27 |
'''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
__magic_name__ = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 27 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_... | 27 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( lowerCamelCase : int):
if num <= 0:
A_ : List[Any] = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(lowerCamelCase)
... | 27 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
__magic_name__ = 0
__magic_name__ = [
[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,... | 27 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datase... | 27 | 1 |
'''simple docstring'''
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __lowerCAmelCase :
'''simple docstring'''
a_ = 42
a_ = None
a_ = None
def lowerCamelCase ( lowerCamelCase : TreeNode | N... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNext... | 27 | 1 |
'''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
@requir... | 27 |
'''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 PretrainedConfig
fr... | 27 | 1 |
'''simple docstring'''
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__magic_name__ = '.'
if __name__ == "__main__":
__magic_name__ = os.path.join(REPO_PATH, 'utils/documentation_tests.... | 27 |
'''simple docstring'''
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 BatchFe... | 27 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 27 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 27 | 1 |
'''simple docstring'''
from collections import defaultdict
from math import ceil, sqrt
def lowerCamelCase ( lowerCamelCase : int = 100_0000 , lowerCamelCase : int = 10):
A_ : defaultdict = defaultdict(lowerCamelCase)
for outer_width in range(3... | 27 |
'''simple docstring'''
import baseaa
def lowerCamelCase ( lowerCamelCase : str):
return baseaa.aaaencode(string.encode("""utf-8"""))
def lowerCamelCase ( lowerCamelCase : bytes):
return baseaa.aaadecode(lowerCamelCase).decode("""utf-8""")
if __name__ ==... | 27 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy a... | 27 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowerCamelCase ( lowerCamelCase : Optional[Any]):
# This defines a "chinese character" as anything in the CJK Unico... | 27 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 27 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( ... | 27 | 1 |
'''simple docstring'''
import os
from collections.abc import Iterator
def lowerCamelCase ( lowerCamelCase : str = "."):
for dir_path, dir_names, filenames in os.walk(lowerCamelCase):
A_ : Dict = [d for d in dir_names if d != """scripts""" and d[0] not in ... | 27 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = ["""torch""", """torchsde"""]
def __init__( self : Any ,*_a : Union[str, Any] ,**_a : ... | 27 | 1 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_atte... | 27 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data ... | 27 | 1 |
'''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if no... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {}
try:
if not is_sentencepiece_available():
raise Op... | 27 | 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 PretrainedConfig
fr... | 27 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, ... | 27 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'junnyu/roformer_chinese_small... | 27 |
'''simple docstring'''
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, PreTrainedToke... | 27 | 1 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
c... | 27 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
__magic_name__ = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
__magic_name__ = reque... | 27 | 1 |
'''simple docstring'''
import cmath
import math
def lowerCamelCase ( lowerCamelCase : float , lowerCamelCase : float , lowerCamelCase : float , lowerCamelCase : float):
A_ : Optional[Any] = math.radians(lowerCamelCas... | 27 |
'''simple docstring'''
from ... import PretrainedConfig
__magic_name__ = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = NEZHA_PRE... | 27 | 1 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
't5-small': 'https://huggingface.co/t5-small/resolv... | 27 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( lowerCamelCase : dict , lowerCamelCase : str):
A_ , A_ : List[Any] = set(lowerCamelCase), [start]
while stack:
A_ : Optional[Any] =... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( ):
for n in range(1 , 100_0000):
yield n * (n + 1) // 2
def lowerCamelCase ( lowerCamelCase : Union[str, Any]):
A_ : List[Any] = 1
A_ : Optional[int] = 2
... | 27 |
'''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,
MobileViTImageP... | 27 | 1 |
'''simple docstring'''
__magic_name__ = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowerCamelCase ( lowerCamelCase : str):
A_ : List[str] = {"""*""": op.mul, """/""": op.truediv, """+""": op.add, """-""": op.sub}
A_ : ... | 27 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
r... | 27 | 1 |
'''simple docstring'''
import numpy as np
def lowerCamelCase ( lowerCamelCase : np.array):
return (2 / (1 + np.exp(-2 * vector))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 27 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : ... | 27 | 1 |
'''simple docstring'''
from math import pi, sqrt, tan
def lowerCamelCase ( lowerCamelCase : float):
if side_length < 0:
raise ValueError("""surface_area_cube() only accepts non-negative values""")
return 6 * side_length**2
def lowerCamelCase ( lower... | 27 |
'''simple docstring'''
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def lowerCamelCase ( lowerCamelCase : str , lowerCamelCase : complex , lowerCamelCase : str = "x" , lowerCamelCase : float = 10**-1... | 27 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : ... | 27 |
'''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
__magic_name__ = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 27 | 1 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 27 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( lowerCamelCase : int):
if num <= 0:
A_ : List[Any] = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(lowerCamelCase)
... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : int , lowerCamelCase : int):
return int((input_a, input_a).count(0) != 0)
def lowerCamelCase ( ):
assert nand_gate(0 , 0) == 1
assert nand_gate(0 , 1) == 1
... | 27 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datase... | 27 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import requir... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__magic_name__ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNext... | 27 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ = {
'configuration_tapas': ['TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TapasConfig'],
'tokenization_tapas': ['TapasTokenizer'],... | 27 |
'''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 PretrainedConfig
fr... | 27 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
__magic_name__ = list[list[float | int]]
def lowerCamelCase ( lowerCamelCase : Matrix , lowerCamelCase : Matrix):
A_ : int = len(lowerCamelCase)
... | 27 |
'''simple docstring'''
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 BatchFe... | 27 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_... | 27 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 27 | 1 |
'''simple docstring'''
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 BatchFe... | 27 |
'''simple docstring'''
import baseaa
def lowerCamelCase ( lowerCamelCase : str):
return baseaa.aaaencode(string.encode("""utf-8"""))
def lowerCamelCase ( lowerCamelCase : bytes):
return baseaa.aaadecode(lowerCamelCase).decode("""utf-8""")
if __name__ ==... | 27 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( ... | 27 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowerCamelCase ( lowerCamelCase : Optional[Any]):
# This defines a "chinese character" as anything in the CJK Unico... | 27 | 1 |
'''simple docstring'''
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowerCamelCase ( lowerCamelCase : dic... | 27 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( ... | 27 | 1 |
'''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import... | 27 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = ["""torch""", """torchsde"""]
def __init__( self : Any ,*_a : Union[str, Any] ,**_a : ... | 27 | 1 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy... | 27 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data ... | 27 | 1 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def lowerCamelCase ( lowerCamelCase : int , lowerCamelCase : int , lowerCamelCase : int , lowerCamelCase : int ... | 27 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {}
try:
if not is_sentencepiece_available():
raise Op... | 27 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : list):
A_ : List[Any] = False
while is_sorted is False: # Until all the indices are traversed keep looping
A_ : Optional[Any] = True
for i in range(0 , ... | 27 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, ... | 27 | 1 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase ( lowerCamelCase : str):
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia... | 27 |
'''simple docstring'''
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, PreTrainedToke... | 27 | 1 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class __lowerCAmelCase ( datasets.BeamBasedBuilder ):
'''simple docstring'''
... | 27 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
__magic_name__ = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
__magic_name__ = reque... | 27 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
import numpy as np
__magic_name__ = [8, 5, 9, 7]
__magic_name__ = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
__magic_name__ = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5... | 27 |
'''simple docstring'''
from ... import PretrainedConfig
__magic_name__ = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
a_ = NEZHA_PRE... | 27 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.uti... | 27 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( lowerCamelCase : dict , lowerCamelCase : str):
A_ , A_ : List[Any] = set(lowerCamelCase), [start]
while stack:
A_ : Optional[Any] =... | 27 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageRe... | 27 |
'''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,
MobileViTImageP... | 27 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.