code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ... | 83 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 50 ) -> int:
'''simple docstring'''
snake_case : Union[str, Any] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(r... | 83 | 1 |
'''simple docstring'''
from __future__ import annotations
class snake_case__ :
"""simple docstring"""
def __init__( self : List[str] , UpperCamelCase__ : List[str]=None ) -> Optional[Any]:
"""simple docstring"""
... | 83 |
'''simple docstring'''
class snake_case__ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : list[int] ) -> None:
"""simple docstring"""
snake_case : List[Any] = len(UpperCamelCase... | 83 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class snake_c... | 83 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 83 | 1 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class snake_case__ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : Optional[int] , UpperCamelCase__ : ... | 83 |
'''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(_... | 83 | 1 |
'''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"microsoft/xprophetnet-large-wiki100-cased": (
"https://huggingface... | 83 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase... | 83 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"configuration_xlm_roberta_xl": [
"XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP",
"XLMRobertaXLConfig",
"XLMRobe... | 83 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class snake_case__ :
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : int , UpperCamelCase__ : MutableSeque... | 83 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from d... | 83 |
'''simple docstring'''
import os
def _UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
snake_case : int = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE__ ) , '''num.txt''' )
with open(SCREAMING_SNAKE_CASE__ ) as file_hand:
return str(sum(int(... | 83 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {
"configuration_vision_text_dual_encoder": ["VisionTextDualEncoderConfig"... | 83 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 1 , SCREAMING_SNAKE_CASE__ = 1000 ) -> int:
'''simple docstring'''
snake_case : Dict = 1
snake_case : str = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE__ , digit +... | 83 | 1 |
'''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... | 83 |
'''simple docstring'''
from collections.abc import Generator
def _UpperCamelCase ( ) -> Generator[int, None, None]:
'''simple docstring'''
snake_case ,snake_case : Tuple = 0, 1
while True:
snake_case ,snake_case : List[Any] = b, a + b
yie... | 83 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class snake_case__ ( __SCREA... | 83 |
'''simple docstring'''
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 83 | 1 |
'''simple docstring'''
import re
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> bool:
'''simple docstring'''
snake_case : Optional[Any] = re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAK... | 83 |
'''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 ... | 83 | 1 |
'''simple docstring'''
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowercase__ = numpy.array([0, 0])
lowercase__ = numpy.array([0.5, 0.8_66_02_54])
lowercase__ = numpy.array([1, 0])
lowercase__... | 83 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 83 | 1 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class snake_case__ ( unittest.TestCase ):
"""simple docstring"""
def lowerCAmelCase ( self : int ) -> Union... | 83 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase = ["""image_processor""", """to... | 83 | 1 |
'''simple docstring'''
import sys
lowercase__ = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"668966489504452445... | 83 |
'''simple docstring'''
from functools import lru_cache
@lru_cache
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
... | 83 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 3 , SCREAMING_SNAKE_CASE__ = 7 , SCREAMING_SNAKE_CASE__ = 100_0000 ) -> int:
'''simple docstring'''
snake_case : Tuple = 0
snake_case : Tuple = 1
for current_denominator in... | 83 |
'''simple docstring'''
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ... | 83 | 1 |
'''simple docstring'''
from statistics import mean, stdev
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = 3 ) -> list:
'''simple docstring'''
snake_case : List[str] = min(SCREAMING_SNAKE_CASE__ )
snake_case : Tuple = ma... | 83 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list:
'''simple docstring'''
snake_case : Any = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case : Optional[int] = collection[i]
snak... | 83 | 1 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_... | 83 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path"... | 83 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__=2_8123 ) -> List[Any]:
'''simple docstring'''
snake_case : List[Any] = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit ... | 83 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixi... | 83 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
@staticmethod
@abstractmethod
def lowerCAmelCase ( UpperCamelCase__ : Argume... | 83 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from di... | 83 | 1 |
'''simple docstring'''
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForIm... | 83 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 83 | 1 |
'''simple docstring'''
from math import pi
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> float:
'''simple docstring'''
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(9_0, 1_0))
| 83 |
'''simple docstring'''
import requests
lowercase__ = "" # <-- Put your OpenWeatherMap appid here!
lowercase__ = "https://api.openweathermap.org/data/2.5/"
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "Chicago" , SCREAMING_SNAKE_CASE__ = APPID ) -> dict:
'''sim... | 83 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {"v... | 83 |
'''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartFor... | 83 | 1 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 83 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 50 ) -> int:
'''simple docstring'''
snake_case : Union[str, Any] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(r... | 83 | 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,
is_vision_available,
)
lowercase__ = {
"configuration_c... | 83 |
'''simple docstring'''
class snake_case__ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : list[int] ) -> None:
"""simple docstring"""
snake_case : List[Any] = len(UpperCamelCase... | 83 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from di... | 83 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 83 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase = ["""image_processor""", """to... | 83 |
'''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(_... | 83 | 1 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transforme... | 83 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase... | 83 | 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
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTra... | 83 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class snake_case__ :
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : int , UpperCamelCase__ : MutableSeque... | 83 | 1 |
'''simple docstring'''
import math
import sys
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> str:
'''simple docstring'''
snake_case : List[str] = ''''''
try:
with open(SCREAMING_SNAKE_CASE__ , '''rb''' ) as binary_file:
snake_case : L... | 83 |
'''simple docstring'''
import os
def _UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
snake_case : int = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE__ ) , '''num.txt''' )
with open(SCREAMING_SNAKE_CASE__ ) as file_hand:
return str(sum(int(... | 83 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200 ) -> int:
'''simple docstring'''
snake_case : Any = [1, 2, 5, 10, 20, 50, 100, 200]
snake_case : Any = [0] * (pence + 1)
snake_case : str = 1 # base case: 1 way to ... | 83 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 1 , SCREAMING_SNAKE_CASE__ = 1000 ) -> int:
'''simple docstring'''
snake_case : Dict = 1
snake_case : str = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE__ , digit +... | 83 | 1 |
'''simple docstring'''
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 83 |
'''simple docstring'''
from collections.abc import Generator
def _UpperCamelCase ( ) -> Generator[int, None, None]:
'''simple docstring'''
snake_case ,snake_case : Tuple = 0, 1
while True:
snake_case ,snake_case : List[Any] = b, a + b
yie... | 83 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list:
'''simple docstring'''
snake_case : Any = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case : Optional[int] = collection[i]
snak... | 83 |
'''simple docstring'''
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 83 | 1 |
'''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
... | 83 |
'''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 ... | 83 | 1 |
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class snake_case__ ( unittest.TestCase ):
"""simple docstring"""
def ... | 83 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 83 | 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():
... | 83 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase = ["""image_processor""", """to... | 83 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 83 |
'''simple docstring'''
from functools import lru_cache
@lru_cache
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
... | 83 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if n == 1 or not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
return 0
elif n == 2:
return 1
else:
snake_case : int = [0, 1]
f... | 83 |
'''simple docstring'''
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ... | 83 | 1 |
'''simple docstring'''
import os
import sys
import unittest
lowercase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dumm... | 83 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list:
'''simple docstring'''
snake_case : Any = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case : Optional[int] = collection[i]
snak... | 83 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json''',
'''micros... | 350 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path"... | 83 | 0 |
'''simple docstring'''
import math
import sys
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if number != int(lowercase__ ):
raise ValueError('''the value of input must be a natural number''' )
if number < 0:
raise ValueError('''the v... | 351 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixi... | 83 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {
"configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", ... | 352 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from di... | 83 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"configuration_bigbird_pegasus": [
"BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BigBirdPegasusConfig",
"BigBirdPegasusOnnxConfig",
... | 353 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 83 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"configuration_blip_2": [
"BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Blip2Config",
"Blip2QFormerConfig",
"Blip2VisionConfig",
... | 354 |
'''simple docstring'''
import requests
lowercase__ = "" # <-- Put your OpenWeatherMap appid here!
lowercase__ = "https://api.openweathermap.org/data/2.5/"
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "Chicago" , SCREAMING_SNAKE_CASE__ = APPID ) -> dict:
'''sim... | 83 | 0 |
'''simple docstring'''
import unittest
from transformers import DebertaConfig, 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... | 355 |
'''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartFor... | 83 | 0 |
'''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 snake_ca... | 356 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 50 ) -> int:
'''simple docstring'''
snake_case : Union[str, Any] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(r... | 83 | 0 |
'''simple docstring'''
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():
... | 357 |
'''simple docstring'''
class snake_case__ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : list[int] ) -> None:
"""simple docstring"""
snake_case : List[Any] = len(UpperCamelCase... | 83 | 0 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class snake_case__ ( lowercase__ ):
"""... | 358 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 83 | 0 |
'''simple docstring'''
import os
from pathlib import Path
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> Union[str, Any]:
'''simple docstring'''
snake_case : List[Any] = {
'''en''': '''Ma... | 359 |
'''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(_... | 83 | 0 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowercase__ = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("ker... | 360 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase... | 83 | 0 |
'''simple docstring'''
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import ... | 361 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class snake_case__ :
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : int , UpperCamelCase__ : MutableSeque... | 83 | 0 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> Optional[Any]:
'''simple docstring'''
snake_case : Tuple = list(range(len(lowercase__ ) ) )
sna... | 362 |
'''simple docstring'''
import os
def _UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
snake_case : int = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE__ ) , '''num.txt''' )
with open(SCREAMING_SNAKE_CASE__ ) as file_hand:
return str(sum(int(... | 83 | 0 |
'''simple docstring'''
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
lowercase__ = logging.getLogger(__name__)
class snake_case__ ( __lowercas... | 363 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 1 , SCREAMING_SNAKE_CASE__ = 1000 ) -> int:
'''simple docstring'''
snake_case : Dict = 1
snake_case : str = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE__ , digit +... | 83 | 0 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessin... | 364 |
'''simple docstring'''
from collections.abc import Generator
def _UpperCamelCase ( ) -> Generator[int, None, None]:
'''simple docstring'''
snake_case ,snake_case : Tuple = 0, 1
while True:
snake_case ,snake_case : List[Any] = b, a + b
yie... | 83 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if not postfix_notation:
return 0
snake_case : List[Any] = {'''+''', '''-''', '''*''', '''/'''... | 365 |
'''simple docstring'''
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 83 | 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
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"sail/p... | 366 |
'''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 ... | 83 | 0 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..t... | 367 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 83 | 0 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> str:
snake_case : Tuple = int(_UpperCamelCase )
if decimal in (0, 1): # Exit cases for the recursion
return str(_UpperCamelCase )
snake_case ,snake_case : Dict = divmod(_UpperCamelCase ... | 368 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase = ["""image_processor""", """to... | 83 | 0 |
'''simple docstring'''
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_... | 369 |
'''simple docstring'''
from functools import lru_cache
@lru_cache
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
... | 83 | 0 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class snake_case__ ( __Upp... | 370 |
'''simple docstring'''
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ... | 83 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for idx in range(1 ... | 371 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list:
'''simple docstring'''
snake_case : Any = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case : Optional[int] = collection[i]
snak... | 83 | 0 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = 0 , SCREAMING_SNAKE_CASE__ = 0 ) -> Any:
'''simple docstring'''
snake_case : List[Any] = right or len(__a ) - 1
if left > right:
ret... | 350 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path"... | 83 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowercase__ = TypeVar("T")
lowercase__ = TypeVar("U")
class snake_case__ ( Generic[T, U] ):
"""simple docstring"""
... | 351 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixi... | 83 | 0 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 400_0000 ) -> int:
'''simple docstring'''
snake_case : List[str] = [0, 1]
snake_case : List[str] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
... | 352 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from di... | 83 | 0 |
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 100 ) -> List[Any]:
'''simple docstring'''
snake_case : int = set()
snake_case : Any = 0
snake_case : Optional[Any] = n + 1 # maximum limit
for a in range(2 , _A ):
for b in... | 353 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 83 | 0 |
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
lowercase__ = WebClient(token=os.environ["CI_SLACK_BOT_TOKEN"])
def _UpperCamelCase ( SCREAMING_SNAKE_CASE... | 354 |
'''simple docstring'''
import requests
lowercase__ = "" # <-- Put your OpenWeatherMap appid here!
lowercase__ = "https://api.openweathermap.org/data/2.5/"
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "Chicago" , SCREAMING_SNAKE_CASE__ = APPID ) -> dict:
'''sim... | 83 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
'''configuration_autoformer''': [
'''AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 355 |
'''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartFor... | 83 | 0 |
'''simple docstring'''
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class snake_case__ ( tf.keras.optimizer... | 356 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 50 ) -> int:
'''simple docstring'''
snake_case : Union[str, Any] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(r... | 83 | 0 |
'''simple docstring'''
# 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. W... | 357 |
'''simple docstring'''
class snake_case__ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : list[int] ) -> None:
"""simple docstring"""
snake_case : List[Any] = len(UpperCamelCase... | 83 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation... | 358 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 83 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Op... | 359 |
'''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(_... | 83 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase__ = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE... | 360 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase... | 83 | 0 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> Union[str, Any]:
'''simple docstring'''
snake_case : Any ... | 361 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class snake_case__ :
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : int , UpperCamelCase__ : MutableSeque... | 83 | 0 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , ) -> tuple:
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise Val... | 362 |
'''simple docstring'''
import os
def _UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
snake_case : int = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE__ ) , '''num.txt''' )
with open(SCREAMING_SNAKE_CASE__ ) as file_hand:
return str(sum(int(... | 83 | 0 |
'''simple docstring'''
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowercase__ = "sshleifer/bart... | 363 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 1 , SCREAMING_SNAKE_CASE__ = 1000 ) -> int:
'''simple docstring'''
snake_case : Dict = 1
snake_case : str = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE__ , digit +... | 83 | 0 |
import argparse
import gc
import json
import os
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import... | 364 |
'''simple docstring'''
from collections.abc import Generator
def _UpperCamelCase ( ) -> Generator[int, None, None]:
'''simple docstring'''
snake_case ,snake_case : Tuple = 0, 1
while True:
snake_case ,snake_case : List[Any] = b, a + b
yie... | 83 | 0 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
lowercase__ = [int(0.5 * n * (n + 1)) for n in range(1, 1_0_1)]
def _UpperCamelCase ( ) -> Optional[int]:
'''simple docstring'''
snake_case : List[str] = os.path.di... | 365 |
'''simple docstring'''
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 83 | 0 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SN... | 366 |
'''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 ... | 83 | 0 |
'''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 367 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 83 | 0 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
lowercase__ = True
except (ImportError, ModuleNotFoundError):
lowercase__ = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", quiet=True... | 368 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase = ["""image_processor""", """to... | 83 | 0 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = 0 ) -> list:
'''simple docstring'''
snake_case : Optional[int] = length or len(_snake_case )
snake_case : Union[str, Any] = False
for i in range(length - ... | 369 |
'''simple docstring'''
from functools import lru_cache
@lru_cache
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
... | 83 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {"configuration_xlnet": ["XLNET_PRETRAIN... | 370 |
'''simple docstring'''
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ... | 83 | 0 |
'''simple docstring'''
import re
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list:
'''simple docstring'''
return [char.split() for char in re.split(R'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> str:
'''s... | 371 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list:
'''simple docstring'''
snake_case : Any = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case : Optional[int] = collection[i]
snak... | 83 | 0 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
lower... | 350 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path"... | 83 | 0 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> float:
'''simple docstring'''
if digit_amount > 0:
return round(number - int(_UpperCAmelCase ) , _UpperCAmelCase )
return number - int(_UpperCAmelCase )
if __name__ ==... | 351 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixi... | 83 | 0 |
'''simple docstring'''
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity... | 352 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from di... | 83 | 0 |
from __future__ import annotations
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
snake_case : int = list(range(len(lowerCamelCase__ ) ) )
snake_case : Optional[int]... | 353 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 83 | 0 |
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
from unilm.wavlm... | 354 |
'''simple docstring'''
import requests
lowercase__ = "" # <-- Put your OpenWeatherMap appid here!
lowercase__ = "https://api.openweathermap.org/data/2.5/"
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "Chicago" , SCREAMING_SNAKE_CASE__ = APPID ) -> dict:
'''sim... | 83 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
lowercase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
def... | 355 |
'''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartFor... | 83 | 0 |
'''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, TruncationStra... | 356 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 50 ) -> int:
'''simple docstring'''
snake_case : Union[str, Any] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(r... | 83 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_ava... | 357 |
'''simple docstring'''
class snake_case__ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : list[int] ) -> None:
"""simple docstring"""
snake_case : List[Any] = len(UpperCamelCase... | 83 | 0 |
'''simple docstring'''
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__=0 ) -> Dict:
'''simple docstring'''
... | 358 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 83 | 0 |
'''simple docstring'''
import torch
from transformers import AutoModel
class snake_case__ ( torch.nn.Module ):
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : Any="sayef/fsner-bert-base-uncased" ) -> Any:
... | 359 |
'''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(_... | 83 | 0 |
'''simple docstring'''
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
deprecate(
"pipelines_utils",
"0.22.0",
"Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffuser... | 360 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase... | 83 | 0 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case__ ( __lowercase ):
"""simple docstring"""
lowerCamelCase = (CMStochasticIterativeScheduler,)
lo... | 361 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class snake_case__ :
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : int , UpperCamelCase__ : MutableSeque... | 83 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
... | 362 |
'''simple docstring'''
import os
def _UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
snake_case : int = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE__ ) , '''num.txt''' )
with open(SCREAMING_SNAKE_CASE__ ) as file_hand:
return str(sum(int(... | 83 | 0 |
'''simple docstring'''
import baseaa
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> Optional[int]:
'''simple docstring'''
return baseaa.aaaencode(string.encode('''utf-8''' ) )
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> Dict:
'''simple docstri... | 363 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 1 , SCREAMING_SNAKE_CASE__ = 1000 ) -> int:
'''simple docstring'''
snake_case : Dict = 1
snake_case : str = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE__ , digit +... | 83 | 0 |
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformer... | 364 |
'''simple docstring'''
from collections.abc import Generator
def _UpperCamelCase ( ) -> Generator[int, None, None]:
'''simple docstring'''
snake_case ,snake_case : Tuple = 0, 1
while True:
snake_case ,snake_case : List[Any] = b, a + b
yie... | 83 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_ut... | 365 |
'''simple docstring'''
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 83 | 0 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.array:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 366 |
'''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 ... | 83 | 0 |
'''simple docstring'''
import numpy as np
class snake_case__ :
"""simple docstring"""
def __init__( self : Tuple , UpperCamelCase__ : List[str]=None , UpperCamelCase__ : int=None , UpperCamelCase__ : Dict=None ,... | 367 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 83 | 0 |
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