code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import comet # From: unbabel-comet
import torch
import datasets
A__ : Union[str, Any] = datasets.logging.get_logger(__name__)
A__ : str = """\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
title =... | 233 |
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 Accelerator... | 233 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 225 | import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import os
... | 225 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowercase : List[str] = {"""tokenization_bertweet""": ["""BertweetTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_bertweet import BertweetTokenizer
else:
import sys
lowercase : str = _LazyModule(__name__,... | 336 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableUnCL... | 336 | 1 |
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase ( lowercase__ ):
def __init__( self , UpperCAmelCase__ , UpperCAmelCase__ ):
super().__init__()
self.register_modules(unet=UpperCAm... | 700 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def UpperCamelCase ( _A : list , _A : list , _A : list , _A : list , _A : lis... | 232 | 0 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTextConfig,
... | 193 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.util... | 193 | 1 |
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
a_ = logging.getLogger()
def __lowerCAmelCase ( A_ : Optional[int] ... | 286 | import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism... | 286 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class __SCREAMING_SNAKE_... | 92 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , UpperCAmelCase__ : Union[str, Any] , UpperCAmelCase__ : int , UpperCAmelCase__ ... | 92 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 518 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
... | 518 | 1 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelFor... | 525 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_mo... | 525 | 1 |
def snake_case( __magic_name__ , __magic_name__ ) -> Optional[Any]:
'''simple docstring'''
lowercase : int = 0
lowercase : List[Any] = len(__snake_case ) - 1
while left <= right:
# ... | 707 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ = {
'configuration_altclip': [
'ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AltCLIPConfig',
'AltCLIPTextConf... | 596 | 0 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class a__( lowerCamelCase__ ):
lowercase__ = (EulerDiscreteScheduler,)
lowercase__ = 10
... | 526 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase: Tuple = logging.get_lo... | 526 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ : str = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
... | 443 |
from sklearn.metrics import fa_score
import datasets
UpperCAmelCase_ : List[Any] = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
UpperCAmelCase_ : Optional[Any] ... | 443 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A : str = logging.get_logger(__name__)
A : Dict = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
'https://hu... | 516 | """simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
A : int = get_logger(__name__)
A : Dict = r'\n Args:\n input_ids (`jnp.... | 516 | 1 |
'''simple docstring'''
def _a ( __lowerCAmelCase : float , __lowerCAmelCase : float , __lowerCAmelCase : int ):
"""simple docstring"""
if principal <= 0:
raise Exception('''Principal borrowed must be > 0''' )
if rate_per_annum < 0:
raise Exception(... | 710 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_co... | 502 | 0 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a =logging.get_logger(__name__)
a ="▁"
a ... | 652 |
'''simple docstring'''
def UpperCamelCase_( ):
'''simple docstring'''
snake_case_ = [3_1, 2_8, 3_1, 3_0, 3_1, 3_0, 3_1, 3_1, 3_0, 3_1, 3_0, 3_1]
snake_case_ = 6
snake_case_ = 1
snake_case_ = 1_9_0_1
snake_case_ = ... | 400 | 0 |
'''simple docstring'''
import baseaa
def lowercase__( __UpperCamelCase: Dict ):
"""simple docstring"""
return baseaa.baaencode(string.encode('utf-8' ) )
def lowercase__( __UpperCamelCase: Union[str, Any] ):
"""si... | 714 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ,__UpperCamelCase: bool ,__UpperCamelCase: list[int] ,__UpperCamelCase: float ):
"""simple docstring"""
... | 508 | 0 |
import sys
from pathlib import Path
UpperCAmelCase_ : Optional[int] = Path(__file__).resolve().parents[3] / "src"
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # noqa
import itertools # noqa
import json # noqa
import os # noqa
import unittest # noqa
from ... | 491 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_avai... | 34 | 0 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase__: list[float] ) -> bool:
if len(lowerCAmelCase__ ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
... | 710 |
'''simple docstring'''
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, res... | 238 | 0 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.b... | 105 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE (A ) -> bool:
"""simple docstring"""
lowercase__ = [int(A ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(A ) == 4 and all(0 <= int(A ) <= 254 for octet in octets )
if __name__ == "__mai... | 460 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from ... | 355 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowercase (_SCREAMING_SNAKE_CASE :List[str] , _SCREAMING_SNAKE_CASE :Any , _SCREAMING_SNAKE_CASE :str ):
SCREAMING_SNAKE_CASE : int = 0
if s... | 355 | 1 |
_lowerCamelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Any , UpperCamelCase__: Optional[Any] , UpperCa... | 6 |
from torch import nn
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: str ):
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'''Unsupported activation function:... | 6 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_t... | 34 | import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class lowercase__ ( UpperCamelCase_):
def __init__( self : str , UpperCamelCase__ : Optional[int] , UpperCamelCase__ : Optio... | 34 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils impor... | 545 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def snake_case_ ( lowerCAmelCase_ : ndarray ):
return np.dot(lowerCAmelCase_ , lowerCAmelCase_ )
class lowerCAmelCase :
'''simple docstring'''
def __init... | 149 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(chec... | 308 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : str = logging.get_logger(__name__)
_lowerCamelCase : Optional[int] = {
"""microsoft/git-base""": """https://huggingfa... | 308 | 1 |
'''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 OptionalDependency... | 452 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__SCREAMING_SNAKE_CASE : List[str] = {
'''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Graph... | 452 | 1 |
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_... | 234 | import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
A = {
'facebook/maskformer-swin-base-ade': (
'https://huggingface.c... | 234 | 1 |
'''simple docstring'''
def a ( _UpperCAmelCase ) -> bool:
"""simple docstring"""
if not isinstance(_UpperCAmelCase , _UpperCAmelCase ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(_UpperCAmelCase ) == 0:
... | 697 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase =logging.get_logger(__name__)
__lowerCAmelCase ={
"go... | 697 | 1 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class lowerCamelCase__( __lowerCamelCase , __lowerCamelCase):
UpperC... | 80 |
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import torch
UpperCAmelCase_... | 80 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torch
class ... | 547 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
SCREAMING_SNAKE_CASE__ : List[Any] = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_pytor... | 643 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : List[str] = logging.get_logger(__name__)
__a : Union[str, Any] = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.co/mi... | 298 |
from __future__ import annotations
def snake_case_ ( SCREAMING_SNAKE_CASE_ ) -> list[int]:
lowercase__ : List[str] = [True] * limit
lowercase__ : Union[str, Any] = False
lowercase__ : List[str] = False
... | 298 | 1 |
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTeacher,
EfficientFormerIma... | 113 |
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
_lowerCAmelCase : int ="""scheduler_config.json"""
class __UpperCamelCase ( _a ):
'''simple docstring'''
... | 113 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __snake_case( unittest.TestCase )... | 708 | """simple docstring"""
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
lowerCamelCase : ... | 237 | 0 |
'''simple docstring'''
__UpperCAmelCase = """0.18.2"""
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion... | 379 |
'''simple docstring'''
def __A ( lowerCamelCase_ , lowerCamelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : str = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
SCREAMING_SNAKE_CASE : Dict = n - k
# Calculate C(n,k)
for i in range... | 379 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCase__ : str = get_tests... | 700 |
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class _snake_case :
def __init__( self , SCREAMING_SNAKE_CASE_ = None):
'''simple docstring'''
if components is None:
lowercase_... | 495 | 0 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'''files''' , [
['''full:README.md''', '''dataset_infos.json'''],
['''empty:README.md'''... | 72 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
_lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'''google/umt... | 454 | 0 |
"""simple docstring"""
import socket
def lowercase_ ( ):
'''simple docstring'''
UpperCAmelCase : int = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
UpperCAmelCase : List[str] = socket.gethostname()
UpperCAmelCase : Any = ... | 704 |
"""simple docstring"""
snake_case_ : str = [
"""DownloadConfig""",
"""DownloadManager""",
"""DownloadMode""",
"""StreamingDownloadManager""",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manag... | 292 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging... | 453 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_con... | 453 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGene... | 707 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from tr... | 210 | 0 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_bytes
fro... | 276 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class _SCREAMING_SNAKE_CASE ( Generic[T] ):
def __init__( self , lowerCamelCase ):
snake_case__ = data
sna... | 276 | 1 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowercase = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for Transfer Learned"""
... | 591 | def lowerCamelCase_ ( UpperCamelCase__ : int = 100 ):
'''simple docstring'''
UpperCamelCase__ = (n * (n + 1) // 2) ** 2
UpperCamelCase__ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print... | 591 | 1 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import tor... | 481 |
"""simple docstring"""
from typing import Any
class a__ :
def __init__( self : List[str] , UpperCamelCase_ : Any):
"""simple docstring"""
__UpperCAmelCase : str = data
__UpperCAmelCase : Optional[Any] = None
... | 77 | 0 |
"""simple docstring"""
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin... | 158 |
"""simple docstring"""
from __future__ import annotations
def __snake_case ( UpperCamelCase = 4 ) -> list[list[int]]:
"""simple docstring"""
a__ = abs(UpperCamelCase ) or 4
return [[1 + x + y * row_size for x in range(UpperCamelCase )] for y in range(UpperCamelCa... | 158 | 1 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization impor... | 261 | from timeit import timeit
def SCREAMING_SNAKE_CASE_ ( snake_case__ ) -> int:
if number < 0:
raise ValueError('''the value of input must not be negative''' )
lowerCAmelCase = 0
while number:
number &= number - 1
result ... | 312 | 0 |
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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEA... | 710 |
from typing import List
import numpy as np
def _A ( __snake_case :dict ) -> int:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {key: len(__snake_case ) for key, value in gen_kwargs.items() if isinstance(__snake_case , __snake_case ... | 214 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_visio... | 482 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A : List[str] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for... | 602 | 0 |
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,
)
lowerCamelCase_ = {
'''configuration_clip''': [
'''CLIP_P... | 161 |
from itertools import count
def UpperCamelCase( lowercase_ = 50 ) -> int:
'''simple docstring'''
snake_case_ = [1] * min_block_length
for n in count(lowercase_ ):
fill_count_functions.append(1 )
for block_length in range(lowercase_ , n + 1 ... | 161 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__lowerCamelCase : Tuple = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqCo... | 653 |
'''simple docstring'''
from collections import deque
from .hash_table import HashTable
class A_ (a_ ):
"""simple docstring"""
def __init__( self :List[str] , *lowerCAmelCase__ :Optional[Any] , **lowerCAmelCase__ ... | 653 | 1 |
from math import asin, atan, cos, radians, sin, sqrt, tan
_lowerCamelCase = 6378137.0
_lowerCamelCase = 6356752.314245
_lowerCamelCase = 6378137
def _lowerCAmelCase ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float , __l... | 709 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 447 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class A_ :
lowerCAmelCase__ = 42
lowerCAmelCase__ = None
lowerCAmelCase__ = None
_lowerCAmelCase : List[str] ... | 46 |
from __future__ import annotations
def lowerCAmelCase__( lowercase : list[int] , lowercase : int ) -> int:
if len(lowercase ) < k or k < 0:
raise ValueError("Invalid Input" )
__snake_case : Tuple = sum(array[:k] )
for i in rang... | 243 | 0 |
'''simple docstring'''
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from tr... | 716 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
snake_case_ : List[Any] = 0.00
snake_case_ : int = 0
for resistor in resistors:
if resistor <= 0:
sna... | 92 | 0 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if... | 328 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/faceboo... | 675 | 0 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
a_ = '\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Saurav Kadava... | 665 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'configuration_deberta': ['DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', ... | 665 | 1 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_swi... | 108 | """simple docstring"""
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
__magic_name__ = logging.get_logger(__name__)... | 232 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import TensorType, lo... | 702 | import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
A : str = logging.getLogger(__name__)
@dataclass
class lowerCamelCase (SCREAMING_SNAKE_CASE__ ):
"""simple doc... | 356 | 0 |
"""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 Decod... | 426 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def A... | 426 | 1 |
import sys
_lowerCamelCase : Optional[Any] = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"668966489504... | 196 |
def _UpperCAmelCase (UpperCamelCase_ : str ):
'''simple docstring'''
_lowerCAmelCase : List[str] = [int(UpperCamelCase_ ) for i in ip_va_address.split(""".""" ) if i.isdigit()]
return len(UpperCamelCase_ ) == 4 and all(0 <= int(UpperCamelCase_ )... | 196 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase__ : Dict ={
"configuration_mvp": ["MVP_PRETRAINED_CONFIG_ARCHIVE_MAP", "MvpConfig", "MvpOnnxConfig"],
"tokenization_mvp": ["... | 101 | """simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokeni... | 564 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ = {"configuration_yolos": ["YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP", "YolosConfig", "YolosOnnxConfig"]}
try:
... | 490 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( a_ : str ):
__a = ''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def SCREAMING_SNAKE_CASE ( a_ : str ):
__... | 490 | 1 |
def snake_case (UpperCAmelCase__ ) -> List[str]:
if len(__snake_case ) <= 1:
return lst
UpperCamelCase_: Union[str, Any] = 1
while i < len(__snake_case ):
if lst[i - 1] <= lst[i]:
i += 1
else:
UpperCamelCase_: Tupl... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 0 |
def _UpperCamelCase ( lowercase__ = 10 , lowercase__ = 22 ):
__SCREAMING_SNAKE_CASE : Optional[int] = range(1 , lowercase__ )
__SCREAMING_SNAKE_CASE : int = range(1 , lowercase__ )
return sum(
1 for power in powers for base in bases if len(str(base**... | 717 |
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _lowercase ( A__ ):
'''simple docstring'''
def __init__( self :Optional[Any] , lowerCAmelCase__ :Union[str, Any] , ... | 260 | 0 |
def __A ( _A ):
"""simple docstring"""
if not isinstance(_A , _A ):
raise ValueError("Input series is not valid, valid series - [2, 4, 6]" )
if len(_A ) == 0:
raise ValueError("Input list must be a non empty list" )
if len(_A ) == 1:
return Tr... | 197 | from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Any = """T5Config"""
class A_ ( a... | 197 | 1 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 720 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase : List[str] ={"""configuration_xglm""": ["""XG... | 412 | 0 |
from __future__ import annotations
from typing import Generic, TypeVar
_lowerCAmelCase = TypeVar("""T""")
class _UpperCAmelCase ( Generic[T] ):
def __init__( self , a__ ):
A_ : Tuple = data
A_ : List[str] = self
A... | 569 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
fro... | 421 | 0 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLik... | 203 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
_snake_case : int = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.self",
"self.proj": "output.d... | 203 | 1 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
_UpperCAmelCase : Tuple = '''examples/'''
_UpperCAmelCase : Union[str, Any] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''':... | 72 |
import argparse
import os
import re
SCREAMING_SNAKE_CASE__ : Any = """src/transformers/models/auto"""
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
SCREAMING_SNAKE_CASE__ : Union[str, Any] ... | 112 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.toke... | 432 |
'''simple docstring'''
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from... | 432 | 1 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester... | 226 |
def __lowerCAmelCase ( __magic_name__ = 1_0_0 ):
_lowercase: Dict = set()
_lowercase: List[Any] = 0
_lowercase: List[Any] = n + 1 # maximum limit
for a in range(2 , __magic_name__ ):
for b in range(2 , __magic_name__ ):
_lowercas... | 226 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {}
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
_A : Tuple = """llama"... | 48 |
"""simple docstring"""
from copy import deepcopy
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ = None , lowercase__ = None ):
if arr is None and size is not None:
snake_case_ : str = size
... | 48 | 1 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def snake_case (UpperCAmelCase__ ) -> Any:
UpperCamelCase_: Optional[int] = args.pruning_method
UpperCamelCase_: Any ... | 57 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase : Any = {
"""tiny.en""": """https://openaipublic.azureedge.net/main/whisper/models/d3d... | 336 | 0 |
'''simple docstring'''
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
B... | 709 |
'''simple docstring'''
from __future__ import annotations
def a ( UpperCamelCase_ : list[float] , UpperCamelCase_ : list[float] ) -> float:
snake_case__ =sorted(numsa + numsa )
snake_case__ , snake_case__ =divmod(len(UpperCamelCase_ ) , 2 )
... | 581 | 0 |
'''simple docstring'''
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
_a : Dict = 4
_a : Union[str, Any] = 3
class lowerca... | 447 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
def __lowerCAmelCase ( UpperCamelCase ) -> List[str]:
lowerCAmelCase__ ... | 678 | 0 |
'''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,
MobileViTVaForImage... | 9 |
'''simple docstring'''
from math import factorial
UpperCamelCase : dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def A__ ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeErro... | 9 | 1 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def A_ ( lowercase_ ) -> int:
... | 326 |
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 A_ ( lowercase_ , lowercase_ , lowercase_ , lowercase_ ) -> Dict:
# Initialis... | 326 | 1 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def SCREAMING_SNAKE_CASE ( snake_case_ : Optional[Any] , snake_case_ : List[str] , snake_case_ : Optional[int] = 10**-10 ):
... | 702 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
__l... | 25 | 0 |
from manim import *
class __snake_case ( snake_case__ ):
"""simple docstring"""
def UpperCAmelCase_ ( self : Any ) -> List[str]:
'''simple docstring'''
lowerCAmelCase_ : int = Rectangle(height=0.5 ,width=0.5 )
low... | 659 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_a = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"MobileBertConfig",... | 481 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_a... | 558 | """simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class _UpperCAmelC... | 558 | 1 |
import argparse
import copy
def _A ( _lowercase ) -> List[str]:
"""simple docstring"""
__UpperCamelCase = {}
with open(_lowercase ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
__UpperCamelCas... | 1 |
'''simple docstring'''
from __future__ import annotations
lowerCamelCase : List[str] = []
def _SCREAMING_SNAKE_CASE (A , A , A ) -> bool:
"""simple docstring"""
for i in range(len(A ) ):
if board[row][i] == 1:
retu... | 460 | 0 |
"""simple docstring"""
a :Union[str, Any] = {
"a": "AAAAA",
"b": "AAAAB",
"c": "AAABA",
"d": "AAABB",
"e": "AABAA",
"f": "AABAB",
"g": "AABBA",
"h": "AABBB",
"i": "ABAAA",
"j": "BBBAA",
"k": "ABAAB",
"l": "ABABA",
"m": "ABABB",
"n": "ABBAA",
"o": "A... | 12 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
... | 528 | """simple docstring"""
def _lowerCamelCase( a ):
return " ".join(
"".join(word[::-1] ) if len(a ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words("""Hey wollef sroirraw"""))
| 528 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''asapp/sew-tiny-100k''': '''https://huggingface.co/asapp/sew-tiny-100k/resolve/ma... | 709 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def lowe... | 251 | 0 |
import torch
from transformers import AutoModel
class lowercase ( torch.nn.Module ):
def __init__( self , snake_case="sayef/fsner-bert-base-uncased" ):
super(__UpperCamelCase , self ).__init__()
snake_case_ = AutoModel.from_pretrained(__... | 362 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer... | 367 | 0 |
'''simple docstring'''
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
UpperCamelCase : Optional[Any] = 'src/diffusers'
# Matches is_xxx_available()
UpperCamelCase ... | 710 |
'''simple docstring'''
UpperCamelCase : Tuple = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def A__ ( __lowerCAmelCase : int ):
lowerCamelCase__ = 0
while number:
# Increased Speed Slightly by checking every 5 digits... | 9 | 0 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( lowercase__ , lowercase__ ):
if b == 0:
return (1, 0)
((UpperCAmelCase__) , (UpperCAmelCase__)) : Optional[Any] = extended_euclid(lowercase__ , a % b )
UpperCAmel... | 199 |
'''simple docstring'''
import operator as op
def snake_case_ ( lowercase__ ):
UpperCAmelCase__ : Optional[Any] = []
UpperCAmelCase__ : Any = lambda lowercase__ , lowercase__ : int(x / y ) # noqa: E731 integer division operation
Upp... | 199 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ =logging.get_logger(__name__)
lowercase__ ={
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json'
),
... | 702 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
'tokenization_ctrl': ['CTRLTokenizer'],
}
try:
if not is_torch_ava... | 326 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : Sequence[float] , _UpperCAmelCase : float ):
return sum(c * (x**i) for i, c in enumerate(_UpperCAmelCase ) )
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : Sequence[flo... | 4 |
'''simple docstring'''
from math import factorial
def __lowerCamelCase ( A__ , A__ , A__ ) -> float:
"""simple docstring"""
if successes > trials:
raise ValueError('successes must be lower or equal to trials' )
if ... | 430 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A = {"""configuration_plbart""": ["""PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PLBartConfig""... | 721 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
"""microsoft/xprophetnet-large-wiki100-cased""": (
"""https://huggingface.co/microsoft/xprophetnet-large-wiki100... | 147 | 0 |
"""simple docstring"""
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 7 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'facebook/wav2vec2-base-960h': 'https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/config.json',
# See ... | 30 | 0 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassification,
AutoTok... | 356 | from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class lowerCamelCase (yaml.SafeLoader ):
"""simple docstring"""
def __A ( self : str , __magic_name__ : str ) -> str:
SCREAMING_SNAKE_CASE_ = ... | 356 | 1 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTr... | 34 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def __snake_case ( _lowercase ):
"""simple docstring"""
if "cls_token" in name:
UpperCamelCas... | 34 | 1 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE ( ):
lowercase = HfArgumentParser(lowercase_ )
lowercase = parser.parse_args_into_dataclasses()[0]
lowe... | 715 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 653 | 0 |
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowerCamelCase__ ( __A :str ,__A :str ,__A :Optional[str] = None ):
"""simple docstring"""
if version.parse(hfh.__version__ ... | 268 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging... | 268 | 1 |
import re
def A ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
UpperCAmelCase_ = re.compile(
r'''^(?:0|94|\+94|0{2}94)''' r'''7(0|1|2|4|5|6|7|8)''' r'''(-| |)''' r'''\d{7}$''' )
return bool(re.search(__UpperCAmelCase , __UpperCAmelCase... | 716 |
def A ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
return x if y == 0 else greatest_common_divisor(__UpperCAmelCase , x % y )
def A ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docs... | 561 | 0 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
A_: List[Any] = logging.get_logger(__name__)
class _lowercase ( _UpperCAmelCase ):
"""simple docstring"""
def __init__( self , *UpperCAmelCase , **UpperCAmelCase... | 398 | # using dfs for finding eulerian path traversal
def __lowerCAmelCase ( _A ,_A ,_A ,_A=None ):
"""simple docstring"""
_lowercase = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
_lowercase , _... | 398 | 1 |
def A__ ( __A ):
'''simple docstring'''
if not all(x.isalpha() for x in string ):
raise ValueError("""String must only contain alphabetic characters.""" )
_lowerCamelCase : str = sorted(string.lower() )
return len(__A ) == len(set(__A ) )
if _... | 15 | import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformer... | 15 | 1 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import req... | 105 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(">=", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed.checkpoint.default_plan... | 393 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( __lowerCAmelCase = 200 ) -> int:
'''simple docstring'''
lowerCamelCase__ =[1, 2, 5, 10, 20, 50, 100, 200]
lowerCamelCase__ =[0] * (pence + 1)
lowerCamelCase__ =1 # base case: 1 way to make 0 pence
... | 717 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a =logging.get_logger(__name__)
class __UpperCAmelCase ( __lowerCAmelCase ):
def __init__( self , *_lowerCamelCase , **_lowerCamelCase ):
... | 132 | 0 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_... | 210 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from u... | 447 | 0 |
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ ) -> list:
_lowercase : List[str] = len(lowerCamelCase_ )
_lowercase : List[Any] = [[0] * n for i in range(lowerCamelCase_ )]
for i in range(lowerCamelCase_ ):
_l... | 354 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from ..test_modeling_... | 354 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
... | 75 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTeste... | 455 | 0 |
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase : int = get_tests_dir('''fixtures/spiece.model''')... | 703 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def lowercase ( __A : Optional[Any] ) -> Optional[Any]:
'''simple ... | 315 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.