code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. 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
... | 12 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 12 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_com... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
SCREAMING_SNAKE_CASE__ : Optional[Any] = len(__lowerCAmelCase ) + 1
SCREAMING_SNAKE_CASE__ : int = len(__lowerCAmelCase ) + 1
# dp is a 2d mat... | 12 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import Fla... | 12 |
"""simple docstring"""
from math import sqrt
def _lowercase ( __lowerCAmelCase ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all mu... | 12 | 1 |
"""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, loggin... | 12 |
"""simple docstring"""
class __a :
'''simple docstring'''
def __init__( self , _a , _a , _a ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ : Any = name
SCREAMING_SNAKE_CASE__ : Optional[Any] = ... | 12 | 1 |
"""simple docstring"""
import numpy as np
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase = 1E-12 , __lowerCAmelCase = 100 , ) -> tuple[float, np.ndarray]:
assert np.shape(__lowerCAmelCase )[0] == np.shape(__lowerCAmelCase )[1]
... | 12 |
"""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, loggin... | 12 | 1 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotA... | 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"""
def _lowercase ( __lowerCAmelCase = 50 ) -> int:
SCREAMING_SNAKE_CASE__ : Tuple = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
... | 12 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __a (UpperCamelCase_):
'''simple docstring'''
def _a ( self , _a ) -> Union[str, Any]:
"""simple docstring"""
... | 12 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
a :List[str] = logging.get_logger(__name__)
class __a (UpperCamelCase_):
'''simple docstring'''
def __init__( self , *_a , **_a ) -> No... | 12 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 12 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase_)
class __a (UpperCamelCase_):
'''simple docstring'''
_SCREAMI... | 12 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowercase ( __lowerCAmelCase ) -> bool:
return len(set(__lowerCAmelCase ) ) == len(__lowerCAmelCase )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE__ : List[Any] = 1
SCREAMING_SNAKE_CASE__ : int = 1
while repunit:
SCREAMING_SNA... | 12 | 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... | 12 |
"""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,
AutoModelForSequence... | 12 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a :str = logging.get_logger(__name__)
a :Dict = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class __a (UpperCamelCase_):
'''simple docstring'''
_S... | 12 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - ge... | 12 | 1 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE__ : List[Any] = 1
SCREAMING_SNAKE_CASE__ : int = 1
while repunit:
SCREAMING_SNA... | 12 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __a (UpperCamelCase_):
'''simple docstring'''
_SCREAMING_SNAKE_CASE :Tuple = (DDPMScheduler,)
def _a ( self , **_a ) -> ... | 12 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a :Dict = logging.get_logger(__name__)
a ... | 12 |
"""simple docstring"""
import os
a :List[str] = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1_000}
def _lowercase ( __lowerCAmelCase ) -> int:
SCREAMING_SNAKE_CASE__ : Any = 0
SCREAMING_SNAKE_CASE__ : Dict = 0
while in... | 12 | 1 |
"""simple docstring"""
from manim import *
class __a (UpperCamelCase_):
'''simple docstring'''
def _a ( self ) -> Any:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ : Any = Rectangle(height=0.5 , width=0.5 )
SCREA... | 12 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import T... | 12 | 1 |
"""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 transform... | 12 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a :List[Any] = logging.get_logger(__name__)
a :Optional[int] = {
"microsoft/focalnet-tiny":... | 12 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFeat... | 12 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.nu... | 12 | 1 |
"""simple docstring"""
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,
)
if is_sentencepiece_available():
from ..ta.token... | 12 |
"""simple docstring"""
a :List[str] = [
(1_000, "M"),
(900, "CM"),
(500, "D"),
(400, "CD"),
(100, "C"),
(90, "XC"),
(50, "L"),
(40, "XL"),
(10, "X"),
(9, "IX"),
(5, "V"),
(4, "IV"),
(1, "I"),
]
def _lowercase ( __lowerCAmelCase ) -> ... | 12 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a :Any = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_A... | 12 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a :Any = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_A... | 12 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transfor... | 12 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 12 | 1 |
"""simple docstring"""
from random import shuffle
import tensorflow as tf
from numpy import array
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> Union[str, Any]:
SCREAMING_SNAKE_CASE__ : int = int(__lowerCAmelCase )
assert noofclusters < le... | 12 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
a :Optional[Any] = logging.get_logger(__name__)
a :Union[str, Any] = {
"t5-small": "https://huggingface.co/t5-small/r... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import Counter
from random import random
class __a :
'''simple docstring'''
def __init__( self ) -> Optional[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ : int... | 12 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
a :Optional[Any] = [8, 5, 9, 7]
a :List[Any] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
a :int = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, 1, 0, 5... | 12 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
Diffusion... | 12 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 12 | 1 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'{price_plus_tax(100, 0.25) = }')
print(f'{price_plus_tax(125.50, 0.05) = }')
| 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
SCREAMING_SNAKE_CASE__ : Optional[Any] = len(__lowerCAmelCase ) + 1
SCREAMING_SNAKE_CASE__ : int = len(__lowerCAmelCase ) + 1
# dp is a 2d mat... | 12 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a :str = {
"configuration_chinese_clip": [
"CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"ChineseCLIPConfig",
"Chine... | 12 |
"""simple docstring"""
from math import sqrt
def _lowercase ( __lowerCAmelCase ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all mu... | 12 | 1 |
"""simple docstring"""
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
a :Optional[Any] = {
"tiny.en": "https://openaipublic.azureedge.net/main/whispe... | 12 |
"""simple docstring"""
class __a :
'''simple docstring'''
def __init__( self , _a , _a , _a ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ : Any = name
SCREAMING_SNAKE_CASE__ : Optional[Any] = ... | 12 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
a :int = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDepe... | 12 |
"""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, loggin... | 12 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a :int = logging.get_logger(__name__)
a :Union[str, Any] = {
"facebook/xmod-base": "https://hugg... | 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 numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , ) -> list[float]:
SCREAMING_SNAKE_CASE_... | 12 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __a (UpperCamelCase_):
'''simple docstring'''
def _a ( self , _a ) -> Union[str, Any]:
"""simple docstring"""
... | 12 | 1 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _lowercase ( ) -> None:
print("""Making key files...""" )
make_key_files("""rsa""" , 1024 ... | 12 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 12 | 1 |
"""simple docstring"""
def _lowercase ( ) -> Dict:
SCREAMING_SNAKE_CASE__ : List[Any] = 0
for i in range(1 , 1001 ):
total += i**i
return str(__lowerCAmelCase )[-10:]
if __name__ == "__main__":
print(solution())
| 12 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 12 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a :Optional[int] = logging.get_logger(__name__)
class __a (UpperCamelCase_):
'''simple docstring'''
def __init__( self , *_a , **_a ) -> ... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE__ : List[Any] = 1
SCREAMING_SNAKE_CASE__ : int = 1
while repunit:
SCREAMING_SNA... | 12 | 1 |
"""simple docstring"""
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common imp... | 12 |
"""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,
AutoModelForSequence... | 12 | 1 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
return abs(__lowerCAmelCase ) if a == 0 else greatest_common_divisor(b % a , __lowerCAmelCase )
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) ... | 12 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - ge... | 12 | 1 |
"""simple docstring"""
from math import sqrt
def _lowercase ( __lowerCAmelCase ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all mu... | 12 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __a (UpperCamelCase_):
'''simple docstring'''
_SCREAMING_SNAKE_CASE :Tuple = (DDPMScheduler,)
def _a ( self , **_a ) -> ... | 12 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> Tuple:
SCREAMING_SNAKE_CASE__ : ... | 12 |
"""simple docstring"""
import os
a :List[str] = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1_000}
def _lowercase ( __lowerCAmelCase ) -> int:
SCREAMING_SNAKE_CASE__ : Any = 0
SCREAMING_SNAKE_CASE__ : Dict = 0
while in... | 12 | 1 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't... | 12 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import T... | 12 | 1 |
"""simple docstring"""
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _lowerca... | 12 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a :List[Any] = logging.get_logger(__name__)
a :Optional[int] = {
"microsoft/focalnet-tiny":... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> List[Any]:
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(__lowerCAmelCase ):
print(F'''{i}\t\t{d}... | 12 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.nu... | 12 | 1 |
"""simple docstring"""
a :List[str] = [
(1_000, "M"),
(900, "CM"),
(500, "D"),
(400, "CD"),
(100, "C"),
(90, "XC"),
(50, "L"),
(40, "XL"),
(10, "X"),
(9, "IX"),
(5, "V"),
(4, "IV"),
(1, "I"),
]
def _lowercase ( __lowerCAmelCase ) -> ... | 12 |
"""simple docstring"""
a :List[str] = [
(1_000, "M"),
(900, "CM"),
(500, "D"),
(400, "CD"),
(100, "C"),
(90, "XC"),
(50, "L"),
(40, "XL"),
(10, "X"),
(9, "IX"),
(5, "V"),
(4, "IV"),
(1, "I"),
]
def _lowercase ( __lowerCAmelCase ) -> ... | 12 | 1 |
"""simple docstring"""
from math import factorial
a :dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def _lowercase ( __lowerCAmelCase ) -> int:
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError("""Paramete... | 12 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a :Any = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_A... | 12 | 1 |
"""simple docstring"""
a :Tuple = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0",
"huggingface-hub... | 12 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 12 | 1 |
"""simple docstring"""
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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
#
# Un... | 12 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
a :Optional[Any] = logging.get_logger(__name__)
a :Union[str, Any] = {
"t5-small": "https://huggingface.co/t5-small/r... | 12 | 1 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 12 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
a :Optional[Any] = [8, 5, 9, 7]
a :List[Any] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
a :int = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, 1, 0, 5... | 12 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a :Optional[Any] = logging.get_logger(__name__)
a :Optional[Any] = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class __a (UpperC... | 12 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 12 | 1 |
"""simple docstring"""
a :dict[tuple[int, int, int], int] = {}
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> int:
# if we are absent twice, or late 3 consecutive days,
# no further prize strings are possible
if late == 3 o... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
SCREAMING_SNAKE_CASE__ : Optional[Any] = len(__lowerCAmelCase ) + 1
SCREAMING_SNAKE_CASE__ : int = len(__lowerCAmelCase ) + 1
# dp is a 2d mat... | 12 | 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 import require_vision
from ... | 12 |
"""simple docstring"""
from math import sqrt
def _lowercase ( __lowerCAmelCase ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all mu... | 12 | 1 |
"""simple docstring"""
a :int = "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_version,
is_librosa_avail... | 12 |
"""simple docstring"""
class __a :
'''simple docstring'''
def __init__( self , _a , _a , _a ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ : Any = name
SCREAMING_SNAKE_CASE__ : Optional[Any] = ... | 12 | 1 |
"""simple docstring"""
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load_... | 12 |
"""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, loggin... | 12 | 1 |
"""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"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
a :Optional[int] = ""
a :Dict = ""
a :Optional[int] = ""
a :Tuple = 1 # (0 is vertical, 1 is horizontal)
def _lowercase ( ) -> None:
SCREAMING_SNA... | 12 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __a (UpperCamelCase_):
'''simple docstring'''
def _a ( self , _a ) -> Union[str, Any]:
"""simple docstring"""
... | 12 | 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,
AutoModelForSequence... | 12 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 12 | 1 |
"""simple docstring"""
import itertools
import string
from collections.abc import Generator, Iterable
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> Generator[tuple[str, ...], None, None]:
SCREAMING_SNAKE_CASE__ : str = iter(__lowerCAmelCase )
... | 12 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 12 | 1 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
a :Any = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n author={Yo... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE__ : List[Any] = 1
SCREAMING_SNAKE_CASE__ : int = 1
while repunit:
SCREAMING_SNA... | 12 | 1 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 12 |
"""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,
AutoModelForSequence... | 12 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
a :Tuple ... | 12 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - ge... | 12 | 1 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - ge... | 12 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __a (UpperCamelCase_):
'''simple docstring'''
_SCREAMING_SNAKE_CASE :Tuple = (DDPMScheduler,)
def _a ( self , **_a ) -> ... | 12 | 1 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 12 |
"""simple docstring"""
import os
a :List[str] = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1_000}
def _lowercase ( __lowerCAmelCase ) -> int:
SCREAMING_SNAKE_CASE__ : Any = 0
SCREAMING_SNAKE_CASE__ : Dict = 0
while in... | 12 | 1 |
"""simple docstring"""
import os
import sys
import unittest
a :str = 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_dummy_object, find... | 12 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import T... | 12 | 1 |
"""simple docstring"""
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
a :Dict = {
"n_samples": 64,
"horizon": 32,
"num_inference_steps": 20,
"n_guide_steps": 2, # can set to 0 for faster sampling, does not use value network
"scale_gr... | 12 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a :List[Any] = logging.get_logger(__name__)
a :Optional[int] = {
"microsoft/focalnet-tiny":... | 12 | 1 |
"""simple docstring"""
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> Dict:
# ... | 12 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.nu... | 12 | 1 |
"""simple docstring"""
import sys
a :Dict = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856... | 12 |
"""simple docstring"""
a :List[str] = [
(1_000, "M"),
(900, "CM"),
(500, "D"),
(400, "CD"),
(100, "C"),
(90, "XC"),
(50, "L"),
(40, "XL"),
(10, "X"),
(9, "IX"),
(5, "V"),
(4, "IV"),
(1, "I"),
]
def _lowercase ( __lowerCAmelCase ) -> ... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import TypedDict
class __a (UpperCamelCase_):
'''simple docstring'''
_SCREAMING_SNAKE_CASE :str
_SCREAMING_SNAKE_CASE :int
def _lowercase ( __lowerCAmelCase ) -> list[str]:
... | 12 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a :Any = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_A... | 12 | 1 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
a :str = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. and Blondel, M.... | 12 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 12 | 1 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_c... | 12 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
a :Optional[Any] = logging.get_logger(__name__)
a :Union[str, Any] = {
"t5-small": "https://huggingface.co/t5-small/r... | 12 | 1 |
"""simple docstring"""
import math
def _lowercase ( __lowerCAmelCase ) -> list[int]:
SCREAMING_SNAKE_CASE__ : Tuple = []
SCREAMING_SNAKE_CASE__ : List[str] = 2
SCREAMING_SNAKE_CASE__ : Union[str, Any] = int(math.sqrt(__lowerCAmel... | 12 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
a :Optional[Any] = [8, 5, 9, 7]
a :List[Any] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
a :int = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, 1, 0, 5... | 12 | 1 |
"""simple docstring"""
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
a :Union[str, Any] = datasets.utils.logging.get_logger(__name__)
class __a (folder_based_builder.FolderBasedBuilderConfig):
... | 12 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 12 | 1 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
SCREAMING_SNAKE_CASE__ : Optional[Any] = len(__lowerCAmelCase ) + 1
SCREAMING_SNAKE_CASE__ : int = len(__lowerCAmelCase ) + 1
# dp is a 2d mat... | 12 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTeste... | 12 |
"""simple docstring"""
from math import sqrt
def _lowercase ( __lowerCAmelCase ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all mu... | 12 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerat... | 12 |
"""simple docstring"""
class __a :
'''simple docstring'''
def __init__( self , _a , _a , _a ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ : Any = name
SCREAMING_SNAKE_CASE__ : Optional[Any] = ... | 12 | 1 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , ... | 12 |
"""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, loggin... | 12 | 1 |
"""simple docstring"""
import argparse
import os
import re
a :Union[str, Any] = "src/diffusers"
# Pattern that looks at the indentation in a line.
a :int = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
a :Tuple = re.compile(r"^\s*\"([^\"]+)\":")
# Pattern... | 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"""
# flake8: noqa
# Lint as: python3
a :Optional[int] = [
"VerificationMode",
"Version",
"disable_progress_bar",
"enable_progress_bar",
"is_progress_bar_enabled",
"experimental",
]
from .info_utils import VerificationMode
from .logging import disable_progress_bar,... | 12 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __a (UpperCamelCase_):
'''simple docstring'''
def _a ( self , _a ) -> Union[str, Any]:
"""simple docstring"""
... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowercase ( __lowerCAmelCase ) -> float:
if not nums:
raise ValueError("""List is empty""" )
return sum(__lowerCAmelCase ) / len(__lowerCAmelCase )
if __name__ == "__main__":
impor... | 12 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 12 | 1 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> int:
if not numbers:
return 0
if not isinstance(__lowerCAmelCase , (list, tuple) ) or not all(
isinstance(__lowerCAmelCase , __lowerCAmelCase ) for number in numbers ):... | 12 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 12 | 1 |
"""simple docstring"""
import cmath
import math
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> complex:
SCREAMING_SNAKE_CASE__ : Optional[int] = math.radians(__lowerCAmelCase )
SCREAMING_SNAKE_... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE__ : List[Any] = 1
SCREAMING_SNAKE_CASE__ : int = 1
while repunit:
SCREAMING_SNA... | 12 | 1 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow ha... | 12 |
"""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,
AutoModelForSequence... | 12 | 1 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> float:
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
SCREAMING_SNAKE_CASE__ : Optional[int] = sum(__lowerCAmelCase ) / len(__lowerCAm... | 12 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - ge... | 12 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
a :Optional[Any] = {
"google/tapas-base-finetuned-sqa": (
"https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"
),
"google/tapas-base-finetuned-wtq": (
"https://huggingface.co/... | 12 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __a (UpperCamelCase_):
'''simple docstring'''
_SCREAMING_SNAKE_CASE :Tuple = (DDPMScheduler,)
def _a ( self , **_a ) -> ... | 12 | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __a (UpperCamelCase_):
'''simple docstring'''
_SCREAMING_SNAKE_CASE :Union[str, Any] = ["""image_processor""", """tokenizer"""]
_SCREAMING_SNAK... | 12 |
"""simple docstring"""
import os
a :List[str] = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1_000}
def _lowercase ( __lowerCAmelCase ) -> int:
SCREAMING_SNAKE_CASE__ : Any = 0
SCREAMING_SNAKE_CASE__ : Dict = 0
while in... | 12 | 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
if is_torch_avai... | 12 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import T... | 12 | 1 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests
... | 12 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a :List[Any] = logging.get_logger(__name__)
a :Optional[int] = {
"microsoft/focalnet-tiny":... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
a :Dict = 0
a :Any = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, ... | 12 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.nu... | 12 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def _lowercase ( __lowerCAmelCase ) -> Any:
# encoder.embeddings a... | 12 |
"""simple docstring"""
a :List[str] = [
(1_000, "M"),
(900, "CM"),
(500, "D"),
(400, "CD"),
(100, "C"),
(90, "XC"),
(50, "L"),
(40, "XL"),
(10, "X"),
(9, "IX"),
(5, "V"),
(4, "IV"),
(1, "I"),
]
def _lowercase ( __lowerCAmelCase ) -> ... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase = None ) -> list[list[str]]:
SCREAMING_SNAKE_CASE__ : List[str] = word_bank or []
# create a table
SCREAMING_SNAKE_CASE__ : int ... | 12 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a :Any = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_A... | 12 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase_)
class __a (UpperCamelCase_):
'''simple docstring'''
# `task` is not a Clas... | 12 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 12 | 1 |
"""simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> Optional[Any]:
SCREAMING_SNAKE_CA... | 12 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
a :Optional[Any] = logging.get_logger(__name__)
a :Union[str, Any] = {
"t5-small": "https://huggingface.co/t5-small/r... | 12 | 1 |
"""simple docstring"""
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone impor... | 12 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
a :Optional[Any] = [8, 5, 9, 7]
a :List[Any] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
a :int = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, 1, 0, 5... | 12 | 1 |
"""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 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 12 | 1 |
"""simple docstring"""
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a :Dict = logging.get_logger(__name__)
a :str = {
"huggingface/autoformer-tourism-monthly": "https://huggingface.co/huggingface/autoformer-tourism-monthly/r... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
SCREAMING_SNAKE_CASE__ : Optional[Any] = len(__lowerCAmelCase ) + 1
SCREAMING_SNAKE_CASE__ : int = len(__lowerCAmelCase ) + 1
# dp is a 2d mat... | 12 | 1 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_toke... | 12 |
"""simple docstring"""
from math import sqrt
def _lowercase ( __lowerCAmelCase ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all mu... | 12 | 1 |
"""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, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_imag... | 12 |
"""simple docstring"""
class __a :
'''simple docstring'''
def __init__( self , _a , _a , _a ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ : Any = name
SCREAMING_SNAKE_CASE__ : Optional[Any] = ... | 12 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
a :Optional[Any] = logging.get_logger(__name__)
a :Union[str, Any] = {
"t5-small": "https://huggingface.co/t5-small/r... | 12 |
"""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, loggin... | 12 | 1 |
"""simple docstring"""
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def _lowercase ( __lowerCAmelCase... | 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"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class __a ... | 12 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __a (UpperCamelCase_):
'''simple docstring'''
def _a ( self , _a ) -> Union[str, Any]:
"""simple docstring"""
... | 12 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 12 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 12 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fro... | 12 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 12 | 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 import require_vision
from ... | 12 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE__ : List[Any] = 1
SCREAMING_SNAKE_CASE__ : int = 1
while repunit:
SCREAMING_SNA... | 12 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...t... | 12 |
"""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,
AutoModelForSequence... | 12 | 1 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
a :Union[str, Any] = l... | 700 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - ge... | 12 | 0 |
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