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 logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def a_ ( __lowercase : Union[dict, list, tuple, torch.Tensor] ) -> List[T... | 686 |
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformers import AutoTok... | 686 | 1 |
"""simple docstring"""
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _a ( lowercase_ ):
'''simple docstring'''
UpperCamelCase__ = (EulerDiscreteScheduler... | 706 |
"""simple docstring"""
def A( snake_case_ , snake_case_ ):
"""simple docstring"""
return "\n".join(
F"""{number} * {i} = {number * i}""" for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_table(number=5, number_o... | 120 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Optional[int] = {
'configuration_nllb_moe': [
'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
'NllbMoeConfig',
]
}
try:
if not is_torch_ava... | 556 | 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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_forma... | 486 | 0 |
'''simple docstring'''
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():
impo... | 312 |
'''simple docstring'''
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> Optional[Any]:
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
UpperCAmelCase__ : Optional[Any] = (boundary[1] - boundary[0]) / steps
UpperCAmelCase__ ... | 312 | 1 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ):
"""simple docstring"""
UpperCAmelCase = {
"en": "Machine learning is great, isn't it?",
"ru": "Машинно... | 333 |
import os
def __UpperCamelCase ( ):
"""simple docstring"""
with open(os.path.dirname(_lowerCAmelCase ) + "/grid.txt" ) as f:
UpperCAmelCase = [] # noqa: E741
for _ in range(20 ):
l.append([int(_lowerCAmelCase ) for x in f.readline().split()] )
... | 333 | 1 |
import random
from .binary_exp_mod import bin_exp_mod
def snake_case_ ( _lowerCAmelCase : Any , _lowerCAmelCase : Dict=1000 ) -> Any:
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is o... | 702 |
'''simple docstring'''
from __future__ import annotations
import time
import numpy as np
UpperCamelCase__: Tuple = [8, 5, 9, 7]
UpperCamelCase__: int = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
Uppe... | 528 | 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 : Any = 4
_A : Tuple = 3
class _l... | 427 | '''simple docstring'''
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class _lowercase ( UpperCAmelCase__ ):
'... | 427 | 1 |
import os
import pytest
from attr import dataclass
UpperCAmelCase__ :List[str] = """us-east-1""" # defaults region
@dataclass
class SCREAMING_SNAKE_CASE :
snake_case__ : str
snake_case__ : Optional[Any] = 'arn:aws:iam::558105141721:role/sagemaker_exec... | 719 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ :Optional[int] = logging.get_logger(__name__)
UpperCAmelCase__ :List[Any] = {
"""asapp/sew-d-tiny-100k""": """https://... | 483 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import Seque... | 63 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 492 | 0 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
fro... | 713 | '''simple docstring'''
import itertools
import math
def UpperCamelCase__ ( _lowercase : int ) -> 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 multiples of 3 ... | 466 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from .... | 19 |
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_swit... | 188 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ = {
'''configuration_efficientnet''': [
'''EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''EfficientNetCo... | 717 | import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def __lowerCAmelCase ( A_ : int ) -> Optional[Any]:
_... | 286 | 0 |
"""simple docstring"""
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOC... | 83 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( UpperCAmelCase__ ):
"""simple docstring"""
if len(UpperCAmelCase__ ) == 0:
return array
_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = min(UpperCAmelCase__ ), max(UpperCAmelCase__ ... | 605 | 0 |
"""simple docstring"""
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def UpperCAmelCase__ (snake_case__ : Any ):
"""simple docstring"""
_snake_case : Dict = {}
_snake_case : Union[str, Any... | 28 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list[int] , snake_case__ : str ):
"""simple docstring"""
_snake_case : str = int(snake_case__ )
# Initialize Result
_snake_case : str = []
# Traverse through ... | 28 | 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 OptionalDependencyN... | 610 |
"""simple docstring"""
import math
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
lowerCAmelCase_ : Any = f'''Input value of [number={number}] must be an integer'''
... | 610 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( __magic_name__ : int ) -> int:
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError('''only integers accepted as input''' )
else:
lowercase : Optional[int] =str(abs... | 708 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCAmelCase ( ) -> List[Any]:
lowercase : Tuple =HfArgumentParser(__magic_name__ )
lowercase : Union[str, Any] =parser.... | 88 | 0 |
"""simple docstring"""
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
SCREAMING_SNAKE_CASE_ = yaml.safe_load(
'''\
name: \"\"
allow_empty: false
allow_empty_... | 373 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = {
"""google/bigbird-roberta-base"... | 67 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCAmelCase : Tuple = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AutoformerConfig',
... | 164 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__lowerCAmelCase : List[str] = logging.get_logger(__name__)
_... | 164 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_SCREAMING_SNAKE_CASE = {
'''configuration_bigbird_pegasus''': [
'''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BigBirdPegasu... | 163 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ : Tuple = {'''configuration_plbart''': ['''PLBART_PRETRAINED_CONF... | 280 | 0 |
from collections.abc import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> float:
lowerCAmelCase__ : float = a
lowerCAmelCase__ : float = b
if function(SCREAMING_SNAKE_CASE_ ) == 0: # one of... | 69 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( __magic_name__ ):
... | 69 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import TypedDict
class UpperCamelCase ( __SCREAMING_SNAKE_CASE ):
A__ = 42
A__ = 42
def _lowerCAmelCase ( lowerCamelCase__ : str ) -> list[str]:
if not isinstance(lower... | 572 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _lowerCAmelCase ( lowerCamelCase__ : Optional[int], lowerCamelCase__ : int=... | 572 | 1 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers.models.be... | 720 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_to... | 582 | 0 |
'''simple docstring'''
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_M... | 444 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowercase__ ( snake_case__ ):
@staticmethod
@abstractmethod
def UpperCAmelCase__ ( snake_case__ : ArgumentParser ):
raise NotImplementedError()
@abstractm... | 153 | 0 |
import functools
def lowerCAmelCase ( UpperCamelCase__ : str , UpperCamelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase = len(UpperCamelCase__ )
__UpperCAmelCase = len(UpperCamelCase__ )
@functools.cache
def min_distance(U... | 718 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
class A ( UpperCAmelCase ):
a_ = '''bert-generation'''
def __init__( self : str , __a : str=5_0_3_5_8 , __a : int=1_0_2_4 , __a ... | 654 | 0 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
__lowerCAmelCase : Optional[int] =logging.get_logger(__name__)
def UpperCAmelCase__ ( ... | 359 | """simple docstring"""
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, s... | 359 | 1 |
'''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__UpperCamelCase : List[Any] = '''\
@misc{wu2016googles,
title={Google\'s Neural Machine Translation System: Bridging ... | 719 |
'''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/lic... | 270 | 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
... | 657 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {
'''configuration_electra''': ['''ELECTRA_PRETRAINE... | 657 | 1 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class __magic_name__ ( nn.Module ):
UpperCamelCase__ = 42
UpperCamelCase__ = 42
UpperCamelCase__ = 0.0... | 705 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : Any = {
'''configuration_blenderbot_small''': [
... | 145 | 0 |
"""simple docstring"""
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def lowercase__ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str , **lowerCAmelCase__ : Optional[int] ) -> Union[str, Any]:
'''simple docstri... | 642 | '''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
_UpperCamelCase : Any = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Tran... | 396 | 0 |
"""simple docstring"""
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 lowercase ... | 706 |
"""simple docstring"""
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
a = logging.get_logger(__name__)
def lowercase (snake_case__ : s... | 529 | 0 |
from __future__ import annotations
def __a ( A__ : Optional[int] , A__ : int ):
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = set(A_ ), [start]
while stack:
SCREAMING_SNAKE_CASE = stack.pop()
explored.add(A_ )
... | 16 |
from __future__ import annotations
def a__ ( A_, A_ ):
'''simple docstring'''
if b == 0:
return (1, 0)
((__magic_name__) , (__magic_name__)) = extended_euclid(A_, a % b )
__magic_name__ = a // b
return (y, x - k * y)
def a__ ( ... | 529 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=SCREAMING_SNAKE_CASE__ ):
lowerCAmelCase__ : Union[str, Any] = ["sentencepiece"]
def __init__( self : List[Any] , *lowerCamelC... | 721 |
'''simple docstring'''
from __future__ import annotations
from math import pi
def _lowerCamelCase (__lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float ) -> dict[str, float]:
if (inductance, frequency, reactance).co... | 289 | 0 |
'''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 __snake_case ( ... | 38 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class SCREAMING_SNAKE_CASE__ :
lowercase__ = 42
lowercase__ = None
lowercase__ = None
UpperCAmelCase : Dict =... | 567 | 0 |
'''simple docstring'''
def __lowercase (_lowercase ) -> int:
"""simple docstring"""
if not isinstance(_lowercase, _lowercase ):
raise TypeError("""only integers accepted as input""" )
else:
__lowerCamelCase : Any = str(abs(_lo... | 483 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def __lowercase () -> str:
"""simple docstring"""
__lowerCamelCase : Any = HfArgumentParser(_lowercase )
__lowerCamelCase : List[str]... | 483 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
__lowerCAmelCase : Any =list[list[float | int]]
def UpperCAmelCase__ ( lowerCAmelCase__ :Matrix , lowerCAmelCase__ :Matrix ) -> Matrix:
'''simple do... | 359 | """simple docstring"""
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _A ( lowerCAmelCase , unittest.TestCase ):
... | 359 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, ... | 720 |
'''simple docstring'''
from manim import *
class a__ ( a__ ):
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( self ) -> List[str]:
lowerCAmelCase__ = Rectangle(height=0.5 , width=... | 98 | 0 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INP... | 491 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import logging
... | 491 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
UpperCamelCase = r'''
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model outputs. Read the d... | 144 |
def _a ( lowerCamelCase__ ) -> float:
return 10 - x * x
def _a ( lowerCamelCase__ , lowerCamelCase__ ) -> float:
# Bolzano theory in order to find if there is a root between a and b
if equation(lowerCamelCase__ ) * equation(lowerCamelCase__ ... | 144 | 1 |
'''simple docstring'''
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def a__ ( _SCREAMING_SNAKE_CASE : int ) -> Dict:
"""simple docstring"""
def is_in_circle(_SCREAMING_SNAKE_CASE : ... | 71 |
"""simple docstring"""
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class lowercase ( lowercase__ ,unittest.TestCase ):
lowercase = DownBlockaD # noqa F40... | 535 | 0 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ..... | 720 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCase : Dict = logging.get_logger(__name__)
def UpperCamelCase_ ( __a , __a , ... | 151 | 0 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xl... | 256 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow... | 256 | 1 |
import qiskit
def lowercase_ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
snake_case__ : Optional[int] =qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
snake_case__ : ... | 408 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class _lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def UpperCA... | 408 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeriesTransformerCo... | 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_convbert import ConvBertTokenizer
lowercase__ :Optional[i... | 522 | 0 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
... | 715 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import... | 143 | 0 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
A: Union[str, Any] = logging.get_logger(__name__)
A: List[Any] ... | 160 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
snake_case__ : int = {
'configuration_audio_spectrogram_transformer': [
'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ASTCon... | 408 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
def get_matched_characters(lowercase_ : str , lowercase_ : str ) -> str:
lowercase = []
lowercase = min(len(_stra... | 706 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase_ : Union[str, An... | 653 | 0 |
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
lowercase_ = logging.get_logger(__name__)
def __lowerCAmelCase ( S... | 413 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from ... | 413 | 1 |
'''simple docstring'''
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
lowerCAmelCase = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
lowerCAmelCase = typing.Union[np.floataa, int, float] # noqa:... | 701 |
'''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/LICE... | 551 | 0 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
_a : Optional[Any] = datasets.utils.logging.get_logger(__name__)
class UpperCamelCase_ ( folder_based_builder.FolderBasedBuil... | 479 |
'''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 n... | 597 | 0 |
"""simple docstring"""
from functools import reduce
_A = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950... | 228 |
"""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 ... | 228 | 1 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
loggi... | 321 | def __lowercase ( _UpperCAmelCase , _UpperCAmelCase ) -> List[Any]:
'''simple docstring'''
__lowercase = (boundary[1] - boundary[0]) / steps
__lowercase = boundary[0]
__lowercase = boundary[1]
__lowercase = make_points(_UpperCAmelCase , _UpperCAmelCase ... | 321 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowerCamelCase_ = 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_copies # noqa: E402
# This is the ... | 717 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion import StableDiff... | 86 | 0 |
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 import BertTokenizer
__a = logging.get_logger(__name__)
__a ... | 30 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {'''vocab_file''': '''sen... | 167 | 0 |
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 FlaxGener... | 535 |
def SCREAMING_SNAKE_CASE__ ( snake_case__ :List[str] ) -> Dict:
_lowercase = len(snake_case__ )
while cur > 1:
# Find the maximum number in arr
_lowercase = arr.index(max(arr[0:cur] ) )
# Reverse from 0 to mi
_lowercase = a... | 535 | 1 |
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,
WavaVecaFeature... | 254 |
"""simple docstring"""
import warnings
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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAm... | 535 | 0 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import B... | 703 |
'''simple docstring'''
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 t... | 399 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowerCAmelCase : List[str] = logging.get_logger(__name__)
lowerCAmelCase : ... | 3 |
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def _snake_case (__lowercase , __lowercase , __lowercase):
#... | 23 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__SCREAMING_SNAKE_CASE = r'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to co... | 395 |
"""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.tok... | 395 | 1 |
def SCREAMING_SNAKE_CASE_ ( _snake_case :int ) -> list:
_A = int(_snake_case )
if n_element < 1:
_A = ValueError('''a should be a positive number''' )
raise my_error
_A = [1]
_A , _A , _A = (0, 0, 0)
_A ... | 2 |
'''simple docstring'''
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 imp... | 135 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def UpperCAmelCase__ ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ... | 710 |
"""simple docstring"""
def UpperCAmelCase__ ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase=False ):
"""simple docstring"""
if isinstance(_UpperCAmelCase , _UpperCAmelCase ) and isinstance(_UpperCAmelCase , _UpperCAmelCase ):
A_ :... | 302 | 0 |
"""simple docstring"""
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from tra... | 277 | """simple docstring"""
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
Be... | 277 | 1 |
'''simple docstring'''
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 t... | 399 |
'''simple docstring'''
from collections import deque
from .hash_table import HashTable
class A ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
def __init__(self , *_UpperCAmelCase , **_UpperCAmelCase ) -> List[str]:
su... | 399 | 1 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowercase__ ( lowercase_ ) -> List[str]:
"""simple docstring"""
if (
(cp >= 0X4e00... | 624 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('''hub/hopper-medium-v2/unet/hor32''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/unet/hor128''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/value_function''', exist_ok=True)
def A ( __UpperCamelCase ... | 9 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : int = logging.get_logger(__name__)
lowerCAmelCase_ : Optional[Any] = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/mai... | 716 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase_ : List[str] = {
'''configuration_layoutlmv2''': ['''L... | 156 | 0 |
"""simple docstring"""
def lowercase_ ( _snake_case = 10 ,_snake_case = 1_000 ,_snake_case = True ):
assert (
isinstance(UpperCAmelCase_ ,UpperCAmelCase_ )
and isinstance(UpperCAmelCase_ ,UpperCAmelCase_ )
and isinstance(UpperCAmelCase_ ,UpperCAmelCase_... | 223 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def __lowerCamelCase ( UpperCAmelCase_ : int = 8 ):
"""simple docstring"""
a :Optional[int] = ascii_letters + digits + punctuation
... | 445 | 0 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAG... | 469 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__magic_name__ =logging.get_logger(__name__)
__magic_name__ =... | 469 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : ... | 493 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _lowerCAmelCase ( lowerCamelCase__ : Optional[int], lowerCamelCase__ : int=... | 572 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0 ):
lowercase = length or len(lowerCAmelCase__ )
lowercase = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
lowercase , lowercase = list_data[i + ... | 721 |
class A_ :
def __init__( self : Optional[Any] , snake_case__ : Dict , snake_case__ : Union[str, Any] ):
lowercase = name
lowercase = val
def __str__( self : str ):
return F"""{self... | 72 | 0 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from tr... | 28 |
'''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
#
... | 48 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
"caidas/swin2sr-classicalsr-x2-64": (
"https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/c... | 621 |
"""simple docstring"""
class snake_case :
def __init__( self : Optional[int] , a__ : List[Any] , a__ : List[str] , a__ : Tuple ) -> Optional[Any]:
'''simple docstring'''
_A ... | 621 | 1 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
__lowerCAmelCase = logging.getLogger(__name__)
class _lowerCAmelCase ( __snake_case ):
'''sim... | 585 |
'''simple docstring'''
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
... | 585 | 1 |
"""simple docstring"""
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_SCREAMING_SNAKE_CAS... | 721 |
"""simple docstring"""
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_devi... | 239 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : List[str] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolv... | 36 |
import os
import pytest
from attr import dataclass
__lowercase : Optional[int] = '''us-east-1''' # defaults region
@dataclass
class _A :
'''simple docstring'''
__lowerCamelCase : str
__lowerCamelCase : Dict = '''arn:aws:iam::558105141721:role/sagemaker... | 36 | 1 |
'''simple docstring'''
def snake_case_ ( a__ : int ):
"""simple docstring"""
if upper_limit < 0:
raise ValueError("""Limit for the Catalan sequence must be ≥ 0""" )
__lowercase = [0] * (upper_limit + 1)
# Base case: C(0) = C(1)... | 163 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
fro... | 163 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/resolve/main/config... | 467 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_ = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeBertConfig',
'SqueezeBertOnnxConfig... | 562 | 0 |
UpperCamelCase_ = [
[0, 1_6, 1_3, 0, 0, 0],
[0, 0, 1_0, 1_2, 0, 0],
[0, 4, 0, 0, 1_4, 0],
[0, 0, 9, 0, 0, 2_0],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def _UpperCAmelCase ( UpperCamelCase: str , UpperCamelCase: Optional[Any] , UpperCamelCase: int , ... | 376 |
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCAmelCase ( UpperCamelCase: int = 2_0_0_0_0_0_0 ):
"""simple docstring"""
__lowerCAmelCase = [0]
__lowerCAmelCase = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ... | 376 | 1 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
def a_ ( __lowercase : ... | 686 |
import random
from .binary_exp_mod import bin_exp_mod
def a_ ( __lowercase : int , __lowercase : Any=1_000 ) -> int:
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
_snake_case = n - 1
_snake_case ... | 686 | 1 |
'''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_... | 631 |
'''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_vis... | 631 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCamelCase :List[str] = logging.get_logger(__name__)
lowerCamelCase :Tuple = {
'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
'https://huggingface.co/CarlCochet/trajectory-... | 487 |
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
... | 487 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils ... | 229 |
"""simple docstring"""
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_availa... | 229 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def UpperCAmelCase__ ( UpperCAmelCase_ : Sequence[float] , UpperCAmelCase_ : bool = False ) -> float:
if not arr:
return 0
__lowerCamelCase : str = 0 if all... | 13 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {
'configuration_deberta': ['DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Debe... | 665 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json',
# See all SEW... | 712 |
from __future__ import annotations
import requests
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Dict = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(__lowerCamelCase ).json()
def lowerCa... | 381 | 0 |
import itertools
import string
from collections.abc import Generator, Iterable
def __SCREAMING_SNAKE_CASE ( a__ : Iterable[str] ,a__ : int ) -> Generator[tuple[str, ...], None, None]:
__A : Union[str, Any] = iter(a__ )
while True:
__A : Union[str, Any] =... | 17 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import Au... | 568 | 0 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__:Dict = logging.get_logger(__name__... | 721 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__:List[str] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__:Tuple = {
"""google/bi... | 67 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
cl... | 39 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE ( lowerCAmelCase_ , unittest.TestCase ):
snak... | 150 | 0 |
'''simple docstring'''
A: Any = 8.314_462 # Unit - J mol-1 K-1
def _UpperCAmelCase ( a : float , a : float , a : float ) -> float:
"""simple docstring"""
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('Invalid inputs. E... | 7 |
'''simple docstring'''
import os
from distutils.util import strtobool
def _UpperCAmelCase ( a : Any , a : int ) -> Any:
"""simple docstring"""
for e in env_keys:
lowercase_ : Optional[Any] = int(os.environ.get(a , -1 ) ... | 7 | 1 |
import qiskit
def _lowerCAmelCase ( A__ , A__ ):
lowercase__ = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on the q register
lowercase__ = qiskit.QuantumCircuit(__lowercase , __lowercase )
# Apply X (NOT) Gate to Qubits 0 & 1
... | 622 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__SCREAMING_SNAKE_CASE = logging.get_log... | 357 | 0 |
"""simple docstring"""
from __future__ import annotations
class A__ :
def __init__( self , _SCREAMING_SNAKE_CASE = 0 ):
__lowerCAmelCase : List[str] = key
def __lowerCamelCase ( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
assert isinstance(_SCREA... | 549 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available(... | 549 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : list ) -> float:
'''simple docstring'''
UpperCAmelCase_ = 0
while len(snake_case_ ) > 1:
UpperCAmelCase_ = 0
# Consider two files with minimum cost to be merged
... | 78 | def __lowerCAmelCase ( A_ : int , A_ : int ) -> int:
return x if y == 0 else greatest_common_divisor(A_ , x % y )
def __lowerCAmelCase ( A_ : int , A_ : int ) -> int:
return (x * y) // greatest_common_divisor(A_ , A_ )
d... | 221 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__A : Dict = logging.... | 721 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__A : str = tuple[int, int]
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : int , lowercase__ : set[int] , lowercase... | 281 | 0 |
'''simple docstring'''
import re
def snake_case ( snake_case : str ) -> list:
"""simple docstring"""
return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]' , str_ )]
def snake_case ( snake_case : str ) -> str:
"""simple docstring"""
lowerC... | 284 |
'''simple docstring'''
import operator
def snake_case ( snake_case : list , snake_case : bool = False , snake_case : list | None = None ) -> list:
"""simple docstring"""
lowerCAmelCase = operator.lt if reverse else operator.gt
lowerCAmelCase =... | 284 | 1 |
"""simple docstring"""
def snake_case__ ( _lowerCamelCase, _lowerCamelCase ) ->int:
"""simple docstring"""
while a != 0:
__lowercase : List[Any] = b % a, a
return b
def snake_case__ ( _lowerCamelCase, _lowerCamelCase ) ->in... | 719 |
"""simple docstring"""
from collections import deque
def snake_case__ ( _lowerCamelCase ) ->Dict:
"""simple docstring"""
__lowercase : Any = len(_lowerCamelCase )
__lowercase : str = deque()
__lowercase : Tuple = ... | 281 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : List[Any] ={
'''configuration_table_transformer''': [
'''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TableTransformerConfig''',
... | 483 |
'''simple docstring'''
def __UpperCAmelCase ( _UpperCAmelCase : int = 1_00_00_00 ) -> int:
__snake_case = 1
__snake_case = 1
__snake_case = {1: 1}
for inputa in range(2 , _UpperCAmelCase ):
__snake_case = 0
__snake_case = inputa
... | 69 | 0 |
"""simple docstring"""
def __lowerCAmelCase ( lowercase : Union[str, Any] , lowercase : List[str] , lowercase : Tuple , lowercase : Dict ) -> Optional[Any]:
"""simple docstring"""
snake_case : List[str] = [... | 117 |
"""simple docstring"""
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("""3.8"""):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
__snake... | 117 | 1 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
_lowerCAmelCase : int = 1.0_5457_1817E-34 # unit of ℏ : J * s
_lowerCAmelCase : Union[str, Any] = 3E8 # unit of... | 242 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCAmelCase : Optional[int] = {
"configuration_layoutlmv3": [
... | 242 | 1 |
from collections import Counter
from timeit import timeit
def _SCREAMING_SNAKE_CASE ( snake_case = "" , ) -> bool:
return sum(c % 2 for c in Counter(input_str.replace(""" """ , """""" ).lower() ).values() ) < 2
def _SCREAMING_... | 710 |
import os
import string
import sys
a = 1 << 8
a = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 27,
"up": 65 + ARROW_KEY_FLAG,
"down": 66 + ARROW_KEY_FLAG,
"right": 67 + ARROW_KEY_FLAG,
"left": 68 + ARROW_KEY_FLAG,
"mod_int": 91,... | 175 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
a : List[str] = logging.get_logger(__na... | 63 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE : Optional[int] = {
"""... | 197 | 0 |
'''simple docstring'''
from math import factorial
class snake_case :
"""simple docstring"""
def __init__( self , UpperCamelCase , UpperCamelCase ):
"""simple docstring"""
lowerCamelCase_ = real
if isinstance(Upper... | 445 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...featur... | 445 | 1 |
"""simple docstring"""
from cva import destroyAllWindows, imread, imshow, waitKey
def _UpperCAmelCase ( __lowerCamelCase : int ) -> str:
# getting number of pixels in the image
_snake_case , _snake_case = img.shape[0], img.shape[1]
# converting each pixel's color to its nega... | 224 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedu... | 224 | 1 |
"""simple docstring"""
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 import BertTokenizer
UpperCAmelCase__ ... | 710 |
"""simple docstring"""
import random
def lowerCAmelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : float , UpperCamelCase__ : bool = False ):
"""simple docstring"""
__lowercase = {i: [] for i in range(UpperCamelCase__ )}
# if probability is g... | 442 | 0 |
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