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 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
fr... | 5 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
... | 5 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
A__ : Optional[int] = {'''configuration_deit''': ['''DEIT_PRETRAINED_CONFIG_ARCHIVE_M... | 714 |
'''simple docstring'''
import os
import sys
import unittest
A__ : int = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
g... | 124 | 0 |
"""simple docstring"""
from __future__ import annotations
def snake_case ( lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_ = None , lowerCAmelCase_ = False , ) -> tuple[int, float, str]:
_snake_case = cipher_alphabet or [chr(lowerC... | 103 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... | 256 | 0 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info... | 705 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowerCAmelCase__ ( UpperCAmelCase ):
"""simple docstring"""
snake_case__ : List[str] = year % 19
snake_case__ : Optional[Any] = ye... | 172 | 0 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : Tuple ,_UpperCAmelCase : Dict ,_UpperCAmelCase : Optional[Any] ,) -> int:
if (electron_conc, hole_conc, intrinsic_... | 694 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def _a (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCamelCase =[
'''encoder.version''',
'''decoder.ver... | 404 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a = {
"configuration_transfo_xl": ["TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP", "TransfoXLConfig"],
"tokenization_transfo_xl": ["TransfoXLCorpus", "TransfoXL... | 714 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"camembert-base": "https://huggingface.co/ca... | 13 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
lowercase__ : Optional[int] = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full BertForMaskedLM or R... | 8 |
def __UpperCamelCase ( lowerCAmelCase__ : str ):
if n_term == "":
return []
__a : list = []
for temp in range(int(lowerCAmelCase__ ) ):
series.append(f"1/{temp + 1}" if series else '''1''' )
return series
if __name__ == "__main__":
lowercase__ ... | 521 | 0 |
"""simple docstring"""
def lowerCamelCase ( _UpperCamelCase : str = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> Optional[Any]:
'''simple docstring'''
try:
__UpperCAmelCase : int = int(lowerCamelCase_ )
except (TypeError, ValueError):
rai... | 713 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normaliz... | 299 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import lo... | 8 |
UpperCAmelCase_ = 2_5_6
# Modulus to hash a string
UpperCAmelCase_ = 1_0_0_0_0_0_3
def SCREAMING_SNAKE_CASE_ ( _snake_case :str , _snake_case :str ) -> bool:
_A = len(_snake_case )
_A = len(_snake_case )
if p_len > t_len:
return Fa... | 2 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import... | 28 |
"""simple docstring"""
import os
import sys
import unittest
A_ = 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... | 28 | 1 |
"""simple docstring"""
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTest... | 115 |
'''simple docstring'''
a__ : Optional[int] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
a__ : List[Any] = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
a__ : Any = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'T... | 601 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
SCREAMING_SNAKE_CASE_ = r"""
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model o... | 711 |
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> float:
'''simple docstring'''
_validate_point(_SCREAMING_SNAKE_CASE )
_validate_point(_SCREAMING_SNAKE_CASE )
if len(_SCREAMING_SNAKE_CASE ) != len(_SCREAMING_SNAKE_CASE )... | 116 | 0 |
'''simple docstring'''
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
_UpperCamelCase : List[Any] = 'scheduler_config.json'
class _lowercase( _lowerCamelCase ):
... | 396 | '''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 | 1 |
import unittest
import numpy as np
from datasets import load_dataset
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 i... | 362 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
UpperCAmelCase__ = get_tests_dir("fixtures/test_sentencepiece_with_bytefallback.mod... | 362 | 1 |
"""simple docstring"""
import heapq
def snake_case_ ( A_ : dict ):
'''simple docstring'''
_lowerCamelCase : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the q... | 83 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class lowercase__ ( unittest.TestCase ):
def Up... | 339 | 0 |
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_UpperCAmelCase = _symbol_... | 713 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.hugging... | 371 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : Any = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : List[str] = {
"""facebook/timesformer""": """https://huggingface.co/facebook/timesformer/resolve/main/config.json""",
... | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import lo... | 310 | 0 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
a_ : Optional[int] = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''att... | 263 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .t... | 263 | 1 |
def UpperCamelCase_ ( __a ) -> str:
stooge(__a , 0 , len(__a ) - 1 )
return arr
def UpperCamelCase_ ( __a , __a , __a ) -> Optional[Any]:
if i >= h:
return
# If first element is smaller than the last then swap them
... | 37 |
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: Optional[int] = logging.get_logger(__name__)
__UpperCamelCase: Optio... | 266 | 0 |
def A__ ( __lowerCamelCase, __lowerCamelCase ):
SCREAMING_SNAKE_CASE_ = ''''''
for word_or_phrase in separated:
if not isinstance(__lowerCamelCase, __lowerCamelCase ):
raise Exception('''join() accepts only strings to be joined''' )
joined += word_or_phrase + separator
... | 597 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def A__ ( __lowerCamelCase = "laptop" ):
SCREAMING_SNAKE_CASE_ = F'''https://www.amazon.in/laptop/s?k={product}'''
SCREAMING_SNAKE_CASE_ = {
'''User-Agent''': '''Mozilla/5.0 (X11;... | 597 | 1 |
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing import PolynomialFeatures... | 140 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, requ... | 169 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : int ) -> List[Any]:
"""simple docstring"""
def is_in_circle(__magic_name__ : float , __m... | 590 |
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback, get_... | 590 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( lowercase : dict , lowercase : str ) ->set[str]:
"""simple docstring"""
lowercase__ , lowercase__ = set(lowercase ), [start]
w... | 161 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
... | 161 | 1 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : list[int] ):
'''simple docstring'''
if not numbers:
return 0
if not isinstance(__UpperCamelCase , (list, tuple) ) or not all(
isinstance(__UpperCamel... | 21 |
"""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_ava... | 21 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
... | 41 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase = logging.get_logger(__name__)
class A ( UpperCamelCase_ ):
def __init__( self : Optional[Any] , *lowercase_ : str , **lowercase_ : List[Any] ) ... | 464 | 0 |
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common i... | 458 |
def _UpperCAmelCase ( ):
"""simple docstring"""
__lowerCamelCase : Optional[int] = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
__lowerCamelCase : str = 6
__lowerCamelCase : Optional[int] ... | 458 | 1 |
"""simple docstring"""
from __future__ import annotations
lowerCAmelCase__ = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
lowerCAmelCase__ = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def snake_case_ ( A_ : list[float] )... | 83 |
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_... | 53 | 0 |
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase__ = False
lowerCAmelCase__ = True
lowerCAmelCase__ = False
if __name__ == "__main__":
lowerCAm... | 720 |
'''simple docstring'''
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ... | 471 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {
"""configuration_resnet""": ["""RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ResNet... | 235 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowercase_... | 235 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : Dict = {
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'tokenization_xlm': ['XLMTokeniz... | 608 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def lowerCAmelCa... | 608 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_avail... | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[Any] = logging.get_logger(__name__)
lowerCAmelCase_ : List[str] = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve... | 414 | 0 |
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
_SCREAMING_SNAKE_CASE ... | 711 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def __lowerCAmelCase ( ):
print("Making key files..." )
make_key_files("rsa" , 1_0_2_4 )
print("Key files generation successful." )
def ... | 206 | 0 |
'''simple docstring'''
import os
def __a ( ) -> Dict:
with open(os.path.dirname(A__ ) + "/grid.txt" ) as f:
lowerCAmelCase = [] # noqa: E741
for _ in range(20 ):
l.append([int(A__ ) for x in f.readline().split()] )
lowerCAme... | 649 |
'''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... | 649 | 1 |
"""simple docstring"""
__UpperCamelCase : Tuple = [
(1_0_0_0, "M"),
(9_0_0, "CM"),
(5_0_0, "D"),
(4_0_0, "CD"),
(1_0_0, "C"),
(9_0, "XC"),
(5_0, "L"),
(4_0, "XL"),
(1_0, "X"),
(9, "IX"),
(5, "V"),
(4, "IV"),
(1, "I"),
]
def __UpperCAmelCase... | 714 | """simple docstring"""
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__UpperCamelCase : Optional[int] = logging.get_logger(__name__)
__UpperCamelCase : List[str] = ... | 227 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"""studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json""... | 92 |
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
if is_torch_available():
import torch
if is_vision_available... | 290 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,... | 721 |
"""simple docstring"""
from math import factorial
def A( snake_case_ = 20 ):
"""simple docstring"""
lowercase__: Tuple = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
lowercase__: int ... | 120 | 0 |
'''simple docstring'''
import torch
from torch import nn
class _snake_case (nn.Module):
def __init__( self ,_snake_case ,_snake_case ,_snake_case ,_snake_case ,_snake_case=1 ,_snake_case=False ):
super().__init__()
UpperCAmelCase_ : List[Any] = n_... | 71 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
Audio... | 71 | 1 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_objects import * #... | 354 |
from jiwer import compute_measures
import datasets
SCREAMING_SNAKE_CASE : Tuple = "\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL: improved e... | 354 | 1 |
"""simple docstring"""
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
_UpperCamelCase = """."""
if __name__ == "__main__":
_UpperCamelCase = os.path.join(REPO_PATH, """utils/documentati... | 453 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_con... | 453 | 1 |
from random import shuffle
import tensorflow as tf
from numpy import array
def a ( SCREAMING_SNAKE_CASE_ : Optional[Any] , SCREAMING_SNAKE_CASE_ : Optional[int] ):
"""simple docstring"""
UpperCamelCase : Any = int(SCREAMING... | 643 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 643 | 1 |
from __future__ import annotations
import time
import numpy as np
__UpperCamelCase : Dict = [8, 5, 9, 7]
__UpperCamelCase : Any = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
__UpperCamelCase : Tuple = [
[3, 2,... | 248 |
"""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 SPIECE_UNDERLINE, logging
_lowerCAmelCase :Dict = logging... | 506 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelera... | 718 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : Optional[int] = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/m... | 570 | 0 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAmelCase ( A__ ,A__ ):
"""simple docstring"""
@register_to_config
def __init__( self : List[str], *,
lowerCamelCase... | 183 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
A__ : int = importlib.util.find_spec('s3fs') is not None
if _has_safs:
from .safilesystem import... | 183 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Union[str, Any] = {
'''configuration_poolformer''': [
'''POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP'''... | 178 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : Any = logging.get_logger(__name__)
UpperCame... | 178 | 1 |
import itertools
import string
from collections.abc import Generator, Iterable
def lowerCamelCase__ ( __lowerCAmelCase : Iterable[str] , __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = iter(__lowerCAmelCase )
while True... | 290 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...util... | 290 | 1 |
__snake_case :Optional[Any] =0 # The first color of the flag.
__snake_case :List[str] =1 # The second color of the flag.
__snake_case :Any =2 # The third color of the flag.
__snake_case :str =(red, white, blue)
def lowerCamelCase_ ( lowerCAmelCase__ : list ) ... | 224 |
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 224 | 1 |
'''simple docstring'''
def _UpperCamelCase ( __UpperCamelCase = 4_00_00_00 ) -> int:
lowerCamelCase_ = [0, 1]
lowerCamelCase_ = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
low... | 42 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is_vision_ava... | 678 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase = logging.get_logger(__name__)
lowercase = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
# See all Cvt models at https://huggi... | 591 | import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
lowercase = logging.get_logger(__name__)
lowercase = {
"""post_extract_proj""": """feature_pr... | 591 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__snake_case : str = {
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""MobileNetV2Config""",
... | 540 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class lowerCamelCase__ :
def __init__( self ,A = None ):
if components is None:
UpperCAmelCase ... | 341 | 0 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelForQuestionAnswering... | 360 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
A_ = {"tokenization_byt5": ["ByT5Tokenizer"]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
A_ = _LazyModule(__name__, globals()["__file__"], _import_structure,... | 360 | 1 |
def _a ( SCREAMING_SNAKE_CASE = 10_00 ):
"""simple docstring"""
lowercase__ = 2**power
lowercase__ = str(SCREAMING_SNAKE_CASE )
lowercase__ = list(SCREAMING_SNAKE_CASE )
lowercase__ = 0
for i in list_num:
sum_of_num += int(SCREAMING_SNAKE_CASE )
retur... | 43 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import rep... | 43 | 1 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...te... | 407 |
def _lowerCAmelCase ( __magic_name__ :int , __magic_name__ :int ):
return int((input_a, input_a).count(0 ) == 0 )
def _lowerCAmelCase ( ):
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , ... | 407 | 1 |
"""simple docstring"""
snake_case_ : str = {"""a""": ["""c""", """b"""], """b""": ["""d""", """e"""], """c""": [], """d""": [], """e""": []}
snake_case_ : Optional[int] = ["""a""", """b""", """c""", """d""", """e"""]
def lowercase_ ( _lowercase : Tuple , _lowercase ... | 595 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_t... | 595 | 1 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow_... | 235 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as... | 235 | 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
... | 69 |
'''simple docstring'''
import collections
import os
import re
from pathlib import Path
_UpperCamelCase : Optional[int] = 'src/transformers'
# Matches is_xxx_available()
_UpperCamelCase : int = re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {x... | 541 | 0 |
"""simple docstring"""
import pytest
_lowerCAmelCase = """__dummy_dataset1__"""
_lowerCAmelCase = """
import json
import os
import datasets
REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"train\": REPO_URL + \"wikiann-bn-trai... | 720 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _lowerCAmelCase ( unittest.T... | 93 | """simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def lowercase__( __SCREAMING_SNAKE_CASE : An... | 425 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__magic_name__ : List[str] = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV2Config',
... | 608 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class lowerCamelCase ( __snake_case ):
"""simple docstring"""
lo... | 608 | 1 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class a__ :
pass
| 361 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def SCREAMING_SNAKE_CASE ( snake_case_ : Union[str, Any] , snake_case_ : Union[str, Any] ):
# ===== initialization =====
snake_case__ : st... | 297 | 0 |
'''simple docstring'''
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_... | 721 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
UpperCamelCase_ : str = logging.get_logger(__name__)
UpperCamelCase_ : Opt... | 394 | 0 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : List[Any] = """"""
for i in table:
res += inp[i - 1]
return res
def UpperCamelCase (SCREAMING_SNAKE_CASE ):... | 102 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase__ : List[Any] = logging.get_logger(__name__)
UpperCAmelCase__ : List[str] = {"vocab_file": "vocab.json"}
Uppe... | 48 | 0 |
"""simple docstring"""
def snake_case ( A__ ,A__ ):
UpperCAmelCase_ : Tuple = word.split()
def justify(A__ ,A__ ,A__ ) -> str:
UpperCAmelCase_ : int = max_width - width
UpperCAmelCase_ : Any = len(A__ )
if len(A__ ) == 1:
... | 463 |
"""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 im... | 463 | 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 ... | 418 |
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
__UpperCamelCase = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str,... | 551 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase :Tuple = {
"configuration_table_transformer": [
"TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TableTransformerConfig",
"TableTransform... | 703 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokeniz... | 26 | 0 |
"""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_a... | 95 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_util... | 543 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Tuple ={
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InformerConf... | 715 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
lowerCAmelCase : Tuple = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return r... | 693 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case = {'''configuration_vit''': ['''VIT_... | 103 |
import heapq
def lowerCAmelCase_ ( lowerCamelCase ):
__magic_name__ : list[list] =[]
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Priority Queue
# heapq works with... | 21 | 0 |
def _UpperCAmelCase ( ):
"""simple docstring"""
for n in range(1 , 1_000_000 ):
yield n * (n + 1) // 2
def _UpperCAmelCase ( _SCREAMING_SNAKE_CASE : Tuple ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = 1
SCREAMING_S... | 620 |
def _UpperCAmelCase ( _SCREAMING_SNAKE_CASE : list , _SCREAMING_SNAKE_CASE : list , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
if index == number_of_items:
return 0
SCRE... | 620 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available... | 102 |
from datetime import datetime
import requests
def __a ( __lowerCAmelCase ) -> bytes:
SCREAMING_SNAKE_CASE : int = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
SCREAMING_SNAKE_CASE : Any = requests.get(base_url +... | 352 | 0 |
"""simple docstring"""
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuratio... | 709 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_avail... | 165 | 0 |
'''simple docstring'''
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class SCREAMING_SNAKE_CASE ( UpperCAmelCase__ , UpperCAmelCase__ ):
'''simple docstring'''
... | 435 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
... | 23 | 0 |
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'''The `image_to_image.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionImg2ImgPipeline` instead.'''
)
| 719 |
def lowercase_ ( _UpperCamelCase ):
'''simple docstring'''
__lowercase = []
__lowercase = []
__lowercase = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
'''%''': 2,
'''+''': 1,
'''-''': 1,
} # Priority of each operator
__lower... | 527 | 0 |
import argparse
import gc
import json
import os
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accel... | 206 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def _lowerCAmelCase ( _lowerCAmelCase="ro" , _lowerCAmelCase="en" , _lowerCAmelCase="wmt16" , _lowerCAmelCase=None )-> None:
try:
import datasets
except (ModuleNotFoundError, Imp... | 126 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( _UpperCamelCase ):
"""simple docstring"""
return 10 - x * x
def _lowerCAmelCase ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
if equation(_UpperCamelCase ) * equation(_UpperCamelCase ) >= 0:
... | 272 |
"""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, LevitImageProcessor
from... | 272 | 1 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class __lowercase ( __snake_case ):
UpperCamelCase = '''M-CLIP'''
def __init__( self : Optional[Any] , __lowerCamelCase : Optional[Any]=... | 377 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->Any:
UpperCAmelCase = 0
UpperCAmelCase = len(lowerCAmelCase_ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase_ ):
if arr[i] > arr[j]:
num_inversions += 1
return num_invers... | 377 | 1 |
def UpperCamelCase ( lowerCAmelCase_ ) -> int:
'''simple docstring'''
_A= 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def UpperCamelCase ( lowerCAmelCase_ ) -> int:
'''si... | 476 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'''BridgeTower/bridgetower-base''': '''https://huggingface.co/BridgeTower/bridge... | 476 | 1 |
from __future__ import annotations
def _a ( lowerCAmelCase , lowerCAmelCase )-> Dict:
if nth_term == "":
return [""]
SCREAMING_SNAKE_CASE_ = int(lowercase_ )
SCREAMING_SNAKE_CASE_ = int(lowercase_ )
SCREAMING_SNAKE_CASE_ ... | 360 |
'''simple docstring'''
def __UpperCamelCase ( lowercase_ : list[int] , lowercase_ : list[int] , lowercase_ : int ):
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, ne... | 536 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
lowerCAmelCase_ : Union[str, Any] = "\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that develo... | 461 | '''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xope... | 461 | 1 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TF... | 67 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, slo... | 641 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import TypedDict
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = 42
SCREAMING_SNAKE_CASE = 42
def _lowerc... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> list:
__lowerCAmelCase : List[str] = len(__snake_case )
__lowerCAmelCase : Dict = []
for i in range(len(__snake_case ) - pat_len + 1 ):
__lowerCAmelCase ... | 615 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floa... | 5 | import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowercase : Any =get_tests_dir('''fixtures/test_sentencepiece_with_bytefallb... | 305 | 0 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def lowerCAmelCase_ ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
asse... | 710 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
'funnel-transformer/small-base': 'h... | 328 | 0 |
"""simple docstring"""
import argparse
import os
import re
lowerCamelCase__ : Union[str, Any] = "src/transformers"
# Pattern that looks at the indentation in a line.
lowerCamelCase__ : Tuple = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0... | 698 |
"""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_fast import BertTokenizerFast
from .tokenization_dpr import DPR... | 698 | 1 |
"""simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = len(lowerCamelCase__ )
lowerCAmelCase__ = len(matrix[0] )
lowerCAmelCase__ = min(lowerCamelCase__ , lowerCamelCase__ )
for row in... | 717 | """simple docstring"""
import pprint
import requests
__lowerCAmelCase : Union[str, Any] = "https://zenquotes.io/api"
def _UpperCAmelCase ( ):
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def _Upper... | 674 | 0 |
"""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_input... | 102 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
"facebook/xmod-base": "https://huggingface.co/f... | 332 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class _snake_case (__SCREAMING_SNAKE_CASE):
def __init__( self ,*_snake_case ,**_snake_case ):
... | 700 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {"""configuration_deit""": ["""DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", ... | 323 | 0 |
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_available():
import ... | 9 |
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 | 1 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import Pr... | 700 |
"""simple docstring"""
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def lowercase ( lowerCAmelCase__ : Optional[int] ) -> int:
monkeypatch.setattr('''datasets.utils.deprecation_utils._emitted_deprecation_warnings''' , s... | 65 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
UpperCAmelCase : Optional[int] = TypeVar('T')
class lowerCamelCase__ ( Generic[T] ):
"""simple docstring"""
def __init__( sel... | 139 |
"""simple docstring"""
from math import pow
def lowerCamelCase ( _UpperCamelCase : int , _UpperCamelCase : int , _UpperCamelCase : int , _UpperCamelCase : int , _UpperCamelCase : int , ) -> tuple[int, int]:
'''simple docstring'''
... | 139 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
Condition... | 715 | '''simple docstring'''
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class __A ( UpperCamelCase__ ):
a__ : Optional[int]... | 415 | 0 |
from ..utils import DummyObject, requires_backends
class a_ ( metaclass=a_ ):
'''simple docstring'''
__a: Union[str, Any] = ['''speech''']
def __init__( self , *lowercase_ , **lowercase_ ) -> L... | 318 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxT... | 318 | 1 |
'''simple docstring'''
from math import factorial
def _snake_case ( lowercase = 1_0_0 ) -> int:
return sum(int(lowercase ) for x in str(factorial(lowercase ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip()))) | 697 |
'''simple docstring'''
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_d... | 697 | 1 |
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
_snake_case = logging.get_logger(__name__)
class _snake_case ( _lowercase ):
def __init__( self: List[Any] , *__lowerCamelCase: List[str... | 382 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case = {
'''configuration_table_transformer''': [
'''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TableTransformerConfig''',
'''TableTr... | 382 | 1 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
# TODO Update this
A__ = {
"""facebook/esm-1b""": """https://huggingface.co/facebook/esm-1b/resolve/ma... | 706 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requir... | 184 | 0 |
'''simple docstring'''
from __future__ import annotations
def A (__lowerCamelCase :str , __lowerCamelCase :list[str] | None = None , __lowerCamelCase :dict[str, float] | None = None , __lowerCamelCase :bool = False , ):
_lowerCAmelCase = cipher_alphabet or [chr(_... | 5 | """simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformer... | 564 | 0 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
_a : Union[str, Any] = ''
_a : Optional[Any] = ''
_a : List[str] = ''
_a : Optional[Any] = 1 # (0 is vertical, 1 is horizontal)
def SCREAMING_SNA... | 663 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int ) -> bool:
return sum(i for i in range(1 ,number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('Program to check whether a number is a Perfect number or not...')
_a : int ... | 663 | 1 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : str , __lowerCAmelCase : int ):
return [sentence[i : i + ngram_size] for i in range(len(__lowerCAmelCase ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
testmod()
| 50 |
'''simple docstring'''
def _UpperCamelCase ( lowerCAmelCase__: str ) -> bool:
return credit_card_number.startswith(('34', '35', '37', '4', '5', '6') )
def _UpperCamelCase ( lowerCAmelCase__: str ) -> bool:
SCREAMING_SNAKE_CASE_ = cred... | 294 | 0 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int ) -> list:
__a = len(lowerCAmelCase__ )
__a = [[0] * n for i in range(lowerCAmelCase__ )]
for i in range(lowerCAmelCa... | 65 |
"""simple docstring"""
from typing import 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 Batc... | 65 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenization_m2m_10... | 401 | 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 transformers.ut... | 401 | 1 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = None , UpperCamelCase__ = None , ... | 705 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
require_torch... | 334 | 0 |
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