code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _lowercase( __a : int , __a : int , __a : int , __a : int , __a : int , __a : int ):
# prepare kernel
... | 20 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : List[Any] = {
'configuration_mobilebert': [
'MOBILEBERT_PRET... | 44 | 0 |
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
if... | 21 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase__ :
def __init__( self : Optional[Any],__A : list[tuple[float, float]] ):
_lowerCamelCase : Tuple = list_of_points
# Degr... | 44 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from trans... | 22 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=A ):
lowerCAmelCase_ = ['transformers', 'torch', 'note_seq']
def __init__( self : str,*__A : List[str],**__A : List[Any] ):
requ... | 44 | 0 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
snake_case__ : Tuple = logging.get_logger(__name__)
def _snake_case (__lowercase , __lowercase):
UpperCamelCa... | 23 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 44 | 0 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@req... | 24 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCAmelCase__ :
def __init__( self : Any,__A : int=2,__A : Any=3,__A : Optional[int]=6_4,__A : ... | 44 | 0 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
a_ = argparse.ArgumentParser()
parser.add_argument('--dump_path', default=None, type=str, required=True, help='Pa... | 25 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table i... | 44 | 0 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from da... | 26 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : str = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
... | 44 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_a... | 27 |
'''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 BatchFeature
from ... | 44 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTeste... | 28 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transform... | 44 | 0 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ ):
if not nums: # Makes sure that the list is not empty
raise ValueError('''List is empty''' )
lowerCamelCase_ = sum(lowerCAmelCase__ ) / len(lowerCAmelCase__ ) # Calculate the average
return sum(abs(x - average ... | 29 |
'''simple docstring'''
import functools
def A_ ( _lowerCAmelCase : list[int] , _lowerCAmelCase : list[int] ):
"""simple docstring"""
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ) or not all(isinstance(_lowerCAmelCase , _lower... | 44 | 0 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__a = 299_792_458
# Symbols
__a ,__a ,__a ,__a = symbols('ct x y z')
def lowerCamelCase__ ( _lowercase ):
'''simple docstring'''
if velocity ... | 30 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transf... | 44 | 0 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 |
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = range(2, 20 + 1)
UpperCAmelCase_ : str = [10**k for k in range(ks[-1] + 1)]
UpperCAmelCase_ : dict[int, dict[int, list[list[int]]]] = {}
def A_ ( _lowerCAmelCase : Any , _lowerCAmelCase... | 44 | 0 |
import numpy as np
import datasets
UpperCAmelCase_ = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof.... | 32 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSe... | 44 | 0 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __magic_name__ :
'''simple docstring'''
def __init__( self:Union[str, Any] , _a:List[str] ):
snake_case__ = data
snake_case__ = [0X67_452_301,... | 33 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone... | 44 | 0 |
"""simple docstring"""
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import v... | 34 |
'''simple docstring'''
class UpperCAmelCase__ :
def __init__( self : Any,__A : Any,__A : Any,__A : Any ):
_lowerCamelCase : List[Any] = name
_lowerCamelCase : Union[str, Any] = value
_lowerCamelCase : str ... | 44 | 0 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowercase ( enum.Enum ):
lowerC... | 35 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : List[Any] = {
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 44 | 0 |
def lowercase ( __A : int = 100 ) -> int:
'''simple docstring'''
snake_case : Tuple = 0
snake_case : Tuple = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
... | 36 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def A_ ( _lowerCAmelCase : Optional[Any] ):
... | 44 | 0 |
from math import sqrt
def UpperCamelCase_ ( __a ) -> int:
a__ : Union[str, Any] = 0
for i in range(1 , int(sqrt(__a ) + 1 ) ):
if n % i == 0 and i != sqrt(__a ):
total += i + n // i
elif i == sqrt(__a ):
... | 37 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
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_... | 44 | 0 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
A_ : Optional[int] = logging.get_... | 38 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 44 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''facebook/data2vec-text-bas... | 39 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingSt... | 44 | 0 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import ... | 40 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers... | 44 | 0 |
'''simple docstring'''
def _A ( ):
"""simple docstring"""
__lowercase = 0
for i in range(1 , 1001 ):
total += i**i
return str(A__ )[-10:]
if __name__ == "__main__":
print(solution())
| 41 |
'''simple docstring'''
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
_lowerCamelCase : int = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def A_ ( _lowerCAmelCase : int = 5000 ):
"""simple docstring"""
... | 44 | 0 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_... | 42 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : List[Any] = {
'configuration_mobilebert': [
'MOBILEBERT_PRET... | 44 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop... | 43 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase__ :
def __init__( self : Optional[Any],__A : list[tuple[float, float]] ):
_lowerCamelCase : Tuple = list_of_points
# Degr... | 44 | 0 |
from __future__ import annotations
def A ( lowercase__ : list[int] , lowercase__ : int ) -> list[int]:
UpperCamelCase__ :Tuple = 0
UpperCamelCase__ :Any = len(lowercase__ ) - 1
while i < j:
if nums[i] + nums[j] == target:
return [i, j]
elif nums[i] + nums[j] < ... | 45 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=A ):
lowerCAmelCase_ = ['transformers', 'torch', 'note_seq']
def __init__( self : str,*__A : List[str],**__A : List[Any] ):
requ... | 44 | 0 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> int:
'''simple docstring'''
return x if y == 0 else greatest_common_divisor(_lowerCamelCase , x % y )
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) ... | 46 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 44 | 0 |
import math
import tensorflow as tf
from packaging import version
def UpperCAmelCase__ ( lowerCamelCase_ : Tuple ):
__a : Any = tf.convert_to_tensor(lowerCamelCase_ )
__a : Any = 0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(... | 47 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCAmelCase__ :
def __init__( self : Any,__A : int=2,__A : Any=3,__A : Optional[int]=6_4,__A : ... | 44 | 0 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class A ( SCREAMING_SNAKE_CASE__ ):
def __init__( self :... | 48 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table i... | 44 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowercase : int = {
'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfi... | 49 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : str = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
... | 44 | 0 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
return number | (1 << position)
def A__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
return number & ~(1 << position)
def A__ ( ... | 50 |
'''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 BatchFeature
from ... | 44 | 0 |
'''simple docstring'''
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffu... | 51 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transform... | 44 | 0 |
"""simple docstring"""
from __future__ import annotations
A = list[list[int]]
# assigning initial values to the grid
A = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0... | 52 |
'''simple docstring'''
import functools
def A_ ( _lowerCAmelCase : list[int] , _lowerCAmelCase : list[int] ):
"""simple docstring"""
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ) or not all(isinstance(_lowerCAmelCase , _lower... | 44 | 0 |
import qiskit
def a_ ( lowerCAmelCase_ : int, lowerCAmelCase_ : int ):
__lowerCAmelCase = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on the q register
__lowerCAmelCase = qiskit.QuantumCircuit(lowerCAmelCase... | 53 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transf... | 44 | 0 |
from __future__ import annotations
class A :
def __init__( self: Union[str, Any] , _lowerCAmelCase: int = 0 ) -> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase_ =key
def lowerCAmelCase__ ( se... | 54 |
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = range(2, 20 + 1)
UpperCAmelCase_ : str = [10**k for k in range(ks[-1] + 1)]
UpperCAmelCase_ : dict[int, dict[int, list[list[int]]]] = {}
def A_ ( _lowerCAmelCase : Any , _lowerCAmelCase... | 44 | 0 |
def UpperCAmelCase ( a_ ) -> int:
"""simple docstring"""
if n == 1 or not isinstance(a_ , a_ ):
return 0
elif n == 2:
return 1
else:
__A = [0, 1]
for i in range(2 , n + 1 ):
sequence.append(sequence[i - ... | 55 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSe... | 44 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 56 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone... | 44 | 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_availab... | 57 |
'''simple docstring'''
class UpperCAmelCase__ :
def __init__( self : Any,__A : Any,__A : Any,__A : Any ):
_lowerCamelCase : List[Any] = name
_lowerCamelCase : Union[str, Any] = value
_lowerCamelCase : str ... | 44 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCAmelCase ( __UpperCamelCase : Optional[Any] ... | 58 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : List[Any] = {
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 44 | 0 |
def lowerCAmelCase_ ( __a , __a , __a , __a ) -> int:
"""simple docstring"""
lowerCamelCase__ , lowerCamelCase__: Optional[int] =len(__a ), len(grid[0] )
if (
min(__a , __a ) < 0
or row == row_le... | 59 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def A_ ( _lowerCAmelCase : Optional[Any] ):
... | 44 | 0 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
depr... | 60 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
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_... | 44 | 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
if is_torch_available():
import torch
... | 61 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 44 | 0 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
snake_case = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui Wu and M... | 62 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingSt... | 44 | 0 |
a : Optional[int] = 9.8_06_65
def lowerCamelCase__ ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float = g ):
if fluid_density <= 0:
raise ValueError("""Impossible fluid density""" )
i... | 63 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers... | 44 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from .... | 64 |
'''simple docstring'''
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
_lowerCamelCase : int = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def A_ ( _lowerCAmelCase : int = 5000 ):
"""simple docstring"""
... | 44 | 0 |
"""simple docstring"""
__UpperCAmelCase = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', 'U... | 65 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : List[Any] = {
'configuration_mobilebert': [
'MOBILEBERT_PRET... | 44 | 0 |
def __magic_name__ ( SCREAMING_SNAKE_CASE ) -> list:
if len(SCREAMING_SNAKE_CASE ) <= 1:
return [tuple(SCREAMING_SNAKE_CASE )]
_lowercase : List[Any] = []
def generate(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
... | 66 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase__ :
def __init__( self : Optional[Any],__A : list[tuple[float, float]] ):
_lowerCamelCase : Tuple = list_of_points
# Degr... | 44 | 0 |
class A_ :
"""simple docstring"""
def __init__( self : List[str] ) -> Any:
_lowercase = 0
_lowercase = 0
_lowercase = {}
def __UpperCAmelCase ( ... | 67 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=A ):
lowerCAmelCase_ = ['transformers', 'torch', 'note_seq']
def __init__( self : str,*__A : List[str],**__A : List[Any] ):
requ... | 44 | 0 |
def lowercase__ ( A_: str ) -> list:
"""simple docstring"""
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(A_ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__("doctest").testmod()
| 68 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 44 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( _UpperCAmelCase : list[int] , _UpperCAmelCase : int ) -> bool:
__snake_case = len(_UpperCAmelCase )
__snake_case = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum o... | 69 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCAmelCase__ :
def __init__( self : Any,__A : int=2,__A : Any=3,__A : Optional[int]=6_4,__A : ... | 44 | 0 |
from __future__ import annotations
from collections.abc import Iterator
class A:
'''simple docstring'''
def __init__( self : Tuple , A_ : int ) -> None:
"""simple docstring"""
lowerCamelCase_ = value
... | 70 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table i... | 44 | 0 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing impo... | 71 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : str = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
... | 44 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase : str = logging.get_logger(__name__)
_UpperCAmelCase : str = {
'''xlm-roberta-base''': '... | 72 |
'''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 BatchFeature
from ... | 44 | 0 |
from math import isqrt, loga
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = [True] * max_number
for i in range(2 , isqrt(max_number - 1) + 1):
if is_prime[i]:
for j in range(i**2 , _UpperCAmelCase , _UpperCAmelCase):
... | 73 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transform... | 44 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFXLMRobertaModel
@... | 74 |
'''simple docstring'''
import functools
def A_ ( _lowerCAmelCase : list[int] , _lowerCAmelCase : list[int] ):
"""simple docstring"""
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ) or not all(isinstance(_lowerCAmelCase , _lower... | 44 | 0 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..cont... | 75 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transf... | 44 | 0 |
"""simple docstring"""
a_ = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
a_ = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
a_ = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
... | 76 |
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = range(2, 20 + 1)
UpperCAmelCase_ : str = [10**k for k in range(ks[-1] + 1)]
UpperCAmelCase_ : dict[int, dict[int, list[list[int]]]] = {}
def A_ ( _lowerCAmelCase : Any , _lowerCAmelCase... | 44 | 0 |
"""simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
A = """__DUMMY_TRANSFORMERS_USER__"""
A = """Dummy User"""
A = """hf_hZEmnoOEYISjraJtbySaKCNnSuYAvuka... | 77 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSe... | 44 | 0 |
'''simple docstring'''
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 lowerCAmelCase_ ( snake_case_ : Union[dict, list, ... | 78 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone... | 44 | 0 |
SCREAMING_SNAKE_CASE__ : Dict = [0, 2, 4, 6, 8]
SCREAMING_SNAKE_CASE__ : Optional[Any] = [1, 3, 5, 7, 9]
def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> int:
'''simple ... | 79 |
'''simple docstring'''
class UpperCAmelCase__ :
def __init__( self : Any,__A : Any,__A : Any,__A : Any ):
_lowerCamelCase : List[Any] = name
_lowerCamelCase : Union[str, Any] = value
_lowerCamelCase : str ... | 44 | 0 |
def snake_case ( lowerCamelCase = 1_000 ):
'''simple docstring'''
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 80 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : List[Any] = {
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 44 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_snake_case : Any = {
"configuration_chinese_clip": [
"CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"ChineseCLIPConfig",
"Chines... | 81 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def A_ ( _lowerCAmelCase : Optional[Any] ):
... | 44 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMSchedu... | 82 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
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_... | 44 | 0 |
"""simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
lowerCAmelCase__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, ... | 83 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 44 | 0 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
UpperCAmelCase = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh'... | 84 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingSt... | 44 | 0 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
SCREAMING_SNAKE_CASE__ : List[str] = HfArgumentParser(InitializationArguments)
SCREAMING_SNAKE_CASE__ : Tuple = pa... | 85 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers... | 44 | 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():
... | 86 |
'''simple docstring'''
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
_lowerCamelCase : int = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def A_ ( _lowerCAmelCase : int = 5000 ):
"""simple docstring"""
... | 44 | 0 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
_lowerCamelCase : Union[str, Any] = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
... | 87 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : List[Any] = {
'configuration_mobilebert': [
'MOBILEBERT_PRET... | 44 | 0 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _snake_case ( __snake_case : List[str] ):
"""simple docstring"""
return getitem, k
def _snake_case ... | 88 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase__ :
def __init__( self : Optional[Any],__A : list[tuple[float, float]] ):
_lowerCamelCase : Tuple = list_of_points
# Degr... | 44 | 0 |
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ ) -> List[str]:
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(lowerCamelCase_ , n - 1 , lowerCamelCase_ ) * a) % mod
else:
_lowercase ... | 89 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=A ):
lowerCAmelCase_ = ['transformers', 'torch', 'note_seq']
def __init__( self : str,*__A : List[str],**__A : List[Any] ):
requ... | 44 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__UpperCAmelCase = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config'''... | 90 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 44 | 0 |
"""simple docstring"""
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.tes... | 91 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCAmelCase__ :
def __init__( self : Any,__A : int=2,__A : Any=3,__A : Optional[int]=6_4,__A : ... | 44 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
UpperCamelCase_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowercase__ ):
def __init__( self : Optional[int] , ... | 92 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table i... | 44 | 0 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipel... | 93 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : str = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
... | 44 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
... | 94 |
'''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 BatchFeature
from ... | 44 | 0 |
"""simple docstring"""
from __future__ import annotations
lowerCamelCase_ = 8.988E9 # units = N * m^s * C^-2
def snake_case ( A__ ,A__ ,A__ ,A__ ):
UpperCAmelCase_ : str = abs(chargea * chargea )
if (force, chargea, chargea, distance).count(0 ) != 1:
... | 95 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transform... | 44 | 0 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from .... | 96 |
'''simple docstring'''
import functools
def A_ ( _lowerCAmelCase : list[int] , _lowerCAmelCase : list[int] ):
"""simple docstring"""
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ) or not all(isinstance(_lowerCAmelCase , _lower... | 44 | 0 |
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerate.test_utils im... | 97 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transf... | 44 | 0 |
'''simple docstring'''
lowercase__ : Optional[int] = 2_56
# Modulus to hash a string
lowercase__ : Any = 1_00_00_03
def a__ ( lowercase : str, lowercase : str ) -> bool:
"""simple docstring"""
_UpperCamelCase = len(low... | 98 |
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = range(2, 20 + 1)
UpperCAmelCase_ : str = [10**k for k in range(ks[-1] + 1)]
UpperCAmelCase_ : dict[int, dict[int, list[list[int]]]] = {}
def A_ ( _lowerCAmelCase : Any , _lowerCAmelCase... | 44 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
# See all... | 99 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSe... | 44 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDI... | 100 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone... | 44 | 0 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'kwargs, expected', [
({'num_shards': 0, 'max_num_jobs': 1}, []),
({'num_shards': 1_0, 'max_num_jobs': 1}, [range(1_0 )]... | 101 |
'''simple docstring'''
class UpperCAmelCase__ :
def __init__( self : Any,__A : Any,__A : Any,__A : Any ):
_lowerCamelCase : List[Any] = name
_lowerCamelCase : Union[str, Any] = value
_lowerCamelCase : str ... | 44 | 0 |
"""simple docstring"""
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
UpperCamelCase : List[str] = len(SCREAMING_SNAKE_CASE )
UpperCamelCase : Dict = len(matrix[0] )
UpperCamelCase : str = min(SCREAMING_SNAKE_CASE , ... | 102 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : List[Any] = {
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 44 | 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
if is_torch... | 103 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def A_ ( _lowerCAmelCase : Optional[Any] ):
... | 44 | 0 |
"""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.... | 104 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
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_... | 44 | 0 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __UpperCAmelCase ( lowerCamelCase_ : str , lowerCamelCase_ : complex , lowerCamelCase_ : str = "x" , lowerCamelCase_ : float = 10**-10 , lowerCamelCase_ : ... | 105 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 44 | 0 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
fro... | 106 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingSt... | 44 | 0 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorT... | 107 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers... | 44 | 0 |
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self : Dict , lowerCamelCase : Optional[int] , lowerCamelCase : Dict ) -> List[str]:
"""simple docstring"""
_UpperCAmelCase = name
_UpperCAmelCase ... | 108 |
'''simple docstring'''
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
_lowerCamelCase : int = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def A_ ( _lowerCAmelCase : int = 5000 ):
"""simple docstring"""
... | 44 | 0 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def __magic_name__ ( ) -> Union[str, Any]:
'''simple docstring'''
import os as original_os
from os import path as original_path
from os import ren... | 109 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : List[Any] = {
'configuration_mobilebert': [
'MOBILEBERT_PRET... | 44 | 0 |
"""simple docstring"""
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class a ... | 110 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase__ :
def __init__( self : Optional[Any],__A : list[tuple[float, float]] ):
_lowerCamelCase : Tuple = list_of_points
# Degr... | 44 | 0 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowercase , _lowercase , _lowercase ) -> int:
... | 282 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=A ):
lowerCAmelCase_ = ['transformers', 'torch', 'note_seq']
def __init__( self : str,*__A : List[str],**__A : List[Any] ):
requ... | 44 | 0 |
'''simple docstring'''
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
f... | 13 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 44 | 0 |
'''simple docstring'''
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test... | 209 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCAmelCase__ :
def __init__( self : Any,__A : int=2,__A : Any=3,__A : Optional[int]=6_4,__A : ... | 44 | 0 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
__A : Dict = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def lowercase ( ):
"""simple docstring"""
A__ : str =os.path.dirname(os.path.realpath(_lowerCAmelCase ) )
... | 656 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table i... | 44 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowerCAmelCase__ : int , lowerCAmelCase__ : int) -> str:
'''simple docstring'''
while b:
_lowercase : Optional[Any] = b, a % b
return a
def SCREAMING_SNAKE_CASE ( lower... | 125 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : str = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
... | 44 | 0 |
def A__ ( lowerCamelCase = 50 ) -> Optional[Any]:
UpperCamelCase_: Optional[int] = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length... | 548 |
'''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 BatchFeature
from ... | 44 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
... | 570 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transform... | 44 | 0 |
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
SCR... | 112 |
'''simple docstring'''
import functools
def A_ ( _lowerCAmelCase : list[int] , _lowerCAmelCase : list[int] ):
"""simple docstring"""
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ) or not all(isinstance(_lowerCAmelCase , _lower... | 44 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowerCAmelCase__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Optional... | 596 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transf... | 44 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Optio... | 262 |
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = range(2, 20 + 1)
UpperCAmelCase_ : str = [10**k for k in range(ks[-1] + 1)]
UpperCAmelCase_ : dict[int, dict[int, list[list[int]]]] = {}
def A_ ( _lowerCAmelCase : Any , _lowerCAmelCase... | 44 | 0 |
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