code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
SCREAMING_SNAKE_CASE_: int ... | 1 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 0 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import S... | 2 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ = 1000 ):
'''simple docstring'''
A : int = 2**power
A : List[Any] = str(snake_case__ )
A : List[str] = list(snake_case__ )
A : List... | 3 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 0 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extrac... | 4 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 0 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase__ ( lowerCAmelCase , unittest.... | 5 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 0 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def __lowerCAmelCase ( a__ , a__ = True , a__ = math.inf , a__ = -math.inf , a__ = math.inf , a__ = -math.inf , a__ = False , a__ = 100 , a__ = 0.01 ... | 6 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 0 |
from manim import *
class A ( _UpperCAmelCase ):
"""simple docstring"""
def snake_case__ ( self : Any )-> Optional[int]:
'''simple docstring'''
A__ = Rectangle(height=0.5,width=0.5 )
... | 7 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 0 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class snake_case_ ( __A ):
'''simple docstring... | 8 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 0 |
import unittest
from transformers import BigBirdConfig, 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
from transformers.models.big_bird.mo... | 9 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 0 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
__A = transforms.Compose(
... | 10 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 0 |
def _UpperCAmelCase (UpperCamelCase__ : int ):
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise ValueError("Input must be positive" )
return sum(... | 11 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 0 |
# Lint as: python3
import itertools
import os
import re
UpperCAmelCase_ = re.compile(r'([A-Z]+)([A-Z][a-z])')
UpperCAmelCase_ = re.compile(r'([a-z\d])([A-Z])')
UpperCAmelCase_ = re.compile(r'(?<!_)_(?!_)')
UpperCAmelCase_ = re.compile(r'(_{2,})')
UpperCAmelCase_ = r'^\w+... | 12 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 0 |
def A_ ( _UpperCAmelCase = 3 , _UpperCAmelCase = 7 , _UpperCAmelCase = 1_00_00_00 ):
SCREAMING_SNAKE_CASE_: Union[str, Any] = 0
SCREAMING_SNAKE_CASE_: int = 1
for current_denominator in range(1 , limit + 1 ):
SCREAMING_SNAKE_CASE_: int = ... | 13 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> list[int]:
"""simple docstring"""
if num <= 0:
raise ValueError('''Input must be a positive integer''' )
A__ = [True] * (num + 1)
A__ = 2
while p * p <= num:
... | 14 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 | 0 |
import sys
import turtle
def UpperCAmelCase ( a_ , a_ ) -> tuple[float, float]:
"""simple docstring"""
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def UpperCAmelCase ( a_ , a_ , a_ , a_ , ) -> None:
"""simple docstring"""
my_pen.up()
... | 15 |
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():
... | 317 | 0 |
"""simple docstring"""
def __UpperCAmelCase ( __lowerCamelCase , __lowerCamelCase = " " ) -> list:
lowercase__ : Optional[int] = []
lowercase__ : Union[str, Any] = 0
for index, char in enumerate(__lowerCamelCase ):
if char == se... | 16 |
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__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 | 0 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
_a = '\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitle={EMNLP},\n ... | 17 |
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 datasets.table import table_cast
from dat... | 317 | 0 |
from __future__ import annotations
import requests
__lowerCamelCase : int = set(
'''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc... | 18 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 | 0 |
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
__A =logging.get_logger(__name__)
def lowerCamelCase_ ( ):
# Get th... | 19 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_mo... | 317 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, require_... | 20 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str ) -> list:
_snake_case : Optional[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for better performance - dynamic programming
_snake_case : Optiona... | 317 | 0 |
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr, require_zstandard
@... | 21 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
__SCREAMING_SNAKE_CASE :Union[str, Any] = logging.get_logger(__name__)
class A_ ( lowerCAmelCase_ ):
def __init__( self : Tuple , *snake_cas... | 22 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...tes... | 23 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
# See all CANINE models at https://huggingface.co/mod... | 24 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def lowercase_ ( _snake_case ,_snake_case ,_snake_case ,_snake_case ,_snake_case ):
if depth < 0:
raise ValueError("""Depth cannot be less than 0""" )
if len(_snake_case ) ... | 25 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc_bert": ["RoCBertTokenizer... | 26 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Any = logging.get_logger(__name__)
__lowercase : List[str] = {
'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
'https://huggingface.co/CarlCoche... | 27 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 0 |
'''simple docstring'''
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRoberta... | 28 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDis... | 29 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
smartaa_timestep... | 30 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 0 |
'''simple docstring'''
from collections import defaultdict
def UpperCamelCase_ ( _UpperCAmelCase : int ) -> int:
"""simple docstring"""
_UpperCAmelCase : List[str] = 1
_UpperCAmelCase : List[str] = True
for v in ... | 31 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 0 |
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_ : List[str] = {
'... | 32 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVec... | 33 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 0 |
'''simple docstring'''
import qiskit
def snake_case_ (_a : int , _a : int ):
UpperCAmelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
UpperCAmelCase = qiskit.QuantumCircuit(_a ... | 34 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 0 |
'''simple docstring'''
def __snake_case( _lowerCAmelCase , _lowerCAmelCase ) -> Optional[int]:
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
snake_case__ : int = (boundary[1] - boundary[0]) / steps
snake_case__ : Optional[in... | 35 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 0 |
import argparse
import json
import subprocess
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Any = []
_lowerCAmelCase : Optional[int] = (
F"curl -H \"Accept: application/vnd.github+j... | 36 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, ge... | 37 |
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():
... | 317 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _SCREAMING_SNAKE_CASE ( unittest.TestCase , _a ):
def _A ( self : Union[str, Any] ):
UpperCamelCase :Union[str, Any] = load_tool("""text-classification... | 38 |
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__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_a = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTC... | 39 |
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 datasets.table import table_cast
from dat... | 317 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
norm... | 40 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 | 0 |
'''simple docstring'''
class _lowercase :
def __init__( self: Dict , UpperCamelCase__: int , UpperCamelCase__: Dict , UpperCamelCase__: List[Any] ):
lowerCamelCase__ : Dict = name
l... | 41 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_mo... | 317 | 0 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCAmelCase ( _lowerCamelCase ):
__lowercase = ["""image_processor""", """tokenizer"""]
__lowercase = ... | 42 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str ) -> list:
_snake_case : Optional[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for better performance - dynamic programming
_snake_case : Optiona... | 317 | 0 |
from collections.abc import Callable
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self , __lowercase = None) -> None:
# Stores actual heap items.
__UpperCamelCase :list = []
# Stores indexes of each item for supporting updates and deletio... | 43 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 0 |
"""simple docstring"""
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_a : Any ... | 44 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 0 |
"""simple docstring"""
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def lowercase ( lowerCAmelCase__ : str ) -> str:
return "".join(sorted(lowerCAmelCase__ ) )
def lowercase ( lowerCAmelCase__ : s... | 45 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 0 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : Union[str, Any] ... | 46 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 0 |
'''simple docstring'''
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : str = logging.get_logger(__name__)
class A__ ( A__ ):
A__ = ['input_ids'... | 47 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 0 |
from __future__ import annotations
def A ( _SCREAMING_SNAKE_CASE ) -> bool:
lowerCamelCase : int = str(_SCREAMING_SNAKE_CASE )
return len(_SCREAMING_SNAKE_CASE ) == 9 and set(_SCREAMING_SNAKE_CASE ) == set("123456789" )
def A ( )... | 48 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 0 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from... | 49 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 0 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
_UpperCAmelCase : List[str] = {
"""vocab_... | 50 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 0 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __snake_case ( a ):
def lowerCamelCase ( self : Tuple):
"""simple docstring"""
return [
{"col_1": 3... | 51 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
__lowerCamelCase : str = logging.get_logger(__name__) # pylint: disable=invalid-name
class A__ ( __snake_... | 52 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 0 |
'''simple docstring'''
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class snake_case ( __lowerC... | 53 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 0 |
"""simple docstring"""
import warnings
warnings.warn(
'''memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '''
'''`from accelerate import find_executable_batch_size` to avoid this warning.''',
FutureWarning,
)
| 54 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 0 |
'''simple docstring'''
import math
def __snake_case ( UpperCAmelCase_ : int ):
lowerCamelCase_ = 0
lowerCamelCase_ = 0
while num > 0:
lowerCamelCase_ = num % 8
lowerCamelCase_ = octal + (remainder * math.floor(math.pow(10 , UpperCAmelCas... | 55 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 0 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
a : List[Any] = logging.get_logger(__name__)... | 56 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 0 |
"""simple docstring"""
from math import sqrt
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = 0
for i in range(1 , int(sqrt(_UpperCamelCase ) + 1 ) ):
if n % i == 0 and i != sqrt(_UpperCamelCase ):
total += i + n... | 57 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagema... | 58 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 | 0 |
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCamelCase = """
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplification},
autho... | 59 |
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():
... | 317 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
snake_case__ : Optional[int] = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig''... | 60 |
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__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
class A_ (lowercase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : List[str] = """bert-generation"""
def __init__( self , lowercase_=5_0358 , lowercase_=1024 , lowercase_=24 , ... | 61 |
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 datasets.table import table_cast
from dat... | 317 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : str ):
if n_term == "":
return []
__UpperCamelCase =[]
for temp in range(int(SCREAMING_SNAKE_CASE__ ) ):
series.append(F'1/{temp + 1}' if series else '1' )
return series
if __name__ == "__m... | 62 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 | 0 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class __SCREAMING_SNAKE_CASE (datasets.BuilderConfig ):
"""simple docstring""... | 63 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_mo... | 317 | 0 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
A_ = TypeVar('''T''')
A_ = Union[List[T], Tuple[T, ...]]
A_ = Union[T, List[T], Dict[str, T]]
A_ = Union[str, bytes, os.PathLike]
| 64 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str ) -> list:
_snake_case : Optional[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for better performance - dynamic programming
_snake_case : Optiona... | 317 | 0 |
import mpmath # for roots of unity
import numpy as np
class A :
def __init__(self : Union[str, Any] , __UpperCAmelCase : Any=None , __UpperCAmelCase : Optional[int]=None ) -> Dict:
"""simple docstring"""
UpperCAm... | 65 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class lowerCamelCase ( unittest.TestCase ):
... | 66 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase ={
"configuration_... | 67 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 0 |
from PIL import Image
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Image ) -> Image:
'''simple docstring'''
A__ , A__ = image.size
A__ = 0
A__ = image.load()
for i in range(SCREAMING_SNAKE_CASE_ ):
for j in range(SCREAMING_SNAKE_CA... | 68 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 0 |
"""simple docstring"""
import os
def UpperCAmelCase ( ) -> Union[str, Any]:
with open(os.path.dirname(UpperCAmelCase ) + '/p022_names.txt' ) as file:
snake_case_ = str(file.readlines()[0] )
snake_case_ = names.replace('"' ... | 69 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 0 |
'''simple docstring'''
from __future__ import annotations
import requests
A__ : Optional[Any] =set(
'''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post... | 70 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A_ :Dict = {
'''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
'''tokeni... | 71 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 0 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 72 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 0 |
import copy
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
from ..auto import CONFIG_MAPPING
a =logging.get_logger(__name__)
a ={
""... | 73 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 0 |
"""simple docstring"""
def _snake_case ( snake_case__ : str ):
A = 0
for ch in input_str:
A = ord(snake_case__ )
A = pow(2 , snake_case__ )
# If we already turned on bit for current character's unicode
if bitmap >> ch_unicode & 1 == 1:
ret... | 74 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 0 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pyto... | 75 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( _a , _a , _a):
if days_between_payments <= 0:
raise ValueError("days_between_payments must be > 0")
if daily_interest_rate < 0:
raise ValueError("daily_interest_rate must be >= 0")
if principal <= 0:
raise ValueError("prin... | 76 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def a_ ( _lowerCAmelCase : Tuple ):
'''simple docstring'''
return choice(_lowerCAmelCase )
def a_ ( _lowerCAmelCase : list[int] , _lowerCAmelCase : int ):
... | 77 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 0 |
"""simple docstring"""
snake_case_ = """Tobias Carryer"""
from time import time
class A_ :
"""simple docstring"""
def __init__( self :str , lowercase_ :str , lowercase_ :List[Any] , lowercase_ :Union[str, Any] , lowerca... | 78 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 0 |
'''simple docstring'''
import math
def __lowercase ( __lowercase = 100 ) -> int:
'''simple docstring'''
_A = sum(i * i for i in range(1 , n + 1 ) )
_A = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
... | 79 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Any = logging.get_logger(__name__)
a__ : Tuple = {
'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesf... | 80 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 | 0 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __A ( _SCREAMING_SNAKE_CASE ):
"""simple docstring"""
__lowerCAmelCase = ["image_processor... | 81 |
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():
... | 317 | 0 |
def _UpperCAmelCase ( snake_case , snake_case , snake_case ):
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(snake_case ) )
def _UpperCAmelCase ( snake_case , snake_case... | 82 |
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__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import... | 83 |
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 datasets.table import table_cast
from dat... | 317 | 0 |
"""simple docstring"""
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRober... | 84 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : Optional[int] = {
"funnel-transformer/small": "https://huggingface.co/funnel-transform... | 85 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_mo... | 317 | 0 |
"""simple docstring"""
from __future__ import annotations
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
if days_between_payments <= 0:
raise ValueError('days_between_payments must be > 0' )
if daily_interest_rate < 0:
raise ValueError('daily_interest_r... | 86 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str ) -> list:
_snake_case : Optional[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for better performance - dynamic programming
_snake_case : Optiona... | 317 | 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,
... | 87 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 0 |
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 version
from torch imp... | 88 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 0 |
'''simple docstring'''
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accel... | 89 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : float , UpperCamelCase__ : float ) -> float:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def lowerCamelCase_... | 90 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 0 |
"""simple docstring"""
UpperCAmelCase_ : Dict = range(2, 20 + 1)
UpperCAmelCase_ : Union[str, Any] = [10**k for k in range(ks[-1] + 1)]
UpperCAmelCase_ : dict[int, dict[int, list[list[int]]]] = {}
def _A (__a , __a , __a , __a ) -> Any:
"""si... | 91 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 0 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _a ( ):
__lowerCAmelCase = ArgumentParser(
description=(
"PyTorch TPU distributed training launch... | 92 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 0 |
'''simple docstring'''
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ( __SCREAMING_SNAKE_CAS... | 93 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : int ):
"""simple docstring"""
while b:
a , a :Optional[Any] = b, a % b
return a
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ ... | 94 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 0 |
def _A ( SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
a__ : Tuple =0
# if input_string is "aba" than new_input_string become "a|b|a"
a__ : Union[str, Any] =""
a__ : int =""
# append each character + "... | 95 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"""configuration_unispeech""": ["""UNISPEECH_PRETRA... | 96 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 0 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_do... | 97 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 0 |
"""simple docstring"""
import functools
from typing import Any
def a_ ( lowerCamelCase , lowerCamelCase ):
# Validation
if not isinstance(lowerCamelCase , lowerCamelCase ) or len(lowerCamelCase ) == 0:
raise ValueError('the string should be not empty st... | 98 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
Be... | 99 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 0 |
"""simple docstring"""
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone imp... | 100 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 0 |
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