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 pytest
import datasets
# Import fixture modules as plugins
lowercase_ = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowerCamelCase ( __lowerCamelCase : Tuple , __lowerCamelCase : int ) ->List[An... | 58 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase_ = logging.getLogger(__name__)
if __name__ == "__m... | 58 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""facebook/data2vec-text-base""": """http... | 58 |
'''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 OptionalDep... | 58 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 58 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import... | 58 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
... | 58 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def lowerCamelCase ( __lowerCamelCase : str ) ->Optional[int]:
def decorator(__lowerCamelCase : int ):
_SCREAMING_SNAKE_CASE = getattr(__lowerCamelCase , """ha... | 58 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
lowercase_ = ["""small""", """medium""", """large"""]
lowercase_ = """lm_head.decoder.weight"""
lowercase_ = """lm_head.weight"""
def lowerCamelCase ( __lowerCamelCase : str... | 58 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase_ = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""": ... | 58 | 1 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stabl... | 58 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_config... | 58 | 1 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase_ = [
[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, 0, 0, 0, 0, 0],
[0, ... | 58 |
'''simple docstring'''
from collections.abc import Sequence
def lowerCamelCase ( __lowerCamelCase : Sequence[float] , __lowerCamelCase : bool = False ) ->float:
if not arr:
return 0
_SCREAMING_SNAKE_CASE = 0 if allow_empty_subarrays else float("""-... | 58 | 1 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_availab... | 58 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 58 | 1 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from trans... | 58 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""facebook/data2vec-text-base""": """http... | 58 | 1 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowercase_ = g... | 58 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.se... | 58 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class ... | 58 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def lowerCamelCase ( __lowerCamelCase : str ) ->str:
if not sentence:
return ""
_SCREAMING_SNAKE_CASE = dict(zip(__lowerCamelCase , __lowerCamelCase ) )
return lower_t... | 58 | 1 |
'''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 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/bridgetower-bas... | 58 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, 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 ... | 58 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerat... | 58 | 1 |
'''simple docstring'''
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowercase... | 58 |
'''simple docstring'''
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes -... | 58 | 1 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
Channel... | 58 |
'''simple docstring'''
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttent... | 58 | 1 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowercase_ = logging.getL... | 58 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
lowerc... | 58 | 1 |
'''simple docstring'''
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, Li... | 58 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class a_ ( snake_case_ ):
'''simple docstring'''
def snake_case_( self ) -> Tuple:
return [
{"col_1": 3, "col_2": "... | 58 | 1 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_u... | 58 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
fr... | 58 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""shi-labs/dinat-mini-in1k-224""": "... | 58 |
'''simple docstring'''
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
lowercase_ = """Usage of script: script_name <size_of_canvas:int>"""
lowercase_ = [0] * 100 + [1] * 10
random.shuffle(choice)
def lowerCamelCase ... | 58 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class a_ :
'''simple docstring'''
UpperCamelCase = 42 # [batch_size x 3]
UpperCamelCase = 42 # [batch_size x 3]
UpperCamelCase = 42 # [batch_siz... | 58 |
'''simple docstring'''
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase_ = HUGGINGFACE_HUB_CACHE
lowercase_ = """config.json"""
lowercase_ = """diffusion_pytorch_model.bin"""
lowercase_ = """diffusion_flax_model.msgpack"""
lowercase_ = """mod... | 58 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
lowercase_ = """2020.9.26"""
lowercase_ = """xcodz-dot, cclaus, dhruvmanila"""
def lowerCamelCase ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float , ... | 58 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( __lowerCamelCase : int ) ->list[int]:
if num <= 0:
_SCREAMING_SNAKE_CASE = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(__lowerCamelCas... | 58 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenize... | 58 |
'''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,
)
lowercase_ = {"""configuration_mbart""": ["... | 58 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
l... | 58 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase_ = logging.getLogger(__name__)
if __name__ == "__m... | 58 | 1 |
'''simple docstring'''
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class a_ ( snake_case_ ):
'''simple docstring'''
UpperCamelCase = (UnCLIPScheduler,)
def snake_case_( self , **A ) -> Any:
_SCR... | 58 |
'''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 OptionalDep... | 58 | 1 |
'''simple docstring'''
import math
def lowerCamelCase ( __lowerCamelCase : int ) ->bool:
_SCREAMING_SNAKE_CASE = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(__lowerCamelCase )
def lowerCamelCase ( __lowerCa... | 58 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import... | 58 | 1 |
'''simple docstring'''
lowercase_ = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
lowercase_ = [
999,
... | 58 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def lowerCamelCase ( __lowerCamelCase : str ) ->Optional[int]:
def decorator(__lowerCamelCase : int ):
_SCREAMING_SNAKE_CASE = getattr(__lowerCamelCase , """ha... | 58 | 1 |
'''simple docstring'''
def lowerCamelCase ( __lowerCamelCase : int = 10 , __lowerCamelCase : int = 1000 , __lowerCamelCase : bool = True ) ->int:
assert (
isinstance(__lowerCamelCase , __lowerCamelCase )
and isinstance(__lowerCamelCas... | 58 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase_ = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""": ... | 58 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""google/vivit-b-16x2-kinetics400""": (
"""https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
... | 58 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_config... | 58 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_ = {
"""configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TimesformerConfig"""],
}
try:
if not is_torch_availab... | 58 |
'''simple docstring'''
from collections.abc import Sequence
def lowerCamelCase ( __lowerCamelCase : Sequence[float] , __lowerCamelCase : bool = False ) ->float:
if not arr:
return 0
_SCREAMING_SNAKE_CASE = 0 if allow_empty_subarrays else float("""-... | 58 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 58 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 58 | 1 |
'''simple docstring'''
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase ( __lowerCamelCase : Dict , __lowerCamelCase : bool = True , __lowerCamelCase : float = math.inf , __lowerCamelCase : float ... | 58 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""facebook/data2vec-text-base""": """http... | 58 | 1 |
'''simple docstring'''
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_module... | 58 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.se... | 58 | 1 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (... | 58 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def lowerCamelCase ( __lowerCamelCase : str ) ->str:
if not sentence:
return ""
_SCREAMING_SNAKE_CASE = dict(zip(__lowerCamelCase , __lowerCamelCase ) )
return lower_t... | 58 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, log... | 58 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/bridgetower-bas... | 58 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2... | 58 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerat... | 58 | 1 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
f... | 58 |
'''simple docstring'''
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes -... | 58 | 1 |
'''simple docstring'''
from ....utils import logging
lowercase_ = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__( self , A , A=None , A=2048 ) -> Optional[int]:
_SCREAMING_SNAKE_CASE = config.__dict__
... | 58 |
'''simple docstring'''
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttent... | 58 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowercase_ = get_tests_dir("""fixtu... | 58 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
lowerc... | 58 | 1 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class a_ ( snake_case_ ):
'''simple docstring'''
UpperCamelCase = (EulerDiscreteScheduler,)
UpperCamelC... | 58 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class a_ ( snake_case_ ):
'''simple docstring'''
def snake_case_( self ) -> Tuple:
return [
{"col_1": 3, "col_2": "... | 58 | 1 |
'''simple docstring'''
import numpy as np
def lowerCamelCase ( __lowerCamelCase : np.ndarray ) ->np.ndarray:
return 1 / (1 + np.exp(-vector ))
def lowerCamelCase ( __lowerCamelCase : np.ndarray ) ->np.ndarray:
return vector * sigmoid(__lowerCamelCase ... | 58 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
fr... | 58 | 1 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
UpperCAmelCase__ = logging.get_logger(__name__)
class lowercase_ ( lowercase ):
'''simple docstring'''
def __init__( self ... | 0 |
'''simple docstring'''
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
lowercase_ = """Usage of script: script_name <size_of_canvas:int>"""
lowercase_ = [0] * 100 + [1] * 10
random.shuffle(choice)
def lowerCamelCase ... | 58 | 0 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transforme... | 1 |
'''simple docstring'''
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase_ = HUGGINGFACE_HUB_CACHE
lowercase_ = """config.json"""
lowercase_ = """diffusion_pytorch_model.bin"""
lowercase_ = """diffusion_flax_model.msgpack"""
lowercase_ = """mod... | 58 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterM... | 2 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( __lowerCamelCase : int ) ->list[int]:
if num <= 0:
_SCREAMING_SNAKE_CASE = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(__lowerCamelCas... | 58 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ ):
'''simple docstring'''
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case_... | 3 |
'''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,
)
lowercase_ = {"""configuration_mbart""": ["... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
__snake_case =[
[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,... | 4 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase_ = logging.getLogger(__name__)
if __name__ == "__m... | 58 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():
raise Opti... | 5 |
'''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 OptionalDep... | 58 | 0 |
import unittest
import numpy as np
def __lowerCAmelCase ( a__ , a__ , a__ , a__ = None , ) -> np.ndarray:
__a = np.shape(a__ )
__a = np.shape(a__ )
__a = np.shape(a__ )
if shape_a[0] != shape_b[0]:
__a ... | 6 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import... | 58 | 0 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_au... | 7 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def lowerCamelCase ( __lowerCamelCase : str ) ->Optional[int]:
def decorator(__lowerCamelCase : int ):
_SCREAMING_SNAKE_CASE = getattr(__lowerCamelCase , """ha... | 58 | 0 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():... | 8 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase_ = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""": ... | 58 | 0 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
__lowerCAmelCase : Union[str, Any] ={'tokenization_tapex': ['TapexTokenizer']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
__lowerCAmelCase : int =_LazyModule(__name__, globals... | 9 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_config... | 58 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowerCAmelCase_ ( __a ) -> Union[str, Any]:
"""simple docstring"""
def is_in_circle(__a , __a ) -> bool:
lowerCamelCase__: Tuple =sqrt((x... | 10 |
'''simple docstring'''
from collections.abc import Sequence
def lowerCamelCase ( __lowerCamelCase : Sequence[float] , __lowerCamelCase : bool = False ) ->float:
if not arr:
return 0
_SCREAMING_SNAKE_CASE = 0 if allow_empty_subarrays else float("""-... | 58 | 0 |
def _UpperCAmelCase (UpperCamelCase__ : int ):
if num < 0:
return False
_A : int = num
_A : int = 0
while num > 0:
_A : Optional[Any] = rev_num * 10 + (num % 10)
num //= 10... | 11 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 58 | 0 |
UpperCAmelCase_ = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .la... | 12 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""facebook/data2vec-text-base""": """http... | 58 | 0 |
def A_ ( _UpperCAmelCase , _UpperCAmelCase ):
if discount_rate < 0:
raise ValueError("Discount rate cannot be negative" )
if not cash_flows:
raise ValueError("Cash flows list cannot be empty" )
SCREAMING_SNAKE_CASE_: Any = sum(
cash_f... | 13 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.se... | 58 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determ... | 14 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def lowerCamelCase ( __lowerCamelCase : str ) ->str:
if not sentence:
return ""
_SCREAMING_SNAKE_CASE = dict(zip(__lowerCamelCase , __lowerCamelCase ) )
return lower_t... | 58 | 0 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_co... | 15 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/bridgetower-bas... | 58 | 0 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import Conf... | 16 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerat... | 58 | 0 |
"""simple docstring"""
def _A ( UpperCamelCase_ : float, UpperCamelCase_ : float) -> float:
'''simple docstring'''
if mass < 0:
raise ValueError("The mass of a body cannot be negative")
return 0.5 * mass * abs(UpperCamelCase_) * abs(UpperCamelCase_)
if __name__ =... | 17 |
'''simple docstring'''
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes -... | 58 | 0 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ... | 18 |
'''simple docstring'''
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttent... | 58 | 0 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
... | 19 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
lowerc... | 58 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase : Dict = {
"""configuration_resnet""": ["""RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ResNetConfig""",... | 20 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class a_ ( snake_case_ ):
'''simple docstring'''
def snake_case_( self ) -> Tuple:
return [
{"col_1": 3, "col_2": "... | 58 | 0 |
from manim import *
class _lowerCamelCase( _a ):
def UpperCamelCase ( self) -> List[str]:
"""simple docstring"""
_lowercase : Union[str, Any] = Rectangle(height=0.5, width=0.5)
_lowercase : List[Any] ... | 21 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
fr... | 58 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArgument... | 22 |
'''simple docstring'''
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
lowercase_ = """Usage of script: script_name <size_of_canvas:int>"""
lowercase_ = [0] * 100 + [1] * 10
random.shuffle(choice)
def lowerCamelCase ... | 58 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
... | 23 |
'''simple docstring'''
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase_ = HUGGINGFACE_HUB_CACHE
lowercase_ = """config.json"""
lowercase_ = """diffusion_pytorch_model.bin"""
lowercase_ = """diffusion_flax_model.msgpack"""
lowercase_ = """mod... | 58 | 0 |
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
snake_case_ = loggi... | 24 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( __lowerCamelCase : int ) ->list[int]:
if num <= 0:
_SCREAMING_SNAKE_CASE = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(__lowerCamelCas... | 58 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import l... | 25 |
'''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,
)
lowercase_ = {"""configuration_mbart""": ["... | 58 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging
... | 26 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase_ = logging.getLogger(__name__)
if __name__ == "__m... | 58 | 0 |
'''simple docstring'''
from typing import Any
class __UpperCamelCase :
def __init__( self , __a ):
'''simple docstring'''
__a : Optional[int] = data
__a : List[Any] = None
def __repr__( self ):
'''si... | 27 |
'''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 OptionalDep... | 58 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase : List[str] = logging.get_logger(__name__)
_lowerCamelCase : ... | 28 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import... | 58 | 0 |
import unittest
import numpy as np
import requests
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... | 29 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def lowerCamelCase ( __lowerCamelCase : str ) ->Optional[int]:
def decorator(__lowerCamelCase : int ):
_SCREAMING_SNAKE_CASE = getattr(__lowerCamelCase , """ha... | 58 | 0 |
import csv
import tweepy
# Twitter API credentials
__a = ''
__a = ''
__a = ''
__a = ''
def a ( snake_case__: str ):
'''simple docstring'''
# authorize twitter, initialize tweepy
lowercase_ = tweepy.OAuthHandler(snak... | 30 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase_ = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""": ... | 58 | 0 |
'''simple docstring'''
import math
import os
import sys
def UpperCamelCase_ ( _UpperCAmelCase : str ) -> str:
"""simple docstring"""
_UpperCAmelCase : List[str] = ""
try:
with open(_UpperCAmelCase , "rb" ) as binary_file... | 31 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_config... | 58 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, B... | 32 |
'''simple docstring'''
from collections.abc import Sequence
def lowerCamelCase ( __lowerCamelCase : Sequence[float] , __lowerCamelCase : bool = False ) ->float:
if not arr:
return 0
_SCREAMING_SNAKE_CASE = 0 if allow_empty_subarrays else float("""-... | 58 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__A : List[Any] = {
'''configuration_gpt_neo''': ['''GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoConfig'''... | 33 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 58 | 0 |
'''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
A ='\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n author={Yo... | 34 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""facebook/data2vec-text-base""": """http... | 58 | 0 |
'''simple docstring'''
def __snake_case( _lowerCAmelCase , _lowerCAmelCase ) -> int:
snake_case__ : Union[str, Any] = """"""
for i in table:
res += inp[i - 1]
return res
def __snake_case( _lowerCAmelCase ) -> List[Any]:
retu... | 35 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.se... | 58 | 0 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Union[str, Any] = AutoConfig.from_pretra... | 36 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def lowerCamelCase ( __lowerCamelCase : str ) ->str:
if not sentence:
return ""
_SCREAMING_SNAKE_CASE = dict(zip(__lowerCamelCase , __lowerCamelCase ) )
return lower_t... | 58 | 0 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
_lowerCAmelCase = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def _SCREAMING_SNAKE_CASE... | 37 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/bridgetower-bas... | 58 | 0 |
from __future__ import annotations
from typing import Any
class _SCREAMING_SNAKE_CASE ( _a ):
pass
class _SCREAMING_SNAKE_CASE :
def __init__( self : List[Any] , __lowerCamelCase : Any ):
UpperCamelCase :Any = data
UpperCamelCase :Node | N... | 38 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerat... | 58 | 0 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_nu... | 39 |
'''simple docstring'''
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes -... | 58 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus impo... | 40 |
'''simple docstring'''
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttent... | 58 | 0 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from ... | 41 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
lowerc... | 58 | 0 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#... | 42 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class a_ ( snake_case_ ):
'''simple docstring'''
def snake_case_( self ) -> Tuple:
return [
{"col_1": 3, "col_2": "... | 58 | 0 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
__lowercase = '''http://www.mocksite.com/file1.txt'''
__lower... | 43 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
fr... | 58 | 0 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def SCREAMING_SNAKE_CASE ( ) -> str:
_lowerCAmelCase : Optional[Any] = ArgumentParser(... | 44 |
'''simple docstring'''
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
lowercase_ = """Usage of script: script_name <size_of_canvas:int>"""
lowercase_ = [0] * 100 + [1] * 10
random.shuffle(choice)
def lowerCamelCase ... | 58 | 0 |
"""simple docstring"""
import fire
from utils import calculate_rouge, save_json
def lowercase ( lowerCAmelCase__ : Tuple , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str]=None , **lowerCAmelCase__ : Dict ) -> int:
__a = ... | 45 |
'''simple docstring'''
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase_ = HUGGINGFACE_HUB_CACHE
lowercase_ = """config.json"""
lowercase_ = """diffusion_pytorch_model.bin"""
lowercase_ = """diffusion_flax_model.msgpack"""
lowercase_ = """mod... | 58 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"junnyu/ro... | 46 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( __lowerCamelCase : int ) ->list[int]:
if num <= 0:
_SCREAMING_SNAKE_CASE = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(__lowerCamelCas... | 58 | 0 |
'''simple docstring'''
import os
def _lowerCAmelCase ( _UpperCamelCase : Union[str, Any] ) -> Optional[Any]:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =len(grid[0] )
_SCREAMING_SNAKE_CASE =len(_UpperCamelCase )
_SCREAMING_SNAKE... | 47 |
'''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,
)
lowercase_ = {"""configuration_mbart""": ["... | 58 | 0 |
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
SCREAMING_SNAKE_CASE__ : Tuple = logging.get... | 48 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase_ = logging.getLogger(__name__)
if __name__ == "__m... | 58 | 0 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class _A ( nn.Module ):
UpperCamelCase__ : int
UpperCamelCase__ : jnp.dtype = jnp.floataa
def _lowerCamelCase ( self : List[str]):
'''simple docstring'''
__... | 49 |
'''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 OptionalDep... | 58 | 0 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCAmelCase ( __UpperCamelCase ):
UpperCAmelCase__ = """M-CLIP"""
def __init__( self : Optional[Any] , UpperCAmelCase : Union[str, Any]=1024 , UpperCAmelCas... | 50 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import... | 58 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def A (__A : Dict ) -> List[Any]:
"""simple docstring"""
UpperCAmelCase_ = S... | 51 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def lowerCamelCase ( __lowerCamelCase : str ) ->Optional[int]:
def decorator(__lowerCamelCase : int ):
_SCREAMING_SNAKE_CASE = getattr(__lowerCamelCase , """ha... | 58 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
... | 52 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase_ = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""": ... | 58 | 0 |
'''simple docstring'''
import math
import sys
def lowercase__ ( __lowercase : str ) -> str:
"""simple docstring"""
__UpperCamelCase = ''
try:
with open(__lowercase , 'rb' ) as binary_file:
__UpperCamelCase ... | 53 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_config... | 58 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def UpperCAmelCase__ (lo... | 54 |
'''simple docstring'''
from collections.abc import Sequence
def lowerCamelCase ( __lowerCamelCase : Sequence[float] , __lowerCamelCase : bool = False ) ->float:
if not arr:
return 0
_SCREAMING_SNAKE_CASE = 0 if allow_empty_subarrays else float("""-... | 58 | 0 |
'''simple docstring'''
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
a_ : int = [
# (stable-diffusion, HF Diffusers)
("""time_embed.0.weight""", """... | 55 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class a :
def __init__( self : Union[str, Any] , lowercase_ : int , lowercase_ : MutableSequence[float] ):
if len(lowercase_ ) != deg... | 56 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""facebook/data2vec-text-base""": """http... | 58 | 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.org/licenses/LICENSE-2.0... | 57 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.se... | 58 | 0 |
def UpperCamelCase ( __lowerCamelCase : int ):
snake_case : Optional[Any] = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def UpperCamelCase ( __lowerCamelCase : int = 5000 ):
snake_case : Optional[Any] = [(i *... | 59 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def lowerCamelCase ( __lowerCamelCase : str ) ->str:
if not sentence:
return ""
_SCREAMING_SNAKE_CASE = dict(zip(__lowerCamelCase , __lowerCamelCase ) )
return lower_t... | 58 | 0 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def _snake_case ( _snake_case : int = 1000000 , _snake_case : int = 10 ):
lowerCAmelCase : defaultdict = defaultdict(_snake_case )
for outer_width in range(3 , (t_limit //... | 60 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/bridgetower-bas... | 58 | 0 |
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