code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int , UpperCamelCase__: int ):
SCREAMING_SNAKE_CASE__ = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
SCREAMING_SNAKE_CASE__ = n - k
# Calculate C(n,k)
for i in range(__U... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = "timm_backbone"
def __init__( self :Union[str, Any] ... | 59 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeBertConfig',
'SqueezeBertOnn... | 700 |
from math import pow, sqrt
def SCREAMING_SNAKE_CASE__ ( *UpperCamelCase__: float ):
SCREAMING_SNAKE_CASE__ = len(UpperCamelCase__ ) > 0 and all(value > 0.0 for value in values )
return result
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: ... | 59 | 0 |
'''simple docstring'''
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Optional[Any] , UpperCamelCase__: Optional[Any] ):
SCREAMING_SNAKE_CASE__ = ... | 701 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'shi-labs/nat-mini-in1k-224': 'https://hugg... | 59 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int , UpperCamelCase__: int ):
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
raise ValueError("""partiti... | 702 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 59 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
ViTHybri... | 703 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
def __init__( self :List[Any] , *__A :Tuple , ... | 59 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("""only integers accepted as input""" )
else:
SCREAMING_SNAKE_CASE__ = str(abs(_lowerCamelCase ) )
SCREAMING_SNAKE_CASE__... | 704 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
@require_torch
... | 59 | 0 |
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Dict , UpperCamelCase__: Optional[Any] ):
SCREAMING_SNAKE_CASE__ = int(UpperCamelCase__ )
assert noofclusters < len(UpperCamelCase__ )
... | 705 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl import CORPUS... | 59 | 0 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_availab... | 706 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
... | 59 | 0 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = '▁'
_lowerCamelCase ... | 707 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 59 | 0 |
'''simple docstring'''
from torch import nn
class UpperCamelCase_ ( nn.Module ):
def __init__( self :List[Any] , __A :Tuple , __A :Optional[int] ) -> str:
"""simple docstring"""
super().__init__()
SCREAMING_SNA... | 708 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCamelCase = logging.getLogger(__name__)
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description="""Pr... | 59 | 0 |
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load_dataset... | 709 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list[float]] ):
SCREAMING_SNAKE_CASE__ = []
for data in source_data:
for i, el in enumerate(UpperCamelCase__ ):
if len(UpperCamelCase__ ) < i + 1:
data_lists.append([] )
data_lists[i].append(fl... | 59 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/config.json''',
# See all XGLM models at https://huggin... | 710 |
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__: Dict , **UpperCamelCase__: Any ):
warnings.warn(
(f'... | 59 | 0 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
require_torc... | 711 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_... | 59 | 0 |
# 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
#
# Unless required b... | 712 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils im... | 59 | 0 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = (CMStochasticIterativeScheduler,)
lowerCamelCase_ ... | 713 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/google/pix2struct-textcaps... | 59 | 0 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
... | 714 |
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 UpperCamelCase_ ( unittest.TestCase ):
def ... | 59 | 0 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CONFIG_A... | 59 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase_ ( __snake_case ):
lowerCamelCase_ ... | 716 |
import inspect
import unittest
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self :str ) -> Union[str, Any]:
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
assert... | 59 | 0 |
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__ ( ):
SCREAMING_SNAKE_CASE__ = ArgumentParser(
description=(
"""PyTorch TPU distribu... | 717 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 59 | 0 |
'''simple docstring'''
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import GradientAccu... | 718 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 59 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torc... | 719 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase__ )
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = fi... | 59 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLImgaImgPipeline,
UNeta... | 720 |
# 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
#
# Unless required by app... | 59 | 0 |
from math import pi, sqrt, tan
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: float ):
if side_length < 0:
raise ValueError("""surface_area_cube() only accepts non-negative values""" )
return 6 * side_length**2
def SCREAMING_SNAKE_CASE__ ( UpperCam... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = "timm_backbone"
def __init__( self :Union[str, Any] ... | 59 | 0 |
_lowerCamelCase = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
_lowerCamelCase = [{'type... | 700 |
from math import pow, sqrt
def SCREAMING_SNAKE_CASE__ ( *UpperCamelCase__: float ):
SCREAMING_SNAKE_CASE__ = len(UpperCamelCase__ ) > 0 and all(value > 0.0 for value in values )
return result
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: ... | 59 | 0 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
_lowerCamelCase = {
'facebook/maskformer-swin-base... | 701 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'shi-labs/nat-mini-in1k-224': 'https://hugg... | 59 | 0 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Optional[int] , UpperCamelCase__: Tuple=() , Up... | 702 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 59 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: str = 1 , UpperCamelCase__: Optional[Any] = 1_000 ):
SCREAMING_SNAKE_CASE__ = 1
SCREAMING_SNAKE_CASE__ = 0
for divide_by_number in range(lowerCAmelCase_ , digit + 1 ):
SCREAMING_SNAKE_CASE__ = ... | 703 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
def __init__( self :List[Any] , *__A :Tuple , ... | 59 | 0 |
_lowerCamelCase = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
_lowerCamelCase = ['a', 'b', 'c', 'd', 'e']
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Optional[int] , UpperCamelCase__: List[str] , UpperCamelCase__: Optional[in... | 704 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
@require_torch
... | 59 | 0 |
import operator as op
_lowerCamelCase = 'scaler.pt'
_lowerCamelCase = 'pytorch_model'
_lowerCamelCase = 'random_states'
_lowerCamelCase = 'optimizer'
_lowerCamelCase = 'scheduler'
_lowerCamelCase = 'pytorch_model.bin'
_lowerCamelCase = 'pytorch_model.bin.i... | 705 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl import CORPUS... | 59 | 0 |
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dime... | 706 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
... | 59 | 0 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class UpperCamelCa... | 707 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 59 | 0 |
'''simple docstring'''
# using dfs for finding eulerian path traversal
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Union[str, Any] , UpperCamelCase__: List[str] , UpperCamelCase__: List[Any] , UpperCamelCase__: List[str]=None ):
SCREAM... | 708 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCamelCase = logging.getLogger(__name__)
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description="""Pr... | 59 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: List[str] ):
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
SCREAMING_SNAKE_CASE__ = 0
while number:
# This way we ... | 709 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list[float]] ):
SCREAMING_SNAKE_CASE__ = []
for data in source_data:
for i, el in enumerate(UpperCamelCase__ ):
if len(UpperCamelCase__ ) < i + 1:
data_lists.append([] )
data_lists[i].append(fl... | 59 | 0 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_lowe... | 710 |
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__: Dict , **UpperCamelCase__: Any ):
warnings.warn(
(f'... | 59 | 0 |
from manim import *
class UpperCamelCase_ ( SCREAMING_SNAKE_CASE_ ):
def _snake_case ( self :Union[str, Any] ) -> List[str]:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = Rectangle(height=0.5 , width=0.5 )
SCREAMIN... | 711 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_... | 59 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: str , UpperCamelCase__: int ):
return [sentence[i : i + ngram_size] for i in range(len(lowerCamelCase_ ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
testmod() | 712 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils im... | 59 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int , UpperCamelCase__: int ):
return number | (1 << position)
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int , UpperCamelCase__: int ):
return number ... | 713 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/google/pix2struct-textcaps... | 59 | 0 |
import pprint
import requests
_lowerCamelCase = 'https://zenquotes.io/api'
def SCREAMING_SNAKE_CASE__ ( ):
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def SCREAMING_SNAKE_CASE__ ( ):
return requests.get(API_ENDPOINT_URL + """/random""" ... | 714 |
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 UpperCamelCase_ ( unittest.TestCase ):
def ... | 59 | 0 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
to_channel_dime... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CONFIG_A... | 59 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int ):
if isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise TypeError("""\'float\' object cannot be interpreted as an integer""" )
if isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise TypeError("""\... | 716 |
import inspect
import unittest
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self :str ) -> Union[str, Any]:
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
assert... | 59 | 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... | 717 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 59 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
_lowerCamelCase = 1.054571817e-34 # unit of ℏ : J * s
_lowerCamelCase = 3e8 # unit of c : m * s^-1
def ... | 718 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 59 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int = 10 , UpperCamelCase__: int = 22 ):
SCREAMING_SNAKE_CASE__ = range(1 , lowercase_ )
SCREAMING_SNAKE_CASE__ = range(1 , lowercase_ )
return sum(
1 for power in powers for base in bas... | 719 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase__ )
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = fi... | 59 | 0 |
_lowerCamelCase = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', 'U': '..-',
'V': '...-', 'W': ... | 720 |
# 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
#
# Unless required by app... | 59 | 0 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list[float]] ):
SCREAMING_SNAKE_CASE__ = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementa... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = "timm_backbone"
def __init__( self :Union[str, Any] ... | 59 | 0 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase_ ( snake_case_ ):
lowerCamelCase_ = (EulerDiscreteScheduler,)
lowerCamelCase_ = 10... | 700 |
from math import pow, sqrt
def SCREAMING_SNAKE_CASE__ ( *UpperCamelCase__: float ):
SCREAMING_SNAKE_CASE__ = len(UpperCamelCase__ ) > 0 and all(value > 0.0 for value in values )
return result
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: ... | 59 | 0 |
'''simple docstring'''
class UpperCamelCase_ :
def __init__( self :Optional[Any] ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {}
def _snake_case ( self :List[Any] ) -> str:
"""simple docstring"... | 701 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'shi-labs/nat-mini-in1k-224': 'https://hugg... | 59 | 0 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requir... | 702 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 59 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableU... | 703 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
def __init__( self :List[Any] , *__A :Tuple , ... | 59 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_jukebox': [
'JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP',
'JukeboxConfig',
'JukeboxPriorConfig',
'JukeboxVQVAEConfig',
... | 704 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
@require_torch
... | 59 | 0 |
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,
)
_lowerCamelCase = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""", ... | 705 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl import CORPUS... | 59 | 0 |
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision.transforms.functional... | 706 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
... | 59 | 0 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'vocab_file': 'vocab.txt',
'merges_file': 'bpe.... | 707 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 59 | 0 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import Paddi... | 708 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCamelCase = logging.getLogger(__name__)
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description="""Pr... | 59 | 0 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pi... | 709 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list[float]] ):
SCREAMING_SNAKE_CASE__ = []
for data in source_data:
for i, el in enumerate(UpperCamelCase__ ):
if len(UpperCamelCase__ ) < i + 1:
data_lists.append([] )
data_lists[i].append(fl... | 59 | 0 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Optional[int] , UpperCamelCase__: Any , UpperCamelCase__: str , UpperCamelCase__: List[Any]=5 ):
# Adapted from https:... | 710 |
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__: Dict , **UpperCamelCase__: Any ):
warnings.warn(
(f'... | 59 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_ID... | 711 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_... | 59 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCamelCase = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV2Config',
'MobileNetV2OnnxC... | 712 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils im... | 59 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {}
try:
if not is_sentencepiece_available():
raise Option... | 713 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/google/pix2struct-textcaps... | 59 | 0 |
_lowerCamelCase = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
_lowerCamelCase = ['a', 'b', 'c', 'd', 'e']
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Any , UpperCamelCase__: Tuple , UpperCamelCase__: List[str] ):
SCREAMI... | 714 |
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 UpperCamelCase_ ( unittest.TestCase ):
def ... | 59 | 0 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
SCREAMING_SNAKE_CASE__ = parser.add_subparsers... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CONFIG_A... | 59 | 0 |
from __future__ import annotations
from collections.abc import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable[[int | float], int | float] , UpperCamelCase__: int | float , UpperCamelCase__: int | float , UpperCamelCase__: int = 100 ... | 716 |
import inspect
import unittest
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self :str ) -> Union[str, Any]:
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
assert... | 59 | 0 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import ... | 717 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 59 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class UpperCamelCase_ ( SCREAMING_SNAKE_CASE__ ):
lowerCamelCase_ = ["image_processor", "feature_extractor"]
lowerCamelCase_ = "TvltImageProcessor"
lowerCamelCase_ ... | 718 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 59 | 0 |
from __future__ import annotations
_lowerCamelCase = '#'
class UpperCamelCase_ :
def __init__( self :Optional[int] ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {}
def _snake_case ( self :str , ... | 719 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase__ )
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = fi... | 59 | 0 |
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
_lowerCamelCase = TypeVar('T')
class UpperCamelCase_ ( Generic[T] ):
def __init__( self :Optional[Any] , __A :Tuple = True ) -> str:
"""simp... | 720 |
# 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
#
# Unless required by app... | 59 | 0 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import ... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = "timm_backbone"
def __init__( self :Union[str, Any] ... | 59 | 0 |
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_lowerCamelCase = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: List[str] ):
if isinstance(_lowerCAmelCase , np.ndarray ... | 700 |
from math import pow, sqrt
def SCREAMING_SNAKE_CASE__ ( *UpperCamelCase__: float ):
SCREAMING_SNAKE_CASE__ = len(UpperCamelCase__ ) > 0 and all(value > 0.0 for value in values )
return result
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: ... | 59 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_... | 701 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'shi-labs/nat-mini-in1k-224': 'https://hugg... | 59 | 0 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
... | 702 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 59 | 0 |
from __future__ import annotations
from collections import Counter
from random import random
class UpperCamelCase_ :
def __init__( self :Dict ) -> Tuple:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {}
def _snake_case ( self ... | 703 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
def __init__( self :List[Any] , *__A :Tuple , ... | 59 | 0 |
from __future__ import annotations
class UpperCamelCase_ :
def __init__( self :Optional[int] , __A :int ) -> None:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = order
# a_{0} ... a_{k}
SCREAMING_SNAKE_CASE__ = ... | 704 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
@require_torch
... | 59 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list] ):
SCREAMING_SNAKE_CASE__ = current_set.copy()
for row_index, row in enumerate(_lowerCamelCase ):
SCREAMING_SNAKE_CASE__ = row[0]
for column_index, column in enumerate(_lowerCamelCase ):
if mag... | 705 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl import CORPUS... | 59 | 0 |
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
_lowerCamelCase = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
"text-classification",
"... | 706 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
... | 59 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
_lowerCamelCase = {
'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
'albert-large-v1': 'https://huggingface.co/al... | 707 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 59 | 0 |
'''simple docstring'''
import string
from math import logaa
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: str , UpperCamelCase__: str ):
SCREAMING_SNAKE_CASE__ = document.translate(
str.maketrans("""""" , """""" , string.punctuation ) ... | 708 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCamelCase = logging.getLogger(__name__)
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description="""Pr... | 59 | 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
_lowerCamelCase = 'http://www.mocksite.com/file1.txt'
_low... | 709 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list[float]] ):
SCREAMING_SNAKE_CASE__ = []
for data in source_data:
for i, el in enumerate(UpperCamelCase__ ):
if len(UpperCamelCase__ ) < i + 1:
data_lists.append([] )
data_lists[i].append(fl... | 59 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {'vocab_file': 'spm_char.mo... | 710 |
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__: Dict , **UpperCamelCase__: Any ):
warnings.warn(
(f'... | 59 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Optional[int] , UpperCamelCase__: Optional[int] , Uppe... | 711 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_... | 59 | 0 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
_lowerCamelCase = '\\n@inproceedings{snover-etal-2006-study,\n title = "A Study of Translation Edit Rate with Targeted Human Annotation",\n author = "Snover, Matthew and\n Dorr, Bonnie and\n ... | 712 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils im... | 59 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InformerC... | 713 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/google/pix2struct-textcaps... | 59 | 0 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_com... | 714 |
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 UpperCamelCase_ ( unittest.TestCase ):
def ... | 59 | 0 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
def __init__( self :str , *__A :Any , **__A :Dict )... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CONFIG_A... | 59 | 0 |
import math
import tensorflow as tf
from packaging import version
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Dict ):
SCREAMING_SNAKE_CASE__ = tf.convert_to_tensor(UpperCamelCase__ )
SCREAMING_SNAKE_CASE__ = 0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0 ... | 716 |
import inspect
import unittest
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self :str ) -> Union[str, Any]:
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
assert... | 59 | 0 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
_lowerCamelCase = version.parse(version.parse(torch.__versi... | 717 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 59 | 0 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE__ ( ):
with open(os.path.dirname(snake_case_ ) + """/grid.txt""" ) as f:
SCREAMING_SNAKE_CASE__ = [] # noqa: E741
for _ in range(20 ):
l.append([int(snake_case_ ) for x in f.readline().split()]... | 718 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 59 | 0 |
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def SCREAMING_SNAKE_CASE__ ( ... | 719 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase__ )
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = fi... | 59 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFXLMRobertaModel
@re... | 720 |
# 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
#
# Unless required by app... | 59 | 0 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_devic... | 721 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = "timm_backbone"
def __init__( self :Union[str, Any] ... | 59 | 0 |
_lowerCamelCase = '\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/transformers... | 700 |
from math import pow, sqrt
def SCREAMING_SNAKE_CASE__ ( *UpperCamelCase__: float ):
SCREAMING_SNAKE_CASE__ = len(UpperCamelCase__ ) > 0 and all(value > 0.0 for value in values )
return result
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: ... | 59 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list , UpperCamelCase__: list ):
_validate_point(UpperCamelCase__ )
_validate_point(UpperCamelCase__ )
if len(UpperCamelCase__ ) != len(UpperCamelCase__ ):
raise ValueError("""Both... | 701 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'shi-labs/nat-mini-in1k-224': 'https://hugg... | 59 | 0 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common import ... | 702 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 59 | 0 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 703 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
def __init__( self :List[Any] , *__A :Tuple , ... | 59 | 0 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self ... | 704 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
@require_torch
... | 59 | 0 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Optional[int] , UpperCamelCase__: Dict ):
SCREAMING_SNAKE_CASE... | 705 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl import CORPUS... | 59 | 0 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.r... | 706 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
... | 59 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.json',
# See all DP... | 707 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 59 | 0 |
'''simple docstring'''
import argparse
import gc
import json
import os
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
f... | 708 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCamelCase = logging.getLogger(__name__)
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description="""Pr... | 59 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'YituTech/conv-bert-base': 'https://huggingface.... | 709 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list[float]] ):
SCREAMING_SNAKE_CASE__ = []
for data in source_data:
for i, el in enumerate(UpperCamelCase__ ):
if len(UpperCamelCase__ ) < i + 1:
data_lists.append([] )
data_lists[i].append(fl... | 59 | 0 |
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: str , UpperCamelCase__: str , UpperCamelCase__: Optional[str] = None ):
if version.parse(h... | 710 |
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__: Dict , **UpperCamelCase__: Any ):
warnings.warn(
(f'... | 59 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.