code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 1 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 1 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)... | 638 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 1 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowercase__ = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.se... | 638 |
'''simple docstring'''
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... | 638 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 1 |
'''simple docstring'''
import argparse
import json
from tqdm import tqdm
def _UpperCamelCase ( ) -> List[str]:
'''simple docstring'''
snake_case : Tuple = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_pa... | 638 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 1 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> List[Any]:
'''simple docstring'''
def wrapper(*... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 1 |
'''simple docstring'''
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
lowercase__ = datasets.utils.logging.get_logger(__name__)
class snake_case__ ( folder_based_build... | 638 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> Dict: # noqa: E741
'''simple docstring'''
while r - l > 1:
snake... | 638 |
'''simple docstring'''
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
... | 638 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> float:
'''simple docstring'''
return sum(c * (x**i) for i, c in enumerate(SCREAMING_SNAKE_CASE__ ) )
def _UpperCam... | 638 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_... | 638 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Validate tha... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-1... | 638 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 1 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.seriali... | 638 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list:
'''simple docstring'''
snake_case : List[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for bet... | 638 |
'''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... | 638 | 1 |
'''simple docstring'''
import argparse
import json
import subprocess
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> Tuple:
'''simple docstring'''
snake_case : List[Any] = []
snake_case : Optional[int] ... | 638 |
'''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, ... | 638 | 1 |
'''simple docstring'''
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,
... | 638 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 1 |
'''simple docstring'''
import math
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
snake_case : List[Any] = len(SCREAMING_SNAKE_CASE__ )
snake_case : Any = int(math.fl... | 638 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"configuration_electra": ["ELECTR... | 638 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 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-... | 638 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 1 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDep... | 638 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 1 |
'''simple docstring'''
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate im... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 1 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transforme... | 638 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipeli... | 638 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowercase__ = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}... | 638 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
return number | (1 << position)
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> int... | 638 |
'''simple docstring'''
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... | 638 | 1 |
'''simple docstring'''
import os
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "matrix.txt" ) -> int:
'''simple docstring'''
with open(os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE__ ) , SCREAMING_SNAKE_CASE__ ) ) as in_file:
snake_case : Opt... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 1 |
'''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
lowercase__ = [
"Prosecutor: \"No videos were used in the crash investigation\" German papers say the... | 638 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 1 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAK... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> list[str]:
'''simple docstring'''
if partitions <= 0:
raise ValueError('''partitions must be a positive number!''' )
if pa... | 638 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 1 |
'''simple docstring'''
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class snake_case__ ... | 638 |
'''simple docstring'''
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
... | 638 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
lowercase__ = logging.get_logger(_... | 638 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 1 |
'''simple docstring'''
class snake_case__ :
"""simple docstring"""
def __init__( self : List[str] , UpperCamelCase__ : Optional[int] ) -> List[str]:
"""simple docstring"""
snake_case : Union[str, Any] = ar... | 638 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 1 |
'''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSa... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 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__ = {
"google... | 638 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 1 |
'''simple docstring'''
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.... | 638 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = False ) -> float:
'''simple docstring'''
if not arr:
return 0
snake_case : Any = 0 if allow_empty_subarr... | 638 |
'''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... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
lowercase__ = []
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> bool:
'''simple docstring'''
for i in range(len(SCREAMING_SNAKE_... | 638 |
'''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, ... | 638 | 1 |
'''simple docstring'''
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
... | 638 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
... | 638 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
SCREAMING_SNAKE_CASE__ : Optional[int] = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyN... | 0 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 0 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('''3.8'''):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
__snake_ca... | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def SCREAMING_SNAKE_CASE_ ( _snake_case :Dict ) -> str:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJ... | 2 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 0 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowerCAmelCase : Union[str, Any] = [
# tf -> hf
('/', '.'),
('l... | 3 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[int] = logging.get_logger(__name__)
__UpperCamelCase : Dict = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/... | 4 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 0 |
'''simple docstring'''
def A (__lowerCamelCase :List[Any] ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCAmelCase = len(__lowerCamelCase )
_lowerCAmelCase = max(__... | 5 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 0 |
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor... | 6 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 0 |
"""simple docstring"""
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 ... | 7 |
'''simple docstring'''
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... | 638 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
norm... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 0 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import Reg... | 9 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 0 |
from __future__ import annotations
from collections.abc import Callable
def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case = 100 , ):
_UpperCamelCase = x_start
_UpperCamelCase = fnc(__snake_case )
_UpperCamelCase = ... | 10 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 0 |
'''simple docstring'''
from math import sqrt
def lowerCAmelCase (__A = 1_000_000):
"""simple docstring"""
_a = 0
_a = 0
_a = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 ... | 11 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 0 |
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
lowerCamelCase__ : Optional[Any] = {
"""sample_size""": 3_2,
"""in_channels""": 3,
"""out_channels""": 3,
"""layers_per_bl... | 12 |
'''simple docstring'''
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
... | 638 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependency... | 13 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 0 |
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from trans... | 14 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 0 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging
fr... | 15 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 0 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def __a ( A__ : str = "laptop" ):
SCREAMING_SNAKE_CASE = F"https://www.amazon.in/laptop/s?k={product}"
SCREAMING_SNAKE_CASE = {
"Us... | 16 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 0 |
import datasets
UpperCAmelCase_ : str = '''\
@InProceedings{conneau2018xnli,
author = "Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
and Schwenk, Holger
... | 17 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 0 |
'''simple docstring'''
def __a(SCREAMING_SNAKE_CASE_ : bytes ):
'''simple docstring'''
return "".join([hex(SCREAMING_SNAKE_CASE_ )[2:].zfill(2 ).upper() for byte in list(SCREAMING_SNAKE_CASE_ )] )
def __a(SCREAMING_SNAKE_CASE_ : str ):
'''... | 18 |
'''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... | 638 | 0 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
_a = """examples/"""
_a = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compi... | 19 |
'''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, ... | 638 | 0 |
def _lowercase( __a : int = 100_0000 ):
a__ =[i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , __a ):
phi[j] -=... | 20 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 0 |
def lowerCAmelCase_ ( lowerCamelCase ):
__magic_name__ : List[Any] =[0] * len(lowerCamelCase )
__magic_name__ : Optional[Any] =[]
__magic_name__ : str =[1] * len(lowerCamelCase )
for values in graph.values():
for i ... | 21 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 0 |
'''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class A :
def __init__( self : Tuple , lowerCAmelCase_ : ... | 22 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 0 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
snake_case__ : Tuple = logging.get_logger(__name__)
def _snake_case (__lowercase , __lowercase):
UpperCamelCa... | 23 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _UpperCamelCase (_lowerCamelCase : Union[str, Any] , _lowerCa... | 24 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class _UpperCamelCase ( __A )... | 25 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
... | 26 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@re... | 27 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 0 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 0 |
"""simple docstring"""
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowercase ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,):
for nxt, d in graph[v]:... | 29 |
'''simple docstring'''
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... | 638 | 0 |
import os
from datetime import datetime as dt
from github import Github
__a = [
'good first issue',
'feature request',
'wip',
]
def lowerCamelCase__ ( ):
'''simple docstring'''
UpperCAmelCase_ : str = Github(os.environ['''GITHUB_TOKEN'''] )
Up... | 30 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 0 |
class lowerCamelCase_ : # Public class to implement a graph
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int , _lowerCAmelCase : int , _lowerCAmelCase : list[list[bool]] ):
SCREAMING_... | 31 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 0 |
from collections import defaultdict
from math import gcd
def A__ ( SCREAMING_SNAKE_CASE_ : int = 1_50_00_00 ) -> int:
"""simple docstring"""
_UpperCAmelCase = defaultdict(SCREAMING_SNAKE_CASE_ )
_UpperCAmelCase = 2
while 2 * euclid_... | 32 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 0 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
lowerCamelCase__ : Optional[int] = """
import os
"""
lowerCamelCase__ : Any = """
def foo():
import os
return False
"""
lowerCamelCase__ : Tuple ... | 33 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 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_ = {
'... | 34 |
'''simple docstring'''
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
... | 638 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ :str = {
'configuration_blip': [
'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BlipConfig',
'BlipTe... | 35 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 0 |
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.stable_diffusion import StableDif... | 36 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 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 is_torch_available():... | 37 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A_ : Dict = logging.get_logger(__name__)
A_ : Optional[Any] = {
"facebook/convn... | 38 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multi... | 39 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 0 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from ... | 40 |
'''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... | 638 | 0 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowerCAmelCase__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, ... | 41 |
'''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, ... | 638 | 0 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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 __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 0 |
from __future__ import annotations
from collections.abc import Generator
def _a ( ):
"""simple docstring"""
lowercase__ = {}
lowercase__ = 2
while True:
lowercase__ = factor_map.pop(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
if factor:
lower... | 43 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 0 |
'''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... | 44 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 0 |
from __future__ import annotations
def A ( lowercase__ : list[int] , lowercase__ : int ) -> list[int]:
UpperCamelCase__ :Tuple = 0
UpperCamelCase__ :Any = len(lowercase__ ) - 1
while i < j:
if nums[i] + nums[j] == target:
return [i, j]
elif nums[i] + nums[j] < ... | 45 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Dict = {'''configuration_yolos''': ['''YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YolosConfig''', '''YolosOnnxCo... | 46 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 0 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE__ = logging.get_logger('''transformers.models.speecht5''')
def UpperCAmelCase__ ( lowerCamelCase... | 47 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 0 |
'''simple docstring'''
from __future__ import annotations
def A ( UpperCamelCase_ : int = 4 ) -> list[list[int]]:
'''simple docstring'''
lowerCAmelCase__ = abs(UpperCamelCase_ ) or 4
return [[1 + x + y * row_size for x in range(UpperCamelCase_ )] for ... | 48 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 0 |
"""simple docstring"""
from maths.prime_factors import prime_factors
def lowercase__ ( snake_case_ :int ):
if not isinstance(snake_case_ , snake_case_ ):
__UpperCAmelCase = F'''Input value of [number={number}] must be an integer'''
raise TypeError(snake... | 49 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class UpperCamelCase__ (unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase_ ( s... | 50 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 0 |
'''simple docstring'''
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : str , a__ : List[Any] , a__ : Optional[Any] , a__ : int ):
UpperCAmelCase = name
UpperCAmelCase = ... | 51 |
'''simple docstring'''
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... | 638 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def __A ( a_ :Tuple) -> List[str]:
return choice(a_)
def __A ( a_ :list[int] , a_ :int) -> int:
__a : Optional[int] = random_pivot(a... | 52 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 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 is_torch_available... | 53 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 0 |
from math import ceil
def a__ ( lowercase__ , lowercase__ ):
'''simple docstring'''
UpperCAmelCase_ =list(range(0 , lowercase__ ) )
UpperCAmelCase_ =[item for sublist in list(device_map.values() ) for item in sublist]
... | 54 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE :List[str] = {
'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}
try:
if not is_torch_available():
raise ... | 55 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_a : List[Any] = logging.get_logger(__name__)
def _a (lowercase__ : Union[tf.Tensor, np.ndarray] ) -> List[int]:
"""simple doc... | 56 |
'''simple docstring'''
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
... | 638 | 0 |
from typing import Any
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , ) -> list:
_validation(
UpperCAmelCase__ , UpperCAmelCase__ , UpperC... | 57 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 0 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 ... | 58 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 0 |
import itertools
import string
from collections.abc import Generator, Iterable
def lowerCAmelCase_ ( __a , __a ) -> Generator[tuple[str, ...], None, None]:
"""simple docstring"""
lowerCamelCase__: Optional[int] =iter(__a )
while True:
lowerCamelC... | 59 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 0 |
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