code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
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,
normalize,
rescale,
resi... | 47 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowerCamelCase : Optional[int] = False
class A__ ( ... | 47 | 1 |
'''simple docstring'''
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.ut... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Any = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 47 | 1 |
'''simple docstring'''
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
lowerCamelCase : List[Any] = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\... | 47 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _lowerCAmelCase ( _UpperCamelCase : Dict , _UpperCamelCase : Any=False ) -> Optional[Any]:
"""simple docstring"""
... | 47 | 1 |
'''simple docstring'''
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
lowerCamelCase : Dict = collections.namedtuple("... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : int = {"configuration... | 47 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase : List[str] = logging.get_logger(__name__)
lowerCamelCase : List[Any] = ... | 47 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : str = {
"huggingface/time-series-transformer-tourism-monthly":... | 47 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowerCamelCase : Optional[int] = False
class A__ ( ... | 47 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowerCamelCase : List[Any] = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained ... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : list , _UpperCamelCase : int = 0 ) -> list:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =length or len(_UpperCamelCase )
_SCREAMING_SNAKE_CASE =False
for i i... | 47 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
"ut/deta": "https://huggingface.co/ut/deta/resol... | 47 | 1 |
'''simple docstring'''
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : Any = r"\n Args:\n ... | 47 |
'''simple docstring'''
import numpy as np
from PIL import Image
def _lowerCAmelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : int , _UpperCamelCase : int ) -> np.ndarray:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =n... | 47 | 1 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch... | 47 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCAmelCase ( ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =ArgumentPar... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _lowerCAmelCase ( _UpperCamelCase : float , _UpperCamelCase : float , _UpperCamelCase : bool = False ) ... | 47 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 47 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=A__ ):
A__ = ['torch', 'scipy']
def __init__( self : Optional[Any] , *_a : Any , **_a : Tuple ) -> Optional[Any]:
'''simple docstring... | 47 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowerCAmelCase ( _UpperCamelCase : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or num... | 47 | 1 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
@... | 47 |
'''simple docstring'''
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... | 47 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import C... | 47 |
'''simple docstring'''
import copy
import re
class A__ :
A__ = 'hp'
A__ = {}
A__ = None
@classmethod
def A ( cls : Optional[Any] , _a : Optional[Any] , _a : Any ) -> Union[str, Any]:
'''simple docstring'''
... | 47 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs
if is_torch_availa... | 47 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.f... | 47 | 1 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def _lowerCAmelCase ( _UpperCamelCase : Optional[int]="ro" , _UpperCamelCase : Optional[Any]="en" , _UpperCamelCase : List[str]="wmt16" , _UpperCamelCase : Union[s... | 47 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class A__ ( A__ , A__ ):
@register_to_config
def __init__( self ... | 47 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Any = logging.get_logger(__name__)
lowerCamelCase : Optional[Any] = {
"google/pix2struct-textcaps-base": (
... | 47 |
'''simple docstring'''
# Copyright 2021 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
#
# Unl... | 47 | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : str = logging.get_logger(__name__)
lowerCamelCase... | 47 |
'''simple docstring'''
class A__ :
def __init__( self : Union[str, Any] , _a : int ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =size
_SCREAMING_SNAKE_CASE =[0] * size
_SCREAMING_SNAKE_CASE =[0] * ... | 47 | 1 |
'''simple docstring'''
import numpy as np
from PIL import Image
def _lowerCAmelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : int , _UpperCamelCase : int ) -> np.ndarray:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =n... | 47 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowerCamelCase : Union[str, Any] = TypeVar("KT")
lowerCamelCase : Dict = TypeVar("VT")
class A__ ( Generic[KT, VT] ):
def __init__( self... | 47 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : List[str] = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/conf... | 47 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCamelCase : List[Any] = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import w... | 47 | 1 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class A__ ( A__ ):
def A ( self : Optional[Any] ) -> str:
'''simple docstring'''
return [
{"col_1": 3... | 47 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase : List[str] = logging.get_logger(__name__)
lowerCamelCase : List[Any] = ... | 47 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import Ba... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : int = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available()... | 47 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : str = {
"huggingface/time-series-transformer-tourism-monthly":... | 47 |
'''simple docstring'''
lowerCamelCase : Any = "\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"
low... | 47 | 1 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCAmelCase ( ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =ArgumentPar... | 47 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowerCamelCase : Optional[int] = False
class A__ ( ... | 47 | 1 |
'''simple docstring'''
from statistics import mean
import numpy as np
def _lowerCAmelCase ( _UpperCamelCase : list , _UpperCamelCase : list , _UpperCamelCase : list , _UpperCamelCase : int ) -> list:
"""simple docstring"""
... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Any = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 47 | 1 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import ... | 47 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _lowerCAmelCase ( _UpperCamelCase : Dict , _UpperCamelCase : Any=False ) -> Optional[Any]:
"""simple docstring"""
... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : Union[str, Any] ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE =[], []
while len(_UpperCamelCase ) > 1:
_SCREAMING_SNAKE_CASE , _S... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : int = {"configuration... | 47 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
... | 47 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : str = {
"huggingface/time-series-transformer-tourism-monthly":... | 47 | 1 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 47 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowerCamelCase : List[Any] = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained ... | 47 | 1 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
... | 47 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
"ut/deta": "https://huggingface.co/ut/deta/resol... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ran... | 47 |
'''simple docstring'''
import numpy as np
from PIL import Image
def _lowerCAmelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : int , _UpperCamelCase : int ) -> np.ndarray:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =n... | 47 | 1 |
'''simple docstring'''
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from tr... | 47 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCAmelCase ( ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =ArgumentPar... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : Dict ) -> List[Any]:
"""simple docstring"""
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2,... | 47 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class A__ :
def __init__( self : List[str] , _a : int = 6 ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =None
_SCREAMING_SNAKE_CASE ... | 47 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowerCAmelCase ( _UpperCamelCase : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or num... | 47 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def _lowerCAmelCase ( _UpperCamelCase : Callable , _UpperCamelCase : float , _UpperCamelCase : float , _UpperCamelCase : float , _UpperCamelCase : floa... | 47 |
'''simple docstring'''
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... | 47 | 1 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCamelCase : List[Any] = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import w... | 47 |
'''simple docstring'''
import copy
import re
class A__ :
A__ = 'hp'
A__ = {}
A__ = None
@classmethod
def A ( cls : Optional[Any] , _a : Optional[Any] , _a : Any ) -> Union[str, Any]:
'''simple docstring'''
... | 47 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils ... | 47 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.f... | 47 | 1 |
'''simple docstring'''
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowerCamelCase :... | 47 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class A__ ( A__ , A__ ):
@register_to_config
def __init__( self ... | 47 | 1 |
'''simple docstring'''
lowerCamelCase : List[str] = "\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://... | 47 |
'''simple docstring'''
# Copyright 2021 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
#
# Unl... | 47 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_comm... | 47 |
'''simple docstring'''
class A__ :
def __init__( self : Union[str, Any] , _a : int ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =size
_SCREAMING_SNAKE_CASE =[0] * size
_SCREAMING_SNAKE_CASE =[0] * ... | 47 | 1 |
'''simple docstring'''
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")
class A__ ... | 47 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowerCamelCase : Union[str, Any] = TypeVar("KT")
lowerCamelCase : Dict = TypeVar("VT")
class A__ ( Generic[KT, VT] ):
def __init__( self... | 47 | 1 |
'''simple docstring'''
from typing import List
import numpy as np
def _lowerCAmelCase ( _UpperCamelCase : dict ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE ={key: len(_UpperCamelCase ) for key, value in gen_kwargs.items() if isinstance(_UpperC... | 47 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCamelCase : List[Any] = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import w... | 47 | 1 |
'''simple docstring'''
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
lowerCamelCase : Any = logging.get_logger(__name__)
lowerCamelCase : Optional[int] = {
... | 47 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase : List[str] = logging.get_logger(__name__)
lowerCamelCase : List[Any] = ... | 47 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokeni... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : int = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available()... | 47 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A__ ( A__ ):
def __init__( self : str , ... | 47 |
'''simple docstring'''
lowerCamelCase : Any = "\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"
low... | 47 | 1 |
'''simple docstring'''
import os
def _lowerCAmelCase ( ) -> List[str]:
"""simple docstring"""
with open(os.path.dirname(_UpperCamelCase ) + '/grid.txt' ) as f:
_SCREAMING_SNAKE_CASE =[] # noqa: E741
for _ in range(20 ):
l.ap... | 47 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowerCamelCase : Optional[int] = False
class A__ ( ... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : str , _UpperCamelCase : int ) -> list[str]:
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(_UpperCamelCase ) - ngram_size + 1 )]
if __name__ == "__main... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Any = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 47 | 1 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRConte... | 47 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _lowerCAmelCase ( _UpperCamelCase : Dict , _UpperCamelCase : Any=False ) -> Optional[Any]:
"""simple docstring"""
... | 47 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : str = logging.get_logger(__name__)
lowerCamelCase : Dict = {
"googl... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : int = {"configuration... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : int = 1_00_00_00 ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =set(range(3 , _UpperCamelCase , 2 ) )
primes.add(2 )
for p in range(3 , _UpperCamelCas... | 47 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : str = {
"huggingface/time-series-transformer-tourism-monthly":... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _UpperCamelCase : list[int] , _UpperCamelCase : list[int] , _UpperCamelCase : int ) -> tuple[float, list[float]]:
"""simple docstring"""
_SCREAMING_SNAKE_CAS... | 47 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowerCamelCase : List[Any] = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained ... | 47 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
lowerCamelCase : Any = loggi... | 47 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
"ut/deta": "https://huggingface.co/ut/deta/resol... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : dict ) -> bool:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =set()
# To detect a back edge, keep track of vertices currently in the recursion stack
_SCREAMING_SNAKE_CASE =set(... | 47 |
'''simple docstring'''
import numpy as np
from PIL import Image
def _lowerCAmelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : int , _UpperCamelCase : int ) -> np.ndarray:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =n... | 47 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
... | 47 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCAmelCase ( ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =ArgumentPar... | 47 | 1 |
'''simple docstring'''
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils imp... | 47 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 47 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : Tuple = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
"configura... | 47 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowerCAmelCase ( _UpperCamelCase : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or num... | 47 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .toke... | 47 |
'''simple docstring'''
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... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _UpperCamelCase : str , _UpperCamelCase : str ) -> bool:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =get_failure_array(_UpperCamelCase )
# 2) Step thro... | 47 |
'''simple docstring'''
import copy
import re
class A__ :
A__ = 'hp'
A__ = {}
A__ = None
@classmethod
def A ( cls : Optional[Any] , _a : Optional[Any] , _a : Any ) -> Union[str, Any]:
'''simple docstring'''
... | 47 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORD... | 47 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.f... | 47 | 1 |
'''simple docstring'''
import sys
import turtle
def _lowerCAmelCase ( _UpperCamelCase : tuple[float, float] , _UpperCamelCase : tuple[float, float] ) -> tuple[float, float]:
"""simple docstring"""
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def ... | 47 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class A__ ( A__ , A__ ):
@register_to_config
def __init__( self ... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : int , _UpperCamelCase : int ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def _lowerCAmelCase ( ) -> None:
"""simple docs... | 47 |
'''simple docstring'''
# Copyright 2021 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
#
# Unl... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class A__ :
A__ = 42
A__ = None
A__ = None
def _lowerCAmelCase ( ) ... | 47 |
'''simple docstring'''
class A__ :
def __init__( self : Union[str, Any] , _a : int ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =size
_SCREAMING_SNAKE_CASE =[0] * size
_SCREAMING_SNAKE_CASE =[0] * ... | 47 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : List[Any] = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BridgeTower... | 47 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowerCamelCase : Union[str, Any] = TypeVar("KT")
lowerCamelCase : Dict = TypeVar("VT")
class A__ ( Generic[KT, VT] ):
def __init__( self... | 47 | 1 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
imp... | 47 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCamelCase : List[Any] = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import w... | 47 | 1 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedI... | 47 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase : List[str] = logging.get_logger(__name__)
lowerCamelCase : List[Any] = ... | 47 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Any = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : int = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available()... | 47 | 1 |
'''simple docstring'''
from collections import defaultdict
def _lowerCAmelCase ( _UpperCamelCase : str , _UpperCamelCase : str ) -> bool:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =first_str.lower().strip()
_SCREAMING_SNAKE_CASE ... | 47 |
'''simple docstring'''
lowerCamelCase : Any = "\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"
low... | 47 | 1 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
lowerCamelCase : int = Mapping[str, np.ndarray]
lowerCamelCase : Union[str, Any] = Mappi... | 47 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowerCamelCase : Optional[int] = False
class A__ ( ... | 47 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCase : Tuple = get_t... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Any = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 47 | 1 |
'''simple docstring'''
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
lowerCamelCas... | 47 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _lowerCAmelCase ( _UpperCamelCase : Dict , _UpperCamelCase : Any=False ) -> Optional[Any]:
"""simple docstring"""
... | 47 | 1 |
'''simple docstring'''
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 : Tuple = logging.get_logger(__name__)
lowerCamelCase : ... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : int = {"configuration... | 47 | 1 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Optional[int] = logging.get_logger(__name__)
lowerCamelCase : Tuple = {
"huggingface/autoformer-tourism-monthly": "https://hugg... | 47 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : str = {
"huggingface/time-series-transformer-tourism-monthly":... | 47 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diff... | 47 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowerCamelCase : List[Any] = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained ... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : str ) -> str:
"""simple docstring"""
return "".join(chr(ord(_UpperCamelCase ) - 32 ) if 'a' <= char <= 'z' else char for char in word )
if __name__ == "__main__":
from doctest import testmod... | 47 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
"ut/deta": "https://huggingface.co/ut/deta/resol... | 47 | 1 |
'''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
lowerCamelCase : Tuple = "1"
lowerCamelCase : Optional[Any] = "0"
lowerCamelCase : Dict = "1"
lowerCamelCase : List[str] = ort.SessionOptions()
lowerCamelCase : st... | 47 |
'''simple docstring'''
import numpy as np
from PIL import Image
def _lowerCAmelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : int , _UpperCamelCase : int ) -> np.ndarray:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =n... | 47 | 1 |
'''simple docstring'''
lowerCamelCase : Tuple = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def _lowerCAmelCase ( ) -> None:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =input('Enter message: ' )
_SCREAMING_SNAKE_CASE =input('Enter key [alphanumeric]:... | 47 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCAmelCase ( ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =ArgumentPar... | 47 | 1 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
lowerCamelCase : Optional[... | 47 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 47 | 1 |
'''simple docstring'''
from math import factorial
def _lowerCAmelCase ( _UpperCamelCase : int = 1_00 ) -> int:
"""simple docstring"""
return sum(int(_UpperCamelCase ) for x in str(factorial(_UpperCamelCase ) ) )
if __name__ == "__main__":
print(sol... | 47 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowerCAmelCase ( _UpperCamelCase : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or num... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def _lowerCAmelCase ( _UpperCamelCase : list[int] , _UpperCamelCase : list[int] , _UpperCamelCase : int ) -> list[int]:
"""simple docstring"""
_SCREAM... | 47 |
'''simple docstring'''
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... | 47 | 1 |
'''simple docstring'''
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class A__ ( A__ ):
def __init__( self : List[str] , _a : Optional[Any]="" , _a : Any="train" ) -> int:
'''simple docstring... | 47 |
'''simple docstring'''
import copy
import re
class A__ :
A__ = 'hp'
A__ = {}
A__ = None
@classmethod
def A ( cls : Optional[Any] , _a : Optional[Any] , _a : Any ) -> Union[str, Any]:
'''simple docstring'''
... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
lowerCamelCase : List[str] = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def _lowerCAmelCase ( _UpperCamelCase : list[list[int]] , _UpperCamelCase : list[int] ... | 47 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.f... | 47 | 1 |
'''simple docstring'''
import os
from pathlib import Path
def _lowerCAmelCase ( ) -> Tuple:
"""simple docstring"""
from torch.utils.cpp_extension import load
_SCREAMING_SNAKE_CASE =Path(_UpperCamelCase ).resolve().parent.parent.parent / 'kernels' / 'deformable... | 47 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class A__ ( A__ , A__ ):
@register_to_config
def __init__( self ... | 47 | 1 |
'''simple docstring'''
lowerCamelCase : Any = "\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"
low... | 47 |
'''simple docstring'''
# Copyright 2021 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
#
# Unl... | 47 | 1 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 47 |
'''simple docstring'''
class A__ :
def __init__( self : Union[str, Any] , _a : int ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =size
_SCREAMING_SNAKE_CASE =[0] * size
_SCREAMING_SNAKE_CASE =[0] * ... | 47 | 1 |
'''simple docstring'''
lowerCamelCase : Optional[Any] = 2_5_6
# Modulus to hash a string
lowerCamelCase : int = 1_0_0_0_0_0_3
def _lowerCAmelCase ( _UpperCamelCase : str , _UpperCamelCase : str ) -> bool:
"""simple docstring"""
... | 47 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowerCamelCase : Union[str, Any] = TypeVar("KT")
lowerCamelCase : Dict = TypeVar("VT")
class A__ ( Generic[KT, VT] ):
def __init__( self... | 47 | 1 |
'''simple docstring'''
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
lowerCamelCase : List[str] = TypeVar("T")
class A__ ( Generic[... | 47 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCamelCase : List[Any] = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import w... | 47 | 1 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _lowerCAmelCase ( _UpperCamelCase : Tuple , _UpperCamelCase : Optional[Any] , _UpperCamelCase : Dict ) -> Tuple:
"""simple docstring"""
... | 47 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase : List[str] = logging.get_logger(__name__)
lowerCamelCase : List[Any] = ... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _UpperCamelCase : float , _UpperCamelCase : float , _UpperCamelCase : float , ) -> tuple[str, float]:
"""simple docstring"""
if (stress, tangential_force,... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : int = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available()... | 47 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( ) -> list[list[int]]:
"""simple docstring"""
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase : Optional[Any] = generate_large_matrix()
lowerCamelCase : ... | 47 |
'''simple docstring'''
lowerCamelCase : Any = "\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"
low... | 47 | 1 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ... | 47 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowerCamelCase : Optional[int] = False
class A__ ( ... | 47 | 1 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def _lowerCAmelCase ( _UpperCamelCase : Union[dict, lis... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Any = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 47 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : int = {"configuration... | 47 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _lowerCAmelCase ( _UpperCamelCase : Dict , _UpperCamelCase : Any=False ) -> Optional[Any]:
"""simple docstring"""
... | 47 | 1 |
'''simple docstring'''
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class A__ ( nn.Module ):
def __init__( self : int , _a : int = 16 , _a : int = 88 , _a : ... | 47 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : int = {"configuration... | 47 | 1 |
'''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class A__ ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
A__ = [('size', ctypes.c_... | 47 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : str = {
"huggingface/time-series-transformer-tourism-monthly":... | 47 | 1 |
'''simple docstring'''
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_mod... | 47 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowerCamelCase : List[Any] = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained ... | 47 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : str = logging.get_logger(__name__)
lowerCamelC... | 47 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
"ut/deta": "https://huggingface.co/ut/deta/resol... | 47 | 1 |
'''simple docstring'''
from sklearn.metrics import recall_score
import datasets
lowerCamelCase : Optional[Any] = "\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the tru... | 47 |
'''simple docstring'''
import numpy as np
from PIL import Image
def _lowerCAmelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : int , _UpperCamelCase : int ) -> np.ndarray:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =n... | 47 | 1 |
'''simple docstring'''
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
imp... | 47 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCAmelCase ( ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =ArgumentPar... | 47 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
def _lowerCAmelCase ( _UpperCamelCase : float , _UpperCamelCase : float , _UpperCamelCase : float ) -> tuple:
"""simple docstring"""
_SCREAMING... | 47 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 47 | 1 |
'''simple docstring'''
import math
from collections.abc import Iterator
from itertools import takewhile
def _lowerCAmelCase ( _UpperCamelCase : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif num... | 47 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowerCAmelCase ( _UpperCamelCase : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or num... | 47 | 1 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class A__ :
def __init__( self : Tuple , _a : Any , _a : int , _a : int ) -> List[str]:
'''simple docstring'''
if ... | 47 |
'''simple docstring'''
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... | 47 | 1 |
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