code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_conf... | 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'''
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 |
'''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'''
# 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 |
'''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'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase : int = {
"configuration_xlm_roberta_xl": [
"XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP",
"XLMRobertaXLConfig",
"XL... | 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'''
# 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 |
'''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'''
def _lowerCAmelCase ( _UpperCamelCase : int ) -> int:
"""simple docstring"""
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
_SCREAMING_SNAKE_CASE =f"Input value of [number={number}] must be an integer"
... | 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'''
# 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 |
'''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'''
def _lowerCAmelCase ( _UpperCamelCase : int , _UpperCamelCase : int ) -> str:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
_SCREAMING_SNAKE_CASE ... | 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 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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity... | 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'''
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 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 gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
lowerCamelCase : int = False
class A__ ( ... | 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 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 |
'''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 unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_dete... | 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 statistics import mean, stdev
def _lowerCAmelCase ( _UpperCamelCase : list , _UpperCamelCase : int = 3 ) -> list:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =min(_UpperCamelCase )
_SCREAMING_SNAKE_CASE ... | 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 __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 |
'''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 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 |
'''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'''
lowerCamelCase : Dict = "Alexander Joslin"
import operator as op
from .stack import Stack
def _lowerCAmelCase ( _UpperCamelCase : str ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE ={'*': op.mul, '/': op.truedi... | 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 inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteSchedule... | 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'''
def _lowerCAmelCase ( _UpperCamelCase : int ) -> int:
"""simple docstring"""
if a < 0:
raise ValueError('Input value must be a positive integer' )
elif isinstance(_UpperCamelCase , _UpperCamelCase ):
raise Typ... | 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 math
def _lowerCAmelCase ( _UpperCamelCase : float , _UpperCamelCase : float ) -> float:
"""simple docstring"""
return math.pow(_UpperCamelCase , 2 ) - a
def _lowerCAmelCase ( _UpperCamelCase ... | 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 Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, ... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : int = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class A__ ( ... | 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 unittest
from transformers import MraConfig, 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, floats_tensor, ids_tensor, random_attenti... | 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 dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_onn... | 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 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 |
'''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 numpy as np
import datasets
lowerCamelCase : str = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.... | 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 importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
lowerCamelCase : Union[str, Any] = importlib.util.find_spec("s3fs") is not None
if _has_sa... | 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 re
def _lowerCAmelCase ( _UpperCamelCase : str ) -> list:
"""simple docstring"""
return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]' , str_ )]
def _lowerCAmelCase ( _UpperCamelCase : str ... | 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 collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : Optional[int] = ... | 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 PIL import Image
def _lowerCAmelCase ( _UpperCamelCase : Image , _UpperCamelCase : float ) -> Image:
"""simple docstring"""
def brightness(_UpperCamelCase : int ) -> float:
return 1_28 + level + (c - 1_... | 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 inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.util... | 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'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...ut... | 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 argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase : List[Any] = re.compile(r"\b(a|an|the)\b", re.UNICODE)
lowerCamelCase : Dict = None
def _lowerCAmelCase ( ) -> ... | 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 .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class A__ ( unittest.TestCase ):
def A ( self : str ) -> None:
'''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 cva
import numpy as np
class A__ :
def __init__( self : Tuple , _a : float , _a : int ) -> List[Any]:
'''simple docstring'''
if k in (0.04, 0.06):
_SCREAMING_SNAKE_CASE =k
... | 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 : int = 10_00 ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE =1, 1
_SCREAMING_SNAKE_CASE =[]
for i in range(1 , n + 1 ):
... | 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
def _lowerCAmelCase ( _UpperCamelCase : Union[str, Any] ) -> Optional[Any]:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =len(grid[0] )
_SCREAMING_SNAKE_CASE =len(_UpperCamelCase )
_SCREAMING_SNAKE... | 47 |
'''simple docstring'''
from typing import 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 warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( 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'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
Bi... | 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 : list ) -> list:
"""simple docstring"""
for i in range(len(_UpperCamelCase ) - 1 , 0 , -1 ):
_SCREAMING_SNAKE_CASE =False
for j in range(_UpperCamelCase ... | 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 unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCase : Dict = get_tests_di... | 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 collections import deque
class A__ :
def __init__( self : List[Any] , _a : str , _a : int , _a : int ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =process_name # pro... | 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 fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def _lowerCAmelCase ( _UpperCamelCase : Optional[Any] , _UpperCamelCase : Union[str, Any] ... | 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 List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorTy... | 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 typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : int = logging.get_logger(__name__)
lowerCamelCase : Union[str, Any] = {
"nielsr/canine-s": 2_0_4_8,
}
# U... | 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 typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class A__ ( A__ ):
def __init__( self : Union[str, An... | 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 typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase : Optional[Any] = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"JukeboxPrio... | 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'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Optional[int] = {
"configuration_roformer": ["ROF... | 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'''
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def _lowerCAmelCase ( _UpperCamelCase : List[Any] ) -> Dict:
"""simple... | 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 copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
lowerCamelCase : List[Any] = r"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to... | 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 os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .trans... | 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 collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : Union[str, 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 math
import flax.linen as nn
import jax.numpy as jnp
def _lowerCAmelCase ( _UpperCamelCase : jnp.ndarray , _UpperCamelCase : int , _UpperCamelCase : float = 1 , _UpperCamelCase : float = 1 , _UpperCamelCase ... | 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'''
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_to... | 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'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowerCamelCase : Optional[Any] ... | 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 : List[str] ) -> int: # noqa: E741
"""simple docstring"""
_SCREAMING_SNAKE_CASE =len(_UpperCamelCase )
_SCREAMING_SNAKE_CASE =0
_SCREAMING_SNAKE_CASE =[0] * n
... | 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 pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def _lowerCAmelCase ( _UpperCamelCase : Optional[int... | 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 : int = 10 ) -> str:
"""simple docstring"""
if not isinstance(_UpperCamelCase , _UpperCamelCase ) or n < 0:
raise ValueError('Invalid input' )
_SCREAMING_SNAKE_CASE =10**n... | 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'''
lowerCamelCase : Union[str, Any] = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
lowerCamelCase : List[Any] = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def _lowerCAmelCase ( _UpperCamelCase : dict[int, list[int]] , _UpperCa... | 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'''
def _lowerCAmelCase ( _UpperCamelCase : int = 50 ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =[1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
... | 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 : int ) -> bool:
"""simple docstring"""
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("Program to check whether a number ... | 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 flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class A__ ( nn.Module ):
A__ = 42
A__ = 42
A__ = 0.0
A__ = 1
A__... | 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 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 |
'''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 torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCamelCase : Optional[int] = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention... | 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 asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import Accelerator... | 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 sklearn.metrics import mean_squared_error
import datasets
lowerCamelCase : int = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel,... | 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
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_atte... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : str = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
"facebook/xglm-564M": "https://huggingface.co/facebook/xglm-564M/resolve/main/config.json",
... | 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 pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class A__ ( unittest.TestCase ):
def A ( self : Dict ) -> int:
... | 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 argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
... | 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 pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[str] = logging.get_logger(__name__)
lowerCamelCase : Any = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class A__ ( 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'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A__ ( A__ ):
A__ = (DEISMul... | 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 unittest
import numpy as np
def _lowerCAmelCase ( _UpperCamelCase : np.ndarray , _UpperCamelCase : np.ndarray , _UpperCamelCase : np.ndarray , _UpperCamelCase : np.ndarray | None = None , ) -> np.ndarra... | 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
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 |
'''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'''
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToke... | 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 inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 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 ( ) -> Tuple:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =[31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
_SCREAMING_SNAKE_CASE =6
_SCREAMING_SNAKE_CASE =1
_SCREAMING_SNAKE_CASE =... | 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 glob
import os
import random
from string import ascii_lowercase, digits
import cva
lowerCamelCase : Tuple = ""
lowerCamelCase : Union[str, Any] = ""
lowerCamelCase : Dict = ""
lowerCamelCase : str = 1 # (0 is vertical, 1 is horizo... | 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 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 |
'''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 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_roberta import... | 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'''
class A__ : # Public class to implement a graph
def __init__( self : List[Any] , _a : int , _a : int , _a : list[list[bool]] ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =row
... | 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 OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def _lowerCAmelCase ( _UpperCamelCase : Any , _UpperCamelCase : Optional[int] , _UpperCamelCase : List[Any] ) ... | 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 warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : str = logging.get_logger(__name__)
class A__ ( A__ ):
A__ = ['input_ids'... | 47 |
'''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 __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impo... | 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 json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
lowerCamelCase : Any = "."
# Internal ... | 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 List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
lowerCamelCase : Union[str, Any] = log... | 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 import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : Any = logging.get_logger(__name__)
lowerCamelCase : Optional[Any] = {
... | 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
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
lowerCamelCase : Tuple = "\\n\n"
lowerCamelCase : Dict = "\nPerplexity (PPL) is one of ... | 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 collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : Op... | 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 numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
lowerCamelCase : int = pd.read_csv("sample_data.csv", header=None)
... | 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 gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simp... | 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 collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
lowerCamelCase : Any = logging.get_logger(__name__)
lowerCamelCase : D... | 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 os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : Tuple = logging.get_logger(__nam... | 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 os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_ge... | 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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCamelCase : str = {
"configuration_trocr": ["TROCR_PRETRAINED_CONFIG_ARCHIVE_... | 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 argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision.tr... | 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 __future__ import annotations
class A__ :
def __init__( self : int , _a : int ) -> None:
'''simple docstring'''
_SCREAMING_SNAKE_CASE =order
# a_{0} ... a_{k}
_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 logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceCl... | 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 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 |
'''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 |
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