code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
# 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... | 139 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowercase : Union[str, Any] = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 641 | 0 |
def lowercase ( _lowerCAmelCase ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 392 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase : int = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCH... | 641 | 0 |
"""simple docstring"""
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
re... | 434 |
_lowercase : Dict = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0",
"huggingface-hub": "... | 641 | 0 |
from torch import nn
def SCREAMING_SNAKE_CASE__ ( snake_case__ :str ) -> int:
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(F"""Unsupport... | 67 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, slo... | 641 | 0 |
def _a ( lowerCAmelCase , lowerCAmelCase )-> Any:
print('\nThe shortest path matrix using Floyd Warshall algorithm\n' )
for i in range(UpperCamelCase__ ):
for j in range(UpperCamelCase__ ):
if dist[i][j] != float('inf' ):
print(int(dist[i][j] ) , end='... | 360 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.modeli... | 641 | 0 |
'''simple docstring'''
import math
import qiskit
def __A ( a_ : int = 1 ,a_ : int = 1 ,a_ : int = 1 ):
if (
isinstance(UpperCamelCase__ ,UpperCamelCase__ )
or isinstance(UpperCamelCase__ ,UpperCamelCase__ )
or isinstance(UpperCamelCas... | 525 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=__snake_case ):
"""simple docstring"""
lowerCAmelCase = ['note_seq']
def __init__( self , *a__ , **a__ ) -> Optional[int]:
requires_backends(self , ["""n... | 641 | 0 |
"""simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
lowerCAmelCase__ = "<<<<<<< This should probably be modified because it mentions: "
lowerCAmelC... | 645 |
import numpy as np
from transformers import Pipeline
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optional[int]:
"""simple docstring"""
A = np.max(UpperCamelCase__ , axis=-1 , keepdims=UpperCamelCase__ )
A = np.exp(out... | 641 | 0 |
'''simple docstring'''
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won... | 476 |
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 .tokenization_albert import ... | 641 | 0 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
__UpperCAmelCase : List[Any] = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Und... | 584 |
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _lowerCAmelCase ( UpperCamelCase__: Any ) -> Optional[int]:
... | 641 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a : List[Any] = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetCo... | 63 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optio... | 641 | 0 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 164 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( __snake_case ):
"""simple docstring"""
lowerCAmelCase = (IPNDMScheduler,)
lowerCAmelCase = (('num_inference_steps', 5_0)... | 641 | 0 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pip... | 139 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCAmelCase ( ) -> str:
"""simple docstring"""
A = HfArgumentParser(UpperCamelCase__ )
A = parser.parse_args_into_dataclasses()[0]
A = Te... | 641 | 0 |
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
snake_case__ : int = 5_0_0_0_0_0
snake_case__ : List[Any] = os.path.split(__file__)
snake_case__ : Any = os.pa... | 392 |
import unittest
from transformers import XLMConfig, 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 ModelTesterMixin, ids_... | 641 | 0 |
"""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 im... | 434 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"snap-research/efficientformer-l1-300": (
"https://huggingface.co/snap-research... | 641 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise Optiona... | 67 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
_lowercase : List[str] = {
"speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
... | 641 | 0 |
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,
resize,
... | 360 |
def _lowerCAmelCase ( UpperCamelCase__: Union[str, Any] ) -> Dict:
"""simple docstring"""
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
8: [5, 7],
... | 641 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
lowerCAmelCase = 1.054_571_817e-34 # unit of ℏ : J * s
lowerCAmelCase = 3e8 # unit of c : m * s^-1
def... | 525 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeniz... | 641 | 0 |
"""simple docstring"""
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class... | 645 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase : List[str] = logging.get_logger(__name__)
_lowercase : int = [
["attention", "attn"],... | 641 | 0 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import ... | 476 |
import requests
from bsa import BeautifulSoup
def _lowerCAmelCase ( UpperCamelCase__: str = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
A = BeautifulSoup(requests.get(UpperCamelCase__ ).text , """html.parser""" )
A ... | 641 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase : Optional[Any] = {
"configuration_whi... | 584 |
# 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
#
# Unless required by applic... | 641 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( __lowerCamelCase : str ):
return [ord(UpperCamelCase__ ) - 96 for elem in plain]
def lowerCamelCase__ ( __lowerCamelCase : list[int] ):
return "".join(chr(elem + 96 ... | 63 |
_lowercase : Dict = "0.21.0"
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batche... | 641 | 0 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
snake_case_ = logging.get_logger(__name__)
snake_case_ = [
["attention", "attn"],
["encoder_attention", "e... | 164 |
def _lowerCAmelCase ( UpperCamelCase__: str , UpperCamelCase__: int , UpperCamelCase__: Any=False ) -> str:
"""simple docstring"""
if isinstance(UpperCamelCase__ , UpperCamelCase__ ) and isinstance(UpperCamelCase__ , UpperCamelCase__ ):
A ... | 641 | 0 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict impo... | 139 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowercase : Union[str, Any] = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 641 | 0 |
def lowercase ( _lowerCAmelCase ):
if num <= 0:
raise ValueError("""Input must be a positive integer""" )
UpperCAmelCase__ = [True] * (num + 1)
UpperCAmelCase__ = 2
while p * p <= num:
if primes[p]:
for i in range(p * p , num + 1 , Upp... | 392 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase : int = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCH... | 641 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCamelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE... | 434 |
_lowercase : Dict = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0",
"huggingface-hub": "... | 641 | 0 |
def SCREAMING_SNAKE_CASE__ ( snake_case__ :str ) -> bool:
_lowercase = [int(UpperCamelCase__ ) for i in ip_va_address.split('.' ) if i.isdigit()]
return len(UpperCamelCase__ ) == 4 and all(0 <= int(UpperCamelCase__ ) <= 254 for octet in octets )
if __name__ == "__m... | 67 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, slo... | 641 | 0 |
import string
from math import logaa
def _a ( lowerCAmelCase , lowerCAmelCase )-> int:
SCREAMING_SNAKE_CASE_ = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , '' )
SCREAMING_SNAKE_CASE_ ... | 360 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.modeli... | 641 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"google/bigbird-r... | 525 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=__snake_case ):
"""simple docstring"""
lowerCAmelCase = ['note_seq']
def __init__( self , *a__ , **a__ ) -> Optional[int]:
requires_backends(self , ["""n... | 641 | 0 |
"""simple docstring"""
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorStat... | 645 |
import numpy as np
from transformers import Pipeline
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optional[int]:
"""simple docstring"""
A = np.max(UpperCamelCase__ , axis=-1 , keepdims=UpperCamelCase__ )
A = np.exp(out... | 641 | 0 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def lowerCamelCase (_SCREAMING_SNAKE_CASE... | 476 |
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 .tokenization_albert import ... | 641 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class __lowerCAmelCase (__snake_case... | 584 |
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _lowerCAmelCase ( UpperCamelCase__: Any ) -> Optional[int]:
... | 641 | 0 |
import unittest
from transformers import XLMConfig, 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 Mode... | 63 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optio... | 641 | 0 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
snake_case_ = logging.get_logger('''transformers.models.speecht5''')
def snake_case__ ( SCREAMING_SNAKE_CASE_ : Optional[int... | 164 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( __snake_case ):
"""simple docstring"""
lowerCAmelCase = (IPNDMScheduler,)
lowerCAmelCase = (('num_inference_steps', 5_0)... | 641 | 0 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetY... | 139 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCAmelCase ( ) -> str:
"""simple docstring"""
A = HfArgumentParser(UpperCamelCase__ )
A = parser.parse_args_into_dataclasses()[0]
A = Te... | 641 | 0 |
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 snake_case ( __snake_case ):
'''simple docstring'''
... | 392 |
import unittest
from transformers import XLMConfig, 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 ModelTesterMixin, ids_... | 641 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils impor... | 434 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"snap-research/efficientformer-l1-300": (
"https://huggingface.co/snap-research... | 641 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A_ ( __snake_case ):
... | 67 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
_lowercase : List[str] = {
"speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
... | 641 | 0 |
from timeit import timeit
def _a ( lowerCAmelCase )-> int:
if number < 0:
raise ValueError('the value of input must not be negative' )
SCREAMING_SNAKE_CASE_ = 0
while number:
number &= number - 1
result += 1
return result
def ... | 360 |
def _lowerCAmelCase ( UpperCamelCase__: Union[str, Any] ) -> Dict:
"""simple docstring"""
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
8: [5, 7],
... | 641 | 0 |
'''simple docstring'''
from math import pi
def __A ( a_ : int ,a_ : int ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 525 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeniz... | 641 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"naver-clova-ix/donut-base": "https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json",
# Se... | 645 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase : List[str] = logging.get_logger(__name__)
_lowercase : int = [
["attention", "attn"],... | 641 | 0 |
'''simple docstring'''
def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : list[list[int]] ):
def update_area_of_max_square(_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ) -> int:
# BASE CASE
if row >=... | 476 |
import requests
from bsa import BeautifulSoup
def _lowerCAmelCase ( UpperCamelCase__: str = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
A = BeautifulSoup(requests.get(UpperCamelCase__ ).text , """html.parser""" )
A ... | 641 | 0 |
"""simple docstring"""
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__UpperCAmelCase : Optional[Any] = get_tests_d... | 584 |
# 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
#
# Unless required by applic... | 641 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTes... | 63 |
_lowercase : Dict = "0.21.0"
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batche... | 641 | 0 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 164 |
def _lowerCAmelCase ( UpperCamelCase__: str , UpperCamelCase__: int , UpperCamelCase__: Any=False ) -> str:
"""simple docstring"""
if isinstance(UpperCamelCase__ , UpperCamelCase__ ) and isinstance(UpperCamelCase__ , UpperCamelCase__ ):
A ... | 641 | 0 |
"""simple docstring"""
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
class lowerCamelCase... | 139 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowercase : Union[str, Any] = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 641 | 0 |
import warnings
from functools import wraps
from typing import Callable
def lowercase ( _lowerCAmelCase ):
@wraps(UpperCamelCase__ )
def _inner_fn(*_lowerCAmelCase , **_lowerCAmelCase ):
warnings.warn(
(F'''\'{fn.__name__}\' is experimental and might be su... | 392 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase : int = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCH... | 641 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
I... | 434 |
_lowercase : Dict = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0",
"huggingface-hub": "... | 641 | 0 |
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='session' )
def SCREAMING_SNAKE_CASE__ (... | 67 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, slo... | 641 | 0 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.nu... | 360 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.modeli... | 641 | 0 |
'''simple docstring'''
def __A ( a_ : int ,a_ : int ):
return int((input_a, input_a).count(0 ) == 0 )
def __A ( ):
assert and_gate(0 ,0 ) == 0
assert and_gate(0 ,1 ) == 0
assert and_gate(1 ,0 ) == 0
assert and_gate(1 ,1 ) == ... | 525 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=__snake_case ):
"""simple docstring"""
lowerCAmelCase = ['note_seq']
def __init__( self , *a__ , **a__ ) -> Optional[int]:
requires_backends(self , ["""n... | 641 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class SCREAMING_SNAKE_CASE__ :
"""simple docstring"""
a : Tuple =42 # [batch_size x 3]
a : Optional[Any] =42 # [batch_size x 3]
... | 645 |
import numpy as np
from transformers import Pipeline
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optional[int]:
"""simple docstring"""
A = np.max(UpperCamelCase__ , axis=-1 , keepdims=UpperCamelCase__ )
A = np.exp(out... | 641 | 0 |
'''simple docstring'''
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import to... | 476 |
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 .tokenization_albert import ... | 641 | 0 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
__UpperCAmelCase : Union[str, Any... | 584 |
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _lowerCAmelCase ( UpperCamelCase__: Any ) -> Optional[int]:
... | 641 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Optional[Any] = {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}
try:
if not is_torch_available():
rais... | 63 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optio... | 641 | 0 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class SCREAMING_SNAKE_CASE__ (unittest.TestCase ):
... | 164 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( __snake_case ):
"""simple docstring"""
lowerCAmelCase = (IPNDMScheduler,)
lowerCAmelCase = (('num_inference_steps', 5_0)... | 641 | 0 |
"""simple docstring"""
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def lowerCamelCase ( _UpperCamelCase ... | 139 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCAmelCase ( ) -> str:
"""simple docstring"""
A = HfArgumentParser(UpperCamelCase__ )
A = parser.parse_args_into_dataclasses()[0]
A = Te... | 641 | 0 |
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):
import to... | 392 |
import unittest
from transformers import XLMConfig, 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 ModelTesterMixin, ids_... | 641 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2... | 434 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"snap-research/efficientformer-l1-300": (
"https://huggingface.co/snap-research... | 641 | 0 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
snake_case = 2_9_9_7_9_2_4_5_8
# Symbols
snake_case = symbols("""ct x y z""")
def SCREAMING_SNAKE_CASE__ ( snake_case__ :float ) -> float:
... | 67 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
_lowercase : List[str] = {
"speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
... | 641 | 0 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _a ( lowerCAmelC... | 360 |
def _lowerCAmelCase ( UpperCamelCase__: Union[str, Any] ) -> Dict:
"""simple docstring"""
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
8: [5, 7],
... | 641 | 0 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_co... | 525 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeniz... | 641 | 0 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase , __snake_case ):
"""simple docstring"""
def lowercase__ ( self ):
"""si... | 645 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase : List[str] = logging.get_logger(__name__)
_lowercase : int = [
["attention", "attn"],... | 641 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : str = logging.get_logger(__name__)
class __UpperCamelCase ( __snake_case ):
A_ = "encoder-decoder"
A_ = True
... | 476 |
import requests
from bsa import BeautifulSoup
def _lowerCAmelCase ( UpperCamelCase__: str = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
A = BeautifulSoup(requests.get(UpperCamelCase__ ).text , """html.parser""" )
A ... | 641 | 0 |
"""simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def A ( _A ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 584 |
# 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
#
# Unless required by applic... | 641 | 0 |
def lowerCamelCase__ ( __lowerCamelCase : int ):
if upper_limit < 0:
raise ValueError("""Limit for the Catalan sequence must be ≥ 0""" )
__UpperCAmelCase : Optional[Any] = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__Upper... | 63 |
_lowercase : Dict = "0.21.0"
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batche... | 641 | 0 |
import math
import os
import sys
def snake_case__ ( SCREAMING_SNAKE_CASE_ : str ):
'''simple docstring'''
lowercase__ : Any = ''
try:
with open(UpperCamelCase__ , 'rb' ) as binary_file:
lowercase__ : Any = binar... | 164 |
def _lowerCAmelCase ( UpperCamelCase__: str , UpperCamelCase__: int , UpperCamelCase__: Any=False ) -> str:
"""simple docstring"""
if isinstance(UpperCamelCase__ , UpperCamelCase__ ) and isinstance(UpperCamelCase__ , UpperCamelCase__ ):
A ... | 641 | 0 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
UpperCAmelCase : List[str] = numpy.array([0, 0])
UpperCAmelCase : Tuple = numpy.array([0.5, 0.8660254])
UpperCAmelCase ... | 139 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowercase : Union[str, Any] = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1),... | 641 | 0 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 392 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase : int = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCH... | 641 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCamelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREA... | 434 |
_lowercase : Dict = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0",
"huggingface-hub": "... | 641 | 0 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TF... | 67 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, slo... | 641 | 0 |
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _a ( lowerCAmelCase )-> Optional[int]:
SC... | 360 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.modeli... | 641 | 0 |
'''simple docstring'''
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
class lowerCa... | 525 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=__snake_case ):
"""simple docstring"""
lowerCAmelCase = ['note_seq']
def __init__( self , *a__ , **a__ ) -> Optional[int]:
requires_backends(self , ["""n... | 641 | 0 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def a__ ( SCREAMING_SNAKE_CASE : Union[str, Any] , SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
... | 645 |
import numpy as np
from transformers import Pipeline
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optional[int]:
"""simple docstring"""
A = np.max(UpperCamelCase__ , axis=-1 , keepdims=UpperCamelCase__ )
A = np.exp(out... | 641 | 0 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
__lowercase : Union[str, Any] = "\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n"
__lowercase : Any =... | 476 |
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 .tokenization_albert import ... | 641 | 0 |
"""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():
fro... | 584 |
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _lowerCAmelCase ( UpperCamelCase__: Any ) -> Optional[int]:
... | 641 | 0 |
import numpy as np
def lowerCamelCase__ ( __lowerCamelCase : np.ndarray , __lowerCamelCase : float ):
return np.where(vector > 0 , UpperCamelCase__ , (alpha * (np.exp(UpperCamelCase__ ) - 1)) )
if __name__ == "__main__":
... | 63 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def _lowerCAmelCase ( UpperCamelCase__: Optional[Any] ) -> Optio... | 641 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
# See all M-CTC-T models at https:/... | 164 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( __snake_case ):
"""simple docstring"""
lowerCAmelCase = (IPNDMScheduler,)
lowerCAmelCase = (('num_inference_steps', 5_0)... | 641 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig... | 139 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCAmelCase ( ) -> str:
"""simple docstring"""
A = HfArgumentParser(UpperCamelCase__ )
A = parser.parse_args_into_dataclasses()[0]
A = Te... | 641 | 0 |
import os
import sys
snake_case__ : List[Any] = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
Auto... | 392 |
import unittest
from transformers import XLMConfig, 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 ModelTesterMixin, ids_... | 641 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase ( metaclass=__snake_case ):
"""simple docstring"""
__snake_case = ["""sentencepiece"""]
def __init__( self , *_lowercase , **_lowercase ) -... | 434 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"snap-research/efficientformer-l1-300": (
"https://huggingface.co/snap-research... | 641 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
... | 642 |
"""simple docstring"""
from sklearn.metrics import matthews_corrcoef
import datasets
__UpperCAmelCase = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It ... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import 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, random_at... | 642 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_... | 642 | 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/LICE... | 642 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __UpperCAmelCase ( _UpperCamelCase ):
# to overwrite a... | 642 | 1 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __UpperCAmelCase ( _UpperCamelCase ):
__lowerCamelCase : str = (KDPMaDiscreteScheduler,)
... | 642 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 642 | 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_... | 642 |
"""simple docstring"""
import pytest
import datasets
# Import fixture modules as plugins
__UpperCAmelCase = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def lowercase__ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str... | 642 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__UpperCAmelCase = l... | 642 |
"""simple docstring"""
import functools
def lowercase__ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
'''simple docstring'''
a__ : Any = len(lowerCAmelCase__ )
a__ : Optional[int] = len(lowerCAmelCase__ )
@functools.cache
d... | 642 | 1 |
"""simple docstring"""
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_sub... | 642 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : str ) -> list[int]:
'''simple docstring'''
a__ : List[str] = [0 for i in range(len(lowerCAmelCase__ ) )]
# initialize interval's left pointer and right pointer
a__ , a__ : int = 0, 0
for i in ra... | 642 | 1 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class __UpperCAmelCase ( unittest.TestCase ... | 642 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__UpperCAmelCase = loggi... | 642 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/config.json''',
'''google/fnet... | 642 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowerCAmelCase__ : Union[str... | 642 | 1 |
"""simple docstring"""
import math
def lowercase__ ( lowerCAmelCase__ : int ) -> bool:
'''simple docstring'''
return math.sqrt(lowerCAmelCase__ ) * math.sqrt(lowerCAmelCase__ ) == num
def lowercase__ ( lowerCAmelCase__ : int ) -> bool:
'... | 642 |
"""simple docstring"""
import os
def lowercase__ ( ) -> Optional[Any]:
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase__ ) + "/p022_names.txt" ) as file:
a__ : Optional[int] = str(file.readlines()[0] )
a__ : Optional[int] = names.repla... | 642 | 1 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __UpperCAmelCase ( _UpperCamelCase ):
# to overwrite a... | 642 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def lowercase__ ( lowerCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[int]:
'... | 642 | 1 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__UpperCAmelCase = pytest.mark.integration
@pytest.mark.parametrize... | 642 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffus... | 642 | 1 |
"""simple docstring"""
from math import factorial
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int ) -> list[int]:
'''simple docstring'''
a__ : Tuple = [True] * limit
a__ : Tuple = False
a__ : int = False
a__ : Tuple = True
for i in range(3... | 642 | 1 |
"""simple docstring"""
import csv
import tweepy
# Twitter API credentials
__UpperCAmelCase = ''''''
__UpperCAmelCase = ''''''
__UpperCAmelCase = ''''''
__UpperCAmelCase = ''''''
def lowercase__ ( lowerCAmelCase__ : str ) -> None:
'''simple docstr... | 642 |
"""simple docstring"""
__UpperCAmelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase__ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : Optional[in... | 642 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoin... | 642 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __UpperCAmelCase ( unittest.TestCase , _UpperCamelCase ):
def UpperCAmelCase ( self : Dict ) -> List[Any]:
'''simple do... | 642 | 1 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info... | 642 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__UpperCAmelCase = False
class __UpperCAmelCase ( unittest.TestCase ... | 642 | 1 |
"""simple docstring"""
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
ren... | 642 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__UpperCAmelCase = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '... | 642 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> tuple[int, int]:
'''simple docstring'''
if b == 0:
return (1, 0)
((a__) , (a__)) : List[Any] = extended_euclid(lowerCA... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__UpperCAmelCase = tuple[int, int]
class __UpperCAmelCase :
def __init__( self : Union[str, Any] , a_ : set[int] , a_ : Mapping[EdgeT, int] ) -> None:
... | 642 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__UpperCAmelCase = logging.get_logger(__name__)
clas... | 642 | 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
__UpperCAmelCase = logging.get_logger(__name__... | 642 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
a__ : Tuple = prime_factors(lowerCAmelCase__ )
if is_square_free(lowerCA... | 642 | 1 |
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