code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common... | 57 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def snake_case ( A__ ):
UpperCAmelCase_ : Dict = SwinConfig(image_size=1_92 )
if "base" in mod... | 268 | 0 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...... | 207 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as... | 207 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCAmelCase : List[str] = {
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'tokenization_xlm': ['XL... | 88 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import ... | 299 | 0 |
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
Autoen... | 308 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_lowerCAmelCase : Any = logging.get_logger(__name__)
class __magic_name__ ( lowerCAmelCase_ ):
def __init__( self , *__snake_case , **__sn... | 308 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A =logging.get_logger(__name__)
__A ={
'''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/... | 19 |
'''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 .to... | 168 | 0 |
'''simple docstring'''
def __A ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
_UpperCAmelCase : Tuple = mf_knapsack(i - 1 , lowerCAmelCase_ , lowerCAmelC... | 170 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : int = {
'''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig... | 170 | 1 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 253 |
from jiwer import compute_measures
import datasets
lowerCAmelCase : Tuple = '\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL: improved evaluation... | 253 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase = {
"""configuration_blenderbot""": [
"""BLENDERBOT_PRETRAINED... | 358 |
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
snake_case = get_logger(__name__)
snake_case = r"""
Args:
input_ids (`jnp.ndarray` of shape `(batch_size, sequence_le... | 319 | 0 |
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__)
UpperCamelCas... | 65 |
'''simple docstring'''
from __future__ import annotations
import requests
def _A ( snake_case ) -> dict:
_lowercase : Dict = F'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'''
return requests.get(snake_case ).json()
def _A ( snake_... | 250 | 0 |
from manim import *
class lowercase_ ( lowercase ):
'''simple docstring'''
def __lowerCAmelCase ( self : Tuple ) ->Union[str, Any]:
"""simple docstring"""
a = Rectangle(height=0.5 , width=0.5 ... | 26 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCAmelCase__ = logging.get_logger("transformers.models.speecht5")
def _a ( a :Optional[Any] , a :Tuple... | 26 | 1 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _A (lowerCAmelCase__ :int , lowerCAmelCase__ :int , lowerCAmelCase__ :int , lowerCAmelCase__ :int , lowerCAmelCase__ :int , lower... | 168 |
'''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_fla... | 168 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def snake_case (A_ :list , A_ :list ):
'''simple docstring'''
if len(A_ ) != 2 or len(a[0] ) != 2 or len(A_ ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
a ... | 186 |
"""simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTeste... | 186 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 185 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
... | 185 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils ... | 278 |
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertLayer,... | 278 | 1 |
"""simple docstring"""
lowerCamelCase__ = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCamelCase__ = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCamelCase__ = {
0: """Sunday""",
1: """Monday""",
2: """Tuesday""",
3: """Wednesday""",
4: """Thursday""",
5: """Friday""",
... | 86 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Tuple = logging.get_logger(__name__)
snake_case_ : Optional[int] = {
"SCUT-DLVCLab/lilt-roberta-en-base": (
"https://huggingface.co/SCUT-DLVCLab/lilt-robe... | 125 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Att... | 217 |
'''simple docstring'''
def _lowerCAmelCase ( lowerCamelCase_ : int = 6_0_0_8_5_1_4_7_5_1_4_3 ):
try:
__lowercase = int(lowerCamelCase_ )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n ... | 217 | 1 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTe... | 207 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
A__ : Optional[int] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pas... | 207 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A : Union[str, Any] = logging.get_logger(__name__)
A : List[str] = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-ba... | 227 |
'''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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils... | 227 | 1 |
import re
import string
import numpy as np
import datasets
__lowerCAmelCase : Dict = '\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'
__lowerCAmelCase : Union[str, Any] = '\... | 107 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : Union[str, Any] = {
'''and... | 314 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 369 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
f... | 82 | 0 |
from cva import destroyAllWindows, imread, imshow, waitKey
def lowerCAmelCase_ ( _lowercase : List[Any]) -> List[str]:
"""simple docstring"""
# getting number of pixels in the image
a__ , a__ : str = img.shape[0], img.shape[1]
... | 170 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowercase : int ={}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
... | 170 | 1 |
"""simple docstring"""
import math
def _SCREAMING_SNAKE_CASE ( lowercase_ ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return... | 230 |
"""simple docstring"""
import random
from .binary_exp_mod import bin_exp_mod
def _SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_=10_00 ) -> Optional[Any]:
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
A__ = n - 1
A__ = 0
while... | 230 | 1 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_UpperCAmelCase : str = False
try:
_UpperCAmelCase ... | 50 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_vision_encoder_decoder''': ['''VisionEn... | 319 | 0 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normali... | 209 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
A__ : str = logging.get_logger(__name__)
class lowercase__ ( snake_case__ ):
def __init__( self : Optional[Any] , *snak... | 209 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
... | 26 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.ro... | 26 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase ( metaclass=__snake_case ):
'''simple docstring'''
lowerCamelCase__ =['onnx']
def __init__(self , *a_ , **a_ ):
'''simple docstring'''
requires_backends(self... | 24 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""... | 24 | 1 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class _lowerCamelCase :
"""simple docstring"""
def __init__( self , _SCRE... | 186 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class _lowerCamelCase :
"""simple docstring"""
def __init__( self , _SCRE... | 186 | 1 |
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
'''simple docstring'''
SCREAMING_SNAKE_CASE = [0 for i in range(r + 1 )]
# nc0 = 1
SCREAMING_SNAKE_CASE = 1
for i in range(1 , n + 1 ... | 351 |
from itertools import permutations
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> bool:
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % ... | 193 | 0 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax... | 278 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():
f... | 278 | 1 |
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
@require_optimum
@slow
class _snake_cas... | 367 |
from __future__ import annotations
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE_ ):
return len(set(SCREAMING_SNAKE_CASE_ ) ) == len(SCREAMING_SNAKE_CASE_ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 224 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
__A = logging.getLogger(__nam... | 217 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditio... | 217 | 1 |
import math
import sys
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : str ) -> str:
"""simple docstring"""
UpperCamelCase :Optional[Any] = """"""
try:
with open(__magic_name__ , """rb""" ) as binary_file:
UpperCamelCase :Dict = ... | 62 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 62 | 1 |
import math
from collections.abc import Callable
def a( A : Callable[[float], float] , A : float , A : float ) -> float:
"""simple docstring"""
a = xa
a = xa
while True:
if x_n == x_na or function... | 227 |
from __future__ import annotations
_lowercase: Tuple = list[list[int]]
# assigning initial values to the grid
_lowercase: Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0, 5]... | 227 | 1 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__UpperCamelCase : Dict = 10
def A ( _lowercase , _lowercase , _lowercase , _lowercase ):
fo... | 364 | from __future__ import annotations
from math import pi
def A ( _lowercase , _lowercase , _lowercase ):
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('''One and only one argument must be 0''' )
if inductance < 0:
raise Va... | 258 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class A_ :
'''simple docstring'''
def __init__( self , lowercase_ ):
"""simple docstring"""
UpperCAmelCase_ : list[dict] = []
self.adlist.append(
{"value": ""... | 61 |
from collections.abc import Iterable
from typing import Generic, TypeVar
A__ = TypeVar("""_T""")
class __lowerCAmelCase ( Generic[_T] ):
def __init__( self , _snake_case = None ):
"""simple docstring"""
_lowerCAmelCase = list(... | 82 | 0 |
'''simple docstring'''
import collections
import importlib.util
import os
import re
from pathlib import Path
__A : List[str] = "src/transformers"
# Matches is_xxx_available()
__A : Any = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_... | 368 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_avail... | 89 | 0 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from tran... | 230 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A__ = {
'''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''],
'''tokenization_ctrl''': ['''CTRLTokenizer'''],
}
... | 230 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingS... | 362 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
lowerCAmelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class lower... | 52 | 0 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case = 10**-10 ) -> float:
'''simple docstring'''
lowerCamelCase__ = a
while Tru... | 209 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import tor... | 209 | 1 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewT... | 60 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, lo... | 60 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase__ ( ) -> None:
print('''Making key files...''' )
make_key_files('''rsa''' , 1... | 24 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://hug... | 24 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _snake_case (unittest.TestCase )... | 351 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
fro... | 67 | 0 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Flax... | 107 |
a__: Dict = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
a__: str = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def UpperCamelCase__( UpperCamelCase__ : dict[int, list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : list... | 193 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[Any] = logging.get_logger(__name__)
lowercase : List[Any] = {
"""facebook/timesformer""": """https://huggingface.co/facebook/timesformer/resolve/main/config.json""",
}
cl... | 361 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase : List[str] = {
"""configuration_clip""": [
... | 225 | 0 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self ) -> List[str]:
UpperCamelCase :str = ''
UpperCamelCase :int = ''
... | 259 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : int = 100 ) -> int:
"""simple docstring"""
lowerCAmelCase_ : Any = (n * (n + 1) // 2) ** 2
lowerCAmelCase_ : Optional[int] = n * (n + 1) * (2 * n + 1) // 6
r... | 224 | 0 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")
class UpperCamelCase :
def __i... | 198 |
import argparse
import struct
import unittest
class UpperCamelCase :
def __init__( self , UpperCAmelCase__ ):
A__ = data
# Initialize hash values
A__ = [
0x6A_09E_667,
0xBB_67A_E85,
0x3C_6EF_372,
0xA... | 198 | 1 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampling... | 62 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_A = logging.get_logger(__name__)
_A = {
'Sale... | 62 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, 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... | 338 |
'''simple docstring'''
a : Dict = """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""
def __lowerCamelCase ( ) -> None:
UpperCAmelCase : Optional[int] = input("""Enter message: """ )
UpperCAmelCase : Dict = input("""Enter key [alphanumeric]: """ )
... | 338 | 1 |
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case = logging.get_logger(__name... | 259 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _A ( SCREAMING_SNAKE_CASE__ : Optional[int] , SCREAMING_SNAKE_CASE__ : List[str]=() , SCREAMING_SNAKE_CASE__ : ... | 259 | 1 |
"""simple docstring"""
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
_UpperCamelCase = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any memb... | 361 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_UpperCamelCase = {"""UserAgent""": UserAgent().random}
def _a ( _snake_case ):
"""simple docstring"""
U... | 234 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determi... | 82 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import ... | 89 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterM... | 222 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'configuration_instructblip': [
'INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InstructBlipConfig',
'InstructBlip... | 222 | 1 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
UpperCAmelCase__ = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.par... | 289 |
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 : str = {
"""roberta-b... | 52 | 0 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
Cond... | 175 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers... | 175 | 1 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INPAIN... | 15 |
from __future__ import annotations
__lowerCamelCase = list[list[int]]
# assigning initial values to the grid
__lowerCamelCase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, ... | 59 | 0 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowerCAmelCase__ = get_logger(__name__)
class snake_case__(enum.Enum ):
"""simple docstring"""
lowercase_ = """all_checks"""
lowercase_... | 121 |
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def __lowerCamelCase ( lowerCamelCase__ , lowerCamelCase__=1 ):
"""simple docstring"""
if n_shave_prefix_segments >= 0:
return ".".join(path.split("." )[n_sha... | 121 | 1 |
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...test_config... | 43 | '''simple docstring'''
import logging
import os
from .state import PartialState
class a__ ( logging.LoggerAdapter ):
@staticmethod
def SCREAMING_SNAKE_CASE__ ( a : Optional[Any] ):
"""simple docstring"""
__lowerCamelCase = PartialState()
... | 67 | 0 |
# 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 req... | 116 |
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_ = {
'facebook/xmod-base': 'https://hugg... | 116 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_av... | 6 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ : List[Any] = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
'vocab_file': 'vocab.json',
'toke... | 225 | 0 |
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_determinism()... | 252 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Dict = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santa... | 252 | 1 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerate.test_u... | 198 | '''simple docstring'''
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="""%(message)s""")
def __UpperCamelCase ( UpperCAmelCase ):
return input_array.reshape((input_array.size, 1) )
def __UpperCamelCase ( Uppe... | 198 | 1 |
"""simple docstring"""
import copy
import random
from transformers import CLIPTokenizer
class _a ( _lowerCAmelCase ):
def __init__( self : Any, *lowerCAmelCase__ : Union[str, Any], **lowerCAmelCase__ : Any ) -> Tuple:
... | 128 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def a_ ( _lowercase ):
# This defines a "chinese character" as anything in the CJK Unicode bl... | 128 | 1 |
import unittest
import numpy as np
from transformers import AlbertConfig, 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.numpy as jnp
from... | 338 | from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if i... | 338 | 1 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
A_ : Optional[int] = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n author={Yonghui Wu a... | 141 |
from __future__ import annotations
def UpperCamelCase (lowercase_: float , lowercase_: float , lowercase_: float ) -> dict[str, float]:
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("""One and only one argument must be 0""" )
if resistance < 0:
raise ValueError... | 141 | 1 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'''The `image_to_image.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionImg2ImgPipeline` instead.'''
)
| 254 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __lowerCAmelCase (__lowerCAmel... | 234 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from datasets import load_dataset
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, pre... | 91 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.ut... | 91 | 1 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table import a... | 222 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INPAIN... | 222 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase_ (metaclass=a__ ):
"""simple docstring"""
_lowerCAmelCase = ['flax', 'transformers']
def __init__( self : ... | 4 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from tr... | 4 | 1 |
import numpy as np
def __lowercase ( lowerCamelCase : np.ndarray ):
return 1 / (1 + np.exp(-vector ))
def __lowercase ( lowerCamelCase : np.ndarray ):
return vector * sigmoid(lowerCamelCase )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 175 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_efficientformer': [
'EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'EfficientF... | 175 | 1 |
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class __magic_name__ :
def __init__( self : str , snake_case__ : List[str] ):
'''simp... | 352 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase (a_ :str , a_ :str) -> str | Literal[False]:
lowercase :Union[str, Any] = list(a_)
lowercase :Optional[Any] ... | 172 | 0 |
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
fr... | 121 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
UpperCAmelCase__ : Union[str, Any] = TypeVar('T')
class UpperCAmelCase ( Generic[T] ):
'''simple docstring'''
__UpperCamelCase : deque[T] # Cache store of ke... | 121 | 1 |
'''simple docstring'''
from manim import *
class lowerCAmelCase__ ( a ):
"""simple docstring"""
def UpperCAmelCase__ ( self : List[Any] ) -> Union[str, Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = Rectangle(height=0.5 , width=0... | 331 |
'''simple docstring'''
class lowerCAmelCase__ : # Public class to implement a graph
"""simple docstring"""
def __init__( self : Dict , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : list[list[bool]] ) -> None:
"""simple... | 331 | 1 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils impor... | 116 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
SCREAMING_SNAKE_CASE_:Any = [
"""Prosecutor: \"No videos were used in the crash investigation\" German papers say they saw a cell pho... | 116 | 1 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def lowerCAmelCase_ ( __lowerCamelCase ):
__snake_case : Any = []
__snake_case : Optional[Any] = ... | 358 |
import numpy
class a :
"""simple docstring"""
def __init__( self : str , lowerCamelCase : numpy.ndarray , lowerCamelCase : numpy.ndarray ) -> None:
__snake_case : Any = input_array
# Random initial weights are a... | 134 | 0 |
def __lowerCamelCase ( lowerCamelCase__ : Tuple , lowerCamelCase__ : str , lowerCamelCase__ : str , lowerCamelCase__ : str , lowerCamelCase__ : Union[str, Any] , lowerCamelCase__ : Union[str, Any] ):
'''simple docstring'''
if index ... | 252 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> --key_path <... | 252 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : List[str] = '▁'
a_ :... | 367 |
# 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 ap... | 327 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _lowercase (a_ ... | 128 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
UpperCAmelCase : Dict =argparse.ArgumentParser()
parser.add_argument("""--dump_path""", default=None... | 128 | 1 |
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase_ ( lowerCAmelCase: int , lowerCAmelCase: Union[str, Any] , ... | 260 |
import qiskit
def lowerCamelCase_ ( lowerCAmelCase: int = 2 )-> qiskit.result.counts.Counts:
_snake_case : Dict = qubits
# Using Aer's simulator
_snake_case : List[str] = qiskit.Aer.get_backend('aer_simulator' )
# Creating a Quantum Circuit acting... | 260 | 1 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
UpperCAmelCase = datasets.logging.get_logger(__name__)
UpperCAmelCase = '''\
@inproceedings{bleurt,
title={BLEURT: Learning Robust Metrics for Text Generati... | 141 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mode... | 141 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.util... | 360 |
"""simple docstring"""
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import fl... | 212 | 0 |
"""simple docstring"""
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_uti... | 91 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
UpperCAmelCase_ : Dict = logging.getLogger(__name__)... | 91 | 1 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCAmelCase__ : Optional[int] =[
'kernels/rwkv/wkv_cuda.cu',
'kernels/rwkv/wkv_op.cpp',
'kernels/deformable_detr/ms_deform_attn.h',
'kernels/deformable_detr/cuda/ms_def... | 162 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def a__ ( A__, A__, ... | 162 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=__lowercase ):
lowerCamelCase : Tuple = ['''flax''', '''transformers''']
def __init__( self : Optional[Any] , *UpperCAmelCase__ : ... | 4 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def a_ ( lowerCamelCase : list[int] , lowerCamelCase : list[int] , lowerCamelCase : int ):
lowerCAmelCase = [0] * no_of_processes
lowerCAmelCase = [0] * no_of_proces... | 4 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class UpperCamelCase__ :
"""simple docstring"""
_SCREAMING_SNAKE_CASE = 42 # [batch_size x 3]
... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
"""simple docstring"""
if len(lowerCAmelCase__ ) != len(lowerCAmelCase__ ):
raise ValueError('String lengths must match... | 289 | 1 |
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 _UpperCamelCase ( snake_case__ ) -> Optional[int]: # picklable ... | 157 | """simple docstring"""
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
_a : i... | 172 | 0 |
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as p... | 176 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedK... | 176 | 1 |
'''simple docstring'''
from manim import *
class _lowerCamelCase ( lowercase__ ):
'''simple docstring'''
def __lowerCAmelCase ( self : int ) -> Optional[int]:
__magic_name__ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
__magic_... | 331 |
'''simple docstring'''
def lowerCamelCase ( ):
"""simple docstring"""
return 1
def lowerCamelCase ( lowerCAmelCase : int ):
"""simple docstring"""
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowerCamelCase ( lowerCAmelCase : int ):
"""s... | 331 | 1 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
__A = logging.getLogger(__name__)
class _lowerCAmelCase ( lowerCamelCase__ ):
"""simple... | 358 |
"""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/LICEN... | 254 | 0 |
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import I... | 9 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoForm... | 134 | 0 |
import math
from datetime import datetime, timedelta
def lowerCamelCase__ ( __lowerCamelCase : int ):
'''simple docstring'''
_UpperCAmelCase : Optional[Any] =year % 1_9
_UpperCAmelCase : Union[str, Any] =year % 4
_UpperCAmelC... | 368 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availab... | 242 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __A ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , )-> float | int:
... | 39 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
_SCREAMING_SNAKE_CASE = namedtuple("""covid_data""", """cases deaths recovered""")
def SCREAMING_SNAKE_CASE__ ( __a = "https://www.worldometers.info/coronavirus/" ):
snake_case_ ... | 327 | 0 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
lowercase : Optional[int] = True
except (ImportError, ModuleNotFoundError):
lowercase : List[Any] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('... | 350 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase : List[Any] = {
'configuration_pix2struct': [
'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Pix2StructConfig',
'Pix2S... | 151 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( _SCREAMING_SNAKE_CASE : list[list[int]] ):
'''simple docstring'''
_UpperCAmelCase = len(_SCREAMING_SNAKE_CASE )
# We need to create solution object to save pat... | 260 |
"""simple docstring"""
from pathlib import Path
import numpy as np
from PIL import Image
def lowercase ( _SCREAMING_SNAKE_CASE : np.ndarray ):
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = rg... | 260 | 1 |
'''simple docstring'''
from typing import Any
def UpperCamelCase__ ( lowerCAmelCase ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase = [input_list.count(lowerCAmelCase ) for value in input_list]... | 220 |
'''simple docstring'''
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
... | 220 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
i... | 93 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tokeni... | 212 | 0 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
__UpperCAmelCase : Optional[Any] = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import word_tokeni... | 351 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase : str = logging.get_logger(__name__)
__UpperCAmelCase : int = {
"RWKV/rwkv-4-169m-pile": "https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json",
"RWKV/rwkv-... | 293 | 0 |
'''simple docstring'''
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> bool:
A_ = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 162 |
'''simple docstring'''
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu... | 162 | 1 |
'''simple docstring'''
# Copyright (c) 2021-, NVIDIA CORPORATION. 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/LICENS... | 92 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : Optional[int] = {
"edbeeching/decision-transformer-gym-hopper-medium": (... | 92 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPip... | 289 | """simple docstring"""
import math
def __UpperCAmelCase ( lowercase ):
"""simple docstring"""
_UpperCAmelCase = []
_UpperCAmelCase = 2
_UpperCAmelCase = int(math.sqrt(lowercase ) ) # Size of every segment
_UpperCAmelCase = [T... | 289 | 1 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models... | 345 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( a_ , unittest.TestCase ):
"""simple docstring""... | 345 | 1 |
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