code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
A_ = logging.getLog... | 29 |
'''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from d... | 442 | 0 |
from math import sqrt
def _SCREAMING_SNAKE_CASE ( __snake_case ) -> 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 o... | 720 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import ... | 402 | 0 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : list ) -> list:
"""simple docstring"""
if len(_SCREAMING_SNAKE_CASE ) <= 1:
return [tuple(_SCREAMING_SNAKE_CASE )]
UpperCAmelCase_ : List[str] = []
def generate(_SCREAMING_SNAKE_C... | 71 | """simple docstring"""
import numpy
# List of input, output pairs
SCREAMING_SNAKE_CASE__ : Optional[Any] =(
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
SCREAMING_SNAKE_CASE__ : str =(((515, 22, 13), 555), ((61, 35,... | 434 | 0 |
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : int = len(lowercase )
SCREAMING_SNAKE_CASE : List[Any] = len(matrix[0] )
SCREAMING_SNAKE_CASE : Optional[int] = min(lowercase , lo... | 488 |
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require_torch_gpu
class SCR... | 488 | 1 |
'''simple docstring'''
def __magic_name__ ( ) -> Union[str, Any]:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
__SCREAMING_SNAKE_CASE = 1
while len(__UpperCAmelCase ) < 1e6:
constant.append(str(__UpperCAmelCase ) )
i += 1
... | 109 | 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-large': 'https://huggingfa... | 486 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokenizer"""],
}
try:
... | 541 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class UpperCamelCase_ ( unittest.TestCase ):
def lowerCAmelCase ( self ) -> List[Any]:
debug_launcher(test_script.main )
def ... | 541 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase ,lowerCAmelCase = analyze_text(_UpperCAmelCase )
lowerCAmelCase = list(' '... | 4 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class _lowercase ( A__ ):
'''simple docstring'''
SCREAMING_S... | 696 | 0 |
def lowerCamelCase_ ( A : int = 1_00 ):
"""simple docstring"""
lowerCAmelCase_ = (n * (n + 1) // 2) ** 2
lowerCAmelCase_ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f'''{solution() = }''')
| 718 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"sail/pool... | 413 | 0 |
'''simple docstring'''
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallb... | 517 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from tra... | 517 | 1 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _UpperCAmelCase ( unittest.TestCase ):
UpperCamelCase = JukeboxTokenizer
UpperCamelCase = {
"""artist""": """Zac Br... | 721 |
"""simple docstring"""
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_snake_case : List[str] = Lock()
def A__ ( UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCa... | 524 | 0 |
"""simple docstring"""
#
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc... | 76 |
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosi... | 371 | 0 |
# using dfs for finding eulerian path traversal
def __magic_name__ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_=None):
'''simple docstring'''
lowerCamelCase_ : Union[str, Any] = (path or []) + [u]
for v in graph[u]:
if v... | 720 |
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoM... | 73 | 0 |
"""simple docstring"""
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 imp... | 580 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transfo... | 61 | 0 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def __lowerCAmelCase ( __UpperCamelCase : Any="ro" , __UpperCamelCase : Union[str, Any]="en" , __UpperCamelCase : Union[str, Any]="wmt16" , __UpperCamelCase : int=None... | 21 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__lowerCAmelCase : Optional[int] = argparse.ArgumentParser('''Stable Diffusion script with inte... | 21 | 1 |
'''simple docstring'''
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing impor... | 442 |
import os
import sys
import unittest
UpperCamelCase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_bac... | 256 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
a_ :int = logging.get_logger(__name__)
a_ :Optional[int] ... | 704 |
from math import pow
def a ( A__ , A__ , A__ , A__ , A__ , ) -> tuple[int, int]:
'''simple docstring'''
if current_sum == needed_sum:
# If the sum of the powers is equal to needed_sum, then we have a solution.
solutio... | 250 | 0 |
from __future__ import annotations
class _lowerCAmelCase:
"""simple docstring"""
def __init__( self , _lowerCamelCase ):
UpperCamelCase_: Union[str, Any] = order
# a_{0} ... a_{k}
UpperCamelC... | 57 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def UpperCAmelCase ( _lowercase : int ) -> datetime:
"""simple docstring"""
lowerCAmelCase_ = year % 1_9
lowerCAmelCase_ = year % 4
lowerCAmelCase_ ... | 552 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipeline... | 216 |
'''simple docstring'''
from collections import deque
def __UpperCAmelCase ( A : int ) -> Optional[Any]:
UpperCAmelCase_ : Tuple = len(A )
UpperCAmelCase_ : Dict = deque()
UpperCAmelCase_ : Optional[Any] = [False for _ in r... | 216 | 1 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase (_snake_case ):
'''simple docstring'''
_snake_case : Union[str, Any] = ... | 406 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = R'\n Args:\n input_ids (... | 406 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from... | 714 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow... | 325 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
A : int ... | 636 | import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
__SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
class lowercase_ ( __snake_case ):
_lower... | 670 | 0 |
"""simple docstring"""
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 ..... | 711 |
"""simple docstring"""
from timeit import timeit
def lowercase ( A_ )-> int:
'''simple docstring'''
if number < 0:
raise ValueError("the value of input must not be negative" )
a : Dict = 0
while number:
number &= number - 1
res... | 135 | 0 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
UpperCamelCase = logging.getLog... | 520 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase = {
'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
'tokenization_ctrl': ['CTRLTokenizer'],
}
try:
i... | 520 | 1 |
import os
import sys
import unittest
UpperCAmelCase : str = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_ma... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_roberta_prelayernorm": [
"... | 574 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCamelCase__ = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec... | 574 | 1 |
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin,... | 710 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ ... | 436 | 0 |
'''simple docstring'''
def a__ ( ) -> int:
"""simple docstring"""
return 1
def a__ ( _SCREAMING_SNAKE_CASE : int ) -> int:
"""simple docstring"""
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def a__ ( ... | 71 |
def A ( lowercase__ : int ) -> bool:
if num < 0:
return False
UpperCamelCase__ :int = num
UpperCamelCase__ :int = 0
while num > 0:
UpperCamelCase__ :Optional[int] = rev_num * 10 + (num % 10)
num //= 10
return num_copy == rev_num
if __name__ == "__main__":... | 45 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from tra... | 212 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_v... | 212 | 1 |
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def a ( A__ , A__=1 ) -> int:
'''simple docstring'''
if n_shave_prefix_segments >= 0:
return ".".join(path.split('''.''' )[n_shave_prefix_s... | 35 |
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoModelForMaskedL... | 149 | 0 |
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowercase ( *_SCREAMING_SNAKE_CASE : Any ) -> Union[str, Any]:
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ ... | 702 | """simple docstring"""
from __future__ import annotations
def _lowercase ( _SCREAMING_SNAKE_CASE : int ) -> list[int]:
'''simple docstring'''
__A : List[Any] = [True] * limit
__A : Any = False
__A : ... | 237 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class __snake_case( _lowerCAmelCase ):
'''simple docstring'''
def __init__... | 433 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def _snake_case ( _SCREAMING_SNAKE_CASE... | 433 | 1 |
"""simple docstring"""
def snake_case__ ( _snake_case : int = 4_00_00_00 ):
"""simple docstring"""
UpperCamelCase__ = [0, 1]
UpperCamelCase__ = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:... | 304 | """simple docstring"""
from math import factorial, radians
def snake_case__ ( _snake_case : float , _snake_case : int = 18 , _snake_case : int = 10 ):
"""simple docstring"""
UpperCamelCase__ = angle_in_degrees - ((angle_in_degree... | 304 | 1 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 63 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
UpperCamelCase__ = False
class __SCREAMING_SNAKE_CASE ( unittest.T... | 619 | 0 |
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - generate model_cards - use... | 185 |
from collections import deque
def UpperCamelCase_( _A :Union[str, Any] )-> List[Any]:
UpperCamelCase__ = len(_A )
UpperCamelCase__ = deque()
UpperCamelCase__ = [False for _ in range(_A )]
UpperCamelCase__ = [-1 for _ in range(_A )]
UpperCamelCas... | 185 | 1 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
lowerCAmelCase_ = '''https://www.indeed.co.in/jobs?q=mobile+app+development&l='''
def lowerCamelCase_ ( _UpperCamelCase = "mumbai" ) -> Generator[tuple[str... | 60 |
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.
__snake_case = 10
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , S... | 658 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Tuple = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tok... | 712 |
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached... | 410 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/config.json""",
# See all BioGPT models at https://huggingface.co... | 158 |
'''simple docstring'''
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 (
TFBaseModelOutputWithNoAtten... | 158 | 1 |
UpperCAmelCase_ : Dict = 2_56
# Modulus to hash a string
UpperCAmelCase_ : int = 1_00_00_03
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : str , __magic_name__ : str ) -> bool:
"""simple docstring"""
UpperCamelCase :Opti... | 590 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : Optional[Any] = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwr... | 590 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_av... | 341 |
'''simple docstring'''
def __a(SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ):
'''simple docstring'''
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 18 | 0 |
"""simple docstring"""
import re
def UpperCAmelCase__ ( A__ ) -> bool:
"""simple docstring"""
lowerCamelCase__ = re.compile(
R"^(?:0|94|\+94|0{2}94)" R"7(0|1|2|4|5|6|7|8)" R"(-| |)" R"\d{7}$" )
return bool(re.search(A__ , A__ ) )
if __name__ == "__main__... | 274 |
"""simple docstring"""
# flake8: noqa
# Lint as: python3
SCREAMING_SNAKE_CASE_ : Dict = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
f... | 274 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''kssteven/ibert-roberta-base''': '''https://huggin... | 40 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""kssteven/ibe... | 88 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__A =logging.get_logger(__name__)
class UpperCAmelCase__ ( __UpperCamelCase ):
'''simple docstring'''
Uppe... | 241 |
def a ( _UpperCAmelCase : int = 1 , _UpperCAmelCase : int = 10_00 ):
'''simple docstring'''
__UpperCAmelCase : List[str] = 1
__UpperCAmelCase : Dict = 0
for divide_by_number in range(_UpperCAmelCase , di... | 241 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE :Tuple = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch_available():... | 55 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def _A ( snake_case__ : List[str]="ro" , snake_case__ : int="en" , snake_case__ : Any="wmt16" , snake_case__ : Optional[Any]=None ):
try:
import datasets
except ... | 261 | 0 |
"""simple docstring"""
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.util... | 237 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
lowerCamelCase : Optional[Any] ={
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fine... | 237 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
_validate_point(__lowercase )
_validate_point(__lowercase )
if len(__lowercase ) != len(__lowercase ):
raise ValueError('''Both points mus... | 634 |
'''simple docstring'''
import numpy as np
lowercase : str = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
... | 116 | 0 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__magic_name__ =logging.getLogger(__name__)
class _A :
def __init__(self ) -> Any:
... | 469 | from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProcessor
from .mo... | 469 | 1 |
import unittest
from transformers import 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_t... | 519 |
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : int , _lowerCamelCase : Collection[float] | None = None ):
... | 519 | 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__ : List[str] = False
try:
... | 713 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def UpperCAmelCase ( a_ , a_=1 ) -> str:
"""simple docstring"""
if n_shave_prefix_segments >= 0:
... | 385 | 0 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, 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
from ...test_pipeline_mixin ... | 428 |
def UpperCamelCase__ ( lowerCAmelCase__ ):
if not isinstance(lowerCAmelCase__ ,lowerCAmelCase__ ):
lowercase = f"""Input value of [number={number}] must be an integer"""
raise TypeError(lowerCAmelCase__ )
if number < 1:
lowercase = f"""Input va... | 428 | 1 |
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 lowerCAmelCase__ ( unitte... | 234 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https://huggingface.co/models?filter=cvt
}
clas... | 234 | 1 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class A_ ( __UpperCamelCase ):
'''simpl... | 669 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_to... | 669 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase : Any = {
'configuration_perceiver': ['PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_... | 718 |
# 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... | 53 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from... | 103 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase : List[str] = {
"configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
"tokenization_bio... | 405 | 0 |
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
SCREAMING_SNAKE_CASE : Dict = Path(__file__).resolve().parents[3] / "src"
sys.path.insert(1, str(git_repo_path))
... | 238 |
'''simple docstring'''
class snake_case :
"""simple docstring"""
def __init__( self ) -> Tuple:
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ = {}
... | 238 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractio... | 317 |
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
__lowerCamelCase = logging.getLogger(__n... | 317 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase =logging.get_logger(__name__)
__UpperCAmelCase ... | 261 |
"""simple docstring"""
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 =False
try:
__UpperCAm... | 261 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCAmelCase ( lowerCamelCase_) -> List[Any]:
if not nums:
raise ValueError('List is empty')
return sum(_lowerCAmelCase) / len(_lowerCAmelCase)
if __name__ == "__main__":
import d... | 596 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transf... | 44 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availabl... | 282 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenize... | 282 | 1 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.... | 79 |
'''simple docstring'''
def __UpperCamelCase ( lowercase_ : int = 1_000_000 ):
"""simple docstring"""
a_ = set(range(3 , lowercase_ , 2 ) )
primes.add(2 )
for p in range(3 , lowercase_ , 2 ):
... | 536 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 700 | import numpy as np
def __lowerCamelCase (UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : float = 1e-12 , UpperCAmelCase__ : int = 1_0_0 , ):
assert np.shape(UpperCAmelCase__ )[0] == np.shape(UpperCAme... | 647 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torc... | 35 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import ... | 260 | 0 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASE... | 721 |
from sklearn.metrics import mean_squared_error
import datasets
__lowerCamelCase : List[str] = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel,... | 501 | 0 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowerCamelCase_ : Optional[Any] = datasets.logging.get_logger(__name__)
lowerCamelCase_ : int = """\
@InProceedings{moosavi2019minimu... | 548 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
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_G... | 157 | 0 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from... | 715 |
import math
def __A ( _lowercase ):
'''simple docstring'''
_A = []
_A = 2
_A = int(math.sqrt(_lowercase ) ) # Size of every segment
_A = [True] * (end + 1)
_A = []
while start <= end:
if temp[start] is True... | 62 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A__ ( __SCREAMING_SNAKE_CASE ):
lowerCamelCase__ : Any =["image_processor", "tokenizer"]
lowerCamelCase__ : Dict ... | 154 |
from typing import Any
class A__ :
def __init__( self , lowerCamelCase ) -> Dict:
"""simple docstring"""
__magic_name__ : List[str] = data
__magic_name__ : List[Any] = None
de... | 154 | 1 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
"""simple docstring"""
assert (
isinstance(lowercase_ , lowercase_ ) and number_of_steps > 0
), F"number_of_steps needs to be positive integer, your input {number_of_steps}"
if number_of_steps == 1:
... | 375 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE... | 375 | 1 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 586 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTConfig", "DeiTOnnxConfig... | 586 | 1 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_lza, require... | 716 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Tuple = logging.get_logger(__name__)
UpperCAmelCase_ : List[str] = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
"""... | 440 | 0 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenc... | 690 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 690 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__magic_name__ : int = logging.get_logger(__name__)
__magic_name__ : Optional[int] = {
'... | 710 |
import math
def lowerCAmelCase ( snake_case__ : int )-> str:
A_ = 0
A_ = 0
while num > 0:
A_ = num % 8
A_ = octal + (remainder * math.floor(math.pow(10 , snake_case__ ) ))
counter += 1... | 608 | 0 |
"""simple docstring"""
from string import ascii_uppercase
SCREAMING_SNAKE_CASE_ = {str(ord(c) - 55): c for c in ascii_uppercase}
def lowercase__ ( lowerCAmelCase : int , lowerCAmelCase : int ) -> str:
"""simple docstring"""
... | 373 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_ = {'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARC... | 373 | 1 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_configur... | 710 |
_SCREAMING_SNAKE_CASE : List[str] = range(2, 2_0 + 1)
_SCREAMING_SNAKE_CASE : Optional[Any] = [1_0**k for k in range(ks[-1] + 1)]
_SCREAMING_SNAKE_CASE : dict[int, dict[int, list[list[int]]]] = {}
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : ... | 55 | 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/licens... | 19 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCAmelCase( lowerCamelCase ):
lowercase__ = (DDPMScheduler,)
def UpperCAmelCase ( self , **__a) ->... | 19 | 1 |
"""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 .tokenizat... | 711 |
"""simple docstring"""
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
UpperC... | 430 | 0 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __SCREAMING_SNAKE_CASE ( a__ : int ) -> str:
def wrapper(*a__ : List[Any] ,**a__ : str ):
__A : List[Any] = ... | 17 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
... | 361 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class _A ( _UpperCAmelCase ):
"""simple docstring"""
def __init__( self : Any , A_ : Union[str, Any] , A_ :... | 718 | """simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_configuration_comm... | 93 | 0 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
... | 234 |
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from ...ut... | 234 | 1 |
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : str , UpperCAmelCase_ : List... | 431 |
import gc
import unittest
from transformers import CTRLConfig, 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... | 431 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...... | 481 |
# 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 app... | 481 | 1 |
'''simple docstring'''
from itertools import permutations
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : tuple ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
... | 506 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...u... | 506 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : ... | 452 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[int] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Union[str, Any] = {
'''tanreinama/GPTSAN-2.8B-spout_is_uniform''': (
''... | 452 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
__lowerCAmelCase : Union[str, Any] = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attenti... | 284 |
from __future__ import annotations
def UpperCAmelCase_ ( __lowerCAmelCase ) -> int:
if not nums:
return 0
__lowercase : List[Any] = nums[0]
__lowercase : Union[str, Any] = 0
for num in nums[1:]:
__lowercase , __lowercase : ... | 284 | 1 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
lowercase_ : Optional[int] = logging.get_logger(__name__)
def A__ ( snake_case_ : List[Any] ):
SCREAMING_SNAKE_... | 64 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowerCAmelCase__ ( a , a):
'''simple docstring'''
@register_to_config
def __init__( self , *,
__lowerCamelCase = 4 ... | 503 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, 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_avail... | 714 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__snake_case = 3
def _lowercase ( SCREAMING_SNAKE_CASE_ : int ):
"""simple docstring"""
print("""Generating primitive root of p""" ... | 181 | 0 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def snake_case ( UpperCamelCase__ : int = 3 ) -> qiskit.result.counts.Counts:
if isinstance(UpperCamelCase__ , UpperCamelCase... | 222 |
"""simple docstring"""
def snake_case ( UpperCamelCase__ : str , UpperCamelCase__ : list[str] ) -> str:
lowerCamelCase : str = """"""
for word_or_phrase in separated:
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):... | 222 | 1 |
'''simple docstring'''
def __A ( UpperCAmelCase = 5_0 ) -> int:
'''simple docstring'''
_UpperCamelCase : Optional[int] = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in r... | 204 | '''simple docstring'''
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def snake_case__ ( self : Dic... | 204 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase = {
"configuration_squeezebert": [
"SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SqueezeBertConfig",
"SqueezeBertO... | 45 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}
try:
if not is_torch_available():
... | 253 | 0 |
def _lowerCamelCase ( A_ : Union[str, Any] ) -> Optional[Any]:
'''simple docstring'''
if n_term == "":
return []
UpperCamelCase__ : str =[]
for temp in range(int(_UpperCAmelCase ) ):
series.append(f'''1/{temp + 1}''' if series else "1" )
return series
if _... | 716 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from ..test_modeling_... | 582 | 0 |
snake_case__ : int = {
"""a""": """AAAAA""",
"""b""": """AAAAB""",
"""c""": """AAABA""",
"""d""": """AAABB""",
"""e""": """AABAA""",
"""f""": """AABAB""",
"""g""": """AABBA""",
"""h""": """AABBB""",
"""i""": """ABAAA""",
"""j""": """BBBAA""",
"""k""": """ABAA... | 402 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ : Dict = {
"""configuration_whisper""": ["""WHISPER_PRETRAINED_CONFIG_ARCHI... | 402 | 1 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
__lowercase : Any = object()
# For specifying empty leaf dict `{}`
__lowercase : str = objec... | 66 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCamelCase_ ( _lowerCamelCase : int = 8 ):
lowerCamelCase_ = ascii_letters + digits + punctuation
return "".joi... | 66 | 1 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, 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
from ...te... | 9 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def A ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> int:
A__ = OmegaConf.load(__UpperCamelCase )
A__ = torch.load(__Uppe... | 9 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCAmelCase_ = {'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}
try:
if not is_torch_available():
raise Optional... | 80 |
def lowerCamelCase__ ( A__ : int = 2000000 ):
'''simple docstring'''
__lowerCamelCase = [0 for i in range(n + 1 )]
__lowerCamelCase = 1
__lowerCamelCase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_list[... | 80 | 1 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorc... | 109 |
'''simple docstring'''
import gc
import unittest
from transformers import CTRLConfig, 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_modelin... | 109 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Union[str, Any] = logging.get_logger(__name__)
lowerCAmelCase__ : int = {
"facebook/vit-mae-base": "https://huggingface.co/facebook/vit-mae-base/resolve/main/con... | 329 |
'''simple docstring'''
import requests
lowerCAmelCase__ : Union[str, Any] = "" # <-- Put your OpenWeatherMap appid here!
lowerCAmelCase__ : str = "https://api.openweathermap.org/data/2.5/"
def __UpperCamelCase ( _UpperCAmelCase = "Chicago", _UpperCAmelCase = APPID ):
return r... | 329 | 1 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ : Union[str, Any] , SCREAMING_SNAKE_CASE_ : Dict , SCREAMING_SNAKE_CASE_ : Tuple ) -> Optional[Any]:
_lowercase ... | 287 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def UpperCamelCase__ ( ) -> List[str]:
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as origin... | 287 | 1 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ : Optional[Any] = l... | 705 |
'''simple docstring'''
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a ( UpperCamelCase_ : List[str] ) -> Any:
snake_case__ =args.pruning_method
snake_case__ =args.thresho... | 581 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionPipeline,... | 12 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase : Any = {
"""configuration_blenderbot""": [
"""BLENDERBOT_PRETRAINED_C... | 336 | 0 |
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 ort
... | 708 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...token... | 472 | 0 |
"""simple docstring"""
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"post_extract_pr... | 532 |
"""simple docstring"""
class lowercase :
def __init__( self ) -> Any:
lowerCAmelCase = """"""
lowerCAmelCase = """"""
lowerCAmelCase = []
def _snake_case ( self , lowercase , lowercase ) ... | 532 | 1 |
from __future__ import annotations
def a_ ( __magic_name__ , __magic_name__ ) -> set[str]:
"""simple docstring"""
snake_case : Union[str, Any] = set(__magic_name__ ), [start]
while stack:
snake_case : List[Any] = ... | 710 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( a ):
A__ : List[str] = ['image_processor', 'tokenizer']
A__ : Any = 'CLIPImageProcessor'
A__ : Optional[int] = ('CLIPTo... | 84 | 0 |
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