code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
def _A ( UpperCAmelCase = 1000000 ):
'''simple docstring'''
A__ = set(range(3 ,lowerCamelCase_ ,2 ) )
primes.add(2 )
for p in range(3 ,lowerCamelCase_ ,2 ):
if p not in primes:
co... | 531 |
__snake_case : str ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : ... | 647 | 0 |
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_avai... | 663 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
de... | 647 | 0 |
'''simple docstring'''
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
__magic_name__ : List[str] = {
'n_samples': 64,
'horizon': 32,
'num_inference_steps': 20,
'n_guide_steps': 2, # can set to 0 for faster sampling, does not use... | 672 |
import requests
__snake_case : Optional[int] ='YOUR API KEY'
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str = giphy_api_key):
'''simple docstring'''
lowerCAmelCase__ : Tuple = '''+'''.join(query.split())
lo... | 647 | 0 |
"""simple docstring"""
from manim import *
class __UpperCAmelCase( lowerCamelCase__ ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
'''simple docstring'''
lowercase__ : Union[str, Any]= Rect... | 218 |
from collections.abc import Callable
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase = None ) -> None:
"""simple docstring"""
lowerCAmelCase__ : list = []
# Stores indexes of each item for supporting updates and ... | 647 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
'facebook/s2t-small-librispeech-asr': (
'https://huggingface.co/fac... | 369 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 647 | 0 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def A ( snake_case__ : List[str] , snake_case__ : List[Any]=7 ) -> List[str]:
'''simple docstring'''
__snake_case = None
if token ... | 313 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
snake_case_ =(KDPMaDiscreteScheduler,)
snake_case_ =10
def... | 647 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class UpperCamelCase__ (lowerCamelCase__ ):
'''simple docstring'''
... | 311 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowerCamelCase__ ( unittest.TestCase):
'''simple docstring'''
def lowerCAmelCase__ (self ) -> str:
"""simple docstring"""
... | 647 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__lowercase : int = TypeVar("T")
class _A ( Generic[T] ):
"""simple docstring"""
def __init__( self : Optiona... | 564 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case : List[Any] =get_tests_dir('fixtures/test_sent... | 647 | 0 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowerCamelCase__ ) , 'Tatoeba directo... | 398 |
import math
import unittest
def lowerCAmelCase__ ( lowerCamelCase_ : int):
'''simple docstring'''
assert isinstance(lowerCamelCase_ ,lowerCamelCase_) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 a... | 647 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 175 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logg... | 647 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {'vocab_file': 'sent... | 558 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs
if is_torch_available():
import ... | 647 | 0 |
'''simple docstring'''
import os
import jsonlines
import numpy as np
from tqdm import tqdm
lowerCAmelCase_ = 2_0_4_8
lowerCAmelCase_ = 4_0_9_6
lowerCAmelCase_ = 4_2
lowerCAmelCase_ = os.environ.pop('''PROCESS_TRAIN''', '''false''')
lowerCAmelCase_ ... | 531 |
def lowerCAmelCase__ ( lowerCamelCase_ : Dict):
'''simple docstring'''
lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_)
while cur > 1:
# Find the maximum number in arr
lowerCAmelCase__ : Tuple = arr.index(max(arr[0:cur]))
... | 647 | 0 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowerCamelCase :
"""simple docstring"""
UpperCAmelCase_ = field(
default="codeparrot/codeparrot" , metadata={"help": "Model name or path of mo... | 663 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, To... | 647 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.t... | 672 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case : int ={
'configuration_gpt_bigcode': ['GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTBigCodeConfig'],
}
try:
if not is_torch_available... | 647 | 0 |
"""simple docstring"""
import requests
a : Optional[int] = 'YOUR API KEY'
def lowercase__(A , A = giphy_api_key ) ->Any:
"""simple docstring"""
lowercase__ : Tuple= '''+'''.join(query.split() )
lower... | 218 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class lowerCamelCase__ :
'''simple docstring'''
snake_case_ =None
snake_case_ =False
snake_case_ =False
snake_case_ =False
snake_case_ =Non... | 647 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CA... | 369 |
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int]):
'''simple docstring'''
lowerCAmelCase__ : int = (boundary[1] - boundary[0]) / steps
lowerCAmelCase__ : Optional[int] = boundary[0]
lowerCAmelCase__ : ... | 647 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dim... | 313 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMode... | 647 | 0 |
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
SCREAMING_SNAKE_CASE__ : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAK... | 311 |
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_con... | 647 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( snake_case):
assert isinstance(lowerCamelCase_, lowerCamelCase_), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
__snake_case = f"The input value of [n={numb... | 564 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
def __init__(self ... | 647 | 0 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
A_: List[Any] = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Method for Automatic Eval... | 398 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
__snake_case : List[str] =2_0_4_8
__snake_case : List[Any] =4_0_9_6
__snake_case : Tuple =4_2
__snake_case : List[Any] =os.environ.pop('PROCESS_TRAIN', 'false')
__snake_case :... | 647 | 0 |
from scipy.stats import spearmanr
import datasets
lowercase_: List[Any] = '\nThe Spearman rank-order correlation coefficient is a measure of the\nrelationship between two datasets. Like other correlation coefficients,\nthis one varies between -1 and +1 with 0 implying no correlation.\nPos... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: str = {
'configuration_bloom': ['BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BloomConfig', 'BloomOnnxConfig'],
}
try:
if not is_to... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_: int = logging.get_logger(__name__)
lowercase_: str = {
'RWKV/rwkv-4-169m-pile': 'https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json',
'RWKV/rwkv-4-430m... | 648 |
import unittest
from transformers import BertGenerationConfig, 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... | 648 | 1 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class lowercase__ (__s... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
from collections import defaultdict
from math import ceil, sqrt
def _lowercase ( UpperCAmelCase_ = 1_000_000 , UpperCAmelCase_ = 10):
"""simple docstring"""
snake_case__ : defaultdict = defaultdict(UpperCAmelCase_)
for outer_width in range(3 , (t... | 648 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 | 1 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowercase__ :
"""simple docstring"""
def __init__( self : Dict , __a : List[Any] , __a : int , __a : int ):
if dst_width < 0 or dst_height < 0:
raise ValueE... | 648 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not is_accelerate_available():
return method
snake_case__ : Union[str, An... | 648 | 1 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase_: Optional[Any] = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : Opti... | 648 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 1 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowercase_: int = {
# 1536-bit
5: {
'prime': int(
... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: Union[str, Any] = {
'configuration_distilbert': [
... | 648 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 | 1 |
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available()... | 648 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 | 1 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
lowercase_: Union[str, Any] = False
class lowercase__ (unittest.TestCase ):... | 648 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSp... | 648 | 1 |
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 648 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 | 1 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase_: Optional[Any] = logging.get_logger(__name__)
lowercase_: Dict = {'vocab_f... | 648 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 | 1 |
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
from acceler... | 648 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
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 ... | 648 | 1 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
lowercase_: str = '__DUMMY_TRANSFORMERS_USER__'
lowercase_: Optional[Any] = 'Dummy User'
lowercase_: List[Any] ... | 648 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 | 1 |
from __future__ import annotations
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if nth_term == "":
return [""]
snake_case__ : Any = int(UpperCAmelCase_)
snake_case__ : Union[str, Any] = int(UpperCAme... | 648 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 | 1 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDat... | 648 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__ (__snake_case ):
... | 648 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Any = (CMStochasticIterativeScheduler,)
__UpperCa... | 648 | 1 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowercase__ (nn.Module ):
"""simple docstring"""
__UpperCamelCase : int
__UpperCamelCase : jnp.dtype = jnp.floataa
def lowercase ( self : Union[str, Any] ):
... | 648 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 | 1 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
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 ... | 648 |
# 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 requi... | 648 | 1 |
import string
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : List[Any] = """"""
for i in sequence:
snake_case__ : List[Any] = ord(UpperCAmelCase_)
if 65 <= extract <= 90:
output += chr(155 - extract)
eli... | 648 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 | 1 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 | 1 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import i... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
def _lowercase ( ):
"""simple docstring"""
snake_case__ : str = 0
for i in range(1 , 1_001):
total += i**i
return str(UpperCAmelCase_)[-10:]
if __name__ == "__main__":
print(solution())
| 648 |
import unittest
from transformers import BertGenerationConfig, 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... | 648 | 1 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
lowercase_: Dict = logging.get_l... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
return 1 / (1 + np.exp(-z))
def _... | 648 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 | 1 |
from ...processing_utils import ProcessorMixin
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : List[Any] = ['image_processor', 'feature_extractor']
__UpperCamelCase : Tuple = 'TvltImageProcessor'
__Uppe... | 648 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not is_accelerate_available():
return method
snake_case__ : Union[str, An... | 648 | 1 |
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from tra... | 648 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 1 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
lower... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class lowercase__ (__snake_case ):
"""simple doc... | 648 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 | 1 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_to... | 648 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 | 1 |
from __future__ import annotations
import requests
lowercase_: List[str] = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_catego... | 648 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSp... | 648 | 1 |
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy as np
from .... | 648 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 | 1 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common im... | 648 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 | 1 |
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_availabl... | 648 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
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 ... | 648 | 1 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( sel... | 648 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 | 1 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 | 1 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
return "".join(sorted(UpperCAmelCase_))
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
return... | 648 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 | 1 |
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
lowercase_: Any = 'Usage of script: script_name <size_of_canvas:int>'
lowercase_: List[str] = [0] * 1_00 + [1] * 10
random.shuffle(choice)
def... | 648 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Any = (CMStochasticIterativeScheduler,)
__UpperCa... | 648 | 1 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_t... | 648 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 |
# 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 requi... | 648 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_: str = logging.get_logger(__name__)
lowercase_: Any = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/confi... | 648 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 | 1 |
from __future__ import annotations
from math import gcd
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ = 2 , UpperCAmelCase_ = 1 , UpperCAmelCase_ = 3 , ):
"""simple docstring"""
if num < 2:
raise ValueError("""The input value cannot be less than 2... | 648 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 | 1 |
import collections
import os
import re
from pathlib import Path
lowercase_: Union[str, Any] = 'src/transformers'
# Matches is_xxx_available()
lowercase_: int = re.compile(r'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
lowercase_: Dict ... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
from __future__ import annotations
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if len(UpperCAmelCase_) == 0:
return []
snake_case__ , snake_case__ : List[str] = min(UpperCAmelCase_), max(UpperCAmelCase_)
snake_case__ : List[str]... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowercase_: Optional[Any] = get_tests_... | 648 |
import unittest
from transformers import BertGenerationConfig, 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... | 648 | 1 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
return " ".join(input_str.split()[::-1])
if __name__ == "__main__":
import doctest
doctest.testmod()
| 648 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 | 1 |
def _lowercase ( UpperCAmelCase_ = 1_000_000):
"""simple docstring"""
snake_case__ : List[str] = [i - 1 for i in range(limit + 1)]
for i in range(2 , limit + 1):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , UpperCAmelCase_):... | 648 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not is_accelerate_available():
return method
snake_case__ : Union[str, An... | 648 | 1 |
from __future__ import annotations
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ = None):
"""simple docstring"""
snake_case__ : Union[str, Any] = word_bank or []
# create a table
snake_case__ : int = len(UpperCAmelCase_) + 1
... | 648 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcesso... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_: Dict = logging.get_logger(__name__)
lowercase_: List[Any] = {
'bert-base-unc... | 648 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 | 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_... | 648 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 | 1 |
import string
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
for key in range(len(string.ascii_uppercase)):
snake_case__ : Tuple = """"""
for symbol in message:
if symbol in string.ascii_uppercase:
snake_case__ : Dict ... | 648 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSp... | 648 | 1 |
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_... | 648 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 | 1 |
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
lowercase_: Dict = logging.get_logger(__name__)
lowercase_: List[Any] ... | 648 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 | 1 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
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 ... | 648 | 1 |
import math
def _lowercase ( ):
"""simple docstring"""
snake_case__ : List[Any] = input("""Enter message: """)
snake_case__ : str = int(input(F'Enter key [2-{len(UpperCAmelCase_) - 1}]: '))
snake_case__ : Any = input(""... | 648 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_: Any = logging.get_logger(__name__)
lowercase_: List[Any] = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-cc-news-pretrained-emb... | 648 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 | 1 |
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,
require_torch_gpu,
require_torch_mu... | 648 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 | 1 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class lowercase__ (unittest.TestCase ):
"""simple docstring"... | 648 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Any = (CMStochasticIterativeScheduler,)
__UpperCa... | 648 | 1 |
lowercase_: int = [
(10_00, 'M'),
(9_00, 'CM'),
(5_00, 'D'),
(4_00, 'CD'),
(1_00, 'C'),
(90, 'XC'),
(50, 'L'),
(40, 'XL'),
(10, 'X'),
(9, 'IX'),
(5, 'V'),
(4, 'IV'),
(1, 'I'),
]
def _lowercase ( UpperCAmelCase_):
""... | 648 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 | 1 |
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be check... | 648 |
# 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 requi... | 648 | 1 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import t... | 648 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_: Dict = logging.get_logger(__name__)
lowercase_: Optional[int] = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
# See al... | 648 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 | 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
fro... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
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,
AutoMo... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
from math import factorial, radians
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ = 18 , UpperCAmelCase_ = 10):
"""simple docstring"""
snake_case__ : List[str] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from degre... | 648 |
import unittest
from transformers import BertGenerationConfig, 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... | 648 | 1 |
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase_: int = logging.getLogger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : int = 'masked_bert'
... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_contro... | 648 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 | 1 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepi... | 648 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not is_accelerate_available():
return method
snake_case__ : Union[str, An... | 648 | 1 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = {
"""en""": ""... | 648 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_: Union[str, Any] = {
'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}
try:
if not is_torch_available():
raise... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
import cmath
import math
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = math.radians(UpperCAmelCase_)
snake_case__ : int = math.radian... | 648 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 | 1 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_: List[Any] = logging.get_logger(__name__)
lowercase_: int = {'vocab_file': 'vocab.json'}
lowercase_: List[str] ... | 648 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 | 1 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase__ (__snake_case , unittest.TestCase ):
"""simple docstring""... | 648 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSp... | 648 | 1 |
lowercase_: List[str] = [0, 2, 4, 6, 8]
lowercase_: Optional[Any] = [1, 3, 5, 7, 9]
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if remaining_length == 0:
if digits... | 648 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 | 1 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common im... | 648 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless ... | 648 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
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 ... | 648 | 1 |
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