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 math
import random
def lowercase ( UpperCamelCase : float , UpperCamelCase : bool = False ):
"""simple docstring"""
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
__A : ... | 656 | """simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils... | 656 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCAmelCase__ = TypeVar('T')
class __lowercase (Generic[T] ):
def __init__( self : Union[str, Any]... | 6 |
'''simple docstring'''
import argparse
import struct
import unittest
class __lowercase :
def __init__( self : Tuple , UpperCAmelCase_ : bytes):
UpperCamelCase__ : Dict = data
# Initialize hash values
UpperCamelCas... | 6 | 1 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...image_util... | 439 |
from __future__ import annotations
from math import gcd
def __lowerCAmelCase ( _UpperCamelCase : int , _UpperCamelCase : int = 2 , _UpperCamelCase : int = 1 , _UpperCamelCase : int = 3 , ) -> int | None:
'''simple docstring'''
if num < 2:
raise ValueError('The input v... | 439 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Generic, TypeVar
lowerCAmelCase : Optional[Any] = TypeVar("""T""")
class _UpperCamelCase ( Generic[T]):
'''simple docstring'''
def __init__( self , a_ ) -> None:
... | 425 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunD... | 425 | 1 |
'''simple docstring'''
def A ( UpperCamelCase_ : Optional[int] ) -> str:
'''simple docstring'''
lowerCAmelCase__ = []
lowerCAmelCase__ = set({"(", "[", "{"} )
lowerCAmelCase__ = set({")", "]", "}"} )
lowerCAmelCase__ = ... | 48 |
'''simple docstring'''
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def A ( UpperCamelCase_ : Optional[int] , UpperCamelCase_ ... | 48 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase_: Dict = {"configuration_vit_mae": ["VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_M... | 705 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 668 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kine... | 96 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
SCREAMING_SNAKE_CASE_ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def A__ ( ) -> List[str]:
'''simple docstring'''
_UpperCAmelCase = os.path.dirname(os.path.realpath(... | 426 | 0 |
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name... | 180 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class lowerCamelCase_ ( unittest.TestCase ):
def A ( self ):
"""simple docstring"""
__magic_name__ :Union[str, Any] ... | 180 | 1 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
SCREAMING_SNAKE_CASE__ : Optional[Any] = logging.get_logger(__name__)
class UpperCAmelCase_ ( __lowerCamelCase ):
def __init__( self , *_l... | 79 | def _a ( lowercase__ : int = 60_08_51_47_51_43 ):
'''simple docstring'''
try:
SCREAMING_SNAKE_CASE__ : Dict = int(lowercase__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
... | 85 | 0 |
from __future__ import annotations
A_ = list[list[int]]
# assigning initial values to the grid
A_ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0, 5],
[0, 5, 0, 0, 9, ... | 479 | def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> int:
"""simple docstring"""
while a != 0:
lowercase ,lowercase = b % a, a
return b
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> int... | 479 | 1 |
'''simple docstring'''
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_... | 261 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common im... | 261 | 1 |
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_lowerCAmelCase : Dict = "src/transformers"
_lowerCAm... | 364 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
_lowerCAmelCase : List[Any] = ["small", "medium", "large"]
_lowerCAmelCase : List[Any] = "lm_head.decoder.weight"
_lowerCAmelCase : Optional[int] = "lm_head.weight"
def lowerCAmelCase ( ... | 364 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
lowerCAmelCase = logging... | 174 |
"""simple docstring"""
from collections.abc import Callable
class A_ :
"""simple docstring"""
def __init__( self :Tuple , lowerCamelCase_ :Callable | None = None ):
"""simple docstring"""
lowerCamelCase__ : list... | 174 | 1 |
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformers import Aut... | 685 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=lowerCamelCase_ ):
__a : Tuple = ["flax"]
def __init__( self ,*snake_case__ ,**snake_case__ ):
requires_backends(self ,['flax'] )
@classmethod
... | 685 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : int = 10 , _UpperCamelCase : int = 10_00 , _UpperCamelCase : bool = True ) -> int:
"""simple docstring"""
assert (
isinstance(lowerCamelCase_ , lowerCamelCase_ )
and isinstance(... | 405 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCase__ : Tuple = logging.get_logger(__name__)
UpperCamelCase__ : Option... | 105 | 0 |
'''simple docstring'''
def UpperCAmelCase_ ( __lowercase : list[int] ) -> int:
'''simple docstring'''
if not numbers:
return 0
if not isinstance(__lowercase , (list, tuple) ) or not all(
isinstance(__lowercase , __lowercase ) for number in ... | 119 |
'''simple docstring'''
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def UpperCAmelCase_ ( __lowercase : str ) -> str:... | 119 | 1 |
"""simple docstring"""
lowerCAmelCase: Tuple =8.3_1_4_4_5_9_8
def __snake_case ( __A ,__A ) -> List[Any]:
if temperature < 0:
raise Exception("""Temperature cannot be less than 0 K""" )
if molar_mass <= 0:
raise Exception("""Molar ... | 607 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
A : Optional[Any] = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self ... | 636 | 0 |
"""simple docstring"""
import argparse
import json
import subprocess
def a__ ( a : Optional[Any] , a : Optional[int] ):
"""simple docstring"""
_snake_case : str = []
_snake_case : Optional[Any] = (
f'curl -H "Accept: application/vnd.gith... | 87 |
"""simple docstring"""
from __future__ import annotations
class _UpperCAmelCase :
def __init__( self , snake_case_ , snake_case_ ):
_snake_case , _snake_case : Dict = text, pattern
_snake_case , _snake_case : int = len(sna... | 87 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
... | 347 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class lowercase__ ( __SCREAMING_SNAKE_CASE ... | 475 | 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.utils.testing_utils... | 123 |
'''simple docstring'''
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from uti... | 123 | 1 |
"""simple docstring"""
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_avail... | 4 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipelin... | 4 | 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 _a ( unittest.TestCase ):
"""simple docstri... | 713 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _snake_case (__lowercase , __lowercase , __lowercase = "x" , __lowercase = 10**-10 , __lowercase = 1 , ):
UpperCamelCase_ = symbols(__lower... | 618 | 0 |
"""simple docstring"""
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 _UpperCAmelCase... | 434 | """simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def UpperCamelCase ( SCREAMING_SNAKE_CASE_ ) ->Union[str, Any]:
return ConvertCommand(
args.model_type , args.tf_checkpoint ,... | 434 | 1 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_av... | 713 |
"""simple docstring"""
def snake_case__ ( _lowerCamelCase ) ->list:
"""simple docstring"""
__lowercase : Optional[int] = [0] * len(_lowerCamelCase )
for i in range(1, len(_lowerCamelCase ) ):
# use last results for better performance - dyna... | 281 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
... | 584 | '''simple docstring'''
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simpli... | 390 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase : int = {
"configuration_nllb_moe": [
"NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP",
"NllbMoeConfig",
]
}
try:
if not is_t... | 651 |
from manim import *
class A( UpperCamelCase ):
'''simple docstring'''
def a__ ( self : Optional[Any] ) -> List[str]:
"""simple docstring"""
lowerCamelCase_ = Rectangle(height=0.5 , width=0.5... | 651 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCamelCase__ (... | 607 |
"""simple docstring"""
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
... | 607 | 1 |
'''simple docstring'''
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class snake_case ( lowercase_, lowercase_ ):
"""simple docstring"""
@register_to_config
def _... | 238 |
'''simple docstring'''
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
class ... | 238 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : Optional[Any] = {
'RWKV/rwkv-4-169m-pile': 'https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config... | 643 |
def a__ ( snake_case__ : Tuple ): # noqa: E741
_UpperCAmelCase : Dict = len(snake_case__ )
_UpperCAmelCase : Tuple = 0
_UpperCAmelCase : Union[str, Any] = [0] * n
_UpperCAmelCase : Union[str, Any] = [False] * n
_U... | 643 | 1 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase_ ( _lowerCamelCase ):... | 541 |
def lowerCamelCase__ ( UpperCamelCase__ : list[int] , UpperCamelCase__ : int ) -> bool:
'''simple docstring'''
_snake_case = len(UpperCamelCase__ )
_snake_case = [[False] * (required_sum + 1) for _ in range(arr_len + 1 ... | 541 | 1 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def _lowerCamelCase ( __lowerCamelCase ) -> List[Any]:
'''simple docstring'''
def wrapper(*__lowerCamelCase , ... | 79 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 684 | 0 |
"""simple docstring"""
def _lowerCamelCase ( lowerCamelCase__ : float , lowerCamelCase__ : float ):
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 * mass * abs(lowerCamelCase__ ) * abs(lowerCamelCase__ )
if __name__ == "... | 701 |
"""simple docstring"""
import heapq
def _lowerCamelCase ( lowerCamelCase__ : dict ):
lowercase__ : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Priority Queue
# heapq ... | 128 | 0 |
'''simple docstring'''
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def UpperCamelCase ( lowercase_ : Tuple ) -> Optional[Any]:
'''simple docstring'''
... | 72 |
'''simple docstring'''
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
_UpperCAmelCase : Union[str, Any] = datasets.logging.get_logger(__name__)
_UpperCAmelCase : Optional[Any] = '''\
@InP... | 72 | 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
__lowerCamelCase : Any = logging.get_logger(__name__)
__lowerCamelCase : int = {
... | 38 |
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
__lowerCamelCase : Dict = logging.get_logger(__name__)
__lo... | 38 | 1 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase_ : Optional[int] = {'''UserAgent''': UserAgent().random}
def _lowerCAmelCase ( lowerCamelCase__ : ... | 572 | import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load... | 312 | 0 |
"""simple docstring"""
from math import isclose, sqrt
def lowercase__ ( snake_case_ :float , snake_case_ :float , snake_case_ :float ):
__UpperCAmelCase = point_y / 4 / point_x
__UpperCAmelCase = 2 * normal_gradient / (1 + normal_gradient * normal_gra... | 397 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( snake_case_ :list[int] ):
__UpperCAmelCase = len(snake_case_ ) // 2
# choose the middle 3 elements
__UpperCAmelCase = lst[m - 1 : m + 2]
# if middle element is peak
if thre... | 397 | 1 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self : Tuple , UpperCamelCase_ : list[tuple[float, float]] ):
... | 545 |
"""simple docstring"""
from maths.prime_check import is_prime
def A ( __snake_case: int ) -> int:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
__magic_name__ = F"""Input value of [number={numbe... | 545 | 1 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
MusicgenProcesso... | 705 |
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
_A : Any = logging.get_logger(__name__)
_A : str = {'vocab_file': 'senten... | 130 | 0 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase ): # noqa: E741
'''simple docstring'''
while r - l > 1:
UpperCAmelCase = ... | 673 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : int = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'''facebook/wav2vec2-base-960h''': '''https:... | 673 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : str = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_ava... | 145 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : Optional[Any] = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig'... | 145 | 1 |
class __lowerCamelCase :
"""simple docstring"""
def __init__( self : List[str] , SCREAMING_SNAKE_CASE__ : str ) -> int:
lowerCAmelCase__ = val
lowerCAmelCase__ = None
lowerCAmelCase__ = None
... | 61 |
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... | 235 | 0 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
RequestCounter,... | 718 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiec... | 362 | 0 |
'''simple docstring'''
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
... | 539 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_g... | 539 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Any ={
'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
'google/fnet-large': 'https://huggingface... | 224 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
... | 224 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def __snake_case ( lowerCAmelCase : Sequence[float] , lowerCAmelCase : bool = False ):
if not arr:
return 0
__UpperCAmelCase = 0 if allow_empty_subarrays else float('-inf' )
__UpperCAmelCase ... | 396 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logg... | 125 | 0 |
'''simple docstring'''
# Imports
import numpy as np
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self : int , __A : Tuple=None , __A : Union[str, Any]=None , __A : Optional[Any]=None , __A : int=Non... | 211 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers i... | 211 | 1 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE_... | 329 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_ava... | 451 | 0 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@require_torch
@req... | 701 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLImgaImgPipeline,
UNetaDCo... | 203 | 0 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowercase__( __UpperCamelCase: Optional[int] ,__UpperCamelCase: List[Any] ,__UpperCamelCase: Optional[int] ):
"""simple docstring"""
... | 28 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> --k... | 590 | 0 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def a ( __a ) -> str:
'''simple docstring'''
return getitem, k
def a ( __a , __a ) -> Any:
'''simpl... | 719 |
'''simple docstring'''
import torch
from torch import nn
class lowercase ( nn.Module ):
"""simple docstring"""
def __init__( self , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_=1 , UpperCamelCase_=False... | 280 | 0 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import ... | 563 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBer... | 563 | 1 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInp... | 97 |
from timeit import timeit
def _lowerCamelCase( lowerCAmelCase__ : int ):
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
SCREAMING_SNAKE_CASE_ : Tuple = 0
while number:
number &=... | 97 | 1 |
def lowerCamelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : int ) -> list[str]:
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(UpperCamelCase__ ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest i... | 469 |
def lowerCamelCase_ ( UpperCamelCase__ : str ) -> bool:
"""simple docstring"""
__lowerCamelCase = 0
for ch in input_str:
__lowerCamelCase = ord(UpperCamelCase__ )
__lowerCamelCase = pow(2 , UpperCa... | 469 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
lowerCamelCase = {
"""configuration_audio_spectrogram_transformer""": [
"""AUDIO_SPECTROGRAM_TRANSFORMER_PRETRA... | 14 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {
"""configuration_perceiver""": ["""PERCEIVER_... | 14 | 1 |
'''simple docstring'''
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
_lowercase : Optional[int] = TypeVar("""T""")
class UpperCamelCase__( ... | 210 |
from typing import Dict, Iterable, 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_dimension_forma... | 461 | 0 |
from math import loga
def _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise TypeError('''Input value must be a \'int\'... | 702 |
lowerCAmelCase = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
def _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
lowercase__ = f'a bytes-like object is required, not \'{d... | 429 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {'configuration_van': ['VAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VanConfig']}
try:
if not is_torch_available():
raise Op... | 61 |
_A = '''Alexander Joslin'''
import operator as op
from .stack import Stack
def __UpperCamelCase ( _A ):
lowerCAmelCase_ = {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.sub}
lowerCAmelCase_ = Stack()
lowerCAmelCase_ = Stack()
... | 431 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : str = logging.get_logger(__name__)
a : Any = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
"""goo... | 672 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
a : Tuple = False
class UpperCamelCase_ ( unit... | 672 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> dict[str, float]:
'''simple docstring'''
if (voltage, current, resistance).count(0 ... | 209 | '''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
el... | 209 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 700 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE_ ( metaclass=_lowercase):
'''simple docstring'''
__magic_name__ : List[str] = ['''torch''']
def __init__( self , *lowerCamelCase__ , **... | 150 | 0 |
def lowerCamelCase__ ( __lowerCamelCase : float , __lowerCamelCase : int ):
if digit_amount > 0:
return round(number - int(__lowerCamelCase ) , __lowerCamelCase )
return number - int(__lowerCamelCase )
if __name__ == "__main__":
... | 63 |
def __magic_name__ ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> tuple[float, float]:
# Check if the input is valid
if not len(SCREAMING_SNAKE_CASE ) == len(SCREAMING_SNAKE_CASE ) == 3:
raise ValueError('Please enter a valid equation.' )
i... | 66 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMI... | 557 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE = {
"configuration_distilbert": [
"DISTILBERT_PRETRAINED_... | 557 | 1 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class A ( _a ):
lowercase_ = 'WhisperFeatureExtractor'
lowercase_ = 'WhisperTokenizer'
def __init__( self : Union[str, Any] , ... | 22 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def lowerCamelCase__ ( self : ... | 115 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common im... | 298 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.util... | 298 | 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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_ver... | 613 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 1 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase ( UpperCAmelCase__ : list[int]):
lowerCamelCase : int = len(UpperCAmelCase__) // 2
# choose the middle 3 elements
lowerCamelCase : List[str] = lst[m -... | 449 |
'''simple docstring'''
def UpperCAmelCase ( UpperCAmelCase__ : list[int]):
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty')
lowerCamelCase : int = sum(UpperCAmelCase__) / len(UpperCAmelCase__) # Calculate the... | 449 | 1 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_availab... | 592 |
def lowerCamelCase__ ( snake_case_ : str , snake_case_ : list[str] ) -> str:
__snake_case = ''''''
for word_or_phrase in separated:
if not isinstance(snake_case_ , snake_case_ ):
raise Exception('''join() accepts only strings to be joine... | 592 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = {
"""junnyu/roformer_chinese_small""": """https://huggingfa... | 488 |
# 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 torch
from diffusers.configuration_utils import C... | 488 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__UpperCAmelCase = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''... | 90 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 0 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def A__ ( snake_case_ : Tuple ):
SCREAMING_SNAKE_CASE__: int= [
"""encoder.version""",
"""decoder.version""",
"""model.encoder... | 708 | import re
def A__ ( snake_case_ : str ):
if len(re.findall('''[ATCG]''' , snake_case_ ) ) != len(snake_case_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '''TAGC''' ) )
if __name__ == "__main__":
... | 107 | 0 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a_ : Dict = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(
'The clas... | 73 | from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from... | 166 | 0 |
"""simple docstring"""
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def a__ ( snake_case__ ) -> tup... | 705 |
"""simple docstring"""
def a__ ( snake_case__ = 1_00_00_00 ) -> int:
lowerCamelCase = 1
lowerCamelCase = 1
lowerCamelCase = {1: 1}
for inputa in range(2 , snake_case__ ):
lowerCamelCase = 0
lowerCamelCase ... | 533 | 0 |
import colorsys
from PIL import Image # type: ignore
def a ( snake_case__: float , snake_case__: float , snake_case__: int ):
'''simple docstring'''
lowercase_ = x
lowercase_ = y
for step in range(snake_case__ ): # noqa: B007
lowercas... | 97 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase : List[str] = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
try:
i... | 202 | 0 |
'''simple docstring'''
from __future__ import annotations
class __magic_name__ :
"""simple docstring"""
def __init__( self , _lowercase , _lowercase ) -> List[Any]:
lowercase_ , lowercase_ : Tuple = text, pattern
lowe... | 700 |
'''simple docstring'''
def _UpperCAmelCase ( a : list[list[float]] ) -> list[list[float]]:
"""simple docstring"""
lowercase_ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(a ):
if len(a ) <... | 7 | 0 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
A : Any = logging.get_logger(__name__) # pylint: disable=invalid-name
def UpperCamelCase__ ( SCREAMING_S... | 287 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ : int = 2_00_00_00 ) -> int:
_lowercase = [0 for i in range(n + 1 )]
_lowercase = 1
_lowercase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_lis... | 287 | 1 |
from math import ceil
def A__ ( __A , __A ):
'''simple docstring'''
_lowerCamelCase : List[Any] = list(range(0 , __A ) )
_lowerCamelCase : List[str] = [item for sublist in list(device_map.values() ) for item in sublist]
... | 15 | import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __snake_case ( __lowerCAmelCase ):
'''simple docstring'''
_snake_case = (EulerDiscreteScheduler,)
... | 15 | 1 |
# 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 applic... | 335 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class snake_case_ (lowerCam... | 335 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_A = {
'''configuration_m2m_100''': ['''M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''M2M100Config''', '''M2M100OnnxConfig'''],
'''tokenization_m2m_10... | 717 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
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_... | 189 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : Optional[int] = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : int = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.j... | 226 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class A ( lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase : Any = """"""
lowerCamelCase : s... | 226 | 1 |
'''simple docstring'''
from math import factorial
def SCREAMING_SNAKE_CASE ( a_ : int , a_ : int ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or ... | 490 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( a_ : str ):
__a = ''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def SCREAMING_SNAKE_CASE ( a_ : str ):
__... | 490 | 1 |
def A_ ( _lowerCAmelCase = 1000 ) -> int:
return sum(e for e in range(3 , _lowerCAmelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f"""{solution() = }""")
| 629 |
def A_ ( _lowerCAmelCase ) -> bool:
return str(_lowerCAmelCase ) == str(_lowerCAmelCase )[::-1]
def A_ ( _lowerCAmelCase ) -> int:
return int(_lowerCAmelCase ) + int(str(_lowerCAmelCase )[::-1] )
def A_ ( _lowerCAmelCase = 1_0000 ) -> int:
UpperCamelCase... | 629 | 1 |
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention, ImageClassifie... | 718 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Dict = logging.get_logger(__name__)
lowercase : Optional[Any] = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/res... | 94 | 0 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.... | 234 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_lowercase : str =argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add_argument("--dpm",... | 136 | 0 |
from __future__ import annotations
def lowerCAmelCase__ ( _a : int , _a : int ):
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_bytes:
raise ValueError("partitions can not > number_of_bytes!" )
snake_c... | 718 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def lowerCAmelCase__ ( _a : str , _a : str , **_a : Optional[int] ):
snake_case_ : Any = AutoConfig.from_pretrained(_a , **_a )
snake_case_ :... | 114 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowercase__ =logging.get_logger(__name__)
lowercase__ ={
'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
'https://huggingface.co/CarlCochet/trajectory-transformer-ha... | 263 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
lowercase__ ... | 263 | 1 |
'''simple docstring'''
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class _SCREAMING_SNAKE_C... | 709 |
'''simple docstring'''
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_lowerCAmelCase = Lock()
def UpperCamelCase ( a , a , a , a , a , a , a ) -> Optional[Any]:
'''simple docstring'''
g... | 245 | 0 |
import random
def lowercase_ ( _UpperCamelCase ):
'''simple docstring'''
__lowercase = num - 1
__lowercase = 0
while s % 2 == 0:
__lowercase = s // 2
t += 1
for _ in range(5 ):
__lowercase = random.randrange(2 , num - 1 )... | 639 |
'''simple docstring'''
from collections.abc import Callable
def __snake_case (__UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ):
"""simple docstring"""
lowerCamelCase_ : float = a
lowerCamelCase_ : float = b
if function(__UpperCAmelCase... | 501 | 0 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
UpperCamelCase = pd.read_csv("""sample_data.csv""", header=None)
U... | 120 |
"""simple docstring"""
import os
def A( ):
"""simple docstring"""
with open(os.path.dirname(snake_case_ ) + "/p022_names.txt" ) as file:
lowercase__: str = str(file.readlines()[0] )
lowercase__: str = names.... | 120 | 1 |
from typing import Any
def lowerCAmelCase_ ( lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase , ):
_validation(
lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCa... | 21 |
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 IterableDatasetDict
from ... | 413 | 0 |
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase_ (A : Optional[Any] , A : Union[str, Any] , A : Optional[int] ):
... | 706 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ :List[Any] = logging.get_logger(__name__)
a_ :Union[str, Any] = {"vocab_file": ... | 243 | 0 |
from math import asin, atan, cos, radians, sin, sqrt, tan
a : Tuple = 6_37_81_37.0
a : Any = 6_35_67_52.31_42_45
a : Tuple = 6_378_137
def lowerCamelCase__ ( __lowerCamelCase : float , __lowerCamelCase : float ... | 63 |
from __future__ import annotations
import numpy as np
def UpperCamelCase_( lowerCamelCase_ ) -> Optional[int]:
return np.maximum(0 , lowerCamelCase_ )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 89 | 0 |
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_m... | 259 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCAmelCase = {
"configuration_layoutlmv3": [
"LAYOUTLMV3_PRETRAINED_CO... | 259 | 1 |
"""simple docstring"""
import random
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ : List[str] = [], [], []
for element in data:
if element < pivot:
... | 65 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int = 600_851_475_143 ):
try:
SCREAMING_SNAKE_CASE__ = int(UpperCamelCase__ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable to int.""" )
if n <= 0:
raise ValueError("""P... | 6 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _UpperCamelCase (unittest.TestCase , _UpperCAmelCase ):
def __UpperCAmelCase ( self )-> Optional[Any]:
__lowerCAmelCase = load_tool("text-classification" ... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : int = logging.get_logger(__name__)
lowerCamelCase : Tuple = {
'''caidas/swin2sr-classicalsr-x2-64''': (
'''https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/m... | 290 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_u... | 199 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = {
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""zettametre""": """Zm""",
"""yottam... | 199 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
lowercase__ : Tuple = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for T... | 485 |
"""simple docstring"""
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import Te... | 485 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : Any = {
"configuration_blenderbot_small": [
... | 21 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 180 | 0 |
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_ = {
"camembert-base": "https://huggingface... | 664 |
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIterator
from tqdm imp... | 664 | 1 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_available... | 323 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowerCamelCase__ ( __snake_case, __snake_case, __snake_case, __snake_case, __snake_case ) -> np.array:
"""simple docstring"""
_UpperCamelCase = int(np.cei... | 19 | 0 |
"""simple docstring"""
from functools import reduce
__lowerCAmelCase : Optional[Any] = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''... | 717 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __lowerCAmelCase ( __UpperCamelCase :... | 21 | 0 |
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