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 |
|---|---|---|---|---|
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...te... | 647 |
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 | 1 |
'''simple docstring'''
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def snake_case (UpperCamelCase : Tuple , UpperCamelCase : Optional[int] , UpperCamelCase : List[str]=0 ):
'''simple docstring'... | 705 |
import math
def snake_case (UpperCamelCase : int ):
'''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 not primes
return False
# ... | 235 | 0 |
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,
)
from .test_p... | 151 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def UpperCAmelCase_ ( ):
SCREAMING_SNAKE_CASE__ =ArgumentParser("""Diffusers CLI tool""", usage="""diffusers-cli <command> [<args>]""" )
SCREAMING_SNAKE_CASE__ =parser.add_subparsers(help="... | 151 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
... | 143 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
... | 143 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
_lowercase = logging.get_logger(__name__)
class lowerCAmelCase_ ( __UpperCamelCase ):
'''simple docstring'... | 91 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_config... | 600 | 0 |
'''simple docstring'''
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
a_ : Dict = models... | 710 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _snake_case ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self) -> str:
debug_launcher(test_script.main)
de... | 444 | 0 |
"""simple docstring"""
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def UpperCamelCase__ ( lowercase__ : Optional[int] , lowercase__ : str , lowercase__ : Dict = 1 / sqrt(2 ) ):
snake_case : List[str] = tau * freque... | 134 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a: int = logging.get_logger(__name__)
_a: Optional[Any] = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/resolve... | 162 | 0 |
'''simple docstring'''
import numpy as np
def lowercase__( __UpperCamelCase: np.ndarray ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def lowercase__( __UpperCamelCase: np.ndarray ):
"""simple docstring"... | 707 |
'''simple docstring'''
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def lowercase__( __UpperCamelCase: bytes ,__UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CA... | 508 | 0 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase )
class lowerCamelCase_ ( lowerCamelCase ):
a__ = field(default='''language-modeling''' , meta... | 0 | import argparse
import os
import re
import packaging.version
_UpperCAmelCase = """examples/"""
_UpperCAmelCase = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compile(r""... | 558 | 0 |
"""simple docstring"""
import math
import unittest
def lowerCamelCase (a_ :int) -> bool:
assert isinstance(a_ , a_) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
... | 475 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = ... | 475 | 1 |
"""simple docstring"""
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def UpperCAmelCase ( snake_... | 227 |
"""simple docstring"""
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def UpperCAmelCase ( snake_case : str ):
if "model" in orig_key:
_lowerCAmelCase:str = orig_key.replace('''model.''' , '''''' )
if "norm1" ... | 227 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_commo... | 624 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
lowerCAmelCase__ = (720, 1280) # Height, Width
lowerCAmelCase__ = (0.4, 0.6) # if height or width lower than this scale, drop it.
lowerCAmelCase... | 624 | 1 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : Dict , _SCREAMING_SNAKE_CASE : Optional[Any] , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : List[Any] ) -> Tuple:
"""simple docstring"""
UpperCAmelCase_ : Dict ... | 71 |
"""simple docstring"""
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_sente... | 657 | 0 |
def lowerCamelCase__ ( _lowerCamelCase = 3 , _lowerCamelCase = 7 , _lowerCamelCase = 100_0000 ) ->int:
_UpperCAmelCase =0
_UpperCAmelCase =1
for current_denominator in range(1 , limit + 1 ):
_UpperCAmelCase =current_denominator * numerator // denominator
if curr... | 705 |
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ) ->bool:
_UpperCAmelCase =get_failure_array(_lowerCamelCase )
# 2) Step through text searching for pattern
_UpperCAmelCase , _UpperCAmelCase =0, 0 # index into text, pattern
... | 592 | 0 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from t... | 81 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __lowerCAmelCase ( __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , ):
for nxt, d in graph[v]:
if... | 226 | 0 |
from __future__ import annotations
from collections import Counter
from random import random
class _lowerCamelCase :
"""simple docstring"""
def __init__( self ) -> int:
"""simple docstring"""
UpperCamelCase__ : int = {}
de... | 711 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common imp... | 462 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ : Any = {
"""configuration_llama""": ... | 331 |
'''simple docstring'''
def _lowerCAmelCase (_lowercase = 3 , _lowercase = 7 , _lowercase = 1_00_00_00 ):
"""simple docstring"""
a__ = 0
a__ = 1
for current_denominator in range(1 , limit + 1 ):
a__ = cu... | 331 | 1 |
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
UpperCamelCase = yaml.safe_load(
'\\nname: ""\nallow_empty: false\nallow_empty_text: true\nsubsections:\n - name: "... | 125 |
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 ( lowerCAmelCase_ : Tuple , lowerCAmelCase_ : Dic... | 125 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTe... | 467 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def a__ ( UpperCamelCase_ : str, UpperCamelCase_ : str ):
UpperCAmelCase__ :Any = list(UpperCamelCase_ )
UpperCAmelCase__ :O... | 467 | 1 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def __magic_name__ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = False):
'''simple docstring'''
if radian_mode:
return [magn... | 73 |
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 lowerCAmelCase__ ( ... | 73 | 1 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def UpperCAmelCase_ ( lowerCAmelCase_ ):
"""simple docstring"""
lowercase = FileLock(str(tmpdir / "foo.lock" ) )
lowercase = FileLock(str(tm... | 310 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class UpperCAmelCase :
def __init__(self : Optional[Any] , A__... | 310 | 1 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number | (1 << position)
def _lowercase ( lowerCamelCase__ : int, lowerCamelCase__ : int ):
return number & ~(1 << position)
def _lowercase ( lowerCamelCase_... | 691 |
'''simple docstring'''
def _lowercase ( lowerCamelCase__ : list[int], lowerCamelCase__ : list[int], lowerCamelCase__ : int ):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(lowerCamelCase__ ) )
def _lowercas... | 691 | 1 |
def SCREAMING_SNAKE_CASE__ ( ):
return [list(range(1_000 - i , -1_000 - i , -1 ) ) for i in range(1_000 )]
_lowerCamelCase = generate_large_matrix()
_lowerCamelCase = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[[3, 2], ... | 6 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class lowercase ( UpperCamelCase__ ):
_a = ["i... | 307 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : str = {
... | 714 | import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_common im... | 580 | 0 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
a_ = TypeVar('KEY')
a_ = TypeVar('VAL')
@dataclass(frozen=snake_case , slots=snake_case )
class UpperCAmelCase... | 76 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
a_ = lo... | 76 | 1 |
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_ten... | 649 |
lowerCamelCase : List[str] = '''0.18.2'''
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_li... | 649 | 1 |
'''simple docstring'''
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
__UpperCamelCase : int = HfApi()
__UpperCamelCase : str = {}
# fmt: off
__UpperCamelCase : str = torch.tensor(... | 448 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE ... | 502 | 0 |
"""simple docstring"""
# 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.... | 165 |
"""simple docstring"""
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
UpperCAmelCase_ : Tuple = coll... | 165 | 1 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from acceler... | 229 |
"""simple docstring"""
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils impo... | 237 | 0 |
"""simple docstring"""
def _a ( _snake_case = 10 , _snake_case = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , _snake_case )
UpperCAmelCase = range(1 , _snake_case )
return sum(
1 for power in powers fo... | 74 |
"""simple docstring"""
import math
def _a ( _snake_case ):
"""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... | 74 | 1 |
'''simple docstring'''
from math import isqrt
def a_ ( UpperCamelCase_ ):
A_ = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , UpperCamelCase_ , UpperCamelCase_ ):
... | 452 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 452 | 1 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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 r... | 486 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoCo... | 486 | 1 |
def _A ( SCREAMING_SNAKE_CASE : list , SCREAMING_SNAKE_CASE : int = 0 ):
"""simple docstring"""
a__ : Optional[Any] =length or len(SCREAMING_SNAKE_CASE )
a__ : int =False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]... | 563 |
from math import factorial
UpperCAmelCase : Tuple = {str(d): factorial(d) for d in range(10)}
def _A ( SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(SCREAMING_SNAKE_CASE ) )
def _A ( ):
... | 563 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE ):
lowerCAmelCase_ : Dict =[1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ : List[Any] =0, 0, 0
lowerCAmelCase_ : Union[str, Any] =u... | 305 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase = get_tests_dir('''fixtures/test_sentencepiece_w... | 305 | 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
_A = logging.get_logger(__name__)
_A = {
"microsoft/beit-base-patch16-224-pt22k": (
"https://hu... | 290 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __UpperCAmelCase ( __a : Optional[Any] ,__a : int ,__a : Any ) -> int:
"""simple docstring"""
_a : int = 0
if start < end:
_a ... | 14 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_comm... | 700 |
"""simple docstring"""
import re
def __UpperCAmelCase ( __lowerCamelCase ) -> bool:
lowercase__ : Optional[Any] = re.compile(
r'''^(?:0|94|\+94|0{2}94)''' r'''7(0|1|2|4|5|6|7|8)''' r'''(-| |)''' r'''\d{7}$''' )
return bool(re.search(__lowerCam... | 122 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json'
... | 306 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class ... | 306 | 1 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def a ( __UpperCAmelCase : int = 8 ) -> str:
__magic_name__: Union[str, Any] = a... | 213 |
"""simple docstring"""
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def a ( __UpperCAmelCase : Optional[Any] , __Upp... | 213 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class snake_case ( lowercase ):
"""simple docstring"""
def snake_case ( self ... | 675 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : Optional[Any] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""... | 675 | 1 |
'''simple docstring'''
from math import loga
def _snake_case ( _SCREAMING_SNAKE_CASE : int ) -> List[str]:
"""simple docstring"""
if a < 0:
raise ValueError("""Input value must be a positive integer""" )
elif isinstance(_lowerCAmelCase ... | 711 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHead... | 344 | 0 |
'''simple docstring'''
import math
def lowercase_ ( ) -> None:
"""simple docstring"""
lowercase : Union[str, Any] =input('''Enter message: ''' )
lowercase : List[Any] =int(input(F'Enter key [2-{len(__A ) - 1}]: ' ) )
lowercase : ... | 94 |
"""simple docstring"""
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
__magic_name__ = datasets.load_iris()
__magic_name__ = np.array(data["data"])
__magic_name__ = np.array(data["target"])
__magic_name__ ... | 155 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class A__ ( __UpperC... | 711 |
import math
import random
def lowerCAmelCase ( UpperCAmelCase, UpperCAmelCase = False ) ->float:
"""simple docstring"""
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
lowercase... | 336 | 0 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _a ( *_lowerCamelCase , _lowerCamelCase = None , _lowerCamelCase=True , _lowerCamelCase=2 ) -> Union[str, Any]:
... | 26 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask... | 52 | 0 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_... | 529 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTMSNConfig
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_configuration_common imp... | 529 | 1 |
from manim import *
class UpperCamelCase ( __a ):
def A_ (self ) -> Union[str, Any]:
UpperCamelCase_ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
UpperCamelCase_ : Union[str, Any] = Rectangle(h... | 635 | import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType,... | 635 | 1 |
"""simple docstring"""
def __lowerCAmelCase ( __lowerCAmelCase : int = 200 ) -> int:
_UpperCamelCase : str = [1, 2, 5, 10, 20, 50, 100, 200]
_UpperCamelCase : Optional[Any] = [0] * (pence + 1)
_UpperCamelCase : List[str] = 1 # base case: 1 ... | 239 |
"""simple docstring"""
from math import ceil
def __lowerCAmelCase ( __lowerCAmelCase : int = 1001 ) -> int:
_UpperCamelCase : Tuple = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
_UpperCamelCase : Tuple = 2 * i + 1
_UpperCamelCase... | 239 | 1 |
"""simple docstring"""
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()
a_ = logging.get_logger(__name__)
... | 76 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenization_m... | 144 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, ... | 713 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Tuple = logging.get_logger(__name__)
_lowercase : Optional[int] = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.... | 397 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCAmelCase_ ( __lowercase ):
"""simple docstring"""
... | 14 |
"""simple docstring"""
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,
Distil... | 609 | 0 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _sna... | 460 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _snake_case ( ):
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as original... | 460 | 1 |
import argparse
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 accelerate import Accel... | 47 |
import numpy as np
import datasets
A__ : int = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by P... | 183 | 0 |
from __future__ import annotations
def __a ( __UpperCAmelCase : int , __UpperCAmelCase : int ) -> list[str]:
"""simple docstring"""
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_byte... | 253 |
class snake_case_ :
'''simple docstring'''
def __init__( self : str ) -> Optional[int]:
lowerCamelCase_ : Optional[Any] = ""
lowerCamelCase_ : Dict = ""
lowerCamelCase_ : Union[str, Any] = []
... | 253 | 1 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
A__ : str = logging.get_logger(__name__)
def _lowerCAmelCase ( _UpperCamelCase , _UpperCame... | 353 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase : List[Any] = ... | 396 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( __magic_name__ : int , __magic_name__ : int ) -> float:
'''simple docstring'''
return base * power(__magic_name__ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print("Raise base to the ... | 419 |
'''simple docstring'''
def UpperCamelCase__ ( __magic_name__ : str , __magic_name__ : str ) -> str:
'''simple docstring'''
snake_case__ : int = len(__magic_name__ )
snake_case__ : int = len(__magic_name__ )
snake_case__... | 419 | 1 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def snake_case ( A__ ,A__=False ):
UpperCAmelCase_ : Any = OmegaConf.load(A__ )
if display:
print(yaml.dump(OmegaConf.to_container(A__ ... | 95 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_a... | 95 | 1 |
import csv
import tweepy
# Twitter API credentials
lowercase = """"""
lowercase = """"""
lowercase = """"""
lowercase = """"""
def A__ ( _UpperCAmelCase : str ) -> None:
'''simple docstring'''
snake_case__ : Any = tweepy.OAuthHandler(_UpperCAmelCase ... | 707 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
... | 150 | 0 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTe... | 187 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def a(lowercase__ ):
'''simple docstring'''
snake_case_ = 384
... | 187 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def UpperCAmelCase ( a_ ) -> Union[str, Any]:
"""simple docstring"""
if not postfix_notation:
return 0
A_ : Union[str, Any] = {"""+""", """... | 709 |
'''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, ski... | 385 | 0 |
"""simple docstring"""
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
__A = """scheduler_config.json"""
class _lo... | 93 |
"""simple docstring"""
def __A (_SCREAMING_SNAKE_CASE ) ->str:
"""simple docstring"""
lowerCAmelCase__ :List[Any] = int(_SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(_SCREAMING_SNAKE_CASE )
lowerCAmelCase__ ... | 93 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test... | 353 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():
from trans... | 353 | 1 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
... | 352 |
from datetime import datetime
import requests
def __a ( __lowerCAmelCase ) -> bytes:
SCREAMING_SNAKE_CASE : int = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
SCREAMING_SNAKE_CASE : Any = requests.get(base_url +... | 352 | 1 |
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class _UpperCamelCase( unittest.TestCase ):
def a__ ( self : str ):
_UpperCAmelCase : Tuple = get_activation("swish" )
self.assert... | 718 |
# 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 requir... | 328 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase ... | 90 |
'''simple docstring'''
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_ge... | 384 | 0 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class lowercase__ ( _UpperCAmelCase ):
def A_ ( self : Any ):
return [
{"col_1": 3, "col_2": "a"},
{"col_1": 2, "col_2": "b"},
... | 400 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__snake_case = {
"""configuration_layoutlmv3""": [
"""LAYOUTLMV3_PRETRAINED_CONF... | 400 | 1 |
"""simple docstring"""
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
... | 76 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def A__ ( __A : Any , __A : Dict , __A : Optional[... | 184 | 0 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase_ : List[str] = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0,... | 701 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 | 0 |
'''simple docstring'''
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE = "isbn/0140328726" ):
_snake_case = olid.strip().strip("""/""" ) # Remove leading/trailing whitespace & slashes
... | 585 |
import warnings
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 _Uppe... | 367 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ... | 713 |
'''simple docstring'''
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' ,[None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' ,['default', 0, 100 * 2**20, 900 * 2**20] )
... | 238 | 0 |
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compute_metrics as comput... | 491 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from .... | 491 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from... | 703 |
"""simple docstring"""
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... | 505 | 0 |
from __future__ import annotations
def __lowerCamelCase ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] , lowerCamelCase__ : int ):
'''simple docstring'''
lowerCamelCase = list(range(len(lowerCamelCase__ ) ) )
... | 457 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
UpperCAmelCase : Any = logging.getLogger(__name__)
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = argparse.ArgumentParser(
... | 457 | 1 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
req... | 604 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from ..test_modeling... | 604 | 1 |
"""simple docstring"""
from collections.abc import Callable
def lowerCamelCase__ ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ )-> float:
"""simple docstring"""
UpperCamelCase = a
UpperCamelCase = b
if fun... | 554 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class ... | 554 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_f... | 707 | """simple docstring"""
def lowerCamelCase_ ( __lowerCAmelCase , __lowerCAmelCase = False ) -> str:
'''simple docstring'''
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
lowerCamelCase__ =F'''Expected string as input, foun... | 132 | 0 |
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase_ ( SCREAMING_SNAKE_CASE__ ):
def __init__( self :Any , *__A :Dict , **__A :List[str] ) -> Optional[Any]:
"""simple docstring"""
super().__init__(*__... | 6 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
A : Dict = {
"configuration_speecht5": [
"SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SPEECHT5_PRETRAINED_HIFIGAN_CON... | 140 | 0 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
__UpperCAmelCase :List[str] = (7_2_0, 1_2_8_0) # Height, Width
__UpperCAmelCase :int = (0.4, 0.6) # if height or ... | 702 |
'''simple docstring'''
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs("hub/hopper-medium-v2/unet/hor32", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/unet/hor128", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/value_function", exist_ok=True)
... | 266 | 0 |
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
lowercase_ = models.Sequential()
# Step 1 - Convolution
# Here ... | 74 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from... | 225 | 0 |
from __future__ import annotations
def __magic_name__ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_):
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError("days_between_payments must be > 0")
if daily_interest_rate < 0:
raise ValueErr... | 73 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowerCAmelCase__ ( unittest.TestCase ):
"""simple docstring"""
def _Up... | 73 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( A : list ) -> list:
UpperCAmelCase_ : List[str] = len(A )
for i in range(1 , A ):
UpperCAmelCase_ : str = collection[i]
UpperCAmelCase_ : List[Any] ... | 541 |
'''simple docstring'''
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_UpperCamelCase : str = {1: (1, 1), 2: (2, 1), 3: (3, 1),... | 541 | 1 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | 217 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
'faceboo... | 217 | 1 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def a (lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__=N... | 99 |
'''simple docstring'''
def _A ( lowercase__ ):
assert (
isinstance(lowercase__ , lowercase__ ) and number_of_steps > 0
), f'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
if number_of_steps == 1:
return 1
lowercase__ ... | 325 | 0 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class _UpperCamelCase ... | 193 |
from __future__ import annotations
import math
import random
from typing import Any
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : Union[str, Any] ) -> None:
"""simple docstring"""
SCREAMING_SNAKE_CASE : list[Any] = []
... | 193 | 1 |
"""simple docstring"""
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
... | 19 |
"""simple docstring"""
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class _UpperCAmelCase( lo... | 19 | 1 |
import math
def lowerCamelCase__ ( _a):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number are in format of 6k +/- 1
for i in range(5 ... | 700 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
@flax.struct.dataclass
c... | 193 | 0 |
'''simple docstring'''
_UpperCAmelCase : Tuple = '''ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'''
def UpperCamelCase ( lowercase_ : bytes ) -> bytes:
'''simple docstring'''
if not isinstance(lowercase_ , lowercase_ ):
lowercase =f'a bytes-... | 72 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import l... | 86 | 0 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pyto... | 715 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def UpperCAmelCase__ ( ... | 667 | 0 |
"""simple docstring"""
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
lowercase_ : List[Any] = logging.get_logger(__name__)
... | 572 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 0 |
"""simple docstring"""
def __snake_case ( UpperCamelCase ) -> list:
"""simple docstring"""
if len(UpperCamelCase ) <= 1:
return lst
a__ = 1
while i < len(UpperCamelCase ):
if lst[i - 1] <= lst[i]:
i += 1
else:
a__ , a__ = ls... | 158 |
"""simple docstring"""
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import di... | 158 | 1 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import T... | 332 |
from ..utils import DummyObject, requires_backends
class a ( metaclass=__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
UpperCamelCase_ : Optional[int] = ['note_seq']
def __init__( self : Dict , *lowerCamelCase__ : int , **lowerCamelC... | 332 | 1 |
'''simple docstring'''
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 low... | 713 |
'''simple docstring'''
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def lowerCamelCase ( lowerCamelCase : str , lowerCamelCase : complex , lowerCamelCase : str = "x" , lowerCamelCase : float = 10**-1... | 27 | 0 |
'''simple docstring'''
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,
StableDiffu... | 3 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def A_( A : float , A : float , A : int):
UpperCamelCase = x
UpperCamelCase = y
for step in range(A): # noqa: B007
UpperCamelCase ... | 3 | 1 |
from __future__ import annotations
def _A (lowerCAmelCase__ :list ) -> float:
'''simple docstring'''
if not nums:
raise ValueError('List is empty' )
return sum(lowerCAmelCase__ ) / len(lowerCAmelCase__ )
if __name__ == "__main__":
import d... | 714 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : str = {
"configuration_data2vec_audio": ["DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP", "Data2VecAudioCon... | 532 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
_lowerCamelCase : List[Any] = {
"susnato/ernie-m-base_pytorch": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json"... | 430 |
from collections.abc import Sequence
def __A(lowerCAmelCase = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_UpperCamelCase = nums[0]
for i in range(1 , len(lowerCAmelCase ) ):
_U... | 612 | 0 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
... | 577 |
def UpperCAmelCase__ ( lowerCamelCase_ : list[int] , lowerCamelCase_ : list[int] ):
# Check if the input is valid
if not len(lowerCamelCase_ ) == len(lowerCamelCase_ ) == 3:
raise ValueError('Please enter a valid equation.' )
if e... | 577 | 1 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipeline... | 16 |
'''simple docstring'''
from __future__ import annotations
def __lowercase ( __lowercase , __lowercase ) -> list[int]:
'''simple docstring'''
_A = 0
_A = len(__lowercase ) - 1
while i < j:
if nums[i] + nums[j] == target:
... | 330 | 0 |
'''simple docstring'''
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
SCREAMING_SNAKE_CASE_ = numpy.array([0, 0])
SCREAMING_SNAKE_CASE_ = numpy.array([0.5, 0.8_6_6_0_2_5_4])
SCREAMING_SNAKE_CASE_ = num... | 201 |
'''simple docstring'''
import numpy
# List of input, output pairs
SCREAMING_SNAKE_CASE_ = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
SCREAMING_SNAKE_CASE_ = (((5_15, 22, 13), 5_55), ((61, 35, 49), 1_50))
SCREAMING_SNAKE_CASE... | 201 | 1 |
import argparse
import json
from tqdm import tqdm
def _lowercase ( ):
"""simple docstring"""
UpperCamelCase = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"""--src_path""" , type=SCREAMING_SNAKE_CASE_ ... | 386 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IM... | 386 | 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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
Vilt... | 700 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 300 | 0 |
'''simple docstring'''
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
fro... | 384 |
'''simple docstring'''
from collections.abc import Sequence
def _UpperCAmelCase ( _lowerCamelCase : Sequence[float] , _lowerCamelCase : float ) -> float:
return sum(c * (x**i) for i, c in enumerate(_lowerCamelCase ) )
def _UpperCAmelCase ( _lowerCamelCase : ... | 384 | 1 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFA... | 158 |
"""simple docstring"""
import math
import qiskit
def __snake_case ( UpperCamelCase = 1 , UpperCamelCase = 1 , UpperCamelCase = 1 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
if (
isinstance(UpperCamelCase , UpperCamelCase )
or isinstance(UpperCam... | 158 | 1 |
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