code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = ... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 1 |
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
lowerCamelCase__ : Dict = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, t... | 31 |
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 .tokenization_fnet import F... | 31 | 1 |
import random
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : Dict ) -> tuple:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = [], [], []
for element in data:
if element < pivot:
... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ort
lowerCamelCase_... | 31 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 1 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 1_00 * 2**20, 9_00 * 2**20] )
def UpperCAmelCase... | 31 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Any = {
'microsoft/git-base': 'https://huggingface.co/mi... | 31 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 1 |
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase_ ( __UpperCAmelCase : Union[str, Any] , __UpperCAmelCase : Dict , __UpperCAm... | 31 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 1 |
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
lowerCamelCase__ : Dict = [
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight', 'time_embedding.linear... | 31 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 1 |
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def UpperCAmelCase_ ( __UpperCAmelCase : str , __UpperCAmelCase : str , __UpperCAmelCase : Optional[str] = None ) -> str:
if version.parse(... | 31 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 1 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 1 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available(... | 31 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 1 |
import math
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> list[int]:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = 2
SCREAMING_SNAKE_CASE_ = int(math.sqrt(__UpperCAmelCase ) ) # Size of every segment
SCREAMING_SNAKE_CASE... | 31 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 1 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import... | 31 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 1 |
import os
import string
import sys
lowerCamelCase__ : Any = 1 << 8
lowerCamelCase__ : Optional[int] = {
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,
'le... | 31 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/GP... | 31 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 1 |
import warnings
from ..trainer import Trainer
from ..utils import logging
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : Tuple , _low... | 31 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : int , __UpperCAmelCase : int ) -> str:
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__UpperCAmelCase , int(b / 2 ) ) * actual_power(__UpperCAmelCase , int(b / 2 ) ... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowerCamelCase__ : Union[str, Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailab... | 31 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 1 |
# Algorithm for the pigeonhole sorting
def UpperCAmelCase_ ( __UpperCAmelCase : Any ) -> List[str]:
SCREAMING_SNAKE_CASE_ = min(__UpperCAmelCase ) # min() finds the minimum value
SCREAMING_SNAKE_CASE_ = max(__UpperCAmelCase ) # max() finds the maxim... | 31 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 1 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCamelCase_ :
'''simple docstring'''
lowercase_ = 42 # [batch_size x 3]
lowercase_ = 42 # [batch_size x 3]
lowercase_ = ... | 31 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 1 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedK... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 1 |
import os
from collections.abc import Iterator
def UpperCAmelCase_ ( __UpperCAmelCase : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(__UpperCAmelCase ):
SCREAMING_SNAKE_CASE_ = [d for d in dir_names if d != 'scripts' and d[0] not ... | 31 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 1 |
from maths.prime_check import is_prime
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
SCREAMING_SNAKE_CASE_ = f"Input value of [number={number}] must be an integer"
raise TypeE... | 31 |
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 .tokenization_fnet import F... | 31 | 1 |
import math
import qiskit
def UpperCAmelCase_ ( __UpperCAmelCase : int = 1 , __UpperCAmelCase : int = 1 , __UpperCAmelCase : int = 1 ) -> qiskit.result.counts.Counts:
if (
isinstance(__UpperCAmelCase , __UpperCAmelCase )
or isi... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def UpperCAmelCase_ ( __UpperCAmelCase : Tuple , __UpperCAmelCase : Union[str, Any] , __UpperCAmelCase : int ) -> Dict:
SCREAMING_SNAKE_CASE_ = 0
if start < end... | 31 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 1 |
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr, require_zstandard
@... | 31 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 1 |
import inspect
import unittest
from transformers import MobileNetVaConfig
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 import ConfigTester
from ...... | 31 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 1 |
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_up_block
@dataclass
... | 31 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : str = "The quick brown fox jumps over the lazy dog" , ) -> bool:
SCREAMING_SNAKE_CASE_ = set()
# Replace all the whitespace in our sentence
SCREAMING_SNAKE_CASE_ = input_str.replace(' ' , '' )
... | 31 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 1 |
from __future__ import annotations
from functools import lru_cache
from math import ceil
lowerCamelCase__ : Any = 100
lowerCamelCase__ : Optional[Any] = set(range(3, NUM_PRIMES, 2))
primes.add(2)
lowerCamelCase__ : int
for prime in range(3, ceil(NUM_PRIMES**0.5), 2)... | 31 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 1 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Opt... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 1 |
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageResam... | 31 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 1 |
import math
def UpperCAmelCase_ ( ) -> None:
SCREAMING_SNAKE_CASE_ = input('Enter message: ' )
SCREAMING_SNAKE_CASE_ = int(input(f"Enter key [2-{len(__UpperCAmelCase ) - 1}]: " ) )
SCREAMING_SNAKE_CASE_ = input('Encryption/Decryption [e/d]... | 31 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 1 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> --key_p... | 31 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 1 |
from __future__ import annotations
import time
lowerCamelCase__ : int = list[tuple[int, int]]
lowerCamelCase__ : int = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0]... | 31 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : list[list] ) -> list[list]:
SCREAMING_SNAKE_CASE_ = current_set.copy()
for row_index, row in enumerate(__UpperCAmelCase ):
SCREAMING_SNAKE_CASE_ = row[0]
for column_index, column in enumerate(... | 31 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 1 |
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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, random_attention_mask... | 31 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 1 |
import sys
lowerCamelCase__ : Optional[int] = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'6689664895044... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Dict = {
'roberta... | 31 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 1 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutput... | 31 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 1 |
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 31 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 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__ : List[Any] = logging.get_logger(__name__)
lowerCamelCase__ : O... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 1 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
... | 31 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 1 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
lower... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 1 |
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 lowerCamelCase_ ( _... | 31 |
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 .tokenization_fnet import F... | 31 | 1 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str , _lowerCAmelCase : Tuple , _lowerCAmelCase : int , _lowerCAmelCase : in... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
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_dataset,... | 31 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 1 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCAmelCase_ ( __UpperCAmelCase : str , __UpperCAmelCase : O... | 31 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase__ : List[Any] = {'configuration_mbart... | 31 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 1 |
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 HeunDiscreteScheduler
from... | 31 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : int = 4_00_00_00 ) -> int:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__UpperCAmelCase )
... | 31 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 1 |
import inspect
import unittest
from transformers import MobileViTConfig
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 import ConfigTester
from ...te... | 31 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
fr... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 1 |
import argparse
from collections import defaultdict
def UpperCAmelCase_ ( __UpperCAmelCase : List[Any] , __UpperCAmelCase : List[str] , __UpperCAmelCase : List[str] , __UpperCAmelCase : Any , __UpperCAmelCase : Any ) -> Dict:
SCREA... | 31 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 1 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowerCamelCase_ :
'''simple docstring'''
lowercase_ = None
def lowerCAmelCase_ ( self : Dict ):
SCREAMING_SNAKE_CASE_ = ... | 31 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import Flax... | 31 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 1 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = (KDPMaDiscreteScheduler,)
lowercase_... | 31 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 1 |
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 .tokenization_albert import... | 31 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 1 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class lowerCamelCase_ ( _SC... | 31 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : List[str] = {
'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}
try:
if not ... | 31 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_d... | 31 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 1 |
import math
def UpperCAmelCase_ ( __UpperCAmelCase : float , __UpperCAmelCase : float ) -> float:
if initial_intensity < 0:
raise ValueError('The value of intensity cannot be negative' )
# handling of negative values of initial intensity
i... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 1 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import B... | 31 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase__ : Dict = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CONFIG_ARCHIVE... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 1 |
class lowerCamelCase_ : # Public class to implement a graph
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int , _lowerCAmelCase : int , _lowerCAmelCase : list[list[bool]] ):
SCREAMING_... | 31 |
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 .tokenization_fnet import F... | 31 | 1 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pip... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : Tuple , __UpperCAmelCase : List[Any] , __UpperCAmelCase : List[Any] , __UpperCAmelCase : Optional[int] ) -> str:
if height >= 1:
move_tower(height - 1 , __UpperCAmelCase , __Upp... | 31 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : dict ) -> set:
SCREAMING_SNAKE_CASE_ = set()
# edges = list of graph's edges
SCREAMING_SNAKE_CASE_ = get_edges(__UpperCAmelCase )
# While there are still elements in edges list, take an arbitrary edge
... | 31 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 1 |
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
lowerCamelCase__ : List[str] = logging.get_logger(__name__)
def UpperCAmelCase_ (... | 31 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 1 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
FlaxForcedBOSTo... | 31 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 1 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from... | 31 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 1 |
from __future__ import annotations
import requests
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> dict:
SCREAMING_SNAKE_CASE_ = f"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
return requests.get(__UpperCAmelCase ).json()
def UpperC... | 31 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 1 |
def UpperCAmelCase_ ( ) -> Tuple:
for n in range(1 , 1_00_00_00 ):
yield n * (n + 1) // 2
def UpperCAmelCase_ ( __UpperCAmelCase : Union[str, Any] ) -> Union[str, Any]:
SCREAMING_SNAKE_CASE_ = 1
SCREAMING_SNAKE_CASE_ = ... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_torch
c... | 31 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 1 |
import colorsys
from PIL import Image # type: ignore
def UpperCAmelCase_ ( __UpperCAmelCase : float , __UpperCAmelCase : float , __UpperCAmelCase : int ) -> float:
SCREAMING_SNAKE_CASE_ = x
SCREAMING_SNAKE_CASE_ = y
for ste... | 31 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 1 |
import math
import flax.linen as nn
import jax.numpy as jnp
def UpperCAmelCase_ ( __UpperCAmelCase : jnp.ndarray , __UpperCAmelCase : int , __UpperCAmelCase : float = 1 , __UpperCAmelCase : float = 1 , __UpperCAmelCase : float = 1.0E4 , ... | 31 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 1 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 1 |
import cva
import numpy as np
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : float , _lowerCAmelCase : int ):
if k in (0.04, 0.06):
SCREAMING_SNAKE_CASE_ = k
... | 31 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 1 |
# Copyright 2022 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 appl... | 31 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 1 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 1 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py... | 31 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 1 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase__ : str = 'T5Config'
class... | 31 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 1 |
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils impor... | 31 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 1 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : int = 10 , __UpperCAmelCase : int = 22 ) -> int:
SCREAMING_SNAKE_CASE_ = range(1 , __UpperCAmelCase )
SCREAMING_SNAKE_CASE_ = range(1 , __UpperCAmelCase )
return sum(
... | 31 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 1 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFXLMRobertaModel
... | 31 |
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 .tokenization_fnet import F... | 31 | 1 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class lowerCamelCase_ ( ... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
... | 31 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 1 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 1 |
from __future__ import annotations
from collections import namedtuple
def UpperCAmelCase_ ( __UpperCAmelCase : float , __UpperCAmelCase : float , __UpperCAmelCase : float ) -> tuple:
SCREAMING_SNAKE_CASE_ = namedtuple('result' , 'name valu... | 31 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 1 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Tuple: # picklable for mul... | 31 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : str , __UpperCAmelCase : Union[str, Any] ) -> Any:
SCREAMING_SNAKE_CASE_ = [1]
for i in range(2 , __UpperCAmelCase ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[... | 31 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 1 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
lowerCamelCase__ : int = '2.13.1'
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('3.7')... | 31 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 1 |
from ..utils import DummyObject, requires_backends
class lowerCamelCase_ ( metaclass=_SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = ["transformers", "torch", "note_seq"]
def __init__( self : Tuple , *_lowerCAmelCase : List[... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 1 |
lowerCamelCase__ : int = tuple[float, float, float]
lowerCamelCase__ : Optional[Any] = tuple[float, float, float]
def UpperCAmelCase_ ( __UpperCAmelCase : Pointad , __UpperCAmelCase : Pointad ) -> Vectorad:
SCREAMING_SNAKE_CASE_ ... | 31 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 1 |
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ : Union[str, Any] = False
lowerCamelCase__ : List[str] = True
lowerCamelCase__ : Optional[Any] ... | 31 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 1 |
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