code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def _SCREAMING_SNAKE_CASE ( a = 1_00 ) -> Optional[int]:
__A : Union[str, Any] = 0
__A : Optional[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_o... | 701 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : Dic... | 77 | 0 |
from collections.abc import Sequence
def _SCREAMING_SNAKE_CASE ( a = None ) -> int:
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
__A : Dict = nums[0]
for i in range(1 , len(_SCREAMING_SNAKE_C... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a ) -> list:
__A : Optional[int] = [0] * len(a )
for i in range(1 , len(a ) ):
# use last results for better performance - dynamic programming
__A : Optional[int] = prefix_result[i - 1]
whi... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
UpperCAmelCase : Union[str, Any] = logging.get_l... | 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> Union[str, Any]:
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(lowerCamelCase_ )
else:
if x == 0: # 0 raised to any number ... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
import math
import os
import sys
def _SCREAMING_SNAKE_CASE ( a ) -> str:
__A : str = ''
try:
with open(a , 'rb' ) as binary_file:
__A : Union[str, Any] = binary_file.read()
for dat in data:
... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase : str = logging.get_logger(__name__)
UpperCAmelCase : str = {
'''facebook/xmod-base'''... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
from math import factorial, radians
def _SCREAMING_SNAKE_CASE ( a , a = 18 , a = 10 ) -> List[str]:
__A : Optional[int] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from degrees to radians
__A ... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 0 |
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
UpperCAmelCase__ : Optional[Any] = ... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class _A( snake_case__ ):
"""simple docstring"""
UpperCamelCase ... | 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 0 |
from math import sqrt
def _SCREAMING_SNAKE_CASE ( a ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
from collections import defaultdict
from math import gcd
def _SCREAMING_SNAKE_CASE ( a = 1_50_00_00 ) -> int:
__A : Union[str, Any] = defaultdict(__UpperCAmelCase )
__A : Union[str, Any] = 2
while 2 * euclid_m * (euclid_m + 1) <= lim... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
class _A:
"""simple docstring"""
def __init__( self , _A , _A=None , _A=None ):
__A : str = data
__A : Any = previous
__A : Optional[int] = next_node
def __str__( self ):
return... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 0 |
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
UpperCAmelCase : List[Any] = get_tests_dir('''fixtures/test_sentencepiece_with... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( a , a , a , a ) -> Dict:
__A : Optional[Any] = []
__A : Tuple = input_list[low:mid], input_list[mid : high + 1]
while left and right:
result.a... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _A:
"""simple docstring"""
def __init__( self , _A=2 , _A=3 , _A=64 , _A=None ):
__A : List... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 0 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def _SCREAMING_SNAKE_CASE ( a ) -> Tuple:
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output , args... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class _A:
"""simple docstring"""
UpperCamelCase : torch.Tensor # [batch_size x 3]
UpperCamelCase : torch.Tensor # [batch_size x 3]
UpperCamelCase : torch.T... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
UpperCAmelCase : List[Any] = datasets.logging.get_logger(__name__)
UpperCAmelCase : str = """\
@inproceedings{bleurt,
title={BLEURT: Learning Robust Metrics for T... | 720 |
import copy
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
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def _SCREAMING_SNAKE_CASE ( a , a , a , a , a ) -> Optional[Any]:
__A : Dict ... | 721 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class _A( nn.Module ):
... | 77 | 0 |
'''simple docstring'''
import unittest
from transformers import 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_pipelines_common ... | 700 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 77 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _A( unittest.TestCase ):
"""simple docstring"""
... | 701 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : Dic... | 77 | 0 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
UpperCAmelCase : int = 20_48
UpperCAmelCase : int = 40_96
UpperCAmelCase : Union[str, Any] = 42
UpperCAmelCase : Dict = os.environ.pop('''PROCESS_TRAIN''', '''false''')
UpperCAmelCase ... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
__A : str = inspect.getfi... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_availab... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'''The `inpainting.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionInpaintPipeline` instead.'''
)
| 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
'''xlm-mlm-en-204... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
UpperCAmelCase : ... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
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 VaeImageProces... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> Union[str, Any]:
__A : Dict = len(UpperCAmelCase__ )
__A : int = [[0] * n for i in range(UpperCAmelCase__ )]
for i in range(UpperCAmelCase__ ):
__A : int ... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
UpperCAmelCase : List[str] = logging.get_logger(__name__)
class _A( __UpperCAmelCase ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 0 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _A( UpperCamelCase_ , unittest.TestCase ):
"""simple docstring"""
UpperCamelCase ... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
UpperCAmelCase : Optional[Any] = 6_55_21
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : Optional[Any] = 1
__A : List[str] = 0
for plain_chr in plain_text:
__A : int = (a + ord(__UpperCamelCase ... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
from math import factorial
UpperCAmelCase : Optional[Any] = {str(d): factorial(d) for d in range(10)}
def _SCREAMING_SNAKE_CASE ( a ) -> Optional[Any]:
return sum(DIGIT_FACTORIAL[d] for d in str(a ) )
def _SCREAMING_SNAKE_CASE ( ) ... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 0 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : L... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
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 disable_progress_bar, en... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_c... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 0 |
import json
import sys
def _SCREAMING_SNAKE_CASE ( a , a ) -> Optional[int]:
with open(__lowerCAmelCase , encoding='utf-8' ) as f:
__A : Optional[Any] = json.load(__lowerCAmelCase )
__A : Dict = ["<details... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_xformers_avai... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
UpperCAmelCase : Dict = [0, 2, 4, 6, 8]
UpperCAmelCase : List[Any] = [1, 3, 5, 7, 9]
def _SCREAMING_SNAKE_CASE ( a , a , a , a ) -> int:
if remaining_length == 0:
if digits[0] == 0 or digits[-1] == 0:
r... | 720 |
import copy
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
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 0 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def _SCREAMING_SNAKE_CASE ( a ) -> Optional[int]:
__A : Union[str, Any] = args.pruning_method
__A : Optional[Any] ... | 721 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class _A( nn.Module ):
... | 77 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
UpperCAmelCase : Optional[int] ... | 700 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a ) -> float:
return base * power(_SCREAMING_SNAKE_CASE , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('''Raise base to the power of exponent using recursion...''')
UpperCAmelCase : List[str] ... | 701 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : Dic... | 77 | 0 |
from math import sqrt
def _SCREAMING_SNAKE_CASE ( a = 1_00_00_00 ) -> Dict:
__A : Any = 0
__A : str = 0
__A : List[str] = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a , a=False ) -> Tuple:
if isinstance(lowerCAmelCase_ , lowerCAmelCase_ ) and isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
__A : Union[str, Any] = len(set_a.intersection(lowerCAmelCase_ ) ... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pi... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,... | 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
import math
def _SCREAMING_SNAKE_CASE ( a ) -> List[str]:
__A : Any = [True] * n
__A : Tuple = False
__A : str = False
__A : Tuple = True
for i in range(3 , int(n**0.5 + 1 ) ... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a , a , a ) -> int:
__A : Any = len(lowercase_ ), len(grid[0] )
if (
min(lowercase_ , lowercase_ ) < 0
or row == row_length
or col == col_length
or (row, co... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class _A( UpperCAmelCase_ ):
"""simple docstring"""
UpperCamelCase : Union[str, Any] = (UnCLIPScheduler,)
def UpperCAmelCase_ ( self , **_A ... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_atte... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 0 |
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,
r... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase : Tuple = {
'''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
}
try:
if not is_torch_avai... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def _SCREAMING_SNAKE_CASE ( a ) -> Dict:
... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> Any:
def update_area_of_max_square(a , a ) -> int:
# BASE CASE
if row >= rows or col >= cols:
return 0
__A : Tuple = update_area_of_max_square(a__ ... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a ) -> Dict:
return " ".join(
''.join(word[::-1] ) if len(_UpperCAmelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('''Hey wollef... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Any = {
'''configuration_distilbert''':... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 0 |
import argparse
import struct
import unittest
class _A:
"""simple docstring"""
def __init__( self , _A ):
__A : List[Any] = data
# Initialize hash values
__A : int = [
0X6A_09E_667,
0XBB_67A_E85,... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> Any:
return round(float(moles / volume ) * nfactor )
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> Optional[Any]:
return round(float((moles * 0.0_821 * temperature) / (volume) ... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 720 |
import copy
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
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 0 |
import re
def _SCREAMING_SNAKE_CASE ( a ) -> bool:
__A : List[str] = 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(lowerCAmelCase__ , lowerCAmelCase__ ) )
if __name__... | 721 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class _A( nn.Module ):
... | 77 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_... | 700 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a ) -> Dict:
return number | (1 << position)
def _SCREAMING_SNAKE_CASE ( a , a ) -> Dict:
return number & ~(1 << position)
def _SCREAMING_SNAKE_CASE ( a , a ) -> Optional[... | 701 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : Dic... | 77 | 0 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class _A( _UpperCAmelCase ... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Any = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
'''SCUT-DLVCLab/lilt-roberta-en-base''': (
'''https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
from __future__ import annotations
from typing import TypedDict
class _A( __A ):
"""simple docstring"""
UpperCamelCase : Tuple = 42
UpperCamelCase : Optional[int] = 42
def _SCREAMING_SNAKE_CASE ( a ) -> Option... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( __lowercase ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCase... | 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'''vocab_file''': '''vocab.json''',
... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
UpperCAmelCase : Dict = {'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvaila... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import t... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
import argparse
import os
import re
UpperCAmelCase : Optional[Any] = 'src/diffusers'
# Pattern that looks at the indentation in a line.
UpperCAmelCase : int = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCAmelCase : ... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : Tuple = logging.get_logger(__name__)
UpperCAmelCase__ : Tuple = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolv... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase : str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
el... | 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _A( lowercase_ ):
"""simple docstring"""
UpperCam... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
from __future__ import annotations
import math
class _A:
"""simple docstring"""
def __init__( self , _A ):
__A : Any = size
# approximate the overall size of segment tree with given value
__A : Optional[Any] = [0 for i in rang... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, BlipImageProc... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 0 |
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a , a , a ) -> Dict:
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
__A : str = mf_knapsack(i - 1 , snake_case__ , snake_case__ , snake_case... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase : int = logging.get_logger(__name__)
UpperCAmelCase : int = {
... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Optional[Any] = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : List[str] = '''T5Config'''
class _A... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a , a , a ) -> int:
if height >= 1:
move_tower(height - 1 , a , a , a )
move_disk(a , a )
move_tower(height - 1 , a , a , a )
def _... | 720 |
import copy
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
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 0 |
import torch
def _SCREAMING_SNAKE_CASE ( ) -> Any:
if torch.cuda.is_available():
__A : Any = torch.cuda.device_count()
else:
__A : Optional[Any] = 0
print(F"""Successfully ran on {num_gpus} GPUs""" )
if __name__... | 721 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class _A( nn.Module ):
... | 77 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generati... | 700 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 77 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Dict = {... | 701 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : Dic... | 77 | 0 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( a , a ) -> list[tuple[int, int]]:
__A , __A : str = position
__A : Optional[Any] = [
(y + 1, x + 2),
(y - 1, x + 2),
(y + 1, x - 2),
... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( a , a ) -> int:
__A : list[list[int]] = []
create_all_state(1 , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , [] , __SCREAMING_SNAKE_CASE )
return result
... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase : Dict = logging.get_logger(__name__)
def _SCREAMING_SNAKE_CASE ( a ) -> Optional[A... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a = 60_08_51_47_51_43 ) -> int:
try:
__A : Dict = int(_lowerCamelCase )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ... | 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a ) -> Any:
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
__A : str = str(bin(_SCREAMING_SNAKE_CASE ) )[2:] # remove the leading "0b"
__A : Optional[An... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator,... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMA... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
re... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 0 |
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _SCREAMING_SNAKE_CASE ( a , a , a , a ) -> Any:
__A : Optional[Any] = s.rsplit(a , a )
return new.join(a )
... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
import argparse
import os
import platform
import numpy as np
import psutil
import torch
from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file
from ..utils import is_npu_available, is_xpu_available
def _SCREAMING_SNAKE_CASE ... | 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 0 |
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
if is_flax_available():
from transformers.m... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
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