code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_n... | 72 |
'''simple docstring'''
import math
from collections.abc import Callable
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> float:
'''simple docstring'''
snake_case_ = xa
snake_case_ = xa
while True:
if x_n... | 72 | 1 |
'''simple docstring'''
import re
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
snake_case_ = 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(__UpperCAmelCase... | 72 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_C... | 72 | 1 |
'''simple docstring'''
from math import factorial, radians
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase = 18, __UpperCAmelCase = 10 ) -> float:
'''simple docstring'''
snake_case_ = angle_in_degrees - ((angle_in_degrees // 3_6_0.0) * 3_6_0.0)
# Conver... | 72 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.model... | 72 | 1 |
'''simple docstring'''
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRoberta... | 72 |
'''simple docstring'''
from datetime import datetime
import requests
def __magic_name__ ( __UpperCAmelCase ) -> bytes:
'''simple docstring'''
snake_case_ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
snake_case_ = requests... | 72 | 1 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class a ( _lowerCamelCase ):
snake_case_ ... | 72 |
'''simple docstring'''
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 ... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> str:
'''simple docstring'''
snake_case_ = [False] * len(__UpperCAmelCase )
snake_case_ = []
queue.append(__UpperCAmelC... | 72 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
a : Tuple = 6_378_137.0
a : int = 6_356_752.314_245
a : Dict = 637_8137
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> ... | 72 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> list[list]:
'''simple docstring'''
snake_case_ = current_set.copy()
for row_index, row in enumerate(__UpperCAmelCase ):
snake_case_ = row[0]
for column_index, column ... | 72 | 1 |
'''simple docstring'''
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker... | 72 |
'''simple docstring'''
a : Dict = 6_5521
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
snake_case_ = 1
snake_case_ = 0
for plain_chr in plain_text:
snake_case_ = (a + ord(__UpperCAmelCase... | 72 | 1 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a ( _lowerCamelCase ):
snake_case_ = "Speech2TextFeatureExtractor"
snake_case_ = "Speech2TextTokenizer"
def __init__( self : Tuple ... | 72 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 72 | 1 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class a ( unittest.TestCase ):
def A_ ( self : List[Any] ):
snake_case_ = [
'''safety_checker/pytorch_model.bin''',
... | 72 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> list[int]:
'''simple docstring'''
snake_case_ = int(__UpperCAmelCase )
# Initialize Result
snake_case_ = []
# Traverse through all denomination
for ... | 72 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
a : int = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
for it... | 72 | 1 |
'''simple docstring'''
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 ModelTe... | 72 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a : int = {
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'tokenization_xlm': ['XLMToken... | 72 | 1 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase = None ) -> str:
'''simple docstring'''
if version.parse(hfh.__v... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> int:
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case_ = _modexpt(__UpperCAmelCase, exponent // 2, ... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> float:
'''simple docstring'''
if principal <= 0:
raise Exception('''Principal borrowed must be > 0''' )
if rate_per_annum < 0:
raise Exception('''Rate o... | 72 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
a : Union[str, Any] = 'src/transformers'
# This is to make sure the transf... | 72 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 72 |
'''simple docstring'''
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch... | 72 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common ... | 72 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a ( unitte... | 72 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a : List[str] = {
'configuration_rembert': ['REMBERT_P... | 72 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class a ( unittest.TestCase ):
def A_ ( self : List[Any] ):
snake_case_ = [
'''safety_checker/pytorch_model.bin''',
... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> int:
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case_ = _modexpt(__UpperCAmelCase, exponent // 2, ... | 72 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@datacl... | 72 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaag... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/x... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Any:
'''simple docstring'''
_enforce_args(__UpperCAmelCase, __UpperCAmelCase )
if n == 0:
return 0
snake_case_ = float('''-inf''' )
for i in range(1, ... | 72 |
'''simple docstring'''
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data imp... | 72 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_m... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
a : Tuple ... | 72 | 1 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, ... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Any:
'''simple docstring'''
_enforce_args(__UpperCAmelCase, __UpperCAmelCase )
if n == 0:
return 0
snake_case_ = float('''-inf''' )
for i in range(1, ... | 72 | 1 |
'''simple docstring'''
from math import sqrt
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
assert isinstance(__UpperCAmelCase, __UpperCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
snake_case_ = ... | 72 |
'''simple docstring'''
import math
from collections.abc import Callable
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> float:
'''simple docstring'''
snake_case_ = xa
snake_case_ = xa
while True:
if x_n... | 72 | 1 |
'''simple docstring'''
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('''repo_id''', ['''canonical_dataset_name''', '''org-name/dataset-name'''] )
@pytest.mark.parametrize('''path''', ['''filename.csv''', '''filename with blanks.csv'''... | 72 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_C... | 72 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class a ( metaclass=_lowerCamelCase ):
snake_case_ = ["note_seq"]
def __init__( self : str , *lowercase_ : Tuple , **lowercase_ : Union[str, Any] ):
requires_backends(self , [... | 72 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.model... | 72 | 1 |
'''simple docstring'''
from scipy.stats import pearsonr
import datasets
a : List[Any] = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on t... | 72 |
'''simple docstring'''
from datetime import datetime
import requests
def __magic_name__ ( __UpperCAmelCase ) -> bytes:
'''simple docstring'''
snake_case_ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
snake_case_ = requests... | 72 | 1 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
a : Union[str, Any] ... | 72 |
'''simple docstring'''
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 ... | 72 | 1 |
'''simple docstring'''
from maths.prime_check import is_prime
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
if not isinstance(__UpperCAmelCase, __UpperCAmelCase ):
snake_case_ = F"Input value of [number={number}] must be an integer... | 72 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
a : Tuple = 6_378_137.0
a : int = 6_356_752.314_245
a : Dict = 637_8137
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> ... | 72 | 1 |
'''simple docstring'''
a : List[Any] = 'Alexander Joslin'
import operator as op
from .stack import Stack
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
snake_case_ = {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> list[list]:
'''simple docstring'''
snake_case_ = current_set.copy()
for row_index, row in enumerate(__UpperCAmelCase ):
snake_case_ = row[0]
for column_index, column ... | 72 | 1 |
'''simple docstring'''
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class a ( _lowerCamelCase ):
snake_case_ = (DDPMParallelScheduler,)
def A_ ( self : List[Any] , **lowercase_ : str ):
snak... | 72 |
'''simple docstring'''
a : Dict = 6_5521
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
snake_case_ = 1
snake_case_ = 0
for plain_chr in plain_text:
snake_case_ = (a + ord(__UpperCAmelCase... | 72 | 1 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 72 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 72 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a : List[str] = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Lx... | 72 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 72 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : List[str] = {
'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
'configuration_m... | 72 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
a : int = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
for it... | 72 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
a : Any = list[tuple[int, int]]
a : Any = [
[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],
[1, 0, 1, 0, 0... | 72 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a : int = {
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'tokenization_xlm': ['XLMToken... | 72 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fro... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> int:
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case_ = _modexpt(__UpperCAmelCase, exponent // 2, ... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> list:
'''simple docstring'''
if len(__UpperCAmelCase ) <= 1:
return [tuple(__UpperCAmelCase )]
snake_case_ = []
def generate(__UpperCAmelCase, __UpperCAmelCase ):
... | 72 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
a : Union[str, Any] = 'src/transformers'
# This is to make sure the transf... | 72 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 72 |
'''simple docstring'''
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> list:
'''simple docstring'''
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(__UpperCAmelCase ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__impor... | 72 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a ( unitte... | 72 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
a : Dict = False
class a ( unittest.TestCase )... | 72 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class a ( unittest.TestCase ):
def A_ ( self : List[Any] ):
snake_case_ = [
'''safety_checker/pytorch_model.bin''',
... | 72 | 1 |
'''simple docstring'''
import numpy as np
from transformers import Pipeline
def __magic_name__ ( __UpperCAmelCase ) -> List[str]:
'''simple docstring'''
snake_case_ = np.max(__UpperCAmelCase, axis=-1, keepdims=__UpperCAmelCase )
snake_case_ = ... | 72 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@datacl... | 72 | 1 |
'''simple docstring'''
a : Optional[int] = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader imp... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/x... | 72 | 1 |
'''simple docstring'''
from pathlib import Path
import fire
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> Union[str, Any]:
'''simple docstring'''
snake_case_ = Path(__UpperCAmelCase )
snake_case_ = Path(__Upper... | 72 |
'''simple docstring'''
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data imp... | 72 | 1 |
'''simple docstring'''
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
@re... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
a : Tuple ... | 72 | 1 |
'''simple docstring'''
# 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.... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Any:
'''simple docstring'''
_enforce_args(__UpperCAmelCase, __UpperCAmelCase )
if n == 0:
return 0
snake_case_ = float('''-inf''' )
for i in range(1, ... | 72 | 1 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_t... | 72 |
'''simple docstring'''
import math
from collections.abc import Callable
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> float:
'''simple docstring'''
snake_case_ = xa
snake_case_ = xa
while True:
if x_n... | 72 | 1 |
'''simple docstring'''
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
a : int = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
'KD 6S 9D... | 72 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_C... | 72 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class a ( metaclass=_lowerCamelCase ):
snake_case_ = ["torch", "scipy"]
def __init__( self : Dict , *lowercase_ : Any , **lowercase_ : int ):
requires_backends(self , ['''torc... | 72 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.model... | 72 | 1 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerat... | 72 |
'''simple docstring'''
from datetime import datetime
import requests
def __magic_name__ ( __UpperCAmelCase ) -> bytes:
'''simple docstring'''
snake_case_ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
snake_case_ = requests... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> List[Any]:
'''simple docstring'''
snake_case_ = [0 for i in range(r + 1 )]
# nc0 = 1
snake_case_ = 1
for i in range(1, n + 1 ):
# to compu... | 72 |
'''simple docstring'''
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 ... | 72 | 1 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
a : int = input('Enter image url: ').strip()
print(f'''Downloading image from {url} ...''')
a : Any = BeautifulSoup(requests.get(url).conte... | 72 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
a : Tuple = 6_378_137.0
a : int = 6_356_752.314_245
a : Dict = 637_8137
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> ... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
if not isinstance(__UpperCAmelCase, __UpperCAmelCase ):
snake_case_ = F"Input value of [number={number}] must be an integer"
raise TypeError(__UpperCAmelC... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> list[list]:
'''simple docstring'''
snake_case_ = current_set.copy()
for row_index, row in enumerate(__UpperCAmelCase ):
snake_case_ = row[0]
for column_index, column ... | 72 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import... | 72 |
'''simple docstring'''
a : Dict = 6_5521
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
snake_case_ = 1
snake_case_ = 0
for plain_chr in plain_text:
snake_case_ = (a + ord(__UpperCAmelCase... | 72 | 1 |
'''simple docstring'''
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VAR... | 72 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 72 | 1 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
a : int = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
for it... | 72 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 72 | 1 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class a ( unittest.TestCase ):
def A_ ( self : int ):
snake_case_ = inspect.getfile(acc... | 72 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
a : int = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
for it... | 72 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_... | 72 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a : int = {
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'tokenization_xlm': ['XLMToken... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> tuple[float, float]:
'''simple docstring'''
if not len(__UpperCAmelCase ) == len(__UpperCAmelCase ) == 3:
raise ValueError('''Please enter a valid equation.''' )
if equationa[... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> int:
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case_ = _modexpt(__UpperCAmelCase, exponent // 2, ... | 72 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
... | 72 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
a : Union[str, Any] = 'src/transformers'
# This is to make sure the transf... | 72 | 1 |
'''simple docstring'''
import os
import sys
import unittest
a : Tuple = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_o... | 72 |
'''simple docstring'''
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
assert isinstance(__UpperCAmelCase, __UpperCAmelCase ), F"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
snake_... | 72 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a ( unitte... | 72 | 1 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
a : Dict = {'UserAgent': UserAgent().random}
def __magic_name__ ( __UpperCAmelCase ) -> dict:
'''simple docstring'''
s... | 72 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class a ( unittest.TestCase ):
def A_ ( self : List[Any] ):
snake_case_ = [
'''safety_checker/pytorch_model.bin''',
... | 72 | 1 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
a : Optional[int] = '%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input(... | 72 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@datacl... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> str:
'''simple docstring'''
if not (isinstance(__UpperCAmelCase, __UpperCAmelCase ) and isinstance(__UpperCAmelCase, __UpperCAmelCase )):
raise ValueError('''longest_common_subst... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/x... | 72 | 1 |
'''simple docstring'''
from datetime import datetime
import requests
def __magic_name__ ( __UpperCAmelCase ) -> bytes:
'''simple docstring'''
snake_case_ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
snake_case_ = requests... | 72 |
'''simple docstring'''
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data imp... | 72 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a : List[str] = {'configuration_vit_mae': ['VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMAEConfi... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
a : Tuple ... | 72 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : List[Any] ... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Any:
'''simple docstring'''
_enforce_args(__UpperCAmelCase, __UpperCAmelCase )
if n == 0:
return 0
snake_case_ = float('''-inf''' )
for i in range(1, ... | 72 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class a :
def __init__( self : List[Any] , lowercase_ : int ):
snake_case_ = value
snake_case_ = None
snake_case_ = None... | 72 |
'''simple docstring'''
import math
from collections.abc import Callable
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> float:
'''simple docstring'''
snake_case_ = xa
snake_case_ = xa
while True:
if x_n... | 72 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kand... | 72 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_C... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> str:
'''simple docstring'''
if not isinstance(__UpperCAmelCase, __UpperCAmelCase ):
raise ValueError('''iterations must be defined as integers''' )
if not isinstance(__UpperCAm... | 72 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.model... | 72 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identifi... | 72 |
'''simple docstring'''
from datetime import datetime
import requests
def __magic_name__ ( __UpperCAmelCase ) -> bytes:
'''simple docstring'''
snake_case_ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
snake_case_ = requests... | 72 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load... | 72 |
'''simple docstring'''
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 ... | 72 | 1 |
'''simple docstring'''
import unittest
import numpy as np
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase = None, ) -> np.ndarray:
'''simple docstring'''
snake_case_ = np.shape(__UpperCAmelCase )
snake_case_ ... | 72 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
a : Tuple = 6_378_137.0
a : int = 6_356_752.314_245
a : Dict = 637_8137
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> ... | 72 | 1 |
'''simple docstring'''
from __future__ import annotations
def __magic_name__ ( __UpperCAmelCase ) -> list[int]:
'''simple docstring'''
return [ord(__UpperCAmelCase ) - 96 for elem in plain]
def __magic_name__ ( __UpperCAmelCase ) -> str:
'''simple docstring'''
... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> list[list]:
'''simple docstring'''
snake_case_ = current_set.copy()
for row_index, row in enumerate(__UpperCAmelCase ):
snake_case_ = row[0]
for column_index, column ... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 200_0000 ) -> int:
'''simple docstring'''
snake_case_ = [0 for i in range(n + 1 )]
snake_case_ = 1
snake_case_ = 1
for i in range(2, int(n**0.5 ) + 1 ):
... | 72 |
'''simple docstring'''
a : Dict = 6_5521
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
snake_case_ = 1
snake_case_ = 0
for plain_chr in plain_text:
snake_case_ = (a + ord(__UpperCAmelCase... | 72 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : str = {
'roberta-base': 'http... | 72 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 72 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase = None... | 72 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 72 | 1 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def __magic_name__ ( *__UpperCAmelCase, __UpperCAmelCase = None, __UpperCAmelCase=True, __UpperCAmelCase=2 ) -> int:
'''simple docstring'''
from ..... | 72 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
a : int = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
for it... | 72 | 1 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.model... | 72 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a : int = {
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'tokenization_xlm': ['XLMToken... | 72 | 1 |
'''simple docstring'''
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 __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCA... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> int:
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case_ = _modexpt(__UpperCAmelCase, exponent // 2, ... | 72 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def __magic_name__ ( __UpperCAmelCase ) -> Union[str, A... | 72 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
a : Union[str, Any] = 'src/transformers'
# This is to make sure the transf... | 72 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a : Union[str, Any] = {'configuration_xlnet': ['XLNET_PRET... | 72 |
'''simple docstring'''
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch... | 72 | 1 |
'''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config impor... | 72 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a ( unitte... | 72 | 1 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class a ( _lowerCamelCase ):
snake_case_ = "MCTCTFeatureExtractor"
snake_case_ = "AutoTokenizer"
def __init__( self : Optional[Any] , ... | 72 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class a ( unittest.TestCase ):
def A_ ( self : List[Any] ):
snake_case_ = [
'''safety_checker/pytorch_model.bin''',
... | 72 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> Lis... | 72 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@datacl... | 72 | 1 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
a : Any = logging.get_logger(__name__)
a : Optional[Any] = {name: getattr(transformers, name + '... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/x... | 72 | 1 |
'''simple docstring'''
from torch import nn
class a ( nn.Module ):
def __init__( self : Dict , lowercase_ : Optional[Any] , lowercase_ : Union[str, Any] ):
super().__init__()
snake_case_ = class_size
snake_case_ = e... | 72 |
'''simple docstring'''
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data imp... | 72 | 1 |
'''simple docstring'''
# Copyright (c) 2021-, NVIDIA CORPORATION. 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.... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
a : Tuple ... | 72 | 1 |
'''simple docstring'''
from math import isqrt, loga
def __magic_name__ ( __UpperCAmelCase ) -> list[int]:
'''simple docstring'''
snake_case_ = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Any:
'''simple docstring'''
_enforce_args(__UpperCAmelCase, __UpperCAmelCase )
if n == 0:
return 0
snake_case_ = float('''-inf''' )
for i in range(1, ... | 72 | 1 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def __magic_name__ ( __UpperCAmelCase ) -> List[Any]:
'''simple docstring'''
snake_case_ = [
'''encoder.version''',
... | 72 |
'''simple docstring'''
import math
from collections.abc import Callable
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> float:
'''simple docstring'''
snake_case_ = xa
snake_case_ = xa
while True:
if x_n... | 72 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokeniz... | 72 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_C... | 72 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features... | 72 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.model... | 72 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class a ( _lo... | 72 |
'''simple docstring'''
from datetime import datetime
import requests
def __magic_name__ ( __UpperCAmelCase ) -> bytes:
'''simple docstring'''
snake_case_ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
snake_case_ = requests... | 72 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart impor... | 72 |
'''simple docstring'''
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 ... | 72 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : List[str] = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Autofor... | 72 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
a : Tuple = 6_378_137.0
a : int = 6_356_752.314_245
a : Dict = 637_8137
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> ... | 72 | 1 |
'''simple docstring'''
from heapq import heappop, heappush
import numpy as np
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, ) -> tuple[float | int, list[tuple[int, int]]]:
'''simple docstring'''
snake_case_ ,snake_case_ ... | 72 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> list[list]:
'''simple docstring'''
snake_case_ = current_set.copy()
for row_index, row in enumerate(__UpperCAmelCase ):
snake_case_ = row[0]
for column_index, column ... | 72 | 1 |
'''simple docstring'''
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentPar... | 72 |
'''simple docstring'''
a : Dict = 6_5521
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
snake_case_ = 1
snake_case_ = 0
for plain_chr in plain_text:
snake_case_ = (a + ord(__UpperCAmelCase... | 72 | 1 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
a : Optional[int] = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def __magic_name__ ( ) -> Dict:
'''simple docstring'''
snake_case_ = os.path.dirname(os.path.realpath(__U... | 72 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 72 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_lowerCamelCase )
class a ( _lowerCamelCase ):
snake_case_ = fiel... | 72 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 72 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(100, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05... | 350 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
a : int = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
for it... | 72 | 0 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_para... | 351 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a : int = {
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'tokenization_xlm': ['XLMToken... | 72 | 0 |
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