code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ ( lowercase , lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = BeautifulSoup(requests.get(_lowerCamelCase , params=_lowerCamelCase ).content , "html.parser" )
SC... | 62 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPip... | 24 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowercase : List[Any] = logging.get_logger(__name__)
__lowercase : Any = {
... | 36 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 24 | 0 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelin... | 97 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ : List[str] = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'... | 24 | 0 |
from math import factorial
def __magic_name__ ( lowercase = 100 ) -> int:
"""simple docstring"""
return sum(map(_lowerCamelCase , str(factorial(_lowerCamelCase ) ) ) )
if __name__ == "__main__":
print(solution(int(input("""Enter... | 458 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = abs(_lowerCamelCase )
__snake_case = 0
while n > 0:
res += n % 10
n //= 10
return res
def ... | 24 | 0 |
"""simple docstring"""
def _snake_case ( _snake_case : list[int] , _snake_case : list[int] ) -> None:
'''simple docstring'''
_A = len(_lowerCamelCase )
print('The following activities are selected:' )
# The first activity is always sele... | 7 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : Optional[Any] )-> Dict:
'''simple docstring'''
__snake_case = []
__snake_case = []
__snake_case = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
... | 24 | 0 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
UpperCAmelCase_ : Tuple = logging.get_logger(__name__)
def Upp... | 120 |
'''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_featur... | 24 | 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."
)
| 393 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCamelCase (_lowerCamelCase : Tuple )-> List[str]:
'''simple... | 24 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-b... | 552 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
__snake_case = 1
__snake_case = 1
while repunit:
__snake_case ... | 24 | 0 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( lowerCamelCase__ : str , lowerCamelCase__ : Union[str, Any] , lowerC... | 457 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def _UpperCamelCase (_l... | 24 | 0 |
'''simple docstring'''
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(""".""")
def _lowerCAmelCase (_lowercase ):
"""simple docstring"""
... | 331 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : int )-> float:
'''simple docstring'''
__snake_case = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# form... | 24 | 0 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> list[list[int]]:
UpperCAmelCase__ : Any = []
create_all_state(1 , _lowerCamelCase , _lowerCamelCase , [] , _lowerCamelC... | 75 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import ... | 24 | 0 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
return x + 2
class SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple do... | 62 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = [[0 for _ in range(_lowerCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__snake_case = 1
fo... | 24 | 0 |
__lowercase : Any = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
__lowercase : str =... | 36 |
'''simple docstring'''
import argparse
import os
import re
UpperCAmelCase_ : List[str] = '''src/transformers/models/auto'''
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCAmelCase_ : Tuple = re.... | 24 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import S... | 97 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _UpperCamelCase (*_lowerCamelCase : str , _lowerCamelCase : Optional[Union[Dict, Any]] = None , _lowerCamelCase : List[Any]=True , _low... | 24 | 0 |
class UpperCamelCase__ :
'''simple docstring'''
def __init__( self, snake_case__ ) -> str:
"""simple docstring"""
lowercase_ : Tuple = n
lowercase_ : Optional[Any] = [None] * self.n
... | 458 |
'''simple docstring'''
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTe... | 24 | 0 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from... | 7 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 24 | 0 |
'''simple docstring'''
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTea... | 120 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowerCAmelCase ( __lowerCAmelCase):
def __init__( self ... | 24 | 0 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A_ = '''src/diffusers'''
A... | 393 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingS... | 24 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_ = {
'''configuration_m2m_100''': ['''M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''M2M100Config''', '''M2M... | 552 |
'''simple docstring'''
from collections import deque
def _UpperCamelCase (_lowerCamelCase : Union[str, Any] )-> Optional[int]:
'''simple docstring'''
__snake_case = len(_lowerCamelCase )
__snake_case = deque()
__snake_case ... | 24 | 0 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepiece
@slow ... | 457 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@req... | 24 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffu... | 331 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import... | 24 | 0 |
'''simple docstring'''
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> bool:
UpperCAmelCase__ : Optional[int] = len(_lowerCamelCase )
UpperCAmelCase__ : Tuple = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for ... | 75 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transform... | 24 | 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... | 62 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPip... | 24 | 0 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_... | 36 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 24 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeriesTransformerConfig''',
],
... | 97 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ : List[str] = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'... | 24 | 0 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
UpperCAmelCase_ = 2_048
UpperCAmelCase_ = 4_096
UpperCAmelCase_ = 42
UpperCAmelCase_ = os.environ.pop("""PROCESS_TRAIN""", """false""")
UpperCAmelCase_ = {'''null''': 0, '''short'''... | 458 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = abs(_lowerCamelCase )
__snake_case = 0
while n > 0:
res += n % 10
n //= 10
return res
def ... | 24 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_ax... | 7 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : Optional[Any] )-> Dict:
'''simple docstring'''
__snake_case = []
__snake_case = []
__snake_case = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
... | 24 | 0 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos.jso... | 120 |
'''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_featur... | 24 | 0 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
... | 393 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCamelCase (_lowerCamelCase : Tuple )-> List[str]:
'''simple... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_co... | 552 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
__snake_case = 1
__snake_case = 1
while repunit:
__snake_case ... | 24 | 0 |
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.kandinsky.text_encoder import ... | 457 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def _UpperCamelCase (_l... | 24 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
... | 331 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : int )-> float:
'''simple docstring'''
__snake_case = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# form... | 24 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_input... | 75 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import ... | 24 | 0 |
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, require_vision, slow, ... | 62 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = [[0 for _ in range(_lowerCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__snake_case = 1
fo... | 24 | 0 |
def lowercase ( __A : int ) -> int:
'''simple docstring'''
snake_case : Optional[int] = abs(_lowerCamelCase )
snake_case : Tuple = 0
while n > 0:
res += n % 10
n //= 10
return res
def lowercase ( __A : ... | 36 |
'''simple docstring'''
import argparse
import os
import re
UpperCAmelCase_ : List[str] = '''src/transformers/models/auto'''
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCAmelCase_ : Tuple = re.... | 24 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from ..tes... | 97 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _UpperCamelCase (*_lowerCamelCase : str , _lowerCamelCase : Optional[Union[Dict, Any]] = None , _lowerCamelCase : List[Any]=True , _low... | 24 | 0 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy,... | 458 |
'''simple docstring'''
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTe... | 24 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a = {
'''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
'''tokeni... | 7 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 24 | 0 |
'''simple docstring'''
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def UpperCAmelCase_ ( A , A , A ):
'''simple docstring'''
_a : List[Any] = AlbertC... | 120 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowerCAmelCase ( __lowerCAmelCase):
def __init__( self ... | 24 | 0 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
A_ = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh''',
'''... | 393 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingS... | 24 | 0 |
"""simple docstring"""
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require... | 552 |
'''simple docstring'''
from collections import deque
def _UpperCamelCase (_lowerCamelCase : Union[str, Any] )-> Optional[int]:
'''simple docstring'''
__snake_case = len(_lowerCamelCase )
__snake_case = deque()
__snake_case ... | 24 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __lowercase ( __lowerCAmelCase ):
"""simple docstring"""
@staticmethod
@abstractmethod
def __A ( A ) -> Dict:
'''simple docstring'''
raise NotImplementedError()
... | 457 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@req... | 24 | 0 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
... | 331 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import... | 24 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 75 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transform... | 24 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class SCREAMING_SNAKE_CASE ( nn.Module ):
'''simple docstring'''
def __init__( self : Union[str, Any] , UpperCAmelCase_ : ... | 62 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPip... | 24 | 0 |
import math
import os
import sys
def lowercase ( __A : str ) -> str:
'''simple docstring'''
snake_case : Dict = """"""
try:
with open(_lowerCamelCase , """rb""" ) as binary_file:
snake_case : Tuple = binary_file.read... | 36 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 24 | 0 |
from random import randint, random
def a ( snake_case__: int , snake_case__: int , snake_case__: int , snake_case__: bool = False , snake_case__: bool = False , snake_case__: int = 5 , ):
'''simple docstring'''
lowercase_ = [[-1] * number_of_cells] # Cr... | 97 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ : List[str] = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'... | 24 | 0 |
import pprint
import requests
UpperCAmelCase_ = '''https://zenquotes.io/api'''
def __magic_name__ ( ) -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __magic_name__ ( ) -> list:
... | 458 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = abs(_lowerCamelCase )
__snake_case = 0
while n > 0:
res += n % 10
n //= 10
return res
def ... | 24 | 0 |
"""simple docstring"""
import math
def _snake_case ( _snake_case : list , _snake_case : int ) -> int:
'''simple docstring'''
_A = len(_lowerCamelCase )
_A = int(math.floor(math.sqrt(_lowerCamelCase ) ) )
_A = 0
... | 7 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : Optional[Any] )-> Dict:
'''simple docstring'''
__snake_case = []
__snake_case = []
__snake_case = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
... | 24 | 0 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def UpperCAmelCase_ ( A ):
'''simple docstring'''
_... | 120 |
'''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_featur... | 24 | 0 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
A_ = '''\
'''
A_ = '''
Perplexity (PPL) is one of the most common metrics for evaluating language models.
It is define... | 393 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCamelCase (_lowerCamelCase : Tuple )-> List[str]:
'''simple... | 24 | 0 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def UpperCAmelCase ( _lowercase : Optional[int] ) -> Any:
"""simple docstring"""
return getitem, k
def UpperCAmelCase ... | 552 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
__snake_case = 1
__snake_case = 1
while repunit:
__snake_case ... | 24 | 0 |
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
deprecate(
"pipelines_utils",
"0.22.0",
"Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils ins... | 457 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def _UpperCamelCase (_l... | 24 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase_ : Optional[Any] = {
'''configuration_clipseg''': [
'''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''CLIP... | 331 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : int )-> float:
'''simple docstring'''
__snake_case = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# form... | 24 | 0 |
'''simple docstring'''
UpperCamelCase__ = range(2, 2_0 + 1)
UpperCamelCase__ = [1_0**k for k in range(ks[-1] + 1)]
UpperCamelCase__ = {}
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> str:
Upp... | 75 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import ... | 24 | 0 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class SCREAMING_SNAKE_CASE ... | 62 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = [[0 for _ in range(_lowerCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__snake_case = 1
fo... | 24 | 0 |
def lowercase ( __A : int , __A : int ) -> int:
'''simple docstring'''
return number | (1 << position)
def lowercase ( __A : int , __A : int ) -> int:
'''simple docstring'''
return number & ~(1 << position)
def ... | 36 |
'''simple docstring'''
import argparse
import os
import re
UpperCAmelCase_ : List[str] = '''src/transformers/models/auto'''
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCAmelCase_ : Tuple = re.... | 24 | 0 |
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 97 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _UpperCamelCase (*_lowerCamelCase : str , _lowerCamelCase : Optional[Union[Dict, Any]] = None , _lowerCamelCase : List[Any]=True , _low... | 24 | 0 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level... | 458 |
'''simple docstring'''
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTe... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( _snake_case : int , _snake_case : int ) -> list[str]:
'''simple docstring'''
if partitions <= 0:
raise ValueError('partitions must be a positive number!' )
i... | 7 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 24 | 0 |
'''simple docstring'''
from itertools import permutations
def UpperCAmelCase_ ( A ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
_a : int = [7, 1_... | 120 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowerCAmelCase ( __lowerCAmelCase):
def __init__( self ... | 24 | 0 |
A_ = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
A_ = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def UpperCAmelCase ( UpperCAmelCase ,UpperCAmelCase ,UpperCAmelCase )-> list[int]:
'''simple docstring'''
SCREAMING_SNAKE_CASE_ = ... | 393 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingS... | 24 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
lowercase_ = logging.get_logger(__name__)
class __a ( __lowerCAmelCase ):
def __init__( self ... | 552 |
'''simple docstring'''
from collections import deque
def _UpperCamelCase (_lowerCamelCase : Union[str, Any] )-> Optional[int]:
'''simple docstring'''
__snake_case = len(_lowerCamelCase )
__snake_case = deque()
__snake_case ... | 24 | 0 |
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
... | 457 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@req... | 24 | 0 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _lowerCAmelCase (_lowercase = 3 ):
"""simple docstring"""
if isinstance(_lowerCamelCase , _lower... | 331 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import... | 24 | 0 |
'''simple docstring'''
def a__ ( lowerCAmelCase__ ) -> Dict:
UpperCAmelCase__ : Optional[int] = []
UpperCAmelCase__ : Optional[Any] = []
UpperCAmelCase__ : List[Any] = {
'''^''': 3,
'''*''': 2,
... | 75 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transform... | 24 | 0 |
import os
snake_case = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1_000}
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = 0
SCREAMING_SNAKE_CASE : Dict ... | 62 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPip... | 24 | 0 |
from __future__ import annotations
def lowercase ( __A : list[float] , __A : Dict ) -> List[Any]:
'''simple docstring'''
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(_lowerCamelCase ):
print(f"""{i}\t\t{d}""" )
... | 36 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 24 | 0 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def a ( *snake_case__: str , snake_case__: Optional[Union[Dict, Any]] = None , snake_case__: List[Any]=True , snake_case__: str=2 ):
'''simple docstring'''
... | 97 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ : List[str] = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'... | 24 | 0 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def __magic_name__ ( lowercase , lowercase , lowercase ) -> ... | 458 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = abs(_lowerCamelCase )
__snake_case = 0
while n > 0:
res += n % 10
n //= 10
return res
def ... | 24 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, Tens... | 7 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : Optional[Any] )-> Dict:
'''simple docstring'''
__snake_case = []
__snake_case = []
__snake_case = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
... | 24 | 0 |
'''simple docstring'''
import random
def UpperCAmelCase_ ( A , A , A ):
'''simple docstring'''
_a : Tuple = a[left_index]
_a : Optional[Any] = left_index + 1
for j in range(left_index + 1 , _lowerCamelCase ):
if a[j] < pivot:
_a , ... | 120 |
'''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_featur... | 24 | 0 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizer... | 393 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCamelCase (_lowerCamelCase : Tuple )-> List[str]:
'''simple... | 24 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ... | 552 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
__snake_case = 1
__snake_case = 1
while repunit:
__snake_case ... | 24 | 0 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __ver... | 457 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def _UpperCamelCase (_l... | 24 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
UpperCamelCase_ : Optional[Any] = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfi... | 331 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : int )-> float:
'''simple docstring'''
__snake_case = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# form... | 24 | 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,
... | 75 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import ... | 24 | 0 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_availa... | 62 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = [[0 for _ in range(_lowerCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__snake_case = 1
fo... | 24 | 0 |
from __future__ import annotations
def lowercase ( __A : list[int] , __A : int ) -> list[list[int]]:
'''simple docstring'''
snake_case : Union[str, Any] = []
snake_case : Optional[int] = []
snake_case : Dict = 0
... | 36 |
'''simple docstring'''
import argparse
import os
import re
UpperCAmelCase_ : List[str] = '''src/transformers/models/auto'''
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCAmelCase_ : Tuple = re.... | 24 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, s... | 97 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _UpperCamelCase (*_lowerCamelCase : str , _lowerCamelCase : Optional[Union[Dict, Any]] = None , _lowerCamelCase : List[Any]=True , _low... | 24 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
# See all GPT... | 458 |
'''simple docstring'''
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTe... | 24 | 0 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available(... | 7 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 24 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class a ( __lowerCAmelCase ):
'''simple docstring'''
def __init__( self , ... | 120 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowerCAmelCase ( __lowerCAmelCase):
def __init__( self ... | 24 | 0 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():... | 393 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingS... | 24 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from tra... | 552 |
'''simple docstring'''
from collections import deque
def _UpperCamelCase (_lowerCamelCase : Union[str, Any] )-> Optional[int]:
'''simple docstring'''
__snake_case = len(_lowerCamelCase )
__snake_case = deque()
__snake_case ... | 24 | 0 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from trans... | 457 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@req... | 24 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_input... | 331 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import... | 24 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testin... | 75 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transform... | 24 | 0 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCamelCase__ ( lowercase , lowercase , lowercase = False ):
"""simple docstring"""
if radian_mode:
return [magnitude * cos(_lowerCamelCase ... | 62 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPip... | 24 | 0 |
from sklearn.metrics import fa_score
import datasets
__lowercase : Dict = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
__lowercase : Union[str, Any] = '''
Args:
p... | 36 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 24 | 0 |
import os
def a ( snake_case__: str = "matrix.txt" ):
'''simple docstring'''
with open(os.path.join(os.path.dirname(_lowerCamelCase ) , _lowerCamelCase ) ) as in_file:
lowercase_ = in_file.read()
lowercase_ = [[int(_lowerCamelCase )... | 97 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ : List[str] = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'... | 24 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
# See all Cvt models at htt... | 458 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = abs(_lowerCamelCase )
__snake_case = 0
while n > 0:
res += n % 10
n //= 10
return res
def ... | 24 | 0 |
"""simple docstring"""
import json
import os
from ...utils.constants import SAGEMAKER_PARALLEL_EC2_INSTANCES, TORCH_DYNAMO_MODES
from ...utils.dataclasses import ComputeEnvironment, SageMakerDistributedType
from ...utils.imports import is_botoa_available
from .config_args import SageMakerConfig
from .config_util... | 7 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : Optional[Any] )-> Dict:
'''simple docstring'''
__snake_case = []
__snake_case = []
__snake_case = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
... | 24 | 0 |
'''simple docstring'''
class a :
'''simple docstring'''
def __init__( self , lowerCamelCase_ , lowerCamelCase_=None , lowerCamelCase_=None ) -> Dict:
_a : Optional[int] = data
_a : str = previous
_a : Optional[Any] = next... | 120 |
'''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_featur... | 24 | 0 |
def UpperCAmelCase ( UpperCAmelCase )-> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE_ = [[0 for _ in range(_lowerCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
SCREAMING_SNAKE_CASE_ = 1
for n in range(m + 1 ):
... | 393 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCamelCase (_lowerCamelCase : Tuple )-> List[str]:
'''simple... | 24 | 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,
)
lowercase_ = {
'''configuration_roberta''': ... | 552 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
__snake_case = 1
__snake_case = 1
while repunit:
__snake_case ... | 24 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, Fla... | 457 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def _UpperCamelCase (_l... | 24 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diff... | 331 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : int )-> float:
'''simple docstring'''
__snake_case = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# form... | 24 | 0 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers i... | 75 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import ... | 24 | 0 |
def lowerCamelCase__ ( lowercase , lowercase , lowercase , lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Any = len(_lowerCamelCase ), len(grid[0] )
if (
min(_lowerCamelCase , _lowerCamelCase ) < ... | 62 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int )-> int:
'''simple docstring'''
__snake_case = [[0 for _ in range(_lowerCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__snake_case = 1
fo... | 24 | 0 |
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