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 |
|---|---|---|---|---|
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
from transform... | 305 |
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class A ( tf.keras.layers.Layer ):
'''simple docstring'''
... | 305 | 1 |
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.u... | 366 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils impo... | 281 | 0 |
"""simple docstring"""
class lowercase :
def __init__( self , lowercase ) -> None:
lowerCAmelCase = set_counts
lowerCAmelCase = max(lowercase )
lowerCAmelCase = len(lowercase )
lowerCA... | 46 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import ... | 46 | 1 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
UpperCamelCase__ : Opti... | 330 |
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
fro... | 330 | 1 |
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerate.tes... | 201 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__a: Dict = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenization_ctrl""": ["""CTRLToke... | 198 | 0 |
'''simple docstring'''
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
a_ = '\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang... | 222 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
# See all BioGPT models at https://huggingfac... | 222 | 1 |
"""simple docstring"""
def __a ( _SCREAMING_SNAKE_CASE ) ->bool:
a__: set[int] = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
a__: set[int] = set()
return any(
node not in visited and depth_first_search(_SCREAMING_SNAKE_CASE , ... | 290 | """simple docstring"""
def __a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->Union[str, Any]:
if height >= 1:
move_tower(height - 1 , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE )
move_dis... | 290 | 1 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
snake_case : Any = logging.getLogger(__name__)
def __lowercase ( ):
a__ = argparse.ArgumentParser(
description='Prepare TFRecor... | 109 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : List[Any] , __lowerCAmelCase : Optional[Any] , __lowerCAmelCase : str , __lowerCAmelCase : List[str] ): # noqa: E741
while r - l > 1:
a__ = (l + r... | 109 | 1 |
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
__a = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__a = [ord(letter) for letter in string.ascii_lowercase]
__a = {ord(char) for char... | 337 |
from heapq import heappop, heappush
import numpy as np
def __lowercase ( a__ , a__ , a__ , a__ , ) -> tuple[float | int, list[tuple[int, int]]]:
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE = grid.shape
__SCREAMING_SNAKE_CASE ... | 257 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attentio... | 84 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Dict = {name: getattr(transform... | 84 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxMode... | 287 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase =logging.get_logger(__name__)
_lowerCamelCase ={
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/bridgetower-base/blob/main/con... | 287 | 1 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils im... | 365 |
from __future__ import annotations
from random import random
class UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCamelCase_ = None ):
lowercase_ :Tuple = value
lowercase_ :Tuple = r... | 252 | 0 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
A = False
class __lowercase ( unittest.TestCase ... | 160 |
"""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_ima... | 160 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
snak... | 236 |
'''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_avai... | 236 | 1 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class _UpperCAmelCase ( snake_case_ ... | 79 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase_ = {
'''configuration_longformer''': [
'''LONGFORMER_PRE... | 79 | 1 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class lowerCAmelCase_... | 339 |
from __future__ import annotations
def __magic_name__ ( __lowerCAmelCase : list , __lowerCAmelCase : int | None = None , __lowerCAmelCase : int | None = None ) -> None:
if start is None:
__lowerCamelCase = 0
if end is None:
... | 339 | 1 |
"""simple docstring"""
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
lowercase__ : Tuple = 2_9_9_7_9_2_4_5_8
# Symbols
lowercase__ , lowercase__ , lowercase__ , lowercase__ : Any ... | 224 |
"""simple docstring"""
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
... | 224 | 1 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
SCREAMING_SNAKE_CASE : Any = input("Enter image url: ").strip()
print(f"Downloading image from {url} ...")
SCREAMING_SNAKE_CASE : Union[str, Any] = ... | 252 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common i... | 252 | 1 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase__( __lowerCamelCase):
UpperCAmelCase__ : Tuple = (UnCLIPScheduler,)
def lowerCAmelCase__ ( self: List[Any] , **UpperCamelCase_: Any )... | 12 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
__A ='''2.13.1'''
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('''3.7'''):
raise ImportWarning(
... | 19 | 0 |
"""simple docstring"""
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus... | 205 |
"""simple docstring"""
def UpperCAmelCase ( a_ = 10 ):
'''simple docstring'''
if not isinstance(a_, a_ ) or n < 0:
raise ValueError('Invalid input' )
lowerCamelCase : Union[str, Any] = 10**n
lowerCamelCase : int = 2_8433 ... | 205 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_encoder import M... | 253 |
import argparse
from collections import defaultdict
import yaml
lowerCAmelCase : Dict = 'docs/source/en/_toctree.yml'
def A_ ( a ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[int] = defaultdict(a )
for doc in model_doc:
... | 253 | 1 |
def UpperCamelCase ( lowerCAmelCase__ = 100 ):
'''simple docstring'''
lowercase = set()
lowercase = 0
lowercase = n + 1 # maximum limit
for a in range(2 , _lowerCamelCase ):
for b in range(2 , _lowerCamelCase ... | 370 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ :Any = {
"configuration_distilbert": [
"DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_... | 97 | 0 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, FlaxMTaF... | 121 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase__ : Any = logging.get_logger(__name__)
class UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ... | 121 | 1 |
import os
def _SCREAMING_SNAKE_CASE ( ):
A_ : Optional[Any] = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , '''num.txt''' )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(SCREAMING_SNAKE_CASE ) for line in file_hand ) )[:10]
if __name__ == "__main__":... | 65 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import BaseT... | 65 | 1 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
UpperCamelCase = datasets.logging.get_logger(__name__)
UpperCamelCase = '''\
@InProceedings{moosavi2019minimum,
... | 87 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : str = logging.get_logger(__name__)
__a : int = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
# See all W... | 210 | 0 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
def __lowerCamelCase ( lowerCamelCase__ : Any ):
... | 66 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
UpperCAmelCase : Optional[Any] = logging.get_logger(... | 66 | 1 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
SCREAMING_SNAKE_CASE :List[Any] = False
class UpperCAmelCase ( unittest.TestCase ):
'''si... | 15 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
SCREAMING_SNAKE_CASE... | 15 | 1 |
"""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 = 'src/transformers'
# This is to make sure the transformers module imp... | 357 |
"""simple docstring"""
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import lo... | 144 | 0 |
"""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 : Tupl... | 44 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowercase : int = logging.get_logger(__name__)
_lowercase : List[Any] ... | 93 | 0 |
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 ModelTesterMixin, ids_tensor, rand... | 119 | def __lowerCamelCase ( lowerCAmelCase__ ):
lowerCAmelCase__ = len(lowerCAmelCase__ )
for i in range(lowerCAmelCase__ ):
for j in range(i + 1 , lowerCAmelCase__ ):
if numbers[j] < numbers[i]:
lowerCAmelCa... | 119 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
... | 55 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_availab... | 344 | 0 |
from __future__ import annotations
UpperCAmelCase : Union[str, Any] = 10
def __lowerCamelCase ( lowerCamelCase__ : list[int] ):
'''simple docstring'''
lowerCamelCase = 1
lowerCamelCase = max(lowerCamelCase__ )
while place... | 357 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/conf... | 66 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelera... | 78 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
snake_case_ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5On... | 78 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkou... | 365 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case : List[Any] = get_tests_dir('''fixtures/test_sentenc... | 281 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __a ( __lowerCamelCase ):
UpperCAmelCase_ , UpperCAmelCase_ : List[Any] = analyze_text(__lowerCamelCase )
UpperCAmelCase_ :... | 61 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class _UpperCAmelCase (... | 292 | 0 |
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 PaddingStrategy, l... | 351 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested... | 145 | 0 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowercase_ = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def _snake_case( SCREAMING_SNAKE_CA... | 7 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _conc... | 34 | 0 |
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_opt... | 354 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available... | 82 | 0 |
'''simple docstring'''
from math import pow
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , ) -> tuple[int, int]:
if current_sum == needed_sum:
# If the sum of the powers is equal to neede... | 181 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProc... | 181 | 1 |
"""simple docstring"""
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import Gra... | 126 | """simple docstring"""
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
... | 126 | 1 |
'''simple docstring'''
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
lowercase : Optional[Any] = logging.get_logg... | 3 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_st... | 147 | 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 impor... | 357 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPh... | 251 | 0 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
UpperCAmelCase : List[str] =["""small""", """medium""", """large"""]
UpperCAmelCase : int ="""lm_head.decoder.weight"""
UpperCAmelCase : List[str] ="""lm_he... | 128 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInput,... | 128 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : List[Any] =logging.get_logger(__name__)
__lowerCAmelCase : List[Any... | 32 | """simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def UpperCAmelCase__ ( lowerCAmelCase__ :Any , lowerCAmelCase__ :Optional[Any] , lowerCAmelCase__ :Dict , lowerCAmelCase__ :Any ) ->... | 32 | 1 |
from __future__ import annotations
_a = [True] * 1_0_0_0_0_0_1
_a = 2
while i * i <= 1_0_0_0_0_0_0:
if seive[i]:
for j in range(i * i, 1_0_0_0_0_0_1, i):
_a = False
i += 1
def _a ( SCREAMING_SNAKE_CASE : int ) -> bool:
"""simple... | 322 |
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_ ( snake_case__ ):
... | 322 | 1 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import... | 350 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowercase : List[str] = logging.get_logger(__name__)
lowercase : Tuple = {
"""google/umt5-small""": """https://huggingface.co/g... | 285 | 0 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def __SCREAMING_SNAKE_CASE ( __UpperCamelCase : str ) -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = ... | 219 | from numpy import exp, pi, sqrt
def __SCREAMING_SNAKE_CASE ( __UpperCamelCase : Any , __UpperCamelCase : float = 0.0 , __UpperCamelCase : float = 1.0 ) -> int:
"""simple docstring"""
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - ... | 219 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ = {"""configuration_plbart""": ["""PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PLBartConf... | 367 |
import qiskit
def lowerCamelCase_ ( lowerCAmelCase: int = 2 )-> qiskit.result.counts.Counts:
_snake_case : Dict = qubits
# Using Aer's simulator
_snake_case : List[str] = qiskit.Aer.get_backend('aer_simulator' )
# Creating a Quantum Circuit acting... | 260 | 0 |
'''simple docstring'''
from timeit import timeit
def lowercase__ ( __UpperCamelCase )-> int:
if number < 0:
raise ValueError("""the value of input must not be negative""" )
UpperCamelCase = 0
while number:
number &= n... | 321 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase = 1000 )-> int:
UpperCamelCase = -1
UpperCamelCase = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
UpperC... | 321 | 1 |
'''simple docstring'''
__snake_case : Dict = 8.3_144_598
def _UpperCAmelCase ( _UpperCamelCase : float, _UpperCamelCase : float ) -> float:
if temperature < 0:
raise Exception('''Temperature cannot be less than 0 K''' )
if mola... | 362 | '''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( _UpperCamelCase : int | str ) -> bool:
A_ = str(_UpperCamelCase )
return n == n[::-1]
def _UpperCAmelCase ( _UpperCamelCase : int = 1_00_00_00 ... | 18 | 0 |
__UpperCamelCase : str = {
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': 'da... | 182 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__UpperCamelCase : Tuple = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
... | 182 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'''s-JoL/Open-Llama-V1''': '''https://huggingface.co/s-JoL/Open-Llama-V1/blob/mai... | 360 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
Wa... | 340 | 0 |
import math
from collections.abc import Callable
def A__ ( __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
SCREAMING_SNAKE_CASE_ = xa
SCREAMING_SNAKE_CASE_ = xa
while True:
if x_n == x_na or function(UpperCAmelCase_ ) == function(UpperCAmelCase_ ):
raise Z... | 299 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classe... | 185 | 0 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
A_ = field(
... | 368 |
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 SCREAMING_SNAKE_CASE ( unittest.TestCase )... | 75 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
class __a ( lowercase_ ):
__lowercase : List[Any] = 'encoder-decoder'
__lowercase : Optional[Any] ... | 196 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __A ( lowerCamelCase_ ):
"... | 323 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__lowerCamelCase )
class lowercase__ ( __lowerCamelCase ):
'''simple docstring'''
... | 247 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from t... | 247 | 1 |
'''simple docstring'''
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def __A ( lowerCamelCase... | 323 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A = {"configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig", "IBertOnnxConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNot... | 10 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class A :
__magic_name__ = field(
me... | 311 |
'''simple docstring'''
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
lowercase : Any = 'src/transform... | 311 | 1 |
from maths.prime_check import is_prime
def UpperCamelCase_( lowerCamelCase_ ) -> Dict:
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
_lowercase : Any = F'''Input value of [number={number}] must be an integer'''
raise TypeError(UpperCAmelCase_... | 21 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availabl... | 151 | 0 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...te... | 362 | import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
__UpperCamelCase : Dict ... | 258 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( __snake_case : list[float] ):
lowercase_ : str = 0.00
lowercase_ : str = 0
for resistor in resistors:
if resistor <= 0:
lowercase_ : str = ... | 33 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVe... | 325 | 0 |
from __future__ import annotations
UpperCAmelCase__ : List[Any] = 'Muhammad Umer Farooq'
UpperCAmelCase__ : str = 'MIT'
UpperCAmelCase__ : Optional[int] = '1.0.0'
UpperCAmelCase__ : Any = 'Muhammad Umer Farooq'
UpperCAmelCase__ : Optional[An... | 301 |
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_tokeni... | 301 | 1 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
_SCREAMING_SNAKE_CASE = ["""small""", """medium""", """large"""]
_SCREAMING_SNAKE_CASE = """lm_head.decoder.weight"""
_SCREAMING_SNAKE_CASE = """lm_head.weight"""
def... | 180 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : str = logging.get_logger(__name__)
__a : Optional[int] = {
"""google/vivit-b-16x2-kinetics400""": (
"""https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
),
... | 210 | 0 |
"""simple docstring"""
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __a ( unittest.TestCase ):
def snake_case_ ( self ):
debug_launcher(test_script.main ... | 369 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
fro... | 80 | 0 |
"""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 im... | 17 |
'''simple docstring'''
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokeniz... | 104 | 0 |
"""simple docstring"""
import math
import tensorflow as tf
from packaging import version
def __lowerCamelCase ( a_ : Optional[Any] ) -> List[str]:
__SCREAMING_SNAKE_CASE :str = tf.convert_to_tensor(lowerCamelCase__ )
__SCREAMING... | 350 |
"""simple docstring"""
from torch import nn
class _SCREAMING_SNAKE_CASE( nn.Module ):
def __init__( self ,SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ) -> List[str]:
"""simple docstring"""
super()... | 239 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 100 ) -> int:
_a : Optional[int] =n * (n + 1) * (2 * n + 1) / 6
_a : int =(n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__m... | 276 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class A__ ( UpperCAmelCase__ ):
__UpperCamelCase : str
__UpperCamelCase : int
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> li... | 276 | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_SCREAMING_SNAKE_CASE : str = logging.get_logger(__name... | 92 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def UpperCamelCase_( snake_case : np.ndarray ):
'''simple docstring'''
snake_case_ , snake_case_ = np.shape(snake_case )
if rows != columns:
snake_case_ ... | 92 | 1 |
'''simple docstring'''
# Algorithm for the pigeonhole sorting
def UpperCamelCase_ ( snake_case_ : Any ) -> Dict:
'''simple docstring'''
__lowerCAmelCase = min(snake_case_ ) # min() finds the minimum value
__lowerCAmelC... | 229 | '''simple docstring'''
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 ... | 229 | 1 |
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 torc... | 279 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase_ = get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.mod... | 279 | 1 |
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,
EfficientFormerForImageClassificationWithTeacher,
EfficientFormerImag... | 325 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
lowerCamelCase__ = logging.get_logger(__n... | 234 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case ) -> str:
"""simple docstring"""
_UpperCamelCase = int(__snake_case )
if decimal in (0, 1): # Exit cases for the recursion
return str(__snake_case )
_UpperCame... | 100 |
"""simple docstring"""
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock... | 100 | 1 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
UpperCAmelCase_ : str = HfArgumentParser(InitializationArguments)
UpperCAmelCase_ : str = parser.parse_args()
# Lo... | 32 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 53 | 0 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
A : Dict = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
... | 363 |
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 __versi... | 33 | 0 |
import math
class lowercase__ :
def __A ( self : List[str] , UpperCamelCase__ : list[list[float]] , UpperCamelCase__ : list[int] ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Optional[int] ... | 182 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase : Any = {'configuration_mbar... | 182 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...... | 264 |
'''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
_lowercase : Optional[Any] = logging.get_logger(__nam... | 264 | 1 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowerCamelCase_ ... | 43 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[Any] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAv... | 48 | 0 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCAmelCase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
def ... | 184 |
'''simple docstring'''
import os
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
lowerCAmelCase__ : List[str] = len(grid[0] )
lowerCAmelCase__ : int = len(UpperCamelCase )
lowerCAmelCase__ : Optional[int] ... | 184 | 1 |
'''simple docstring'''
import heapq
import sys
import numpy as np
lowerCamelCase : List[Any] = tuple[int, int]
class __lowerCAmelCase :
'''simple docstring'''
def __init__(self : Dict ):
'''simple docstring'''
lowercase__ ... | 2 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def ... | 254 | 0 |
from collections.abc import Sequence
from queue import Queue
class SCREAMING_SNAKE_CASE__ :
"""simple docstring"""
def __init__( self : Optional[int] , __A : Dict , __A : Tuple , __A : int , __A : Optional[Any]=None , ... | 286 |
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def SCREAMING_SNAKE_CASE ( snake_case_ : str ):
snake_case__ : Optional[Any] = [
"encoder.version",
"decoder.version",
"model.encoder.ve... | 286 | 1 |
'''simple docstring'''
def UpperCamelCase__ ( lowerCAmelCase = 1_00_00_00 ):
"""simple docstring"""
_lowerCAmelCase = set(range(3 , _lowercase , 2 ) )
primes.add(2 )
for p in range(3 , _lowercase , 2... | 70 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : list ) ->int:
'''simple docstring'''
if not grid or not grid[0]:
raise TypeError("The grid does not contain the appropriate information" )
for cell_n in range(1 , len(g... | 105 | 0 |
'''simple docstring'''
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _lowercase ( __A ,__A=None ):
'''simple docstring'''
__UpperCamelCase = ... | 371 |
'''simple docstring'''
def _lowercase ( __A ):
'''simple docstring'''
if number < 0:
raise ValueError("""number must not be negative""" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 243 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, ... | 33 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWit... | 33 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A : Dict = {'configuration_mbart': ['MBART_PRETRAINED_CONFIG_AR... | 265 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion import Stabl... | 265 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/config.json',
# See all XGLM models at https://hugg... | 308 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase_ = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mask2FormerConfig',
],
}
tr... | 308 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ = {'''processing_layoutxlm''': ['''... | 132 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
_snake_case : Optional[Any] = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def UpperCAmelCase__ (snake_case__ : int = 50_00 ):
"""simple docstring"""
... | 132 | 1 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoModelWithLMHead,
... | 49 |
import argparse
from collections import defaultdict
import yaml
A_ : List[str] = 'docs/source/en/_toctree.yml'
def UpperCamelCase (lowercase_: Optional[int] ) -> List[str]:
A__ : Dict = defaultdict(lowercase_ )
A__ : Optional[int] = []... | 192 | 0 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion import Stable... | 102 |
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
@maybe_allow_in_graph
class ... | 102 | 1 |
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compute_metrics... | 59 |
"""simple docstring"""
def a__ ( lowerCAmelCase , lowerCAmelCase ) -> bool:
UpperCAmelCase__ : Any = len(lowerCAmelCase )
UpperCAmelCase__ : List[Any] = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum o... | 171 | 0 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention... | 359 |
import requests
__A = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def lowerCamelCase_ ( UpperCamelCase__ : str ) -> None:
"""simple docstring"""
__lowerCamelCase = requests.get(_NEWS_API + bbc_news_api_key ).jso... | 348 | 0 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def _SCREAMING_SNAKE_CASE ( _lowercase : List[Any] ) ->Dict:
'''simple docstring'''
a ... | 105 |
"""simple docstring"""
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffu... | 148 | 0 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase_ : ... | 170 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowerCAmelCase_ : Dict = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add... | 170 | 1 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
snake_case_ = ['''image_processor''', '''tokenizer''']
snake_case... | 90 |
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Any:
'''simple docstring'''
__lowerCamelCase = 0
__lowerCamelCase = 0
__lowerCamelCase = {}
def lowercase_... | 90 | 1 |
'''simple docstring'''
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def __a ( _UpperCam... | 142 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __a ( _UpperCamelCase: Tuple , _UpperCamelCase: Optional[int] , _UpperCamelCase: Optional[int]=None , **_UpperCamelCase: Any ) -> Optional[Any]:
"""simple docstring"""... | 142 | 1 |
"""simple docstring"""
def __A (_SCREAMING_SNAKE_CASE = 10 , _SCREAMING_SNAKE_CASE = 22 ) ->int:
"""simple docstring"""
lowerCAmelCase__ :Any = range(1 , _SCREAMING_SNAKE_CASE )
lowerCAmelCase__ :Optional[Any] = range(1 , _SCREAMIN... | 293 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_ARCHIVE_... | 293 | 1 |
"""simple docstring"""
import numpy as np
def lowercase__ ( snake_case_ :Union[str, Any] , snake_case_ :Optional[Any] , snake_case_ :Tuple , snake_case_ :Union[str, Any] , snake_case_ :str ):
__UpperCAmelCase = int(np.ceil((x_end - xa) / h ) )
__Up... | 86 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_fla... | 86 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import... | 80 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__lowerCAmelCase : Union[str, Any] =0... | 197 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase (SCREAMING_SNAKE_CASE_ : list , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ) -> list:
SCREAMING_SNAKE_CASE ... | 38 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e impo... | 38 | 1 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
A__ : List[str] =pd.read_csv('''sample_d... | 70 |
import numpy as np
def __magic_name__ ( A : np.array ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def __magic_name__ ( A : np.array ):
'''simple docstring'''
return vector * sigmoid(1.7_02 * vector )
if __name__ == "__main... | 107 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logg... | 356 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, Dist... | 97 | 0 |
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