code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from math import sqrt
def lowercase ( a__ : int = 1000000 ) -> int:
_UpperCamelCase = 0
_UpperCamelCase = 0
_UpperCamelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
f... | 362 | """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_ ( _lowercase):
... | 54 | 0 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _lowercase):
def __init__( self : List[str] , *__UpperCamelCase : Union[str, Any]... | 363 | """simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_ava... | 54 | 0 |
"""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
UpperCAmelCase = """src/transformers"""
UpperCAmelCase ... | 364 | """simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
UpperCAmelCase = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""":... | 54 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""facebook/xlm-roberta-xl""": """https:... | 365 | """simple docstring"""
import numpy as np
def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict:
_UpperCamelCase = int(np.ceil((x_end - xa) / h ) )
_UpperCamelCa... | 54 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def lowercase ( a__ : str = "AAPL" ) -> str:
_UpperCamelCase = F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
_UpperCamelCase = BeautifulSoup(requests.get(a__ ... | 366 | """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 jax.numpy... | 54 | 0 |
"""simple docstring"""
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def lowercase ( a__ : np.ndarray , a__ : np.ndarray , a__ : np.ndarray , a__ : int , a__ : int ) -> np.ndarray:
_UpperCamelCase ... | 367 | """simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProce... | 54 | 0 |
"""simple docstring"""
def lowercase ( a__ : list[list[int]] , a__ : int , a__ : int , a__ : list[int] ) -> bool:
# 1. Validate that path exists between current and next vertices
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
... | 368 | """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 ... | 54 | 0 |
"""simple docstring"""
from functools import lru_cache
@lru_cache
def lowercase ( a__ : int ) -> int:
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__... | 369 | """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 transformers.utils impor... | 54 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArgumen... | 370 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:... | 54 | 0 |
"""simple docstring"""
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Li... | 371 | """simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=None, type=str, required=True... | 54 | 0 |
"""simple docstring"""
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
UpperCAmelCase : Optional[int] = HfArgumentParser(InitializationArguments)
UpperCAmelCase : int = parser.parse_args()
#... | 350 | """simple docstring"""
from __future__ import annotations
UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2
def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]:
_UpperCamelCase = abs(chargea ... | 54 | 0 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class UpperCAmelCase_ ( _lowercase):
def _UpperCamelCase ( self : Optional[Any] , __UpperCamelCase : str ) -> List[str]:
... | 351 | """simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCAmelCase_ ( _lowercase):
def __init__( self : Any , __UpperCamelCase : Optional... | 54 | 0 |
"""simple docstring"""
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowercase ( a__ : List[Any] , a__ : bool = True , a__ : float = math.inf , a__ : float = -math.inf , a__ : float = math.inf , a__ : float = -... | 352 | """simple docstring"""
import qiskit
def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts:
_UpperCamelCase = qubits
# Using Aer's simulator
_UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quan... | 54 | 0 |
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
UpperCAmelCase = [
# (stable-diffusion, HF Diffusers)
("""time_embed.0.weight""", """time_embedding.linear_1.weight"""),
("... | 353 | """simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
UpperCAmelCase = """\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang, Alex... | 54 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
UpperCAmelCase =... | 354 | """simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0,... | 54 | 0 |
"""simple docstring"""
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
UpperCAmelCase = get_tests_dir("""fixtures/test_... | 355 | """simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 54 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( a__ : list[int | str] ) -> None:
create_state_space_tree(a__ , [] , 0 , [0 for i in range(len(a__ ) )] )
def lowercase ( a__ : list[int | str] , a__ : l... | 356 | """simple docstring"""
from __future__ import annotations
import math
def lowercase ( a__ : int ) -> list[int]:
if num <= 0:
_UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(a__ )
_Upp... | 54 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=_lowercase):
snake_case__ = ['''keras_nlp''']
def __init__( self : Any , *__UpperCamelCase : Union[str, Any] , **__UpperCamelCase : int )... | 357 | """simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionSch... | 54 | 0 |
"""simple docstring"""
def lowercase ( a__ : Union[str, Any] ) -> List[Any]:
_UpperCamelCase = [0] * len(a__ )
_UpperCamelCase = []
_UpperCamelCase = []
_UpperCamelCase = 0
for values in graph.values():
... | 358 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}
... | 54 | 0 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from tran... | 359 | """simple docstring"""
def lowercase ( a__ : Tuple , a__ : str ) -> Tuple:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]:
return ... | 54 | 0 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
UpperCAmelCase = """\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved evaluati... | 360 | """simple docstring"""
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,
nest... | 54 | 0 |
"""simple docstring"""
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from... | 361 | """simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils impor... | 54 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 362 | """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_ ( _lowercase):
... | 54 | 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 torch
if... | 363 | """simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_ava... | 54 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( a__ : int = 4 ) -> list[list[int]]:
_UpperCamelCase = abs(a__ ) or 4
return [[1 + x + y * row_size for x in range(a__ )] for y in range(a__ )]
def lowercase ( ... | 364 | """simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
UpperCAmelCase = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""":... | 54 | 0 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
snake_case_ = HUGGINGFACE_HUB_CACHE
snake_case_ = """config.json"""
snake_case_ = """diffusion_pytorch_model.bin"""
snake_case_ = """diffusion_flax_model.msgpack"""
snake_case_ ... | 365 | """simple docstring"""
import numpy as np
def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict:
_UpperCamelCase = int(np.ceil((x_end - xa) / h ) )
_UpperCamelCa... | 54 | 0 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def lowercase ( ) -> List[Any]:
_UpperCamelCase = HfArgumentParser(a__ )
_UpperCamelCase = parser.parse_args_into_dataclasses()[0]
... | 366 | """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 jax.numpy... | 54 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
UpperCAmelCase = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
"""https://huggin... | 367 | """simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProce... | 54 | 0 |
"""simple docstring"""
import math
def lowercase ( a__ : int ) -> bool:
_UpperCamelCase = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(a__ )
def lowercase ( a__ : float = 1 / 12345 ... | 368 | """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 ... | 54 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
f... | 369 | """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 transformers.utils impor... | 54 | 0 |
"""simple docstring"""
def lowercase ( a__ : Union[str, Any] , a__ : Optional[int] ) -> int:
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
_UpperCamelCase = (boundary[1] - boundary[0]) / steps
_UpperCamelCase = ... | 370 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:... | 54 | 0 |
"""simple docstring"""
import warnings
warnings.warn(
"""memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: """
"""`from accelerate import find_executable_batch_size` to avoid this warning.""",
FutureWarning,
)
| 371 | """simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=None, type=str, required=True... | 54 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class UpperCAmelCase_ ( unittest.TestCase):
... | 350 | """simple docstring"""
from __future__ import annotations
UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2
def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]:
_UpperCamelCase = abs(chargea ... | 54 | 0 |
"""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():
from .tokeniza... | 351 | """simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCAmelCase_ ( _lowercase):
def __init__( self : Any , __UpperCamelCase : Optional... | 54 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...te... | 352 | """simple docstring"""
import qiskit
def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts:
_UpperCamelCase = qubits
# Using Aer's simulator
_UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quan... | 54 | 0 |
UpperCAmelCase = {
"""joule""": 1.0,
"""kilojoule""": 1_000,
"""megajoule""": 1_000_000,
"""gigajoule""": 1_000_000_000,
"""wattsecond""": 1.0,
"""watthour""": 3_600,
"""kilowatthour""": 3_600_000,
"""newtonmeter""": 1.0,
"""calorie_nutr""": 4_186.8,
"""kilocalorie_nutr"""... | 353 | """simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
UpperCAmelCase = """\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang, Alex... | 54 | 0 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
UpperCAme... | 354 | """simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0,... | 54 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}
... | 355 | """simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 54 | 0 |
"""simple docstring"""
from math import sqrt
def lowercase ( a__ : int ) -> bool:
assert isinstance(a__ , a__ ) and (
number >= 0
), "'number' must been an int and positive"
_UpperCamelCase = True
# 0 and 1 are none primes.
if... | 356 | """simple docstring"""
from __future__ import annotations
import math
def lowercase ( a__ : int ) -> list[int]:
if num <= 0:
_UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(a__ )
_Upp... | 54 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_lowercase)
class UpperCAmelCase_ ( _lowercase):
snake_case__ = field(default='''language-modeling''' ... | 357 | """simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionSch... | 54 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
UpperCAmelCase = False
class UpperCAmelCase_ ( unittest.TestCase)... | 358 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}
... | 54 | 0 |
"""simple docstring"""
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 ... | 359 | """simple docstring"""
def lowercase ( a__ : Tuple , a__ : str ) -> Tuple:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]:
return ... | 54 | 0 |
"""simple docstring"""
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class UpperCAmelCase_ ( _low... | 360 | """simple docstring"""
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,
nest... | 54 | 0 |
"""simple docstring"""
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
fr... | 361 | """simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils impor... | 54 | 0 |
"""simple docstring"""
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available,... | 362 | """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_ ( _lowercase):
... | 54 | 0 |
from argparse import ArgumentParser
from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parse... | 363 | """simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_ava... | 54 | 0 |
"""simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0,... | 364 | """simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
UpperCAmelCase = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""":... | 54 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
... | 365 | """simple docstring"""
import numpy as np
def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict:
_UpperCamelCase = int(np.ceil((x_end - xa) / h ) )
_UpperCamelCa... | 54 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProce... | 366 | """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 jax.numpy... | 54 | 0 |
"""simple docstring"""
def lowercase ( a__ : int = 1000000 ) -> int:
_UpperCamelCase = set(range(3 , a__ , 2 ) )
primes.add(2 )
for p in range(3 , a__ , 2 ):
if p not in primes:
continue
primes.dif... | 367 | """simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProce... | 54 | 0 |
"""simple docstring"""
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, ... | 368 | """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 ... | 54 | 0 |
"""simple docstring"""
import numpy as np
from PIL import Image
def lowercase ( a__ : np.ndarray , a__ : int , a__ : int ) -> np.ndarray:
_UpperCamelCase = np.array(a__ )
if arr.shape[0] != arr.shape[1]:
raise ValueError('''The i... | 369 | """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 transformers.utils impor... | 54 | 0 |
"""simple docstring"""
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class UpperCAmelCase_ ( tf.keras.optimizers.schedules.LearningRateSc... | 370 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:... | 54 | 0 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowercase ( ) -> str:
_UpperCamelCase = ArgumentParser(
description=(
... | 371 | """simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=None, type=str, required=True... | 54 | 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 lowercase ( a__ : List[str] ) -> List[str]:
_UpperCamelCase = ... | 350 | """simple docstring"""
from __future__ import annotations
UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2
def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]:
_UpperCamelCase = abs(chargea ... | 54 | 0 |
"""simple docstring"""
from __future__ import annotations
from cmath import sqrt
def lowercase ( a__ : int , a__ : int , a__ : int ) -> tuple[complex, complex]:
if a == 0:
raise ValueError('''Coefficient \'a\' must not be zero.''' )
_UpperC... | 351 | """simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCAmelCase_ ( _lowercase):
def __init__( self : Any , __UpperCamelCase : Optional... | 54 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDepende... | 352 | """simple docstring"""
import qiskit
def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts:
_UpperCamelCase = qubits
# Using Aer's simulator
_UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quan... | 54 | 0 |
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
UpperCAmelCase = (
"""This metric will be removed from the library soon, metrics should be handl... | 353 | """simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
UpperCAmelCase = """\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang, Alex... | 54 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase = {
"""configuration_convbert""": ["""CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", "... | 354 | """simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0,... | 54 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
"""microsoft/ma... | 355 | """simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 54 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCAmelCase = {"""tokenization_bertweet""": ["""BertweetTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_bertweet import BertweetTokenizer
else:
import sys
UpperCAmelCase = _LazyModule(__name__, gl... | 356 | """simple docstring"""
from __future__ import annotations
import math
def lowercase ( a__ : int ) -> list[int]:
if num <= 0:
_UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(a__ )
_Upp... | 54 | 0 |
"""simple docstring"""
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa: F401
deprecate(
"""stable diffusion controlnet""",
"""0.22.0""",
"""Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diff... | 357 | """simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionSch... | 54 | 0 |
"""simple docstring"""
def lowercase ( a__ : int , a__ : int ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def lowercase ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
assert or... | 358 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}
... | 54 | 0 |
"""simple docstring"""
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = """T5Config"""
... | 359 | """simple docstring"""
def lowercase ( a__ : Tuple , a__ : str ) -> Tuple:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]:
return ... | 54 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"""
... | 360 | """simple docstring"""
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,
nest... | 54 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""huggingface/time-series-transformer-tourism-monthly""": (
"""https://hu... | 361 | """simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils impor... | 54 | 0 |
"""simple docstring"""
import qiskit
def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts:
_UpperCamelCase = qubits
# Using Aer's simulator
_UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quan... | 362 | """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_ ( _lowercase):
... | 54 | 0 |
def lowercase ( a__ : int = 1000 ) -> int:
_UpperCamelCase = 2**power
_UpperCamelCase = 0
while n:
_UpperCamelCase , _UpperCamelCase = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution... | 363 | """simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_ava... | 54 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase = {"""configuration_van""": ["""VAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VanConfig"""]}
try:
if not is_torch_available():
r... | 364 | """simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
UpperCAmelCase = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""":... | 54 | 0 |
"""simple docstring"""
from itertools import permutations
def lowercase ( a__ : tuple ) -> bool:
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
_UpperCamelCa... | 365 | """simple docstring"""
import numpy as np
def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict:
_UpperCamelCase = int(np.ceil((x_end - xa) / h ) )
_UpperCamelCa... | 54 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTest... | 366 | """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 jax.numpy... | 54 | 0 |
"""simple docstring"""
import sys
def lowercase ( a__ : Optional[Any] ) -> Any:
_UpperCamelCase = len(a__ )
_UpperCamelCase = [[0 for x in range(a__ )] for x in range(a__ )]
_UpperCamelCase = [[0 for x in range(a__ ... | 367 | """simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProce... | 54 | 0 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def lowercase ( a__ : List[str] ) -> Any:
_UpperCamelCase = {}
... | 368 | """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 ... | 54 | 0 |
"""simple docstring"""
UpperCAmelCase = frozenset(
[
"""prompt""",
"""height""",
"""width""",
"""guidance_scale""",
"""negative_prompt""",
"""prompt_embeds""",
"""negative_prompt_embeds""",
"""cross_attention_kwargs""",
]
)
UpperCAmelCase ... | 369 | """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 transformers.utils impor... | 54 | 0 |
"""simple docstring"""
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_util... | 370 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:... | 54 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
UpperCAmelCase : List[str] = logging.get_log... | 371 | """simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=None, type=str, required=True... | 54 | 0 |
"""simple docstring"""
import re
from ..utils import cached_file
# docstyle-ignore
UpperCAmelCase : List[Any] = """
Human: <<task>>
Assistant: """
UpperCAmelCase : Optional[Any] = """huggingface-tools/default-prompts"""
UpperCAmelCase : str = {"""chat""": """chat_prompt_template.txt... | 350 | """simple docstring"""
from __future__ import annotations
UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2
def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]:
_UpperCamelCase = abs(chargea ... | 54 | 0 |
"""simple docstring"""
def lowercase ( a__ : int ) -> int:
if not isinstance(a__ , a__ ):
raise TypeError('''only integers accepted as input''' )
else:
_UpperCamelCase = str(abs(a__ ) )
_UpperCamelCase = ... | 351 | """simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCAmelCase_ ( _lowercase):
def __init__( self : Any , __UpperCamelCase : Optional... | 54 | 0 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params im... | 352 | """simple docstring"""
import qiskit
def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts:
_UpperCamelCase = qubits
# Using Aer's simulator
_UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quan... | 54 | 0 |
import torch
from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool
class UpperCAmelCase_ ( _lowercase):
snake_case__ = '''facebook/bart-large-mnli'''
snake_case__ = (
'''This is a tool that classifies an English ... | 353 | """simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
UpperCAmelCase = """\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang, Alex... | 54 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.ja... | 354 | """simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0,... | 54 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DD... | 355 | """simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 54 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
"""tokeniz... | 356 | """simple docstring"""
from __future__ import annotations
import math
def lowercase ( a__ : int ) -> list[int]:
if num <= 0:
_UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(a__ )
_Upp... | 54 | 0 |
"""simple docstring"""
import torch
def lowercase ( ) -> List[Any]:
if torch.cuda.is_available():
_UpperCamelCase = torch.cuda.device_count()
else:
_UpperCamelCase = 0
print(F'''Successfully ran on {num_gpus} GPUs''' )
if __... | 357 | """simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionSch... | 54 | 0 |
"""simple docstring"""
from ... import PretrainedConfig
UpperCAmelCase = {
"""sijunhe/nezha-cn-base""": """https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json""",
}
class UpperCAmelCase_ ( _lowercase):
snake_case__ = NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
... | 358 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}
... | 54 | 0 |
"""simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if... | 359 | """simple docstring"""
def lowercase ( a__ : Tuple , a__ : str ) -> Tuple:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]:
return ... | 54 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
... | 360 | """simple docstring"""
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,
nest... | 54 | 0 |
"""simple docstring"""
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowercase ( a__ : str = "" ) -> dict[str, float]:
_UpperCamelCase = url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
_Uppe... | 361 | """simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils impor... | 54 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _lowercase):
def __init__( self : Optional[Any] , *__UpperCamelCase : ... | 362 | """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_ ( _lowercase):
... | 54 | 0 |
def lowercase ( a__ : int , a__ : int ) -> int:
while b:
_UpperCamelCase , _UpperCamelCase = b, a % b
return a
def lowercase ( a__ : int , a__ : int ) -> int:
return a if b == 0 else eucl... | 363 | """simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_ava... | 54 | 0 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class UpperCAmelCase_ ( logging.LoggerAdapter):
@staticmethod
def _UpperCamelCase ( __UpperCamelCase : Tuple ) -> Dict:
_UpperCamelCase = PartialState()
... | 364 | """simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
UpperCAmelCase = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""":... | 54 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class UpperCAmelCase_ ( ... | 365 | """simple docstring"""
import numpy as np
def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict:
_UpperCamelCase = int(np.ceil((x_end - xa) / h ) )
_UpperCamelCa... | 54 | 0 |
"""simple docstring"""
import numpy as np
class UpperCAmelCase_ :
def __init__( self : List[str] ) -> Optional[int]:
_UpperCamelCase = (0, 0)
_UpperCamelCase = None
_UpperCamelCase = 0
_UpperCamelCase... | 366 | """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 jax.numpy... | 54 | 0 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowercase ( a__ : int = 8 ) -> str:
_UpperCamelCase = ascii_letters + digits + punctuation
return "".j... | 367 | """simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProce... | 54 | 0 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_ava... | 368 | """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 ... | 54 | 0 |
"""simple docstring"""
def lowercase ( a__ : int ) -> int:
assert (
isinstance(a__ , a__ ) and number_of_steps > 0
), F'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
if number_of_steps == 1:
return 1
_UpperCa... | 369 | """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 transformers.utils impor... | 54 | 0 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/config.json""",
"""xlnet-lar... | 370 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:... | 54 | 0 |
"""simple docstring"""
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 371 | """simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=None, type=str, required=True... | 54 | 0 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def a_ ( lowerCamelCase : Optional[int] ):
# enco... | 55 |
'''simple docstring'''
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
... | 55 | 1 |
'''simple docstring'''
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
__snake_case =logging.getLogger(__name__)
if... | 55 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester... | 55 | 1 |
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