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"""
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
class __lowerCamelCase ( __lowercase ):
def __init__(self , *lowerCamelCase... | 317 |
"""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
SCREAMING_SNAKE_CASE : List[str] = False
class __lowerCamelCase... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : list[int] , snake_case_ : list[int] , snake_case_ : int ) -> bool:
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in ... | 317 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_util... | 317 | 1 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 317 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict:
"""simple docstring"""
return getitem, k
def __UpperCAm... | 317 | 1 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import Tensor... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(snake_case_ : int ) -> int:
if target < 0:
r... | 317 | 1 |
"""simple docstring"""
from math import asin, atan, cos, radians, sin, sqrt, tan
SCREAMING_SNAKE_CASE : str = 6_3_7_8_1_3_7.0
SCREAMING_SNAKE_CASE : Optional[Any] = 6_3_5_6_7_5_2.3_1_4_2_4_5
SCREAMING_SNAKE_CASE : Any = 6_3_7_8_1_3_7
def __UpperCAmelCase ... | 317 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
SCREAMING_SNAKE_CASE : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
SCREAMING_SNAKE_CASE : list[int] ... | 317 | 1 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int:
"""simple docstring"""
_lowerCAmelCase = limit + 1
_lowerCAmelCase = [0] * limit
for first_term in range(1 , snake_case_ ):
for n in range(sn... | 317 | 1 |
"""simple docstring"""
from functools import reduce
SCREAMING_SNAKE_CASE : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''1254069874715852386305... | 317 |
"""simple docstring"""
from functools import reduce
SCREAMING_SNAKE_CASE : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''1254069874715852386305... | 317 | 1 |
"""simple docstring"""
from __future__ import annotations
def __UpperCAmelCase ( snake_case_ : list[list[int]] ) -> int:
"""simple docstring"""
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first colum... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int:
"""simple docstring"""
try:
_lowerCAmelCase = int(snake_case_ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable ... | 317 | 1 |
"""simple docstring"""
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def __UpperCAmelCase ( snake_case_ : Dict ) ... | 317 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelFor... | 317 | 1 |
"""simple docstring"""
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 acce... | 317 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''... | 317 | 1 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
# TODO Update this
SCREAMING_SNAKE_CASE : Tupl... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
SCREAMING_SNAKE_CASE : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
SCREAMING_SNAKE_CASE : list[int] ... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : list ) -> list:
"""simple docstring"""
for i in range(len(snake_case_ ) - 1 , 0 , -1 ):
_lowerCAmelCase = False
for j in range(snake_case_ , 0 , -1 ):
... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : str , snake_case_ : str ) -> list:
"""simple docstring"""
_lowerCAmelCase = len(snake_case_ )
_lowerCAmelCase = []
for i in range(len(snake_case_ ) - pat_len + ... | 317 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_ava... | 317 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
SCREAMING_SNAKE_CASE : List[str] = False
class __lowerCamelCase... | 317 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Any = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c... | 317 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Any = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class ... | 317 |
"""simple docstring"""
import math
def __UpperCAmelCase ( snake_case_ : int ) -> list[int]:
"""simple docstring"""
_lowerCAmelCase = []
_lowerCAmelCase = 2
_lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ... | 317 | 1 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
SCREAMING_SNAKE_CASE : int = pytest.mark.integration
@pytest.m... | 317 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width
SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo... | 317 | 1 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerCamelCase ( __lowercase , __lowercase ):
@register_to_config
def __init__(self , *,
lowerCamelC... | 317 |
"""simple docstring"""
# 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]' w... | 317 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_v... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
class __lowerCamelCase :
def __init__(self ):
'''simple docstring'''
_lowerCAmelCase = {} # Mapping from char to TrieNode
_lowerCAmelCase = False
def A__ (self , lowerCamelCase ):
'''si... | 317 |
"""simple docstring"""
from math import isqrt
def __UpperCAmelCase ( snake_case_ : int ) -> list[int]:
"""simple docstring"""
_lowerCAmelCase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
... | 317 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def __UpperCAmelCase ( snake_case_ : Optional[... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
SCREAMING_SNAKE_CASE : Optional[Any] = datasets.logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Union[str, Any] = '''\
@inproceedings{bleu... | 317 |
"""simple docstring"""
from __future__ import annotations
import queue
class __lowerCamelCase :
def __init__(self , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase = data
_lowerCAmelCase = None
_lowerCAmelCase = ... | 317 | 1 |
"""simple docstring"""
import tensorflow as tf
from ...tf_utils import shape_list
class __lowerCamelCase ( tf.keras.layers.Layer ):
def __init__(self , lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase=1 , lowerCamelCase=False ,... | 317 |
"""simple docstring"""
from __future__ import annotations
class __lowerCamelCase :
def __init__(self , lowerCamelCase , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase , _lowerCAmelCase = text, pattern
_lowerCAmelCase , _low... | 317 | 1 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modu... | 317 |
"""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
SCREAMING_SNAKE_CASE : List[str] = False
class __lowerCamelCase... | 317 | 1 |
"""simple docstring"""
import os
import sys
SCREAMING_SNAKE_CASE : Dict = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering... | 317 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_util... | 317 | 1 |
"""simple docstring"""
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_t... | 317 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict:
"""simple docstring"""
return getitem, k
def __UpperCAm... | 317 | 1 |
"""simple docstring"""
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_model... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(snake_case_ : int ) -> int:
if target < 0:
r... | 317 | 1 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : List[Any] = {'''vocab_file''': ''... | 317 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
SCREAMING_SNAKE_CASE : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
SCREAMING_SNAKE_CASE : list[int] ... | 317 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int:
"""simple docstring"""
_lowerCAmelCase = limit + 1
_lowerCAmelCase = [0] * limit
for first_term in range(1 , snake_case_ ):
for n in range(sn... | 317 | 1 |
"""simple docstring"""
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_... | 317 |
"""simple docstring"""
from functools import reduce
SCREAMING_SNAKE_CASE : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''1254069874715852386305... | 317 | 1 |
"""simple docstring"""
import requests
SCREAMING_SNAKE_CASE : int = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def __UpperCAmelCase ( snake_case_ : str ) -> None:
"""simple docstring"""
_lowerCAmelCase = re... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int:
"""simple docstring"""
try:
_lowerCAmelCase = int(snake_case_ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable ... | 317 | 1 |
"""simple docstring"""
import os
SCREAMING_SNAKE_CASE : List[Any] = {'''I''': 1, '''V''': 5, '''X''': 1_0, '''L''': 5_0, '''C''': 1_0_0, '''D''': 5_0_0, '''M''': 1_0_0_0}
def __UpperCAmelCase ( snake_case_ : str ) -> int:
"""simple docstring"""
_lowe... | 317 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelFor... | 317 | 1 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.... | 317 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''... | 317 | 1 |
"""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 M... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : list ) -> list:
"""simple docstring"""
for i in range(len(snake_case_ ) - 1 , 0 , -1 ):
_lowerCAmelCase = False
for j in range(snake_case_ , 0 , -1 ):
... | 317 | 1 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should ... | 317 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_ava... | 317 | 1 |
"""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 ... | 317 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Any = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c... | 317 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''... | 317 |
"""simple docstring"""
import math
def __UpperCAmelCase ( snake_case_ : int ) -> list[int]:
"""simple docstring"""
_lowerCAmelCase = []
_lowerCAmelCase = 2
_lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ... | 317 | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __lowerCamelCase ( __lowercase ):
__UpperCamelCase = 'SpeechT5FeatureExtractor'
__UpperCamelCase = 'SpeechT5Tokenizer'
def __init__(self , lowerCamelCase , lowerCamelCas... | 317 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width
SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : str ) -> list:
"""simple docstring"""
_lowerCAmelCase = [0] * len(snake_case_ )
for i in range(1 , len(snake_case_ ) ):
# use last results for better performance - dynamic pro... | 317 |
"""simple docstring"""
# 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]' w... | 317 | 1 |
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[Any] = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
SCREAMING_SNAKE_CASE : List[Any] = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def __UpperCAmelCase ( snake_case_ : dict[int, list[int]] , ... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import B... | 317 |
"""simple docstring"""
from math import isqrt
def __UpperCAmelCase ( snake_case_ : int ) -> list[int]:
"""simple docstring"""
_lowerCAmelCase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int:
"""simple docstring"""
try:
_lowerCAmelCase = int(snake_case_ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable ... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
from math import factorial
SCREAMING_SNAKE_CASE : dict[str, int] = {str(digit): factorial(digit) for digit in range(1_0)}
def __UpperCAmelCase ( snake_case_ : int ) -> int:
"""simple docstring"""
if not isinstance(snake_case_ ... | 317 |
"""simple docstring"""
from __future__ import annotations
import queue
class __lowerCamelCase :
def __init__(self , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase = data
_lowerCAmelCase = None
_lowerCAmelCase = ... | 317 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
class __lowerCamelCase ( __lowercase ):
def __init__(self , *lowerCamelCa... | 317 |
"""simple docstring"""
from __future__ import annotations
class __lowerCamelCase :
def __init__(self , lowerCamelCase , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase , _lowerCAmelCase = text, pattern
_lowerCAmelCase , _low... | 317 | 1 |
"""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,
MusicgenForConditionalGenera... | 317 |
"""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
SCREAMING_SNAKE_CASE : List[str] = False
class __lowerCamelCase... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : Optional[Any] ) -> Any:
"""simple docstring"""
_lowerCAmelCase = []
_lowerCAmelCase = set({"""(""", """[""", """{"""} )
_lowerCAmelCase = set({""")""", """]""", ... | 317 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_util... | 317 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer, TF... | 317 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict:
"""simple docstring"""
return getitem, k
def __UpperCAm... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int ) -> int:
"""simple docstring"""
_lowerCAmelCase = [1]
_lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase = 0, 0, 0
_lowerCAmelCase = ugly_nums[... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(snake_case_ : int ) -> int:
if target < 0:
r... | 317 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE : int = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 317 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
SCREAMING_SNAKE_CASE : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
SCREAMING_SNAKE_CASE : list[int] ... | 317 | 1 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __UpperCAmelCase ( snake_case_ : Optional[int] , snake_case_ : Any=False ) -> str:
"""simple docstring"""
_lower... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int:
"""simple docstring"""
_lowerCAmelCase = limit + 1
_lowerCAmelCase = [0] * limit
for first_term in range(1 , snake_case_ ):
for n in range(sn... | 317 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
class __lowerCamelCase ( __lowercase ):
__UpperCamelCase = 'bert-generation'
def __init__(self , lowerCamelCase=50_358 , lowerCamelCase=1_024 , lowerCamelCase=24 , lowerCamelCase=1... | 317 |
"""simple docstring"""
from functools import reduce
SCREAMING_SNAKE_CASE : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''1254069874715852386305... | 317 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__)
SCRE... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int:
"""simple docstring"""
try:
_lowerCAmelCase = int(snake_case_ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable ... | 317 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE : List[str] = {'''configuration_plbart''': ['''PLBART... | 317 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelFor... | 317 | 1 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
f... | 317 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''... | 317 | 1 |
"""simple docstring"""
from collections.abc import Generator
from math import sin
def __UpperCAmelCase ( snake_case_ : bytes ) -> bytes:
"""simple docstring"""
if len(snake_case_ ) != 32:
raise ValueError("""Input must be of length 32""" )
_lowerCAme... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int:
"""simple docstring"""
try:
_lowerCAmelCase = int(snake_case_ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable ... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : list ) -> list:
"""simple docstring"""
for i in range(len(snake_case_ ) - 1 , 0 , -1 ):
_lowerCAmelCase = False
for j in range(snake_case_ , 0 , -1 ):
... | 317 | 1 |
"""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 ... | 317 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_ava... | 317 | 1 |
"""simple docstring"""
import torch
from torch import nn
class __lowerCamelCase ( nn.Module ):
def __init__(self , lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase , lowerCamelCase=1 , lowerCamelCase=False ):
'''simple docstring'''
... | 317 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Any = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c... | 317 | 1 |
"""simple docstring"""
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerC... | 317 |
"""simple docstring"""
import math
def __UpperCAmelCase ( snake_case_ : int ) -> list[int]:
"""simple docstring"""
_lowerCAmelCase = []
_lowerCAmelCase = 2
_lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ... | 317 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import... | 317 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width
SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo... | 317 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 317 |
"""simple docstring"""
# 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]' w... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int , snake_case_ : int ) -> str:
"""simple docstring"""
return "\n".join(
F"""{number} * {i} = {number * i}""" for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : list ) -> bool:
"""simple docstring"""
if not isinstance(snake_case_ , snake_case_ ):
raise ValueError("""Input series is not valid, valid series - [2, 4, 6]""" )
if len(snake_case_ ) == 0:
... | 317 |
"""simple docstring"""
from math import isqrt
def __UpperCAmelCase ( snake_case_ : int ) -> list[int]:
"""simple docstring"""
_lowerCAmelCase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
... | 317 | 1 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for t... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE : Dict = {
'''configuration_efficientformer''': [
'''EFF... | 317 |
"""simple docstring"""
from __future__ import annotations
import queue
class __lowerCamelCase :
def __init__(self , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase = data
_lowerCAmelCase = None
_lowerCAmelCase = ... | 317 | 1 |
"""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 .... | 317 |
"""simple docstring"""
from __future__ import annotations
class __lowerCamelCase :
def __init__(self , lowerCamelCase , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase , _lowerCAmelCase = text, pattern
_lowerCAmelCase , _low... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 1000 ) -> int:
"""simple docstring"""
_lowerCAmelCase , _lowerCAmelCase = 1, 1
_lowerCAmelCase = []
for i in range(1 , n + 1 ):
_lowerCAmelCase ... | 317 |
"""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
SCREAMING_SNAKE_CASE : List[str] = False
class __lowerCamelCase... | 317 | 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
SCREAMING_SNAKE_CASE : Tuple = logging.getLogger(__name__... | 317 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_util... | 317 | 1 |
"""simple docstring"""
from manim import *
class __lowerCamelCase ( __lowercase ):
def A__ (self ):
'''simple docstring'''
_lowerCAmelCase = Rectangle(height=0.5 , width=0.5 )
_lowerCAmelCase = Rectangle(height=0.46 ... | 317 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict:
"""simple docstring"""
return getitem, k
def __UpperCAm... | 317 | 1 |
"""simple docstring"""
SCREAMING_SNAKE_CASE : Any = 0 # The first color of the flag.
SCREAMING_SNAKE_CASE : Optional[int] = 1 # The second color of the flag.
SCREAMING_SNAKE_CASE : List[str] = 2 # The third color of the flag.
SCREAMING_SNAKE_CASE : Option... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(snake_case_ : int ) -> int:
if target < 0:
r... | 317 | 1 |
"""simple docstring"""
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
... | 317 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
SCREAMING_SNAKE_CASE : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
SCREAMING_SNAKE_CASE : list[int] ... | 317 | 1 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermar... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int:
"""simple docstring"""
_lowerCAmelCase = limit + 1
_lowerCAmelCase = [0] * limit
for first_term in range(1 , snake_case_ ):
for n in range(sn... | 317 | 1 |
"""simple docstring"""
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager imp... | 317 |
"""simple docstring"""
from functools import reduce
SCREAMING_SNAKE_CASE : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''1254069874715852386305... | 317 | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowerCamelCase ( __lowercase ):
__UpperCamelCase = ['image_processor', 'tokenizer']
__UpperCamelCase = 'AutoImageProcessor'
__Upp... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int:
"""simple docstring"""
try:
_lowerCAmelCase = int(snake_case_ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable ... | 317 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization... | 317 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelFor... | 317 | 1 |
"""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 tra... | 317 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''... | 317 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
import random
from typing import Any
def __UpperCAmelCase ( snake_case_ : list ) -> list[Any]:
"""simple docstring"""
for _ in range(len(snake_case_ ) ):
_lowerCAmelCase = random.randint(0 , len(snake_case_ ) -... | 317 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : list ) -> list:
"""simple docstring"""
for i in range(len(snake_case_ ) - 1 , 0 , -1 ):
_lowerCAmelCase = False
for j in range(snake_case_ , 0 , -1 ):
... | 317 | 1 |
"""simple docstring"""
import numpy as np
import qiskit
def __UpperCAmelCase ( snake_case_ : int = 8 , snake_case_ : int | None = None ) -> str:
"""simple docstring"""
_lowerCAmelCase = np.random.default_rng(seed=snake_case_ )
# Roug... | 317 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_ava... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 10**9 ) -> int:
"""simple docstring"""
_lowerCAmelCase = 1
_lowerCAmelCase = 2
_lowerCAmelCase = 0
_lowerCAmelCase = 0
_lowerCAmelCase ... | 317 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Any = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c... | 317 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__... | 317 |
"""simple docstring"""
import math
def __UpperCAmelCase ( snake_case_ : int ) -> list[int]:
"""simple docstring"""
_lowerCAmelCase = []
_lowerCAmelCase = 2
_lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ... | 317 | 1 |
"""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_convbert import ConvBertTokenizer
SCREAMING_SNAKE_CASE : Optional[Any] ... | 317 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width
SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo... | 317 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_acceler... | 317 |
"""simple docstring"""
# 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]' w... | 317 | 1 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
fr... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
class __lowerCamelCase ( __lowercase ):
def __init__(self , *lowerCamelCase , **low... | 317 |
"""simple docstring"""
from math import isqrt
def __UpperCAmelCase ( snake_case_ : int ) -> list[int]:
"""simple docstring"""
_lowerCAmelCase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
... | 317 | 1 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ..... | 317 |
"""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... | 317 | 1 |
"""simple docstring"""
import string
import numpy
def __UpperCAmelCase ( snake_case_ : int , snake_case_ : int ) -> int:
"""simple docstring"""
return b if a == 0 else greatest_common_divisor(b % a , snake_case_ )
class __lowerCamelCase :
... | 317 |
"""simple docstring"""
from __future__ import annotations
import queue
class __lowerCamelCase :
def __init__(self , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase = data
_lowerCAmelCase = None
_lowerCAmelCase = ... | 317 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 317 |
"""simple docstring"""
from __future__ import annotations
class __lowerCamelCase :
def __init__(self , lowerCamelCase , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase , _lowerCAmelCase = text, pattern
_lowerCAmelCase , _low... | 317 | 1 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def __UpperCAmelCase ( snake_case_ : List[str] , snake_case_ : str , snake_case_ : Dict , snake_case_ : Tuple ) -> Dict:
"""simple docstring"""
_low... | 317 |
"""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
SCREAMING_SNAKE_CASE : List[str] = False
class __lowerCamelCase... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : Any ) -> List[str]:
"""simple docstring"""
_lowerCAmelCase , _lowerCAmelCase = [], []
while len(snake_case_ ) > 1:
_lowerCAmelCase , _lowerCAmelCase = min(sna... | 317 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_util... | 317 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
SCREAMING_SNAKE_CASE : List[str] = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
e... | 317 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict:
"""simple docstring"""
return getitem, k
def __UpperCAm... | 317 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 50 ) -> int:
"""simple docstring"""
_lowerCAmelCase = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
... | 350 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(snake_case_ : int ) -> int:
if target < 0:
r... | 317 | 0 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transf... | 351 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
SCREAMING_SNAKE_CASE : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
SCREAMING_SNAKE_CASE : list[int] ... | 317 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : Any = {
'''configuration_mgp_str''': ['''MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MgpstrConfig'''],
'''processing_mgp... | 352 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int:
"""simple docstring"""
_lowerCAmelCase = limit + 1
_lowerCAmelCase = [0] * limit
for first_term in range(1 , snake_case_ ):
for n in range(sn... | 317 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
... | 353 |
"""simple docstring"""
from functools import reduce
SCREAMING_SNAKE_CASE : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''1254069874715852386305... | 317 | 0 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : list ) -> list:
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
_lowerCAmelCase = []
def generate(snake_case_ : int , snake_c... | 354 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int:
"""simple docstring"""
try:
_lowerCAmelCase = int(snake_case_ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable ... | 317 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE : List[Any] = {
'''configuration_efficientnet''': [
... | 355 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelFor... | 317 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[str] = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:... | 356 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''... | 317 | 0 |
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaXLForSequenceCla... | 357 |
"""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... | 317 | 0 |
from itertools import product
def __UpperCAmelCase ( snake_case_ : int , snake_case_ : int ) -> List[str]:
"""simple docstring"""
_lowerCAmelCase = sides_number
_lowerCAmelCase = max_face_number * dice_number
_lowerCAmelCase ... | 358 |
"""simple docstring"""
def __UpperCAmelCase ( snake_case_ : list ) -> list:
"""simple docstring"""
for i in range(len(snake_case_ ) - 1 , 0 , -1 ):
_lowerCAmelCase = False
for j in range(snake_case_ , 0 , -1 ):
... | 317 | 0 |
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