code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import math
def a__ ( lowerCAmelCase__ = 100 ):
UpperCAmelCase_ = sum(i * i for i in range(1 , n + 1 ) )
UpperCAmelCase_ = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return square_of_sum - s... | 721 |
"""simple docstring"""
from __future__ import annotations
import math
def a__ ( lowerCAmelCase__ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all e... | 14 | 0 |
"""simple docstring"""
import gc
import threading
import time
import psutil
import torch
class lowercase__ :
'''simple docstring'''
def __init__( self : Any ) -> List[Any]:
'''simple docstring'''
... | 700 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""Yitu... | 14 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCamelCase = {
"""configuration_trocr""": ["""TROCR_PRETR... | 701 |
"""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
lowerCamelCase = logging.get_logger(__name__)
lowe... | 14 | 0 |
"""simple docstring"""
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCa... | 702 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaF... | 14 | 0 |
"""simple docstring"""
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample... | 703 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ ):
if len(lowerCAmelCase__ ) == 0:
return []
UpperCAmelCase_ , UpperCAmelCase_ = min(lowerCAmelCase__ ), max(lowerCAmelCase__ )
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
lowerCamelCase = """\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\... | 704 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {
"""configuration_perceiver""": ["""PERCEIVER_... | 14 | 0 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase = False... | 705 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
... | 14 | 0 |
"""simple docstring"""
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase ... | 706 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if not head:
return True
# split the list to two parts
UpperCAmelCase_ , UpperCAmelCase_ = head.next, head
while fast and fast.next:
UpperCAmelCase_ = ... | 14 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.... | 707 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, ... | 14 | 0 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokeni... | 708 |
"""simple docstring"""
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requir... | 14 | 0 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowercase__ ( datasets.BeamBasedBuilder ):
... | 709 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import P... | 14 | 0 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noq... | 710 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...t... | 14 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = int(_lowercase )
if n_element < 1:
UpperCAmelCase_ = ValueError("a should be a positive number" )
raise my_error
UpperCAmelCase_ = ... | 711 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 14 | 0 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_config... | 712 |
"""simple docstring"""
import string
def a__ ( lowerCAmelCase__ ):
for key in range(len(string.ascii_uppercase ) ):
UpperCAmelCase_ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 14 | 0 |
"""simple docstring"""
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowercase__ ( UpperCAmelCase__ ):
... | 713 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availa... | 14 | 0 |
"""simple docstring"""
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = ("dense.weight", "atte... | 714 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = []
UpperCAmelCase_ , UpperCAmelCase_ = input_list[low:mid], inpu... | 14 | 0 |
"""simple docstring"""
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoMod... | 715 |
"""simple docstring"""
lowerCamelCase = {
"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,
"kiloca... | 14 | 0 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class lowercase__ ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
UpperCamel... | 716 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 14 | 0 |
"""simple docstring"""
import warnings
from .generation import TFGenerationMixin
class lowercase__ ( UpperCAmelCase__ ):
'''simple docstring'''
warnings.warn(
'''Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py`... | 717 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementati... | 14 | 0 |
"""simple docstring"""
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_w... | 718 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , ):
UpperCAmelCase_ , UpperCAmelCase_ = grid.shape
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 im... | 719 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = x
UpperCAmelCase_ = y
for step in range(lowerCAmelCase__ ): # n... | 14 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ = 1000 ):
UpperCAmelCase_ = 2**power
UpperCAmelCase_ = str(_UpperCamelCase )
UpperCAmelCase_ = list(_UpperCamelCase )
UpperCAmelCase_ = 0
for i in list_n... | 720 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase = {
"""configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}
try:
if not is_to... | 14 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosi... | 721 |
"""simple docstring"""
from __future__ import annotations
import math
def a__ ( lowerCAmelCase__ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all e... | 14 | 0 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowerc... | 700 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""Yitu... | 14 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inp... | 701 |
"""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
lowerCamelCase = logging.get_logger(__name__)
lowe... | 14 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
l... | 702 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaF... | 14 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase__ ( metaclass=_UpperCAmelCase ):
'''simple docstring'''
UpperCamelCase = ["""onnx"""]
def __init__( self : Union[str, Any] , *_... | 703 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ ):
if len(lowerCAmelCase__ ) == 0:
return []
UpperCAmelCase_ , UpperCAmelCase_ = min(lowerCAmelCase__ ), max(lowerCAmelCase__ )
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
lowerCamelCase = logging.getLogger(__name__)
class lowercase__ :
... | 704 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {
"""configuration_perceiver""": ["""PERCEIVER_... | 14 | 0 |
"""simple docstring"""
from functools import reduce
lowerCamelCase = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""125406987471585238630507156... | 705 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
... | 14 | 0 |
"""simple docstring"""
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
... | 706 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if not head:
return True
# split the list to two parts
UpperCAmelCase_ , UpperCAmelCase_ = head.next, head
while fast and fast.next:
UpperCAmelCase_ = ... | 14 | 0 |
"""simple docstring"""
import requests
lowerCamelCase = """https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""
def a__ ( lowerCAmelCase__ ):
# fetching a list of articles in json format
UpperCAmelCase_ = requests.get(_NEWS_API + bbc_ne... | 707 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, ... | 14 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
"""edbeeching/decision-transformer-gym-hopper-medium""": (
"""https://huggingface.co/edbeeching/decision-transformer-gym-ho... | 708 |
"""simple docstring"""
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requir... | 14 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers impor... | 709 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import P... | 14 | 0 |
"""simple docstring"""
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import To... | 710 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...t... | 14 | 0 |
"""simple docstring"""
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
lowerCamelCase = """scheduler_config.json"""... | 711 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 14 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_ME... | 712 |
"""simple docstring"""
import string
def a__ ( lowerCAmelCase__ ):
for key in range(len(string.ascii_uppercase ) ):
UpperCAmelCase_ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 14 | 0 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
lowerCamelCase = object()
# For specifying empty leaf dict `{}`
lowerCamelCase = ... | 713 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availa... | 14 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""ut/deta""": """https://huggingface.co/ut/deta/resol... | 714 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = []
UpperCAmelCase_ , UpperCAmelCase_ = input_list[low:mid], inpu... | 14 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase = {
'''configuration_vision_encoder_decoder''': ['''Vision... | 715 |
"""simple docstring"""
lowerCamelCase = {
"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,
"kiloca... | 14 | 0 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class lowercase__ ( UpperCamelCase_ ):
UpperCamelCase = ['''image_processor''', '''tokenizer''']
UpperCamelCase = '''AutoImagePr... | 716 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 14 | 0 |
"""simple docstring"""
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .fi... | 717 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementati... | 14 | 0 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class lowercase__ ( unittest.TestCase ):
'''simple docstring'''
def lowercase__ ( self : List[Any] ) -> str:
'''simple docstring... | 718 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , ):
UpperCAmelCase_ , UpperCAmelCase_ = grid.shape
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = hex_num.strip()
if not hex_num:
raise ValueError("No value was passed to the function" )
UpperCAmelCase_ = hex_num[0] == """-"""
if is_negativ... | 719 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = x
UpperCAmelCase_ = y
for step in range(lowerCAmelCase__ ): # n... | 14 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
"""google/f... | 720 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase = {
"""configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}
try:
if not is_to... | 14 | 0 |
"""simple docstring"""
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
lowerCamelCase = datasets.utils.logging.get_logger(__name__)
class lowercase__ ( folder_based_builder.Fol... | 721 |
"""simple docstring"""
from __future__ import annotations
import math
def a__ ( lowerCAmelCase__ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all e... | 14 | 0 |
"""simple docstring"""
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
lowerCamelCase = TypeVar("""T""")
class lowercase__ ( Generic[T] ):
'''simple docstring'''
def __init__( self ... | 700 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""Yitu... | 14 | 0 |
"""simple docstring"""
import numpy as np
class lowercase__ :
def __init__( self : Tuple ) -> List[str]:
'''simple docstring'''
UpperCAmelCase_ = (0, 0)
UpperCAmelCase_ = None
... | 701 |
"""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
lowerCamelCase = logging.get_logger(__name__)
lowe... | 14 | 0 |
"""simple docstring"""
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def ... | 702 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaF... | 14 | 0 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
lowerCamelCase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_ve... | 703 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ ):
if len(lowerCAmelCase__ ) == 0:
return []
UpperCAmelCase_ , UpperCAmelCase_ = min(lowerCAmelCase__ ), max(lowerCAmelCase__ )
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowerCamelCase = {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
lowerCamelCase = _LazyModule(... | 704 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {
"""configuration_perceiver""": ["""PERCEIVER_... | 14 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import c... | 705 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
... | 14 | 0 |
"""simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
lowerCamelCase = """<<<<<<< This should probably be modified because it me... | 706 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if not head:
return True
# split the list to two parts
UpperCAmelCase_ , UpperCAmelCase_ = head.next, head
while fast and fast.next:
UpperCAmelCase_ = ... | 14 | 0 |
"""simple docstring"""
import os
from pathlib import Path
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = {
"en": "Machine learning is great, isn't it?",
"ru": "Машинное обучение - это здорово, не т... | 707 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, ... | 14 | 0 |
"""simple docstring"""
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecu... | 708 |
"""simple docstring"""
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requir... | 14 | 0 |
"""simple docstring"""
import math
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ = 0 , lowerCAmelCase__ = 0 ):
UpperCAmelCase_ = end or len(A_ )
for i in range(A_ , A_ ):
UpperCAmelCase_ = i
UpperCAmelCas... | 709 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import P... | 14 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
... | 710 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...t... | 14 | 0 |
"""simple docstring"""
from torch import nn
class lowercase__ ( nn.Module ):
'''simple docstring'''
def __init__( self : int , _UpperCAmelCase : Optional[int] , _UpperCAmelCase : List[str] ) -> Optional[Any]... | 711 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 14 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def a__ ( lowerCAmelCase__ , lowerCAmelCase__=1000 ):
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
UpperCAmelCase_ = n - 1
Up... | 712 |
"""simple docstring"""
import string
def a__ ( lowerCAmelCase__ ):
for key in range(len(string.ascii_uppercase ) ):
UpperCAmelCase_ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 14 | 0 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_... | 713 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availa... | 14 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowerCamelCase = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11""")
... | 714 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = []
UpperCAmelCase_ , UpperCAmelCase_ = input_list[low:mid], inpu... | 14 | 0 |
"""simple docstring"""
lowerCamelCase = """Alexander Joslin"""
import operator as op
from .stack import Stack
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
UpperCAmelCase_ = S... | 715 |
"""simple docstring"""
lowerCamelCase = {
"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,
"kiloca... | 14 | 0 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReas... | 716 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 14 | 0 |
"""simple docstring"""
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# ... | 717 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementati... | 14 | 0 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def a__ ( lowerCAmelCase__ , lowerCAm... | 718 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , ):
UpperCAmelCase_ , UpperCAmelCase_ = grid.shape
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase ... | 719 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = x
UpperCAmelCase_ = y
for step in range(lowerCAmelCase__ ): # n... | 14 | 0 |
"""simple docstring"""
from __future__ import annotations
lowerCamelCase = 10
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = 1
UpperCAmelCase_ = max(lowerCAmelCase__ )
while placement <= max_digit:
# declare and initialize ... | 720 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase = {
"""configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}
try:
if not is_to... | 14 | 0 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = len(lowerCAmelCase__ )
# We need to create solution object to save path.
UpperCAmelCase_ = [[0 for _ in range(lowerCAmelCase__ )] fo... | 721 |
"""simple docstring"""
from __future__ import annotations
import math
def a__ ( lowerCAmelCase__ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all e... | 14 | 0 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowerca... | 700 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""Yitu... | 14 | 0 |
"""simple docstring"""
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class lowercase__ ( lowerCamelCase__ ):
def __init__( self : Union[str, Any] , _UpperCAmelCase : Any="" , _UpperCAmelCase... | 701 |
"""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
lowerCamelCase = logging.get_logger(__name__)
lowe... | 14 | 0 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
lowerCamelCase = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def a__ ( ):
UpperCAmelCase_ = os.path.dirname(os.path.realpath(UpperCamelCase__ ) )
UpperCAm... | 702 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaF... | 14 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
Channel... | 703 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ ):
if len(lowerCAmelCase__ ) == 0:
return []
UpperCAmelCase_ , UpperCAmelCase_ = min(lowerCAmelCase__ ), max(lowerCAmelCase__ )
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)... | 704 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {
"""configuration_perceiver""": ["""PERCEIVER_... | 14 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
'ksstev... | 705 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
... | 14 | 0 |
"""simple docstring"""
import math
class lowercase__ :
'''simple docstring'''
def __init__( self : Optional[Any] , _UpperCAmelCase : List[str]=0 ) -> List[str]: # a graph with Node 0,1,...,N-1
'''simple d... | 706 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if not head:
return True
# split the list to two parts
UpperCAmelCase_ , UpperCAmelCase_ = head.next, head
while fast and fast.next:
UpperCAmelCase_ = ... | 14 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = ... | 707 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, ... | 14 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
A = 50_000
A = 5_000
A , A = os.path.split(__file__)
A = os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replac... | 708 |
"""simple docstring"""
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requir... | 14 | 0 |
"""simple docstring"""
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def a__ ... | 709 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import P... | 14 | 0 |
"""simple docstring"""
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = OmegaConf.load(lowerCAmelCase__ )
... | 710 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...t... | 14 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ = 100 ):
UpperCAmelCase_ = 0
UpperCAmelCase_ = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
... | 711 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 14 | 0 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate... | 712 |
"""simple docstring"""
import string
def a__ ( lowerCAmelCase__ ):
for key in range(len(string.ascii_uppercase ) ):
UpperCAmelCase_ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 14 | 0 |
"""simple docstring"""
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowerCamelCase = {
# 1536-bit
5: {
... | 713 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availa... | 14 | 0 |
"""simple docstring"""
from random import shuffle
import tensorflow as tf
from numpy import array
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = int(UpperCAmelCase__ )
assert noofclusters < len(UpperCAmelCase__ )
# Fin... | 714 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = []
UpperCAmelCase_ , UpperCAmelCase_ = input_list[low:mid], inpu... | 14 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class lowercase__ ( SCREAMING_SNA... | 715 |
"""simple docstring"""
lowerCamelCase = {
"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,
"kiloca... | 14 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase = {"""configuration_encoder_decoder""": ["""EncoderDecoderConfig... | 716 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 14 | 0 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfD... | 717 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementati... | 14 | 0 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
lowerCamelCase = '\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true ... | 718 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , ):
UpperCAmelCase_ , UpperCAmelCase_ = grid.shape
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def a__ ( lowerCAmelCase__ ):
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class lowercase__ ( ... | 719 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = x
UpperCAmelCase_ = y
for step in range(lowerCAmelCase__ ): # n... | 14 | 0 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common... | 720 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase = {
"""configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}
try:
if not is_to... | 14 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
# 1. Validate that path exists between current and next vertices
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2.... | 721 |
"""simple docstring"""
from __future__ import annotations
import math
def a__ ( lowerCAmelCase__ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all e... | 14 | 0 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def a__ ( lowerCAmelCase__ ):
Upper... | 700 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""Yitu... | 14 | 0 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vi... | 701 |
"""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
lowerCamelCase = logging.get_logger(__name__)
lowe... | 14 | 0 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = 0
if start < end:
UpperCAmelCase_ = ... | 702 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaF... | 14 | 0 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def a__ ( ):
print("Making key files..." )
make_key_files("rsa" , 1024 )
print("K... | 703 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ ):
if len(lowerCAmelCase__ ) == 0:
return []
UpperCAmelCase_ , UpperCAmelCase_ = min(lowerCAmelCase__ ), max(lowerCAmelCase__ )
UpperCAmelCase_ ... | 14 | 0 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCamelCase = input("""Enter image url: """).strip()
print(F"Downloading image from {url} ...")
lowerCamelCase = BeautifulSoup(requests.get(url)... | 704 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {
"""configuration_perceiver""": ["""PERCEIVER_... | 14 | 0 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ ):
if len(lowerCAmelCase__ ) == 0:
return []
UpperCAmelCase_ , UpperCAmelCase_ = min(lowerCAmelCase__ ), max(lowerCAmelCase__ )
UpperCAmelCase_ ... | 705 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
... | 14 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if not all(char in "01" for char in bin_string ):
raise ValueError("Non-binary value was passed to the function" )
if not bin_string:
raise ValueError("Empty string was passed to the function" ... | 706 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if not head:
return True
# split the list to two parts
UpperCAmelCase_ , UpperCAmelCase_ = head.next, head
while fast and fast.next:
UpperCAmelCase_ = ... | 14 | 0 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassificat... | 707 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, ... | 14 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
"""sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json""",
# See all ViT MSN m... | 708 |
"""simple docstring"""
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requir... | 14 | 0 |
"""simple docstring"""
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowerCamelCase = datasets.logging.get_logger(__name__)
lowerCamelCase = """\
@InProcee... | 709 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import P... | 14 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_table,
)
from .np_... | 710 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...t... | 14 | 0 |
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