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"""simple docstring""" import inspect import unittest from transformers import ConvNextConfig from transformers.testing_utils import require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_backbone_common import Back...
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"""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 tokenizers.processors im...
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"""simple docstring""" import functools def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->int: """simple docstring""" a_ = len(UpperCAmelCase ) a_ = len(UpperCAmelCase ) @functools.cache def min_distance(UpperCAmelCase , UpperCAmelCase ) -> ...
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"""simple docstring""" from urllib.parse import quote import pytest from datasets.utils.hub import hf_hub_url @pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] ) @pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] ) @pytest.mark....
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"""simple docstring""" import os import pytest from attr import dataclass UpperCamelCase_ = 'us-east-1' # defaults region @dataclass class snake_case : a_ : str a_ : List[Any] = """arn:aws:iam::558105141721:role/sagemaker_execution_role""" a_ : str ...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'MIT/ast-finetuned-audioset-10-10-0.4593': ( 'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c...
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"""simple docstring""" from __future__ import annotations from random import random from typing import Generic, TypeVar UpperCamelCase_ = TypeVar('KT') UpperCamelCase_ = TypeVar('VT') class snake_case ( Generic[KT, VT] ): def __init__( self , __UpperCAmelCase = "root"...
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"""simple docstring""" from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'xlm-roberta-base': 'https://hugging...
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"""simple docstring""" import inspect import re from hashlib import shaaaa from typing import Dict, List from .arrow import arrow from .audiofolder import audiofolder from .csv import csv from .imagefolder import imagefolder from .json import json from .pandas import pandas from .parquet import parquet from .sq...
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"""simple docstring""" import unittest from transformers import LiltConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common i...
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"""simple docstring""" import json import os from pathlib import Path from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple, Union import sentencepiece from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer from ...utils import logging UpperCamelCase_ = logging.get_l...
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"""simple docstring""" from __future__ import annotations import inspect import unittest from math import floor import numpy as np from transformers import CvtConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_visi...
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"""simple docstring""" from typing import Tuple, Union from ...modeling_outputs import BackboneOutput from ...modeling_utils import PreTrainedModel from ...utils import is_timm_available, is_torch_available, requires_backends from ...utils.backbone_utils import BackboneMixin from .configuration_timm_backbone im...
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"""simple docstring""" import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class snake_case ( SCREAMING_SNAKE_CASE_ ): a_ : Dict = """Speech2TextFeatureExtractor""" a_ : str = """Speech2TextTokeni...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available UpperCamelCase_ = { 'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'], } try: if not is_...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'], } try: if not is_torch_available(): raise Option...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCamelCase_ = { 'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'], 'tokenization_ctrl': ['CTRLTokenizer'], } try...
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"""simple docstring""" from typing import TYPE_CHECKING from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'], 'feature_extraction_mctct': ['MCTCTFeatureExtractor'], ...
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"""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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format from ...image_utils import ( ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) UpperCamelCase_ = { 'configuration_swiftformer': [ 'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwiftFormerConfig', 'Swif...
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"""simple docstring""" UpperCamelCase_ = '0.21.0' from .accelerator import Accelerator from .big_modeling import ( cpu_offload, cpu_offload_with_hook, disk_offload, dispatch_model, init_empty_weights, init_on_device, load_checkpoint_and_dispatch, ) from .data_loader import skip_fir...
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"""simple docstring""" # Usage: # ./gen-card-allenai-wmt16.py import os from pathlib import Path def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->List[Any]: """simple docstring""" a_ = { "en": "Machine learning is great, isn't ...
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"""simple docstring""" from typing import Any class snake_case : def __init__( self , __UpperCAmelCase) ->List[str]: a_ = data a_ = None def __repr__( self) ->str: return F'''Node({self.data})''' class snake_case : de...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->int: """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation(UpperCAmelCase , n - 1 , UpperCAmelCase ) * a) % mod else: ...
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"""simple docstring""" from ....utils import logging UpperCamelCase_ = logging.get_logger(__name__) class snake_case ( SCREAMING_SNAKE_CASE_ ): def __init__( self , __UpperCAmelCase , __UpperCAmelCase=None , __UpperCAmelCase=20_48) ->List[Any]: a_ = ...
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"""simple docstring""" import warnings from ...utils import logging from .image_processing_yolos import YolosImageProcessor UpperCamelCase_ = logging.get_logger(__name__) class snake_case ( SCREAMING_SNAKE_CASE_ ): def __init__( self , *__UpperCAmelCase , **__Uppe...
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"""simple docstring""" from __future__ import absolute_import, division, print_function, unicode_literals from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers import RobertaConfig from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward fr...
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"""simple docstring""" import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class snake_case ( unittest.TestCase ...
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"""simple docstring""" 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, ...
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"""simple docstring""" from heapq import heappop, heappush import numpy as np def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , ) ->tuple[float | int, list[tuple[int, int]]]: """simple docstring""" a_ , a_ = grid.shape a_ = [-1, ...
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"""simple docstring""" import json import os import tempfile import datasets from utils import generate_example_dataset, get_duration UpperCamelCase_ = 50000 UpperCamelCase_ = 5000 UpperCamelCase_ , UpperCamelCase_ = os.path.split(__file__) UpperCamelCase_ = os.path.join(RESULTS_BASEPATH, 'resul...
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"""simple docstring""" import numpy as np import torch from imwatermark import WatermarkEncoder # Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66 UpperCamelCase_ = 0b10_11_00_11_11_10_11_00_10_01_00_00_01_11_10_...
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"""simple docstring""" from __future__ import annotations def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->tuple[int, int]: """simple docstring""" if b == 0: return (1, 0) ((a_) , (a_)) = extended_euclid(UpperCAmelCase , a % b ) a_ = a // b retu...
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"""simple docstring""" import math UpperCamelCase_ = 10 UpperCamelCase_ = 7 UpperCamelCase_ = BALLS_PER_COLOUR * NUM_COLOURS def UpperCamelCase ( UpperCAmelCase = 20 ) ->str: """simple docstring""" a_ = math.comb(UpperCAmelCase , UpperCAmelCase ) a_ = math.comb...
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"""simple docstring""" import os import numpy import onnx def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->List[str]: """simple docstring""" a_ = a.name a_ = b.name a_ = "" a_ = "" a_ = a == b a_ = name_a a_ = n...
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"""simple docstring""" import argparse import os from pathlib import Path from typing import Dict import tensorflow as tf import torch from tqdm import tqdm from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer from transformers.models.pegasus.configuration_pegasus import DE...
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"""simple docstring""" import importlib import torch import yaml from omegaconf import OmegaConf from taming.models.vqgan import VQModel def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase=False ) ->List[Any]: """simple docstring""" a_ = OmegaConf.load(UpperCAmelCase ) if ...
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"""simple docstring""" import unittest from transformers import BertGenerationConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modelin...
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"""simple docstring""" import argparse import dataclasses import json import logging import os import shutil from typing import List, Optional import datasets from accelerate import Accelerator from datasets import load_dataset from finetuning import finetune from tqdm.auto import tqdm import transformers from...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig from transformers.utils i...
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"""simple docstring""" from collections import Counter from timeit import timeit def UpperCamelCase ( UpperCAmelCase = "" , ) ->bool: """simple docstring""" return sum(c % 2 for c in Counter(input_str.replace(" " , "" ).lower() ).values() ) < 2 def UpperCamelCase ( UpperCA...
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"""simple docstring""" import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from torchvision import transforms from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification from transformers.image_utils import IM...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase = 4_000_000 ) ->int: """simple docstring""" a_ = [0, 1] a_ = 0 while fib[i] <= n: fib.append(fib[i] + fib[i + 1] ) if fib[i + 2] > n: break i += 1 a_ = 0 for j in range(...
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"""simple docstring""" import os import numpy import onnx def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->List[str]: """simple docstring""" a_ = a.name a_ = b.name a_ = "" a_ = "" a_ = a == b a_ = name_a a_ = n...
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"""simple docstring""" import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class snake_case ( unittest.TestCase ...
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"""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 tokenizers.processors im...
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"""simple docstring""" from .data_collator import ( DataCollatorForLanguageModeling, DataCollatorForPermutationLanguageModeling, DataCollatorForSeqaSeq, DataCollatorForSOP, DataCollatorForTokenClassification, DataCollatorForWholeWordMask, DataCollatorWithPadding, DefaultDataCollat...
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"""simple docstring""" from urllib.parse import quote import pytest from datasets.utils.hub import hf_hub_url @pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] ) @pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] ) @pytest.mark....
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"""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, InputFeature...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'MIT/ast-finetuned-audioset-10-10-0.4593': ( 'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c...
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"""simple docstring""" import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class snake_case ( SCREAMING_SNAKE_CASE_ ): a_ : Dict = """Speech2TextFeatureExtractor""" a_ : str = """Speech2TextTokeni...
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"""simple docstring""" from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'xlm-roberta-base': 'https://hugging...
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"""simple docstring""" import unittest from transformers import LiltConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common i...
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"""simple docstring""" import unittest from transformers import LiltConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common i...
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"""simple docstring""" class snake_case : def __init__( self , __UpperCAmelCase = "" , __UpperCAmelCase = False) ->None: # Mapping from the first character of the prefix of the node a_ = {} # A node will be a leaf if the tree contains its word a_ = ...
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"""simple docstring""" from __future__ import annotations import inspect import unittest from math import floor import numpy as np from transformers import CvtConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_visi...
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"""simple docstring""" import argparse import json from collections import OrderedDict from functools import partial from pathlib import Path import timm import torch from huggingface_hub import hf_hub_download from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor fr...
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"""simple docstring""" import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class snake_case ( SCREAMING_SNAKE_CASE_ ): a_ : Dict = """Speech2TextFeatureExtractor""" a_ : str = """Speech2TextTokeni...
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"""simple docstring""" import copy import os from typing import TYPE_CHECKING, List, Union if TYPE_CHECKING: pass from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'kakaobrain/align-base': 'https...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'], } try: if not is_torch_available(): raise Option...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'SenseTime/deformable-detr': 'https://huggingface.co/sensetime/deformable-detr/resol...
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"""simple docstring""" from typing import TYPE_CHECKING from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'], 'feature_extraction_mctct': ['MCTCTFeatureExtractor'], ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, is_vision_available, ) UpperCamelCase_ = {'processing_layoutxlm': ['LayoutXLMProcessor'...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) UpperCamelCase_ = { 'configuration_swiftformer': [ 'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwiftFormerConfig', 'Swif...
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"""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...
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"""simple docstring""" # Usage: # ./gen-card-allenai-wmt16.py import os from pathlib import Path def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->List[Any]: """simple docstring""" a_ = { "en": "Machine learning is great, isn't ...
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"""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_a...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->int: """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation(UpperCAmelCase , n - 1 , UpperCAmelCase ) * a) % mod else: ...
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"""simple docstring""" import os import sys import unittest UpperCamelCase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, 'utils')) import get_test_info # noqa: E402 from get_test_info import ( # noqa: E402 ...
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"""simple docstring""" import warnings from ...utils import logging from .image_processing_yolos import YolosImageProcessor UpperCamelCase_ = logging.get_logger(__name__) class snake_case ( SCREAMING_SNAKE_CASE_ ): def __init__( self , *__UpperCAmelCase , **__Uppe...
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def UpperCamelCase ( ) ->int: """simple docstring""" return 1 def UpperCamelCase ( UpperCAmelCase ) ->int: """simple docstring""" return 0 if x < 0 else two_pence(x - 2 ) + one_pence() def UpperCamelCase ( UpperCAmelCase ) ->int: """simple docstring""" return...
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"""simple docstring""" import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class snake_case ( unittest.TestCase ...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase ) ->list: """simple docstring""" a_ = len(lowerCamelCase__ ) for i in range(1 , lowerCamelCase__ ): a_ = collection[i] a_ = 0 a_ = i - 1 while low <= high: ...
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"""simple docstring""" from heapq import heappop, heappush import numpy as np def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , ) ->tuple[float | int, list[tuple[int, int]]]: """simple docstring""" a_ , a_ = grid.shape a_ = [-1, ...
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"""simple docstring""" import qiskit def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->str: """simple docstring""" a_ = qiskit.Aer.get_backend("aer_simulator" ) # Create a Quantum Circuit acting on the q register a_ = qiskit.QuantumCircuit(__a , __a ...
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"""simple docstring""" import numpy as np import torch from imwatermark import WatermarkEncoder # Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66 UpperCamelCase_ = 0b10_11_00_11_11_10_11_00_10_01_00_00_01_11_10_...
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from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-bas...
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"""simple docstring""" import math UpperCamelCase_ = 10 UpperCamelCase_ = 7 UpperCamelCase_ = BALLS_PER_COLOUR * NUM_COLOURS def UpperCamelCase ( UpperCAmelCase = 20 ) ->str: """simple docstring""" a_ = math.comb(UpperCAmelCase , UpperCAmelCase ) a_ = math.comb...
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"""simple docstring""" # Copyright 2023 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 # ...
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"""simple docstring""" import argparse import os from pathlib import Path from typing import Dict import tensorflow as tf import torch from tqdm import tqdm from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer from transformers.models.pegasus.configuration_pegasus import DE...
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"""simple docstring""" import argparse import gc import json import os 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 ...
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"""simple docstring""" import unittest from transformers import BertGenerationConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modelin...
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"""simple docstring""" from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available UpperCamelCase_ = {"""configuration_mra""": ["""MRA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MraConfig"""]...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig from transformers.utils i...
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"""simple docstring""" import copy import unittest from transformers.models.auto import get_values from transformers.testing_utils import require_torch, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common import ConfigTest...
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"""simple docstring""" import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from torchvision import transforms from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification from transformers.image_utils import IM...
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"""simple docstring""" import json import os import tempfile import datasets from utils import generate_example_dataset, get_duration UpperCamelCase_ = 50000 UpperCamelCase_ = 5000 UpperCamelCase_ , UpperCamelCase_ = os.path.split(__file__) UpperCamelCase_ = os.path.join(RESULTS_BASEPATH, 'resul...
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"""simple docstring""" import os import numpy import onnx def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->List[str]: """simple docstring""" a_ = a.name a_ = b.name a_ = "" a_ = "" a_ = a == b a_ = name_a a_ = n...
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"""simple docstring""" UpperCamelCase_ = { 'km/h': 1.0, 'm/s': 3.6, 'mph': 1.60_93_44, 'knot': 1.8_52, } UpperCamelCase_ = { 'km/h': 1.0, 'm/s': 0.2_77_77_77_78, 'mph': 0.6_21_37_11_92, 'knot': 0.5_39_95_68_03, } def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ...
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"""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 tokenizers.processors im...
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"""simple docstring""" import shutil import tempfile import unittest from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast from transformers.testing_utils import require_sentencepiece, require_torchaudio from .test_feature_extraction_clap import floats_list @...
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"""simple docstring""" from urllib.parse import quote import pytest from datasets.utils.hub import hf_hub_url @pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] ) @pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] ) @pytest.mark....
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"""simple docstring""" UpperCamelCase_ = 65521 def UpperCamelCase ( UpperCAmelCase ) ->int: """simple docstring""" a_ = 1 a_ = 0 for plain_chr in plain_text: a_ = (a + ord(a_ )) % MOD_ADLER a_ = (b + a) % MOD_ADLER return (b << 16) | a
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'MIT/ast-finetuned-audioset-10-10-0.4593': ( 'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase ) ->list: """simple docstring""" if len(__a ) <= 1: return lst a_ = 1 while i < len(__a ): if lst[i - 1] <= lst[i]: i += 1 else: a_ = lst[i], lst[i - 1] i -=...
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"""simple docstring""" from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'xlm-roberta-base': 'https://hugging...
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"""simple docstring""" from __future__ import annotations from collections.abc import Callable from typing import Generic, TypeVar UpperCamelCase_ = TypeVar('T') UpperCamelCase_ = TypeVar('U') class snake_case ( Generic[T, U] ): def __init__( self , __UpperCAmelCase ...
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"""simple docstring""" import unittest from transformers import LiltConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common i...
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"""simple docstring""" import baseaa def UpperCamelCase ( UpperCAmelCase ) ->Any: """simple docstring""" return baseaa.baaencode(string.encode("utf-8" ) ) def UpperCamelCase ( UpperCAmelCase ) ->Tuple: """simple docstring""" return baseaa.baadecode(a_ ).deco...
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"""simple docstring""" from __future__ import annotations import inspect import unittest from math import floor import numpy as np from transformers import CvtConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_visi...
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from math import pow, sqrt def UpperCamelCase ( *UpperCAmelCase ) ->bool: """simple docstring""" a_ = len(_UpperCamelCase ) > 0 and all(value > 0.0 for value in values ) return result def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->float | ValueError: "...
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"""simple docstring""" import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class snake_case ( SCREAMING_SNAKE_CASE_ ): a_ : Dict = """Speech2TextFeatureExtractor""" a_ : str = """Speech2TextTokeni...
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"""simple docstring""" from dataclasses import dataclass, field from typing import Optional from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser @dataclass class SCREAMING_SNAKE_CASE__ : a_ : str = field( ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'], } try: if not is_torch_available(): raise Option...
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"""simple docstring""" from ..utils import DummyObject, requires_backends class snake_case ( metaclass=__UpperCamelCase ): a_ : List[Any] = ["flax", "transformers"] def __init__( self , *__UpperCAmelCase , **__UpperCAmelCas...
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"""simple docstring""" from typing import TYPE_CHECKING from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'], 'feature_extraction_mctct': ['MCTCTFeatureExtractor'], ...
303
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"""simple docstring""" import argparse import json 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 ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) UpperCamelCase_ = { 'configuration_swiftformer': [ 'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwiftFormerConfig', 'Swif...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase = 1_000_000 ) ->str: """simple docstring""" a_ = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j in range(2 * i , limit + 1 , __a ): ...
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"""simple docstring""" # Usage: # ./gen-card-allenai-wmt16.py import os from pathlib import Path def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->List[Any]: """simple docstring""" a_ = { "en": "Machine learning is great, isn't ...
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"""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, ) UpperCamelCase_ = pytest.mark.integration @pytest.mark.parametrize("path" , ["pa...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->int: """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation(UpperCAmelCase , n - 1 , UpperCAmelCase ) * a) % mod else: ...
303
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"""simple docstring""" import gc import random import unittest import numpy as np import torch from transformers import XLMRobertaTokenizer from diffusers import ( AltDiffusionImgaImgPipeline, AutoencoderKL, PNDMScheduler, UNetaDConditionModel, ) from diffusers.image_proce...
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"""simple docstring""" import warnings from ...utils import logging from .image_processing_yolos import YolosImageProcessor UpperCamelCase_ = logging.get_logger(__name__) class snake_case ( SCREAMING_SNAKE_CASE_ ): def __init__( self , *__UpperCAmelCase , **__Uppe...
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from __future__ import annotations from itertools import permutations from random import randint from timeit import repeat def UpperCamelCase ( ) ->Optional[int]: """simple docstring""" a_ = [randint(-1_000 , 1_000 ) for i in range(10 )] a_ = randint(-5_000 , 5_000 ...
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"""simple docstring""" import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class snake_case ( unittest.TestCase ...
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"""simple docstring""" import gc import unittest import numpy as np import torch from torch.backends.cuda import sdp_kernel from diffusers import ( CMStochasticIterativeScheduler, ConsistencyModelPipeline, UNetaDModel, ) from diffusers.utils import randn_tensor, slow, torch_device from diffusers.ut...
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"""simple docstring""" from heapq import heappop, heappush import numpy as np def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , ) ->tuple[float | int, list[tuple[int, int]]]: """simple docstring""" a_ , a_ = grid.shape a_ = [-1, ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = {'''configuration_wavlm''': ['''WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WavLMConfig''']} try: if not is_torch_available(): r...
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"""simple docstring""" import numpy as np import torch from imwatermark import WatermarkEncoder # Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66 UpperCamelCase_ = 0b10_11_00_11_11_10_11_00_10_01_00_00_01_11_10_...
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from __future__ import annotations from math import pow, sqrt def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->dict[str, float]: """simple docstring""" if (resistance, reactance, impedance).count(0 ) != 1: raise ValueError("One and only one argument must b...
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"""simple docstring""" import math UpperCamelCase_ = 10 UpperCamelCase_ = 7 UpperCamelCase_ = BALLS_PER_COLOUR * NUM_COLOURS def UpperCamelCase ( UpperCAmelCase = 20 ) ->str: """simple docstring""" a_ = math.comb(UpperCAmelCase , UpperCAmelCase ) a_ = math.comb...
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"""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, BatchEncoding, PreTrainedTokenizer from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCam...
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"""simple docstring""" import argparse import os from pathlib import Path from typing import Dict import tensorflow as tf import torch from tqdm import tqdm from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer from transformers.models.pegasus.configuration_pegasus import DE...
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"""simple docstring""" from typing import Optional, Tuple, Union import tensorflow as tf from ...activations_tf import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward from ...modeling_tf_outputs import ( TFBaseModelOutputWithNoAttenti...
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"""simple docstring""" import unittest from transformers import BertGenerationConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modelin...
303
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase ) ->Union[str, Any]: """simple docstring""" for i in range(0 , _UpperCamelCase ): for _ in range(0 , n - i - 1 ): # printing spaces print(" " , end="" ) for _ in range(0 , i + 1 ...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig from transformers.utils i...
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"""simple docstring""" from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { """facebook/xlm-roberta-xl""": """ht...
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"""simple docstring""" import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from torchvision import transforms from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification from transformers.image_utils import IM...
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"""simple docstring""" from string import ascii_uppercase UpperCamelCase_ = {char: i for i, char in enumerate(ascii_uppercase)} UpperCamelCase_ = dict(enumerate(ascii_uppercase)) def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->str: """simple docstring""" a_ = len(a__ ...
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"""simple docstring""" import os import numpy import onnx def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->List[str]: """simple docstring""" a_ = a.name a_ = b.name a_ = "" a_ = "" a_ = a == b a_ = name_a a_ = n...
303
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"""simple docstring""" import argparse import intel_extension_for_pytorch as ipex import torch from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline UpperCamelCase_ = argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False) parser.add_argument('--dpm',...
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"""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 tokenizers.processors im...
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"""simple docstring""" from __future__ import annotations from typing import Any def UpperCamelCase ( UpperCAmelCase ) ->Tuple: """simple docstring""" if not postfix_notation: return 0 a_ = {"+", "-", "*", "/"} a_ = [] for token in postfix_notation: if to...
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"""simple docstring""" from urllib.parse import quote import pytest from datasets.utils.hub import hf_hub_url @pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] ) @pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] ) @pytest.mark....
303
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"""simple docstring""" import unittest from transformers import DebertaConfig, 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 ModelTe...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'MIT/ast-finetuned-audioset-10-10-0.4593': ( 'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c...
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"""simple docstring""" from dataclasses import dataclass, field from typing import Tuple from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends from .benchmark_args_utils import BenchmarkArguments if is_torch_available(): import torch if is_torch_tpu...
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"""simple docstring""" from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'xlm-roberta-base': 'https://hugging...
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"""simple docstring""" import argparse import logging import pickle from collections import Counter logging.basicConfig( format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO ) UpperCamelCase_ = logging.getLogger(__name__) if __name__ == "__main__...
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"""simple docstring""" import unittest from transformers import LiltConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common i...
303
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"""simple docstring""" from __future__ import annotations import unittest import numpy as np from transformers import OPTConfig, is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common...
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"""simple docstring""" from __future__ import annotations import inspect import unittest from math import floor import numpy as np from transformers import CvtConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_visi...
303
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import pytest import requests from datasets.utils.file_utils import http_head from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline @pytest.mark.integration def UpperCamelCase ( ) ->int: """simple docstring""" with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ...
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"""simple docstring""" import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class snake_case ( SCREAMING_SNAKE_CASE_ ): a_ : Dict = """Speech2TextFeatureExtractor""" a_ : str = """Speech2TextTokeni...
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"""simple docstring""" import os from pathlib import Path import numpy as np import pytest from pack_dataset import pack_data_dir from parameterized import parameterized from save_len_file import save_len_file from torch.utils.data import DataLoader from transformers import AutoTokenizer from transformers.mode...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'], } try: if not is_torch_available(): raise Option...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_blip_2': [ 'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Blip2Config', 'Blip2QFormerConfig',...
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"""simple docstring""" from typing import TYPE_CHECKING from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'], 'feature_extraction_mctct': ['MCTCTFeatureExtractor'], ...
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"""simple docstring""" import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, DPMSolverMultistepScheduler, TextToVideoSDPipeline, UNetaDConditionModel, ) from diffusers.utils...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) UpperCamelCase_ = { 'configuration_swiftformer': [ 'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwiftFormerConfig', 'Swif...
303
0
"""simple docstring""" import unittest from transformers import PegasusConfig, PegasusTokenizer, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_configuration_common import ConfigTester from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor if is_fl...
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"""simple docstring""" # Usage: # ./gen-card-allenai-wmt16.py import os from pathlib import Path def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->List[Any]: """simple docstring""" a_ = { "en": "Machine learning is great, isn't ...
303
0
"""simple docstring""" import argparse import json import os import fairseq import torch from torch import nn from transformers import ( SpeechaTextaConfig, SpeechaTextaForCausalLM, SpeechaTextaTokenizer, SpeechEncoderDecoderConfig, SpeechEncoderDecoderModel, WavaVecaConfig, WavaVec...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->int: """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation(UpperCAmelCase , n - 1 , UpperCAmelCase ) * a) % mod else: ...
303
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase ) ->Dict: """simple docstring""" for i in range(0 , UpperCAmelCase ): for _ in range(0 , n - i - 1 ): # printing spaces print(" " , end="" ) for _ in range(0 , i + 1 ...
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"""simple docstring""" import warnings from ...utils import logging from .image_processing_yolos import YolosImageProcessor UpperCamelCase_ = logging.get_logger(__name__) class snake_case ( SCREAMING_SNAKE_CASE_ ): def __init__( self , *__UpperCAmelCase , **__Uppe...
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import sys import turtle def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->Tuple: """simple docstring""" return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2 def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , ) ->int: """simple docstri...
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"""simple docstring""" import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class snake_case ( unittest.TestCase ...
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"""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 ...
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"""simple docstring""" from heapq import heappop, heappush import numpy as np def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , ) ->tuple[float | int, list[tuple[int, int]]]: """simple docstring""" a_ , a_ = grid.shape a_ = [-1, ...
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"""simple docstring""" import argparse import os import gluonnlp as nlp import mxnet as mx import numpy as np import torch from gluonnlp.base import get_home_dir from gluonnlp.model.bert import BERTEncoder from gluonnlp.model.utils import _load_vocab from gluonnlp.vocab import Vocab from packaging import versio...
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"""simple docstring""" import numpy as np import torch from imwatermark import WatermarkEncoder # Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66 UpperCamelCase_ = 0b10_11_00_11_11_10_11_00_10_01_00_00_01_11_10_...
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from __future__ import annotations from collections import deque from collections.abc import Iterator from dataclasses import dataclass @dataclass class snake_case : a_ : Optional[Any] = 42 a_ : str = 42 class snake_case : def __init__( ...
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"""simple docstring""" import math UpperCamelCase_ = 10 UpperCamelCase_ = 7 UpperCamelCase_ = BALLS_PER_COLOUR * NUM_COLOURS def UpperCamelCase ( UpperCAmelCase = 20 ) ->str: """simple docstring""" a_ = math.comb(UpperCAmelCase , UpperCAmelCase ) a_ = math.comb...
303
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"""simple docstring""" import argparse import requests import torch from PIL import Image from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor def UpperCamelCase ( UpperCAmelCase ) ->Dict: """simple docstring""" a_ = SwinConfig(image_size=192 ) ...
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"""simple docstring""" import argparse import os from pathlib import Path from typing import Dict import tensorflow as tf import torch from tqdm import tqdm from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer from transformers.models.pegasus.configuration_pegasus import DE...
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"""simple docstring""" import math from typing import Union import torch from ..configuration_utils import ConfigMixin, register_to_config from ..utils import randn_tensor from .scheduling_utils import SchedulerMixin class snake_case ( lowerCamelCase__ , lowerCamelCase__ ): a_ : ...
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"""simple docstring""" import unittest from transformers import BertGenerationConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modelin...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCamelCase_ = { 'configuration_mobilebert': [ 'MOBILEBERT_PRETRAINED_CONFIG_ARCHI...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig from transformers.utils i...
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"""simple docstring""" import argparse import torch from transformers import ( UniSpeechSatConfig, UniSpeechSatForAudioFrameClassification, UniSpeechSatForSequenceClassification, UniSpeechSatForXVector, WavaVecaFeatureExtractor, logging, ) logging.set_verbosity_info() UpperCamelCase_ ...
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"""simple docstring""" import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from torchvision import transforms from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification from transformers.image_utils import IM...
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"""simple docstring""" class snake_case : def __init__( self , __UpperCAmelCase , __UpperCAmelCase) ->Optional[Any]: a_ = name a_ = val def __str__( self) ->str: return F'''{self.__class__.__name__}({self.name}, {self.val})''' de...
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"""simple docstring""" import os import numpy import onnx def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ) ->List[str]: """simple docstring""" a_ = a.name a_ = b.name a_ = "" a_ = "" a_ = a == b a_ = name_a a_ = n...
303
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"""simple docstring""" from collections import OrderedDict from typing import TYPE_CHECKING, Any, Mapping, Optional from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...onnx.utils import compute_effective_axis_dimension from ...utils import lo...
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"""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 tokenizers.processors im...
303
0
"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCamelCase_ = {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']} try: if not is_vision_available(): ...
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"""simple docstring""" from urllib.parse import quote import pytest from datasets.utils.hub import hf_hub_url @pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] ) @pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] ) @pytest.mark....
303
0
"""simple docstring""" import torch from diffusers import UnCLIPScheduler from .test_schedulers import SchedulerCommonTest class snake_case ( __SCREAMING_SNAKE_CASE ): a_ : str = (UnCLIPScheduler,) def UpperCAmelCase__ ( self , **__UpperCAmelCa...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'MIT/ast-finetuned-audioset-10-10-0.4593': ( 'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c...
303
0
"""simple docstring""" import argparse from collections import defaultdict import yaml UpperCamelCase_ = 'docs/source/en/_toctree.yml' def UpperCamelCase ( UpperCAmelCase ) ->Any: """simple docstring""" a_ = defaultdict(_a ) a_ = [] a_ = [] for doc in d...
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"""simple docstring""" from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'xlm-roberta-base': 'https://hugging...
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"""simple docstring""" import datasets from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py UpperCamelCase_ = """\ @INPROCEEDINGS{Papineni02bleu:a, author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu}, title = {BLEU: a M...
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"""simple docstring""" import unittest from transformers import LiltConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common i...
303
0
"""simple docstring""" import argparse import os from accelerate.utils import ComputeEnvironment from .cluster import get_cluster_input from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file # noqa: F401 from .config_utils import _ask_field, _ask_options, _con...
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"""simple docstring""" from __future__ import annotations import inspect import unittest from math import floor import numpy as np from transformers import CvtConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_visi...
303
0
from __future__ import annotations import numpy as np from numpy import floataa from numpy.typing import NDArray def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , ) ->list[float]: """simple docstring""" a_ = coefficient_matrix.shape a_ = ...
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"""simple docstring""" import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class snake_case ( SCREAMING_SNAKE_CASE_ ): a_ : Dict = """Speech2TextFeatureExtractor""" a_ : str = """Speech2TextTokeni...
303
0
"""simple docstring""" import logging from pathlib import Path import numpy as np import pytorch_lightning as pl import torch from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint from pytorch_lightning.utilities import rank_zero_only from utils_rag import save_json def UpperCamelCase ( Upp...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'], } try: if not is_torch_available(): raise Option...
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"""simple docstring""" import itertools import math def UpperCamelCase ( UpperCAmelCase ) ->bool: """simple docstring""" 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...
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"""simple docstring""" from typing import TYPE_CHECKING from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'], 'feature_extraction_mctct': ['MCTCTFeatureExtractor'], ...
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"""simple docstring""" from collections import OrderedDict from typing import TYPE_CHECKING, Any, List, Mapping, Optional from packaging import version if TYPE_CHECKING: from ... import PreTrainedTokenizer, TensorType from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWit...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) UpperCamelCase_ = { 'configuration_swiftformer': [ 'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwiftFormerConfig', 'Swif...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCamelCase_ = { "configuration_data2vec_audio": ["DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP", "Data2VecAudioConfig"], "configuration_da...
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"""simple docstring""" # Usage: # ./gen-card-allenai-wmt16.py import os from pathlib import Path def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->List[Any]: """simple docstring""" a_ = { "en": "Machine learning is great, isn't ...
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"""simple docstring""" import os import unittest from tempfile import TemporaryDirectory import torch import torch.nn as nn from accelerate.utils import ( OffloadedWeightsLoader, extract_submodules_state_dict, load_offloaded_weight, offload_state_dict, offload_weight, ) class snake...
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"""simple docstring""" def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->int: """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation(UpperCAmelCase , n - 1 , UpperCAmelCase ) * a) % mod else: ...
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