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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_openai.py
# coding=utf-8 # Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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...
30,836
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py
CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/configuration_auto.py
# coding=utf-8 # Copyright 2018 The HuggingFace Inc. team. # # 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 # # Unless required by applicable...
8,111
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/tokenization_bert.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # # 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/LICEN...
22,451
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/configuration_ctrl.py
# coding=utf-8 # Copyright 2018 Salesforce and HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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 # # htt...
5,775
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_auto.py
# coding=utf-8 # Copyright 2018 The HuggingFace Inc. team. # # 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 # # Unless required by applicable...
36,985
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/tokenization_xlnet.py
# coding=utf-8 # Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team. # # 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://ww...
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/tokenization_distilbert.py
# coding=utf-8 # Copyright 2018 The HuggingFace Inc. team. # # 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 # # Unless required by applicable...
2,438
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/configuration_transfo_xl.py
# coding=utf-8 # Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the Lice...
6,819
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/file_utils.py
""" Utilities for working with the local dataset cache. This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp Copyright by the AllenNLP authors. """ from __future__ import (absolute_import, division, print_function, unicode_literals) import sys import json import logging import os impor...
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/__init__.py
__version__ = "2.1.1" # Work around to update TensorFlow's absl.logging threshold which alters the # default Python logging output behavior when present. # see: https://github.com/abseil/abseil-py/issues/99 # and: https://github.com/tensorflow/tensorflow/issues/26691#issuecomment-500369493 try: import absl.logging...
5,761
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/configuration_gpt2.py
# coding=utf-8 # Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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...
6,053
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/tokenization_gpt2.py
# coding=utf-8 # Copyright 2018 The Open AI Team Authors and The HuggingFace Inc. team. # # 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 # # ...
9,802
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/configuration_roberta.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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 cop...
1,415
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/configuration_openai.py
# coding=utf-8 # Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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...
5,100
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_transfo_xl.py
# coding=utf-8 # Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the Lice...
39,657
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_albert.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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 cop...
54,163
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_xlnet.py
# coding=utf-8 # Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the Lice...
72,560
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_xlm.py
# coding=utf-8 # Copyright 2019-present, Facebook, Inc and the HuggingFace Inc. team. # # 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 # # Un...
45,543
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_ctrl.py
# coding=utf-8 # Copyright 2018 Salesforce and HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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 # # h...
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/tokenization_transfo_xl.py
# coding=utf-8 # Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the Lice...
21,824
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/tokenization_openai.py
# coding=utf-8 # Copyright 2018 The Open AI Team Authors and The HuggingFace Inc. team. # # 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 # # ...
7,784
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_transfo_xl_utilities.py
# coding=utf-8 # Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the Lice...
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/modeling_roberta.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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 cop...
25,678
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CLUE
CLUE-master/baselines/models_pytorch/classifier_pytorch/transformers/tokenization_utils.py
# coding=utf-8 # Copyright 2018 The Open AI Team Authors and The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # ...
54,979
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/google_albert_pytorch_modeling.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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...
22,556
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/run_c3.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team. # # 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/LICENS...
34,700
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/test_mrc.py
import argparse import collections import json import os from glob import glob import torch from torch.utils.data import TensorDataset, DataLoader from tqdm import tqdm from pytorch_modeling import BertConfig, BertForQuestionAnswering, ALBertConfig, ALBertForQA from google_albert_pytorch_modeling import AlbertConfig,...
7,116
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py
CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/run_mrc.py
import argparse import collections import json import os import random import numpy as np import torch from google_albert_pytorch_modeling import AlbertConfig, AlbertForMRC from preprocess.cmrc2018_evaluate import get_eval from pytorch_modeling import BertConfig, BertForQuestionAnswering, ALBertConfig, ALBertForQA fro...
13,603
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py
CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/pytorch_modeling.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. 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...
57,982
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130
py
CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/convert_tf_checkpoint_to_pytorch.py
# coding=utf-8 # Copyright 2018 The HugginFace Inc. team. # # 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 # # Unless required by applicable ...
5,188
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py
CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/test_multichoice_mrc.py
from __future__ import print_function import argparse import os from glob import glob import torch from google_albert_pytorch_modeling import AlbertConfig, AlbertForMultipleChoice from preprocess.CHID_preprocess import RawResult, get_final_predictions, write_predictions, \ generate_input from pytorch_modeling imp...
9,007
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/run_multichoice_mrc.py
""" @name = 'roberta_wwm_ext_large' @author = 'zhangxinrui' @time = '2019/11/15' roberta_wwm_ext_large 的baseline版本 coding=utf-8 Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team. Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. Licensed under the Apache License, Version 2.0 ...
16,489
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py
CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/tools/pytorch_optimization.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team. # # 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/LICENS...
8,435
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/tools/utils.py
import collections import os import re from glob import glob import tensorflow as tf import tensorflow.contrib.slim as slim import torch def check_args(args): args.setting_file = os.path.join(args.checkpoint_dir, args.setting_file) args.log_file = os.path.join(args.checkpoint_dir, args.log_file) os.maked...
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/tools/file_utils.py
""" Utilities for working with the local dataset cache. This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp Copyright by the AllenNLP authors. """ import json import logging import os import shutil import tempfile from functools import wraps from hashlib import sha256 from pathlib imp...
8,020
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/tools/official_tokenization.py
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team. # # 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/LICENS...
14,426
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/tools/zh_wiki.py
# -*- coding: utf-8 -*- # copy fom wikipedia zh2Hant = { '呆': '獃', "打印机": "印表機", '帮助文件': '說明檔案', "画": "畫", "龙": "竜", "板": "板", "表": "表", "才": "才", "丑": "醜", "出": "出", "淀": "澱", "冬": "冬", "范": "範", "丰": "豐", "刮": "刮", "后": "後", "胡": "胡", "回": "回", "伙": "夥", "姜": "薑", "借": "借", "克": "克", "困": "困", "漓": "漓", "里": "里", "帘...
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/tools/langconv.py
#!/usr/bin/env python # -*- coding: utf-8 -*- from copy import deepcopy try: import psyco psyco.full() except: pass from .zh_wiki import zh2Hant, zh2Hans import sys py3k = sys.version_info >= (3, 0, 0) if py3k: UEMPTY = '' else: _zh2Hant, _zh2Hans = {}, {} for old, new in ((zh2Hant, _zh2Han...
7,874
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/preprocess/DRCD_output.py
import collections import json import math from tqdm import tqdm from tools.official_tokenization import BasicTokenizer def write_predictions_topk(config, all_examples, all_features, all_results, n_best_size, max_answer_length, do_lower_case, output_prediction_file, ...
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/preprocess/CHID_preprocess.py
''' @author: zhangxinrui @name: dataset_roberta.py @date: 10/07/2019 ''' import collections import os import pickle import numpy as np import json from tqdm import tqdm try: import regex as re except Exception: import re RawResult = collections.namedtuple("RawResult", ["un...
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/preprocess/DRCD_preprocess.py
import collections import copy import json import os from tqdm import tqdm from tools.langconv import Converter SPIECE_UNDERLINE = '▁' def whitespace_tokenize(text): """Runs basic whitespace cleaning and splitting on a peice of text.""" text = text.strip() if not text: return [] tokens = tex...
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/preprocess/cmrc2018_output.py
import collections import json import math from tqdm import tqdm from tools.official_tokenization import BasicTokenizer def write_predictions_topk(FLAGS, all_examples, all_features, all_results, n_best_size, max_answer_length, output_prediction_file, output_nbest_file): _PrelimPredict...
19,623
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/preprocess/cmrc2018_preprocess.py
import collections import json import os from tqdm import tqdm from tools import official_tokenization as tokenization SPIECE_UNDERLINE = '▁' def _improve_answer_span(doc_tokens, input_start, input_end, tokenizer, orig_answer_text): """Returns tokenized answer spans that better match t...
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CLUE
CLUE-master/baselines/models_pytorch/mrc_pytorch/preprocess/cmrc2018_evaluate.py
# -*- coding: utf-8 -*- ''' Evaluation script for CMRC 2018 version: v5 - special Note: v5 - special: Evaluate on SQuAD-style CMRC 2018 Datasets v5: formatted output, add usage description v4: fixed segmentation issues ''' from __future__ import print_function import json import re from collections import OrderedDict ...
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SparseCoupledDictionaryLearning
SparseCoupledDictionaryLearning-master/args.py
# -*- coding: utf-8 -*- """SF DECONVOLVE ARGUMENTS This module sets the arguments for sf_deconvolve.py. :Author: Samuel Farrens <samuel.farrens@gmail.com> :Version: 2.4 :Date: 23/10/2017 """ import argparse as ap from argparse import ArgumentDefaultsHelpFormatter as formatter class ArgParser(ap.ArgumentParser)...
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SparseCoupledDictionaryLearning
SparseCoupledDictionaryLearning-master/CDLOps.py
"""SPARSE COUPLED DICTIONARY LEARNING Sumplementary Class and Methods for the execution of intermediate matrices (Lagrange multiplier matrices, sparse coding matrices) :Author: Nancy Panousopoulou <apanouso@ics.forth.gr> :Reference document: Konstantina Fotiadou, Grigorios Tsagkatakis, Panagiotos Tsakalides `` Lin...
3,834
27.198529
175
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SparseCoupledDictionaryLearning
SparseCoupledDictionaryLearning-master/AuxOps.py
"""SPARSE COUPLED DICTIONARY LEARNING Sumplementary Methods for the execution of intermediate matrices (Lagrange multiplier matrices, sparse coding matrices) :Author: Nancy Panousopoulou <apanouso@ics.forth.gr> :Reference document: Konstantina Fotiadou, Grigorios Tsagkatakis, Panagiotos Tsakalides `` Linear Inverse...
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SparseCoupledDictionaryLearning
SparseCoupledDictionaryLearning-master/SparseCoupledDictionaryTraining.py
"""SPARSE COUPLED DICTIONARY LEARNING The main script for execution :Author: Nancy Panousopoulou <apanouso@ics.forth.gr> ::Reference document: Konstantina Fotiadou, Grigorios Tsagkatakis, Panagiotos Tsakalides `` Linear Inverse Problems with Sparsity Constraints,'' DEDALE DELIVERABLE 3.1, 2016. :Date: December 2...
5,357
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py
pointnerf
pointnerf-master/options/train_options.py
from .base_options import BaseOptions class TrainOptions(BaseOptions): def initialize(self, parser): parser = BaseOptions.initialize(self, parser) self.is_train = True parser.add_argument( '--print_freq', type=int, default=100, help='frequen...
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pointnerf
pointnerf-master/options/base_options.py
import argparse import os from models import find_model_class_by_name from data import find_dataset_class_by_name import torch class BaseOptions: def initialize(self, parser: argparse.ArgumentParser): #================================ global ================================# parser.add_argument('-...
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pointnerf
pointnerf-master/options/__init__.py
from .train_options import TrainOptions from .test_options import TestOptions from .edit_options import EditOptions
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pointnerf
pointnerf-master/options/test_options.py
from .base_options import BaseOptions class TestOptions(BaseOptions): def initialize(self, parser): parser = BaseOptions.initialize(self, parser) self.is_train = False parser.add_argument('--test_num', type=int, default=1, help='test num') parser.add_argument('--test_num_step', type...
486
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pointnerf
pointnerf-master/options/edit_options.py
from .base_options import BaseOptions class EditOptions(BaseOptions): def initialize(self, parser): parser = BaseOptions.initialize(self, parser) self.is_train = False parser.add_argument('--neural_points_names', type=str, nargs='+', ...
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pointnerf
pointnerf-master/models/base_rendering_model.py
import torch import torch.nn as nn import torch.nn.functional as F import numpy as np from utils import format as fmt import os from .base_model import BaseModel from .rendering.diff_render_func import find_render_function, find_blend_function, find_tone_map, alpha_blend from .rendering.diff_ray_marching import find_r...
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pointnerf
pointnerf-master/models/mvs_points_volumetric_model.py
from .base_rendering_model import * from .neural_points_volumetric_model import NeuralPointsVolumetricModel from .neural_points.neural_points import NeuralPoints from .mvs.mvs_points_model import MvsPointsModel from .mvs import mvs_utils from. import base_model from .aggregators.point_aggregators import PointAggregator...
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py
pointnerf
pointnerf-master/models/base_model.py
import torch from torch import nn import os from .helpers.networks import get_scheduler class BaseModel: @staticmethod def modify_commandline_options(parser, is_train): return parser def name(self): return self.__class__.__name__ def initialize(self, opt): self.opt = opt ...
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pointnerf
pointnerf-master/models/__init__.py
import importlib from models.base_model import BaseModel def find_model_class_by_name(model_name): # Given the option --model [modelname], # the file "models/modelname_model.py" # will be imported. model_filename = "models." + model_name + "_model" modellib = importlib.import_module(model_filename...
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pointnerf
pointnerf-master/models/neural_points_volumetric_model.py
from .base_rendering_model import * from .neural_points.neural_points import NeuralPoints from .aggregators.point_aggregators import PointAggregator import os class NeuralPointsVolumetricModel(BaseRenderingModel): @staticmethod def modify_commandline_options(parser, is_train=True): BaseRenderingModel...
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pointnerf
pointnerf-master/models/neural_points/point_query.py
import torch import torch.nn import torch.nn.functional as F import os import numpy as np from numpy import dot from math import sqrt import matplotlib.pyplot as plt import pickle import time from models.rendering.diff_ray_marching import near_far_linear_ray_generation, near_far_disparity_linear_ray_generation parent_d...
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pointnerf-master/models/neural_points/query_point_indices_worldcoords.py
import os import numpy as np from numpy import dot from math import sqrt import pycuda from pycuda.compiler import SourceModule import pycuda.driver as drv import pycuda.gpuarray as gpuarray import matplotlib.pyplot as plt import torch import pickle import time from models.rendering.diff_ray_marching import near_far_li...
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pointnerf-master/models/neural_points/neural_points.py
import torch import torch.nn as nn from data.load_blender import load_blender_cloud import numpy as np from ..helpers.networks import init_seq, positional_encoding import matplotlib.pyplot as plt import torch.nn.utils.prune as prune_param class NeuralPoints(nn.Module): @staticmethod def modify_commandline_op...
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pointnerf-master/models/neural_points/__init__.py
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pointnerf-master/models/neural_points/query_point_indices.py
import os import numpy as np from numpy import dot from math import sqrt import pycuda from pycuda.compiler import SourceModule import pycuda.driver as drv import pycuda.gpuarray as gpuarray import matplotlib.pyplot as plt # from mpl_toolkits.mplot3d import Axes3D import torch import pickle import time # import cupy # ...
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pointnerf-master/models/depth_estimators/mvsnet.py
import torch import torch.nn as nn import torch.nn.functional as F from .module import * class FeatureNet(nn.Module): def __init__(self): super(FeatureNet, self).__init__() self.inplanes = 32 self.conv0 = ConvBnReLU(3, 8, 3, 1, 1) self.conv1 = ConvBnReLU(8, 8, 3, 1, 1) se...
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pointnerf-master/models/depth_estimators/module.py
import torch import torch.nn as nn import torch.nn.functional as F class ConvBnReLU(nn.Module): def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, pad=1): super(ConvBnReLU, self).__init__() self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride=stride, padding=pad...
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pointnerf-master/models/depth_estimators/__init__.py
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pointnerf-master/models/helpers/geometrics.py
import torch def homogenize(m): """Adds homogeneous coordinates to a [..., N,N] matrix, returning [..., N+1, N+1].""" assert m.shape[-1] == m.shape[-2] # Must be square n = m.shape[-1] eye_n_plus_1 = torch.eye(n + 1).cuda().expand(list(m.shape[:-2]) + [-1, -1]) extra_col = eye_n_plus_1[..., :-1, ...
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pointnerf-master/models/helpers/networks.py
import torch import torch.nn as nn from torch.nn import init import functools from torch.optim import lr_scheduler import torch.nn.functional as F import numpy as np def get_nonlinearity_layer(activation_type='PReLU'): if activation_type == 'ReLU': nonlinearity_layer = nn.ReLU(True) elif activation_ty...
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pointnerf-master/models/helpers/__init__.py
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pointnerf-master/models/rendering/diff_ray_marching.py
import torch import torch.nn as nn import torch.nn.functional as F import numpy as np def find_ray_generation_method(name): assert isinstance(name, str), 'ray generation method name must be string' if name == 'cube': return cube_ray_generation elif name == 'near_far_linear': return near_fa...
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pointnerf-master/models/rendering/__init__.py
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pointnerf-master/models/rendering/diff_render_func.py
import torch import torch.nn as nn import torch.nn.functional as F import numpy as np from utils import format as fmt def find_render_function(name): if name == 'radiance': return radiance_render elif name == 'white': return white_color raise RuntimeError('Unknown render function: ' + name...
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pointnerf
pointnerf-master/models/aggregators/point_aggregators.py
import torch import torch.nn as nn import numpy as np import torch.nn.functional as F from ..helpers.networks import init_seq, positional_encoding from utils.spherical import SphericalHarm_table as SphericalHarm from ..helpers.geometrics import compute_world2local_dist class PointAggregator(torch.nn.Module): @...
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pointnerf-master/models/aggregators/__init__.py
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pointnerf-master/models/mvs/renderer.py
import torch import torch.nn.functional as F from .mvs_utils import normal_vect, index_point_feature, build_color_volume def depth2dist(z_vals, cos_angle): # z_vals: [N_ray N_sample] device = z_vals.device dists = z_vals[..., 1:] - z_vals[..., :-1] dists = torch.cat([dists, torch.Tensor([1e10]).to(devi...
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pointnerf
pointnerf-master/models/mvs/mvs_utils.py
import os, torch, cv2, re import numpy as np from torch_scatter import scatter_min, segment_coo, scatter_mean from PIL import Image import torch.nn.functional as F import torchvision.transforms as T from functools import partial import matplotlib.pyplot as plt from scipy.spatial.transform import Rotation as R # Misc ...
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pointnerf-master/models/mvs/mvs_points_model.py
import torch import os from torch.utils.data import DataLoader import imageio # models from .models import * from .renderer import * from .mvs_utils import * from . import filter_utils from ..helpers.networks import init_seq from ..depth_estimators.mvsnet import MVSNet as Ofcl_MVSNet from torch.optim.lr_scheduler impo...
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pointnerf-master/models/mvs/filter_utils.py
import sys import os import pathlib # sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import torch.nn.functional as F import copy import torch import numpy as np import time from models.mvs import mvs_utils from tqdm import tqdm import cv2 from PIL import Image def reproject_with_depth(...
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pointnerf
pointnerf-master/models/mvs/models.py
import torch torch.autograd.set_detect_anomaly(True) import torch.nn as nn from .mvs_utils import * from .mvs_utils import homo_warp from inplace_abn import InPlaceABN from .renderer import run_network_mvs from ..depth_estimators.mvsnet import MVSNet as Ofcl_MVSNet device = torch.device("cuda" if torch.cuda.is_availab...
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pointnerf-master/run/editing.py
import sys import os import pathlib sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import glob import copy import torch import numpy as np import time from options import TrainOptions from options import EditOptions from data import create_data_loader, create_dataset from models import cr...
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pointnerf-master/run/evaluate.py
import os, sys, time, argparse, cv2 import numpy as np try: from skimage.measure import compare_ssim from skimage.measure import compare_psnr except: from skimage.metrics import structural_similarity from skimage.metrics import peak_signal_noise_ratio as compare_psnr def compare_ssim(gt, img, win_s...
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pointnerf-master/run/train_ft_nonstop.py
import sys import os import pathlib sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import glob import copy import torch import numpy as np import time from options import TrainOptions from data import create_data_loader, create_dataset from models import create_model from models.mvs.mvs_p...
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pointnerf-master/run/render_vid.py
import sys import os import pathlib sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import copy import torch import numpy as np import time from options import TestOptions from data import create_data_loader, create_dataset from models import create_model from utils.visualizer import Visu...
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pointnerf-master/run/train_ft.py
import sys import os import pathlib sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import glob import copy import torch import numpy as np import time from options import TrainOptions from data import create_data_loader, create_dataset from models import create_model from models.mvs.mvs_p...
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pointnerf-master/run/test_ft.py
import sys import os import pathlib sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import glob import copy import torch import numpy as np import time from options import TrainOptions from data import create_data_loader, create_dataset from models import create_model from models.mvs.mvs_p...
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pointnerf
pointnerf-master/run/train.py
import sys import os import pathlib sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import copy import torch import numpy as np import time from options import TrainOptions from data import create_data_loader, create_dataset from models import create_model from utils.visualizer import Vis...
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pointnerf
pointnerf-master/run/visualize.py
import sys import os import pathlib sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import copy import torch import numpy as np import time from options import TestOptions from data import create_data_loader, create_dataset from models import create_model from utils.visualizer import Visu...
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pointnerf-master/run/vis_grow_train.py
import sys import os import pathlib sys.path.append(os.path.join(pathlib.Path(__file__).parent.absolute(), '..')) import glob import copy import torch import numpy as np import time from options import TrainOptions from data import create_data_loader, create_dataset from models import create_model from models.mvs.mvs_p...
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pointnerf
pointnerf-master/utils/format.py
PURPLE = '\033[1;35;48m' CYAN = '\033[1;36;48m' BOLD = '\033[1;37;48m' BLUE = '\033[1;34;48m' GREEN = '\033[1;32;48m' YELLOW = '\033[1;33;48m' RED = '\033[1;31;48m' BLACK = '\033[1;30;48m' UNDERLINE = '\033[4;37;48m' END = '\033[1;37;0m'
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pointnerf-master/utils/visualizer.py
import numpy as np import os from PIL import Image import shutil from collections import OrderedDict import time import datetime import torch import imageio from utils.util import to8b from models.mvs.mvs_utils import * def mse2psnr(x): return -10.* torch.log(x)/np.log(10.) def save_image(img_array, filepath): a...
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pointnerf-master/utils/util.py
from __future__ import print_function import torch import numpy as np from PIL import Image import os from torchvision.utils import make_grid from os.path import join import torch.nn.functional as F import matplotlib as mpl import matplotlib.cm as cm import matplotlib.pyplot as plt from scipy.spatial.transform import R...
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pointnerf-master/utils/ncg_string.py
'''Manipulate strings''' def underscore2camelcase(s): assert s == s.lower(), 'Invalid underscore string: no upper case character is allowed, in "{}"'.format(s) assert all([x.isdigit() or x.isalpha() or x == '_' for x in s]),\ 'Invalid underscore, all character must be letters or numbers or underscore'...
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pointnerf-master/utils/spherical.py
import torch from scipy.special import sph_harm, lpmn, lpmv from scipy.special import factorial import numpy as np import math import time class SphericalHarm(object): def __init__(self, total_deg): self.total_deg = total_deg self.orderIds, self.lIds, self.mIds, self.num_at_deg, self.m0inorder, se...
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pointnerf
pointnerf-master/data/llff_ft_dataset.py
from models.mvs.mvs_utils import read_pfm import os import numpy as np import cv2 from PIL import Image import torch from torchvision import transforms as T import torchvision.transforms.functional as F from kornia import create_meshgrid import time import json from . import data_utils import glob from torch.utils.data...
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pointnerf
pointnerf-master/data/nerf_synth_ft_dataset.py
from models.mvs.mvs_utils import read_pfm import os import numpy as np import cv2 from PIL import Image import torch from torchvision import transforms as T import torchvision.transforms.functional as F from kornia import create_meshgrid import time import json from torch.utils.data import Dataset, DataLoader import t...
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pointnerf
pointnerf-master/data/dtu_dataset.py
from models.mvs.mvs_utils import read_pfm import os import numpy as np import cv2 from PIL import Image import torch from torchvision import transforms as T import torchvision.transforms.functional as F from torch.utils.data import Dataset, DataLoader import torch import os from PIL import Image import h5py from da...
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pointnerf-master/data/fitplane.py
from skspatial.objects import Plane from skspatial.objects import Points from skspatial.plotting import plot_3d from plyfile import PlyData, PlyElement import matplotlib.pyplot as plt import numpy as np # points = Points([[0, 0, 0], [1, 3, 5], [-5, 6, 3], [3, 6, 7], [-2, 6, 7]]) # plydata = PlyData.read("/home/xharlie...
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pointnerf-master/data/base_dataset.py
import torch.utils.data as data from PIL import Image class BaseDataset(data.Dataset): def __init__(self): super(BaseDataset, self).__init__() def name(self): return self.__class__.__name__ @staticmethod def modify_commandline_options(parser, is_train): return parser def...
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pointnerf-master/data/download-scannet.py
#!/usr/bin/env python # Downloads ScanNet public data release # Run with ./download-scannet.py (or python download-scannet.py on Windows) # -*- coding: utf-8 -*- import argparse import os import urllib.request #(for python3) import urllib import tempfile BASE_URL = 'http://kaldir.vc.in.tum.de/scannet/' TOS_URL = BASE_...
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pointnerf-master/data/dtu_ft_dataset.py
from models.mvs.mvs_utils import read_pfm import os import numpy as np import cv2 from PIL import Image import torch from torchvision import transforms as T import torchvision.transforms.functional as F from kornia import create_meshgrid import time import itertools import random from torch.utils.data import Dataset, D...
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