repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/preprocess.py | # coding=utf-8
| 15 | 7 | 14 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/universal_datamodule/universal_datamodule.py | from pytorch_lightning import LightningDataModule
from typing import Optional
from torch.utils.data import DataLoader, DistributedSampler
from fengshen.models.megatron import mpu
def get_consume_samples(data_model: LightningDataModule) -> int:
if hasattr(data_model.trainer.lightning_module, 'consumed_samples'):
... | 7,829 | 40.210526 | 112 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/universal_datamodule/universal_sampler.py | # coding=utf-8
# Copyright (c) 2020, 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 5,181 | 40.126984 | 89 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/universal_datamodule/__init__.py | from .universal_datamodule import UniversalDataModule
from .universal_sampler import PretrainingSampler, PretrainingRandomSampler
__all__ = ['UniversalDataModule', 'PretrainingSampler', 'PretrainingRandomSampler']
| 215 | 42.2 | 83 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/mmap_dataloader/mmap_index_dataset.py | import numpy as np
import torch
from typing import List
from torch.utils.data import Dataset
class MMapIndexDataset(Dataset):
# datapaths 是所有的内存映射文件的路径
# input_tensor_name 是输入的tensor的名字 例如 ['input_ids'] 会存储在对应的文件里面
def __init__(self, datapaths: List[str], input_tensor_name: List[str]):
dict_idx_fp... | 1,815 | 32.62963 | 81 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/mmap_dataloader/mmap_datamodule.py | from typing import Optional
from pytorch_lightning import LightningDataModule
from torch.utils.data import DataLoader
from fengshen.data.mmap_index_dataset import MMapIndexDataset
class MMapDataModule(LightningDataModule):
@ staticmethod
def add_data_specific_args(parent_args):
parser = parent_args.ad... | 2,461 | 34.681159 | 94 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/dreambooth_datasets/dreambooth_datasets.py | # -*- encoding: utf-8 -*-
'''
Copyright 2022 The International Digital Economy Academy (IDEA). CCNL 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.o... | 6,386 | 33.711957 | 118 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/t5_dataloader/t5_datasets.py | # coding=utf8
import json
from torch.utils.data import Dataset, DataLoader
from tqdm import tqdm
from transformers import BertTokenizer, MT5Config, MT5Tokenizer, BatchEncoding
import torch
import pytorch_lightning as pl
import numpy as np
from itertools import chain
import sys
sys.path.append('../../')
def compute_in... | 25,946 | 45.087034 | 127 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/t5_dataloader/t5_gen_datasets.py | # -*- encoding: utf-8 -*-
'''
@File : t5_gen_datasets.py
@Time : 2022/10/24 19:29
@Author : He Junqing
@Version : 1.0
@Contact : [email protected]
@License : (C)Copyright 2022-2023, CCNL-IDEA
'''
from logging import exception
from transformers import (
BertTokenizer,
MT5Config,
MT5To... | 13,701 | 33.954082 | 101 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/taiyi_stable_diffusion_datasets/taiyi_datasets.py | from torch.utils.data import Dataset, ConcatDataset
import os
from concurrent.futures import ProcessPoolExecutor
import pandas as pd
def add_data_args(parent_args):
parser = parent_args.add_argument_group('taiyi stable diffusion data args')
# 支持传入多个路径，分别加载
parser.add_argument(
"--datasets_path", t... | 6,417 | 35.885057 | 117 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/task_dataloader/medicalQADataset.py | # coding=utf8
import os
import pytorch_lightning as pl
from torch.utils.data import DataLoader, Dataset
from tqdm import tqdm
from transformers import AutoTokenizer
class GPT2QADataset(Dataset):
'''
Dataset Used for yuyuan medical qa task.
Just surpport small datasets, when deal with large datasets it may... | 5,285 | 37.304348 | 102 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/task_dataloader/task_datasets.py | # coding=utf8
from torch.utils.data import Dataset, DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
import json
import torch
import pytorch_lightning as pl
import os
class AbstractCollator:
"""
collector for summary task
"""
def __init__(self, tokenizer, max_enc_length, max_de... | 7,832 | 36.84058 | 114 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/task_dataloader/__init__.py | # coding=utf-8
from .task_datasets import LCSTSDataModel, LCSTSDataset
__all__ = ['LCSTSDataModel', 'LCSTSDataset']
| 116 | 28.25 | 55 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/hubert/hubert_dataset.py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import itertools
import logging
import os
import sys
from typing import Any, List, Optional, Union
import numpy as np
import torch
import to... | 13,124 | 35.256906 | 86 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/clip_dataloader/flickr.py | from torch.utils.data import Dataset, DataLoader
from torchvision.transforms import Normalize, Compose, RandomResizedCrop, InterpolationMode, ToTensor, Resize, \
CenterCrop
from transformers import BertTokenizer
import pytorch_lightning as pl
from PIL import Image
import os
class flickr30k_CNA(Dataset):
def _... | 3,812 | 34.971698 | 112 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/megatron_dataloader/bart_dataset.py | """BART Style dataset. Modified from fairseq."""
import numpy as np
import torch
import math
import re
from fengshen.data.megatron_dataloader.dataset_utils import (
get_samples_mapping
)
class BartDataset(torch.utils.data.Dataset):
def __init__(self, name, indexed_dataset, data_prefix,
num_... | 18,396 | 40.434685 | 103 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/megatron_dataloader/dataset_utils.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors, and NVIDIA.
#
# 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 ... | 30,965 | 38.247148 | 103 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/megatron_dataloader/utils.py | # coding=utf-8
# Copyright (c) 2020, 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 903 | 35.16 | 74 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/megatron_dataloader/bert_dataset.py | # coding=utf-8
# Copyright (c) 2020, 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 8,121 | 40.228426 | 94 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/megatron_dataloader/blendable_dataset.py | # coding=utf-8
# Copyright (c) 2020, 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 2,208 | 32.984615 | 78 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/megatron_dataloader/__init__.py | from . import indexed_dataset
| 30 | 14.5 | 29 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/megatron_dataloader/indexed_dataset.py | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# copied from fairseq/fairseq/data/indexed_dataset.py
# Removed IndexedRawTextDataset since it relied on Fairseq dictionary
# other slight mo... | 18,859 | 31.1843 | 80 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/data_utils/sop_utils.py |
# copy from megatron
def get_a_and_b_segments(sample, np_rng):
"""Divide sample into a and b segments."""
# Number of sentences in the sample.
n_sentences = len(sample)
# Make sure we always have two sentences.
assert n_sentences > 1, 'make sure each sample has at least two sentences.'
# Firs... | 912 | 26.666667 | 79 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/data_utils/common_utils.py | def padding_to_maxlength(ids, max_length, pad_id):
cur_len = len(ids)
len_diff = max_length - len(ids)
return ids + [pad_id] * len_diff, [1] * cur_len + [0] * len_diff
| 180 | 35.2 | 68 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/data_utils/truncate_utils.py |
def truncate_segments(tokens_a, tokens_b, len_a, len_b, max_num_tokens, np_rng):
"""Truncates a pair of sequences to a maximum sequence length."""
# print(len_a, len_b, max_num_tokens)
assert len_a > 0
if len_a + len_b <= max_num_tokens:
return False
while len_a + len_b > max_num_tokens:
... | 579 | 28 | 80 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/data_utils/token_type_utils.py | def create_tokens_and_tokentypes(tokens_a, tokens_b, cls_id, sep_id):
"""Merge segments A and B, add [CLS] and [SEP] and build tokentypes."""
tokens = []
tokentypes = []
# [CLS].
tokens.append(cls_id)
tokentypes.append(0)
# Segment A.
for token in tokens_a:
tokens.append(token)
... | 639 | 23.615385 | 75 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/data_utils/sentence_split.py | import re
class ChineseSentenceSplitter(object):
def merge_symmetry(self, sentences, symmetry=('“', '”')):
# '''合并对称符号，如双引号'''
effective_ = []
merged = True
for index in range(len(sentences)):
if symmetry[0] in sentences[index] and symmetry[1] not in sentences[index]:
... | 1,457 | 39.5 | 108 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/data_utils/mask_utils.py | import collections
import numpy as np
MaskedLmInstance = collections.namedtuple("MaskedLmInstance",
["index", "label"])
def is_start_piece(piece):
"""Check if the current word piece is the starting piece (BERT)."""
# When a word has been split into
# WordPieces,... | 11,400 | 38.863636 | 103 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/sequence_tagging_dataloader/sequence_tagging_collator.py | from dataclasses import dataclass
from torch.utils.data._utils.collate import default_collate
import copy
import torch
import numpy as np
@dataclass
class CollatorForLinear:
args = None
tokenizer = None
label2id = None
def __call__(self, samples):
cls_token = "[CLS]"
sep_token = "[SEP... | 10,403 | 36.970803 | 133 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/sequence_tagging_dataloader/sequence_tagging_datasets.py | from torch.utils.data import Dataset
from fengshen.metric.utils_ner import get_entities
import os
def get_datasets(args):
processor = DataProcessor(args.data_dir, args.decode_type)
train_data = TaskDataset(processor=processor, mode="train")
valid_data = TaskDataset(processor=processor, mode="dev")
te... | 4,409 | 37.017241 | 108 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/bert_dataloader/preprocessing.py | import re
import json
import multiprocessing
from tqdm import tqdm
from pathlib import Path
from itertools import chain
_SPLIT_DATA_PATH = '/data1/datas/wudao_180g'
def cut_sent(path):
"""
中文分句，默认？、。、！、省略号分句，考虑双引号包裹的句子
采用分割替换的方式
"""
path = Path(path)
# print(path)
save_path = str(Path('/d... | 3,724 | 32.558559 | 130 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/data/bert_dataloader/load.py | import os
import re
from pathlib import Path
import glob
from tqdm import tqdm
from contextlib import ExitStack
import datasets
import multiprocessing
from typing import cast, TextIO
from itertools import chain
import json
from concurrent.futures import ProcessPoolExecutor
from random import shuffle
from pytorch_lightn... | 6,756 | 32.616915 | 124 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/pipelines/base.py | _CONFIG_MODEL_TYPE = 'fengshen_model_type'
_CONFIG_TOKENIZER_TYPE = 'fengshen_tokenizer_type'
| 94 | 30.666667 | 50 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/pipelines/test.py | from fengshen.pipelines.text_classification import TextClassificationPipeline
import argparse
from datasets import load_dataset
# 预测 支持批量
# pipe = TextClassificationPipeline(
# model='/data/gaoxinyu/pretrained_model/deberta-base-sp', device=-1)
# print(pipe(['今天心情不好</s>今天很开心', '今天心情很好</s>今天很开心']))
# 训练 支持各种超参调整
... | 717 | 33.190476 | 107 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/pipelines/test_tagging.py | from fengshen.pipelines.sequence_tagging import SequenceTaggingPipeline
import argparse
import os
total_parser = argparse.ArgumentParser("test")
total_parser = SequenceTaggingPipeline.add_pipeline_specific_args(total_parser)
args = total_parser.parse_args()
args.data_dir="/cognitive_comp/lujunyu/data_zh/NER_Aligned/we... | 805 | 34.043478 | 112 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/pipelines/sequence_tagging.py | import torch
import torch.nn.functional as F
from torch.utils.data._utils.collate import default_collate
from dataclasses import dataclass
from typing import Dict, List, Union
from fengshen.models.tagging_models.bert_for_tagging import BertLinear,BertCrf,BertSpan,BertBiaffine
from fengshen.data.sequence_tagging_datalo... | 12,608 | 39.156051 | 154 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/pipelines/text_classification.py | import torch
from torch.utils.data._utils.collate import default_collate
from dataclasses import dataclass
from typing import Dict, List
from .base import (
_CONFIG_MODEL_TYPE,
_CONFIG_TOKENIZER_TYPE)
from fengshen.models.roformer import RoFormerForSequenceClassification
from fengshen.models.longformer import L... | 9,274 | 38.468085 | 106 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/pipelines/tcbert.py | # coding=utf-8
# Copyright 2021 The IDEA Authors. 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
# Unless required by a... | 5,390 | 38.350365 | 116 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/pipelines/multiplechoice.py | # coding=utf-8
# Copyright 2021 The IDEA Authors. 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
# Unless required by a... | 7,967 | 39.653061 | 116 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/pipelines/information_extraction.py | from logging import basicConfig
import torch
from torch import nn
import json
from tqdm import tqdm
import os
import numpy as np
from transformers import BertTokenizer
import pytorch_lightning as pl
from pytorch_lightning import trainer, loggers
from transformers import AlbertTokenizer
from transformers import AutoCon... | 4,151 | 36.071429 | 127 | py |
TFusion | TFusion-master/__init__.py | 1 | 0 | 0 | py | |
TFusion | TFusion-master/TrackViz/pre_process/market_answer_predict.py | from profile.fusion_param import ctrl_msg, get_fusion_param
from train.st_filter import train_tracks
from util.file_helper import read_lines
import numpy as np
from util.serialize import pickle_save
def save_market_train_truth():
ctrl_msg['data_folder_path'] = 'market_market-train'
fusion_param = get_fusion... | 8,645 | 40.171429 | 92 | py |
TFusion | TFusion-master/TrackViz/pre_process/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/TrackViz/profile/fusion_param.py | ctrl_msg = {
'data_folder_path': 'market_market-test',
'cv_num': 0,
'ep': 0,
'en': 0
}
update_msg = {}
def get_fusion_param():
origin_dict = {
'renew_pid_path': 'data/' + ctrl_msg['data_folder_path'] + '/renew_pid.log',
'renew_ac_path': 'data/' + ctrl_msg['data_folder_path'] + '/r... | 3,550 | 52.80303 | 130 | py |
TFusion | TFusion-master/TrackViz/profile/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/TrackViz/post_process/grid_summary.py | from util.file_helper import read_lines, write
def avg_acc(grid_eval_path):
grid_infos = read_lines(grid_eval_path)
before_vision_accs = [0.0, 0.0, 0.0]
before_fusion_accs = [0.0, 0.0, 0.0]
after_vision_accs = [0.0, 0.0, 0.0]
after_fusion_accs = [0.0, 0.0, 0.0]
i_cv_cnt = 0
for i, grid_inf... | 1,724 | 44.394737 | 144 | py |
TFusion | TFusion-master/TrackViz/post_process/track_prob.py | # coding=utf-8
from util.serialize import pickle_load
def binary_search(a, target):
# 不同于普通的二分查找，目标是寻找target最适合的index
low = 0
high = len(a) - 1
while low <= high:
mid = (low + high) // 2
mid_val = a[mid]
if mid_val < target:
low = mid + 1
elif mid_val > tar... | 2,487 | 36.134328 | 111 | py |
TFusion | TFusion-master/TrackViz/post_process/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/TrackViz/util/str_helper.py | def folder(path):
final_slash_idx = -1
for i, c in enumerate(path):
if c == '/':
final_slash_idx = i
if final_slash_idx == -1:
return path
else:
return path[: final_slash_idx]
if __name__ == '__main__':
print(folder('data/top10/test.txt'))
| 298 | 20.357143 | 40 | py |
TFusion | TFusion-master/TrackViz/util/file_helper.py | import os
def write_line(path, content):
with open(path, "a+") as dst_file:
dst_file.write(content + '\n')
def write(path, content):
with open(path, "a+") as dst_file:
dst_file.write(content)
def read_lines(path):
with open(path) as f:
content = list()
while 1:
... | 1,627 | 20.706667 | 40 | py |
TFusion | TFusion-master/TrackViz/util/viz.py | import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
def draw_line(y_s, x_s, y_label, x_label, y_titles, title, line_color=None):
# plt.subplots()
plt.subplots(figsize=(6, 5))
sns.set(font_scale=2.4)
line_styles = ['--', '-']
for i in range(len(y_s)):
plt.plot(x_s, y_s[... | 1,198 | 32.305556 | 106 | py |
TFusion | TFusion-master/TrackViz/util/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/TrackViz/util/serialize.py | import os
import pickle
import random
def random6():
return random.randint(100000, 999999)
def pickle_save(path, obj):
try:
with open(path, 'wb') as f:
pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)
except Exception as e:
print('Unable to save data to', path, e)
return ... | 493 | 18 | 56 | py |
TFusion | TFusion-master/TrackViz/train/st_estim.py | #coding=utf-8
from random import randint
import shutil
from profile.fusion_param import ctrl_msg
from util.file_helper import read_lines, safe_remove, safe_mkdir
from util.serialize import pickle_save
from util.str_helper import folder
def prepare_rand_folder(fusion_param):
rand_predict_path = fusion_param['ren... | 3,995 | 41.063158 | 120 | py |
TFusion | TFusion-master/TrackViz/train/st_filter.py | # coding=utf-8
from post_process.track_prob import track_score
from profile.fusion_param import get_fusion_param, ctrl_msg
from util.file_helper import read_lines, read_lines_and, write, safe_remove
from util.serialize import pickle_load
import numpy as np
import os
def smooth_score(c1, c2, time1, time2, camera_delt... | 19,506 | 45.556086 | 145 | py |
TFusion | TFusion-master/TrackViz/train/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/TrackViz/ctrl/transfer.py | import os
from ctrl.img_st_fusion import init_strict_img_st_fusion
from profile.fusion_param import ctrl_msg, get_fusion_param
from util.file_helper import safe_mkdir
def fusion_dir_prepare(source, target):
fusion_data_path = '/home/cwh/coding/TrackViz/data/'
fusion_train_dir = fusion_data_path + '/' + sourc... | 6,036 | 46.535433 | 135 | py |
TFusion | TFusion-master/TrackViz/ctrl/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/TrackViz/ctrl/img_st_fusion.py | #coding=utf-8
import shutil
import os
from profile.fusion_param import get_fusion_param, ctrl_msg
from train.st_estim import get_predict_delta_tracks, prepare_rand_folder, prepare_diff_folder
from train.st_filter import fusion_st_img_ranker, fusion_st_gallery_ranker
# need to run on src directory
from util.file_help... | 8,198 | 39.191176 | 107 | py |
TFusion | TFusion-master/rank-reid/rank_reid.py | import sys
from baseline.evaluate import market_result_eval, grid_result_eval
from pretrain.eval import train_pair_predict,test_pair_predict, train_rank_predict, test_rank_predict
from transfer.simple_rank_transfer import rank_transfer_2dataset
def get_source_target_info(source, target):
source_model_path = '/ho... | 5,831 | 52.018182 | 160 | py |
TFusion | TFusion-master/rank-reid/transfer/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/rank-reid/transfer/simple_rank_transfer.py | import os
import utils.cuda_util
import numpy as np
from keras import Input
from keras import backend as K
from keras.applications.resnet50 import preprocess_input, ResNet50
from keras.callbacks import EarlyStopping, ReduceLROnPlateau
from keras.engine import Model
from keras.layers import Flatten, Lambda, Dense, Conv2... | 11,654 | 43.484733 | 136 | py |
TFusion | TFusion-master/rank-reid/baseline/evaluate.py | from __future__ import division, print_function, absolute_import
import os
import numpy as np
import tensorflow as tf
from keras.applications.resnet50 import preprocess_input
from keras.backend.tensorflow_backend import set_session
from keras.models import Model
from keras.preprocessing import image
from utils.file_... | 7,555 | 31.568966 | 96 | py |
TFusion | TFusion-master/rank-reid/baseline/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/rank-reid/baseline/train.py | from __future__ import division, print_function, absolute_import
import os
from random import shuffle
import numpy as np
import tensorflow as tf
from keras.applications.resnet50 import ResNet50
from keras.applications.resnet50 import preprocess_input
from keras.backend.tensorflow_backend import set_session
from keras... | 5,745 | 33.407186 | 120 | py |
TFusion | TFusion-master/rank-reid/pretrain/pair_train.py | import os
import numpy as np
from keras import Input
from keras import backend as K
from keras.applications.resnet50 import preprocess_input
from keras.callbacks import EarlyStopping, ReduceLROnPlateau
from keras.engine import Model
from keras.layers import Lambda, Dense, Dropout, Flatten
from keras.models import load... | 10,663 | 40.173745 | 121 | py |
TFusion | TFusion-master/rank-reid/pretrain/eval.py | # coding=utf-8
import os
from keras import backend as K
from keras.engine import Model
from keras.models import load_model
from keras.preprocessing import image
from baseline.evaluate import train_predict, test_predict, grid_result_eval, market_result_eval
from transfer.simple_rank_transfer import cross_entropy_loss
... | 4,102 | 38.07619 | 108 | py |
TFusion | TFusion-master/rank-reid/pretrain/__init__.py | 0 | 0 | 0 | py | |
TFusion | TFusion-master/rank-reid/utils/file_helper.py | import os
def write_line(path, content):
with open(path, "a+") as dst_file:
dst_file.write(content + '\n')
def write(path, content):
with open(path, "a+") as dst_file:
dst_file.write(content)
def read_lines(path):
with open(path) as f:
content = list()
while 1:
... | 1,627 | 20.706667 | 40 | py |
TFusion | TFusion-master/rank-reid/utils/cuda_util.py | import os
from keras.backend import set_session
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" # see issue #152
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
import tensorflow as tf
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.6
set_session(tf.Session(config=config)) | 302 | 26.545455 | 64 | py |
TFusion | TFusion-master/rank-reid/utils/__init__.py | 0 | 0 | 0 | py | |
hyperopt | hyperopt-master/setup.py | import re
import setuptools
with open("hyperopt/__init__.py", encoding="utf8") as f:
version = re.search(r"__version__ = \"(.*?)\"", f.read()).group(1)
if version is None:
raise ImportError("Could not find __version__ in hyperopt/__init__.py")
setuptools.setup(
name="hyperopt",
version=versio... | 2,132 | 32.857143 | 87 | py |
hyperopt | hyperopt-master/docs/autogen.py | # This file has been taken from Keras' `docs` module found here:
# https://github.com/keras-team/keras/blob/master/docs/autogen.py
#
import re
import inspect
import os
import shutil
EXCLUDE = {}
PAGES = [
# {
# 'page': 'target.md',
# 'classes': [
# ],
# 'functions': [
# ... | 12,407 | 32.994521 | 87 | py |
hyperopt | hyperopt-master/docs/__init__.py | 0 | 0 | 0 | py | |
hyperopt | hyperopt-master/hyperopt/main.py | #!/usr/bin/env python
"""
Entry point for bin/* scripts
"""
from future import standard_library
import logging
import os
from . import utils
from .base import SerialExperiment
import sys
standard_library.install_aliases()
logger = logging.getLogger(__name__)
try:
import cloudpickle as pickler
except Exception a... | 3,818 | 26.875912 | 88 | py |
hyperopt | hyperopt-master/hyperopt/base.py | """Base classes / Design
The design is that there are three components fitting together in this project:
- Trials - a list of documents including at least sub-documents:
['spec'] - the specification of hyper-parameters for a job
['result'] - the result of Domain.evaluate(). Typically includes:
['statu... | 34,793 | 33.552135 | 93 | py |
hyperopt | hyperopt-master/hyperopt/tpe.py | """
Graphical model (GM)-based optimization algorithm using Theano
"""
from past.utils import old_div
import logging
import time
import numpy as np
from scipy.special import erf
from . import pyll
from .pyll import scope
from .pyll.stochastic import implicit_stochastic
from .base import miscs_to_idxs_vals
from .base ... | 32,594 | 33.059561 | 93 | py |
hyperopt | hyperopt-master/hyperopt/mongoexp.py | """
Mongodb-based Trials Object
===========================
Components involved:
- mongo
e.g. mongod ...
- driver
e.g. hyperopt-mongo-search mongo://address bandit_json bandit_algo_json
- worker
e.g. hyperopt-mongo-worker --loop mongo://address
Mongo
=====
Mongo (daemon process mongod) is used for IP... | 49,421 | 33.976645 | 115 | py |
hyperopt | hyperopt-master/hyperopt/criteria.py | """Criteria for Bayesian optimization
"""
from past.utils import old_div
import numpy as np
import scipy.stats
def EI_empirical(samples, thresh):
"""Expected Improvement over threshold from samples
(See example usage in EI_gaussian_empirical)
"""
improvement = np.maximum(samples - thresh, 0)
retu... | 2,655 | 26.381443 | 78 | py |
hyperopt | hyperopt-master/hyperopt/rdists.py | """
Extra distributions to complement scipy.stats
"""
from past.utils import old_div
import numpy as np
import numpy.random as mtrand
import scipy.stats
from scipy.stats import rv_continuous # , rv_discrete
from scipy.stats._continuous_distns import lognorm_gen as scipy_lognorm_gen
class loguniform_gen(rv_continuou... | 8,791 | 30.740072 | 82 | py |
hyperopt | hyperopt-master/hyperopt/exceptions.py | """
"""
class BadSearchSpace(Exception):
"""Something is wrong in the description of the search space"""
class DuplicateLabel(BadSearchSpace):
"""A search space included a duplicate label"""
class InvalidTrial(ValueError):
"""Non trial-like object used as Trial"""
def __init__(self, msg, obj):
... | 1,132 | 21.66 | 75 | py |
hyperopt | hyperopt-master/hyperopt/plotting.py | """
Functions to visualize an Experiment.
"""
import pickle
try:
unicode = unicode
except NameError:
basestring = (str, bytes)
else:
basestring = basestring
# -- don't import this here because it locks in the backend
# and we want the unittests to be able to set the backend
# TODO: this is really bad ... | 7,865 | 29.488372 | 119 | py |
hyperopt | hyperopt-master/hyperopt/pyll_utils.py | from past.builtins import basestring
from functools import partial, wraps
from .base import DuplicateLabel
from .pyll.base import Apply, Literal, MissingArgument
from .pyll import scope
from .pyll import as_apply
def validate_label(f):
@wraps(f)
def wrapper(label, *args, **kwargs):
is_real_string = is... | 7,429 | 28.601594 | 88 | py |
hyperopt | hyperopt-master/hyperopt/progress.py | """
Progress is reported using context managers.
A progress context manager takes an `initial` and a `total` argument
and should yield an object with an `update(n)` method.
"""
import contextlib
from tqdm import tqdm
from .std_out_err_redirect_tqdm import std_out_err_redirect_tqdm
@contextlib.contextmanager
def tq... | 898 | 22.051282 | 68 | py |
hyperopt | hyperopt-master/hyperopt/vectorize.py | import sys
import numpy as np
from .pyll import Apply
from .pyll import as_apply
from .pyll import dfs
from .pyll import toposort
from .pyll import scope
from .pyll import stochastic
stoch = stochastic.implicit_stochastic_symbols
def ERR(msg):
print("hyperopt.vectorize.ERR", msg, file=sys.stderr)
@scope.defi... | 16,760 | 37.619816 | 88 | py |
hyperopt | hyperopt-master/hyperopt/utils.py | from future import standard_library
from past.builtins import basestring
from past.utils import old_div
import datetime
import numpy as np
import logging
import os
import shutil
import sys
import uuid
import numpy
from . import pyll
from contextlib import contextmanager
standard_library.install_aliases()
def _get_ra... | 7,894 | 27.919414 | 125 | py |
hyperopt | hyperopt-master/hyperopt/hp.py | """
Support nicer user syntax:
from hyperopt import hp
hp.uniform('x', 0, 1)
"""
from .pyll_utils import hp_choice as choice
from .pyll_utils import hp_randint as randint
from .pyll_utils import hp_pchoice as pchoice
from .pyll_utils import hp_uniform as uniform
from .pyll_utils import hp_uniformint as uniform... | 671 | 32.6 | 53 | py |
hyperopt | hyperopt-master/hyperopt/graph_viz.py | """
Use graphviz's dot language to express the relationship between hyperparamters
in a search space.
"""
from future import standard_library
import io
from .pyll_utils import expr_to_config
standard_library.install_aliases()
def dot_hyperparameters(expr):
"""
Return a dot language specification of a graph... | 2,534 | 30.296296 | 83 | py |
hyperopt | hyperopt-master/hyperopt/spark.py | import copy
import threading
import time
import timeit
import traceback
from hyperopt import base, fmin, Trials
from hyperopt.base import validate_timeout, validate_loss_threshold
from hyperopt.utils import coarse_utcnow, _get_logger, _get_random_id
try:
from py4j.clientserver import ClientServer
from pyspark... | 23,095 | 39.02773 | 103 | py |
hyperopt | hyperopt-master/hyperopt/rand.py | """
Random search - presented as hyperopt.fmin_random
"""
import logging
import numpy as np
from . import pyll
from .base import miscs_update_idxs_vals
logger = logging.getLogger(__name__)
def suggest(new_ids, domain, trials, seed):
rng = np.random.default_rng(seed)
rval = []
for ii, new_id in enumerat... | 1,088 | 26.923077 | 86 | py |
hyperopt | hyperopt-master/hyperopt/atpe.py | """
Implements the ATPE algorithm. See
https://www.electricbrain.io/blog/learning-to-optimize
and
https://www.electricbrain.io/blog/optimizing-optimization to learn more
"""
__authors__ = "Bradley Arsenault"
__license__ = "3-clause BSD License"
__contact__ = "github.com/hyperopt/hyperopt"
from hyperop... | 67,630 | 40.721777 | 202 | py |
hyperopt | hyperopt-master/hyperopt/early_stop.py | import logging
logger = logging.getLogger(__name__)
def no_progress_loss(iteration_stop_count=20, percent_increase=0.0):
"""
Stop function that will stop after X iteration if the loss doesn't increase
Parameters
----------
iteration_stop_count: int
search will stop if the loss doesn't im... | 1,637 | 33.851064 | 111 | py |
hyperopt | hyperopt-master/hyperopt/std_out_err_redirect_tqdm.py | """Redirecting writing to tqdm (the progressbar).
See here: https://github.com/tqdm/tqdm#redirecting-writing
"""
import contextlib
import sys
from tqdm import tqdm
class DummyTqdmFile:
"""Dummy file-like that will write to tqdm."""
file = None
def __init__(self, file):
self.file = file
de... | 1,094 | 22.804348 | 65 | py |
hyperopt | hyperopt-master/hyperopt/__init__.py | from .base import STATUS_STRINGS
from .base import STATUS_NEW
from .base import STATUS_RUNNING
from .base import STATUS_SUSPENDED
from .base import STATUS_OK
from .base import STATUS_FAIL
from .base import JOB_STATES
from .base import JOB_STATE_NEW
from .base import JOB_STATE_RUNNING
from .base import JOB_STATE_DONE
f... | 909 | 20.666667 | 44 | py |
hyperopt | hyperopt-master/hyperopt/fmin.py | from future import standard_library
import functools
import inspect
import logging
import os
import sys
import time
from timeit import default_timer as timer
import numpy as np
from hyperopt import tpe, exceptions
from hyperopt.base import validate_timeout, validate_loss_threshold
from . import pyll
from .utils impo... | 22,699 | 35.495177 | 109 | py |
hyperopt | hyperopt-master/hyperopt/algobase.py | """ Support code for new-style search algorithms.
"""
import copy
from collections import deque
import numpy as np
from . import pyll
from .base import miscs_update_idxs_vals
__authors__ = "James Bergstra"
__license__ = "3-clause BSD License"
__contact__ = "github.com/hyperopt/hyperopt"
class ExprEvaluator:
de... | 10,344 | 39.096899 | 88 | py |
hyperopt | hyperopt-master/hyperopt/anneal.py | # TODO: add this to documentation
"""
Annealing algorithm for hyperopt
Annealing is a simple but effective variant on random search that
takes some advantage of a smooth response surface.
The simple (but not overly simple) code of simulated annealing makes this file
a good starting point for implementing new search a... | 14,079 | 34.288221 | 86 | py |
hyperopt | hyperopt-master/hyperopt/ipy.py | """Utilities for Parallel Model Selection with
on
Author: James Bergstra <[email protected]>
Licensed: MIT
"""
from time import sleep, time
import numpy as np
from .base import Trials
from .base import Domain
from .base import JOB_STATE_NEW
from .base import JOB_STATE_RUNNING
from .base import JOB_STATE_DONE
... | 8,500 | 32.868526 | 88 | py |
hyperopt | hyperopt-master/hyperopt/mix.py | import numpy as np
def suggest(new_ids, domain, trials, seed, p_suggest):
"""Return the result of a randomly-chosen suggest function
For example to search by sometimes using random search, sometimes anneal,
and sometimes tpe, type:
fmin(...,
algo=partial(mix.suggest,
... | 1,089 | 30.142857 | 77 | py |
hyperopt | hyperopt-master/hyperopt/sklearn.py | """Scikit-learn integration.
This class is based on :class:`sklearn.model_selection._search.BaseSearchCV` and
inspired by :class:sklearn.model_selection._search_successive_halving.BaseSuccessiveHalving`.
"""
import numpy as np
from sklearn.model_selection._search import is_classifier
from sklearn.model_selection._sea... | 9,643 | 34.19708 | 102 | py |
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