示例#1
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]

train_dataset = AmbiLocalFeatDataset(
    iccv_res_dir=iccv_res_dir,
    image_dir=cambridge_img_dir,
    lmdb_paths=lmdb_img_cache,
    dataset_list=dataset_list,
    downsample_scale=0.5,
    sampling_num=30,
    sample_res_cache='/mnt/Exp_5/AmbiguousData_pg/temp_cache.bin',
    sub_graph_nodes=24)

# set train parameters
train_params = TrainParameters()
train_params.MAX_EPOCHS = 20
train_params.START_LR = 1.0e-4
train_params.DEV_IDS = [0, 1]
train_params.LOADER_BATCH_SIZE = 1
train_params.LOADER_NUM_THREADS = 0
train_params.VALID_STEPS = 5000
train_params.MAX_VALID_BATCHES_NUM = 20
train_params.CHECKPOINT_STEPS = 6000
train_params.VERBOSE_MODE = True
train_params.NAME_TAG = 'test_gat_cluster'

box = LocalGlobalGATTrainBox(train_params=train_params,
                             ckpt_path_dict=checkpoint_dict)

train_loader = dataloader.DataLoader(train_dataset,
                                     batch_size=1,
                                     shuffle=False,
示例#2
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import pickle
import torch
import torchtext
from trainbox import DPCNNTrainBox
import numpy as np

# [1]
""" Train Parameters ---------------------------------------------------------------------------------------------------
"""
# toggle `DEBUG` to disable logger (won't dump to disk)
DEBUG = False

# set train parameters
train_params = TrainParameters()
train_params.MAX_EPOCHS = 10
train_params.START_LR = 0.01
train_params.DEV_IDS = [0]
train_params.LOADER_BATCH_SIZE = 100
train_params.LOADER_NUM_THREADS = 0
train_params.VALID_STEPS = 250
train_params.MAX_VALID_BATCHES_NUM = 50
train_params.CHECKPOINT_STEPS = 3000
train_params.VERBOSE_MODE = True
train_params.LOADER_VALID_BATCH_SIZE = train_params.LOADER_BATCH_SIZE
train_params.LR_DECAY_FACTOR = 0.1
train_params.LR_DECAY_STEPS = 8

# specific unique description for current training experiments
train_params.NAME_TAG = 'dpcnn'
train_params.DESCRIPTION = 'Initial eval'