Python get_symbol_train Examples

Example #1

File: visualize_net.py Project: NCNU-OpenSource/What-are-you-

def net_visualization(network=None,
                      num_classes=None,
                      data_shape=None,
                      train=None,
                      output_dir=None,
                      print_net=False,
                      net=None):
    # if you specify your net, this means that you are calling this function from somewhere else..
    if net is None:
        if not train:
            net = symbol_factory.get_symbol(network,
                                            data_shape,
                                            num_classes=num_classes)
        else:
            net = symbol_factory.get_symbol_train(network,
                                                  data_shape,
                                                  num_classes=num_classes)

    if not train:
        a = mx.viz.plot_network(net, shape={"data": (1, 3, data_shape, data_shape)}, \
                                node_attrs={"shape": 'rect', "fixedsize": 'false'})
        filename = "ssd_" + network + '_' + str(data_shape) + '_' + 'test'
    else:
        a = mx.viz.plot_network(net, shape=None, \
                                node_attrs={"shape": 'rect', "fixedsize": 'false'})
        filename = "ssd_" + network + '_' + 'train'

    a.render(os.path.join(output_dir, filename))
    if print_net:
        print(net.tojson())

Example #2

File: visualize_net.py Project: mohamedelsiesyibra/mxnet-ssd

def net_visualization(network=None,
                      num_classes=None,
                      data_shape=None,
                      train=None,
                      output_dir=None,
                      print_net=False,
                      net=None):
    # if you specify your net, this means that you are calling this function from somewhere else..
    if net is None:
        if not train:
            net = symbol_factory.get_symbol(network, data_shape, num_classes=num_classes)
        else:
            net = symbol_factory.get_symbol_train(network, data_shape, num_classes=num_classes)

    if not train:
        a = mx.viz.plot_network(net, shape={"data": (1, 3, data_shape, data_shape)}, \
                                node_attrs={"shape": 'rect', "fixedsize": 'false'})
        filename = "ssd_" + network + '_' + str(data_shape)+'_'+'test'
    else:
        a = mx.viz.plot_network(net, shape=None, \
                                node_attrs={"shape": 'rect', "fixedsize": 'false'})
        filename = "ssd_" + network + '_' + 'train'

    a.render(os.path.join(output_dir, filename))
    if print_net:
        print(net.tojson())

Example #3

def net_visualization(network=None,
                      num_classes=None,
                      data_shape=None,
                      train=None,
                      output_dir=None,
                      print_net=False,
                      net=None):
    # if you specify your net, this means that you are calling this function from somewhere else..
    if net is None:
        if not train:
            net = symbol_factory.get_symbol(network, data_shape, num_classes=num_classes)
        else:
            net = symbol_factory.get_symbol_train(network, data_shape, num_classes=num_classes)

Example #4

File: visualize_net.py Project: zhiqi-0/RDMA-MXNet-ps-lite

parser.add_argument('--network',
                    type=str,
                    default='vgg16_reduced',
                    help='the cnn to use')
parser.add_argument('--num-classes',
                    type=int,
                    default=20,
                    help='the number of classes')
parser.add_argument('--data-shape',
                    type=int,
                    default=300,
                    help='set image\'s shape')
parser.add_argument('--train',
                    action='store_true',
                    default=False,
                    help='show train net')
args = parser.parse_args()

if not args.train:
    net = symbol_factory.get_symbol(args.network,
                                    args.data_shape,
                                    num_classes=args.num_classes)
    a = mx.viz.plot_network(net, shape={"data":(1,3,args.data_shape,args.data_shape)}, \
        node_attrs={"shape":'rect', "fixedsize":'false'})
    a.render("ssd_" + args.network + '_' + str(args.data_shape))
else:
    net = symbol_factory.get_symbol_train(args.network,
                                          args.data_shape,
                                          num_classes=args.num_classes)
    print(net.tojson())

Example #5

File: visualize_net.py Project: Piyush3dB/mxnet

from __future__ import print_function
import find_mxnet
import mxnet as mx
import argparse
import sys, os
sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'symbol'))
import symbol_factory


parser = argparse.ArgumentParser(description='network visualization')
parser.add_argument('--network', type=str, default='vgg16_reduced',
                    help = 'the cnn to use')
parser.add_argument('--num-classes', type=int, default=20,
                    help='the number of classes')
parser.add_argument('--data-shape', type=int, default=300,
                    help='set image\'s shape')
parser.add_argument('--train', action='store_true', default=False, help='show train net')
args = parser.parse_args()

if not args.train:
    net = symbol_factory.get_symbol(args.network, args.data_shape, num_classes=args.num_classes)
    a = mx.viz.plot_network(net, shape={"data":(1,3,args.data_shape,args.data_shape)}, \
        node_attrs={"shape":'rect', "fixedsize":'false'})
    a.render("ssd_" + args.network + '_' + str(args.data_shape))
else:
    net = symbol_factory.get_symbol_train(args.network, args.data_shape, num_classes=args.num_classes)
    print(net.tojson())