frame

Howdy, Stranger!

It looks like you're new here. If you want to get involved, click one of these buttons!

Sign In

Howdy, Stranger!

It looks like you're new here. If you want to get involved, click one of these buttons!

Model that does nothing

I am trying to build a model for the NCS that does nothing. When compiling the model I get an error

shape: (400, 400)
res.shape:  (400, 400)
TensorFlow output shape:  (1, 400, 400)
Traceback (most recent call last):
  File "/usr/local/bin/mvNCCompile", line 169, in <module>
    create_graph(args.network, args.image, args.inputnode, args.outputnode, args.outfile, args.nshaves, args.inputsize, args.weights, args.explicit_concat, args.ma2480, args.scheduler, args.new_parser, args)
  File "/usr/local/bin/mvNCCompile", line 148, in create_graph
    load_ret = load_network(args, parser, myriad_config)
  File "/usr/local/bin/ncsdk/Controllers/Scheduler.py", line 110, in load_network
    network.optimize()
  File "/usr/local/bin/ncsdk/Models/Network.py", line 250, in optimize
    self.convert_network_input_to_yxz()
  File "/usr/local/bin/ncsdk/Models/Network.py", line 337, in convert_network_input_to_yxz
    if self.stageslist[0].op in [StageType.fully_connected_layer, StageType.convolution, StageType.max_pooling,
IndexError: list index out of range

My model is build as follows:

import tensorflow as tf
import numpy as np

def main(_):
        graph = tf.Graph()
        with graph.as_default():
                with tf.Session(graph=graph) as sess:
                        x = tf.placeholder(tf.float32, [400, 400], name='input')

                        for n in tf.get_default_graph().as_graph_def().node:
                                print(n.name + ": " + n.op)

                        sess.run(tf.global_variables_initializer())
                        sess.run(tf.local_variables_initializer())

                        # test model
                        in_tensor = tf.get_default_graph().get_tensor_by_name('input:0')
                        input_data = np.random.rand(400, 400).astype(np.float32)
                        known = sess.run('input:0', {in_tensor: input_data})
                        print('Result: ' + str(known))

                        # attempts to use saver but fails due to no variables to save
                        #saver = tf.train.Saver(tf.global_variables())
                        #saver.save(sess, './empty')
                        tf.train.write_graph(sess.graph_def, './', 'empty.pb', as_text=False)

tf.app.run(main=main)

Any idea on how to get past this hurdle?

Comments

Sign In or Register to comment.