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idata
Community Manager
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Tensorflow - mvNCCompile issue

When I try to compile your example from the website "https://movidius.github.io/ncsdk/tf_compile_guidance.html", I get the following error message:

 

I have no idea where my fault lies.

 

Code:

 

from __future__ import absolute_import from __future__ import division from __future__ import print_function import argparse import sys import tempfile import tensorflow as tf FLAGS = None def deepnn(x): with tf.name_scope('reshape'): x_image = tf.reshape(x, [-1, 28, 28, 1]) # First convolutional layer - maps one grayscale image to 32 feature maps. with tf.name_scope('conv1'): W_conv1 = weight_variable([5, 5, 1, 32]) b_conv1 = bias_variable([32]) h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1) # Pooling layer - downsamples by 2X. with tf.name_scope('pool1'): h_pool1 = max_pool_2x2(h_conv1) # Second convolutional layer -- maps 32 feature maps to 64. with tf.name_scope('conv2'): W_conv2 = weight_variable([5, 5, 32, 64]) b_conv2 = bias_variable([64]) h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2) # Second pooling layer. with tf.name_scope('pool2'): h_pool2 = max_pool_2x2(h_conv2) # Fully connected layer 1 -- after 2 round of downsampling, our 28x28 image # is down to 7x7x64 feature maps -- maps this to 1024 features. with tf.name_scope('fc1'): W_fc1 = weight_variable([7 * 7 * 64, 1024]) b_fc1 = bias_variable([1024]) h_pool2_flat = tf.reshape(h_pool2, [-1, 7*7*64]) h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1) # Dropout - controls the complexity of the model, prevents co-adaptation of # features. with tf.name_scope('dropout'): keep_prob = tf.placeholder(tf.float32) h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob) # Map the 1024 features to 10 classes, one for each digit with tf.name_scope('fc2'): W_fc2 = weight_variable([1024, 10]) b_fc2 = bias_variable([10]) y_conv = tf.matmul(h_fc1, W_fc2) + b_fc2 return y_conv def conv2d(x, W): """conv2d returns a 2d convolution layer with full stride.""" return tf.nn.conv2d(x, W, strides=[1, 1, 1, 1], padding='SAME') def max_pool_2x2(x): """max_pool_2x2 downsamples a feature map by 2X.""" return tf.nn.max_pool(x, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME') def weight_variable(shape): """weight_variable generates a weight variable of a given shape.""" initial = tf.truncated_normal(shape, stddev=0.1) return tf.Variable(initial) def bias_variable(shape): """bias_variable generates a bias variable of a given shape.""" initial = tf.constant(0.1, shape=shape) return tf.Variable(initial) def main(_): # Create the model x = tf.placeholder(tf.float32, [None, 784], name="input") # Build the graph for the deep net y_conv = deepnn(x) output = tf.nn.softmax(y_conv, name='output') saver = tf.train.Saver(tf.global_variables()) with tf.Session() as sess: sess.run(tf.global_variables_initializer()) sess.run(tf.local_variables_initializer()) saver.restore(sess, '.' + '/mnist_model') saver.save(sess, '.' + '/mnist_inference') graph_location = "." save_path = saver.save(sess, graph_location + "/mnist_model") if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--data_dir', type=str, default='/tmp/tensorflow/mnist/input_data', help='Directory for storing input data') FLAGS, unparsed = parser.parse_known_args() tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)

 

Error:

 

adves@advesDL-03:~/Dokumente/2018-11 Movidius Neural Compute Stick/Test_MNIST$ mvNCCompile mnist_inference.meta -s 12 -in input -on output -o mnist_inference.graph /usr/local/bin/ncsdk/Controllers/Parsers/TensorFlowParser/Convolution.py:46: SyntaxWarning: assertion is always true, perhaps remove parentheses? assert(False, "Layer type not supported by Convolution: " + obj.type) /usr/local/bin/ncsdk/Controllers/Parsers/Phases.py:322: SyntaxWarning: assertion is always true, perhaps remove parentheses? assert(len(pred) == 1, "Slice not supported to have >1 predecessors") mvNCCompile v02.00, Copyright @ Intel Corporation 2017 ****** Info: No Weights provided. inferred path: mnist_inference.data-00000-of-00001****** shape: [1, 784] Traceback (most recent call last): File "/usr/local/bin/mvNCCompile", line 206, 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.cpp, args) File "/usr/local/bin/mvNCCompile", line 185, in create_graph load_ret = load_network(args, parser, myriad_config) File "/usr/local/bin/ncsdk/Controllers/Scheduler.py", line 146, in load_network parse_ret = parse_tensor(arguments, myriad_conf) File "/usr/local/bin/ncsdk/Controllers/TensorFlowParser.py", line 319, in parse_tensor item_shape = output_item.shape.as_list() File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_shape.py", line 903, in as_list raise ValueError("as_list() is not defined on an unknown TensorShape.") ValueError: as_list() is not defined on an unknown TensorShape.
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