Forums - a really simple custom tf model with ERROR_TF_CONV_RESOLVE_WEIGHTs

Hi All,

I trained a really simple two-layered CNN for binary classification.

img_placeholder = tf.placeholder(tf.float32, shape=batch_shape, name='input')
labels = tf.placeholder(tf.float32, shape=(None, 1))


conv = tf.layers.conv2d(img_placeholder, 8, 3, 1, padding='SAME')
fc = tf.layers.flatten(conv)
out = tf.layers.dense(fc, 1)
pred = tf.nn.sigmoid(out, name='output')
cross_entropy = tf.nn.sigmoid_cross_entropy_with_logits(labels=y, logits=out)
cost = tf.reduce_mean(cross_entropy)
optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate).minimize(cost)

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())

    for step in range(20):
        sess.run(optimizer, feed_dict={img_placeholder: x, labels: y})

    graph = tf.get_default_graph()
    graph_def = graph.as_graph_def()
    tf.train.write_graph(graph_def, "./", "test.pb", False)

With the test.pb I run the following command

snpe-tensorflow-to-dlc --graph test.pb -i input "1,480,480,3" --out_node output

The error message is

FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.

  from ._conv import register_converters as _register_converters

2018-07-26 10:57:28.997478: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2

2018-07-26 10:57:29,089 - 388 - WARNING - ERROR_TF_FALLBACK_TO_ONDEMAND_EVALUATION: Unable to resolve operation output shapes in single pass. Using on-demand evaluation!

2018-07-26 10:57:29,102 - 106 - ERROR - Conversion failed: ERROR_TF_CONV_RESOLVE_WEIGHTS: Cannot resolve convolution layer due to missing weights for operation: conv2d/Conv2D