I'm trying to optimize a saved graph for inference, so I can use it in Android.
My first attempt at using the optimize_for_inference script failed with
google.protobuf.message.DecodeError: Truncated message
So my question is whether the input/output nodes are wrong or the script cannot handle SavedModels (although it's the same extension as a frozen graph .pb)
Regarding the first: since with Estimators we provide input_fn instead of the data itself, which should be considered the input? The first tf operation on it? Like:
x = x_dict['gestures']
# Data input is a 1-D vector of x_dim * y_dim features ("pixels")
# Reshape to match format [Height x Width x Channel]
# Tensor input become 4-D: [Batch Size, Height, Width, Channel]
x = tf.reshape(x, shape=[-1, x_dim, y_dim, 1], name='input')
(...)
pred_probs = tf.nn.softmax(logits, name='output')
BTW: if there is something different in loading a SavedModel in Android, I'd like to know too.
Thank you in advance!