Tensorflow gradient propagation
- ValueError: No gradients provided for any variable in Tensorflow - Stack Overflow
When you do
annotation_pred = tf.to_float(tf.argmax(out, dimension=4, name='prediction')), you get an index of the max value in your tensor. This index can’t be derivated, thus the gradient can’t flow throught this operation.
So as your loss is only defined by this value, and the gradient can’t flow throught it, no gradient can be calculated for your network.
Argmax is okay if I don’t calculate my loss through it.
Python / Numpy ellipsis (…)
- Cookbook/Indexing - SciPy wiki dump
The ellipsis (three dots) indicates “as many ‘:’ as needed” This makes it easy to manipulate only one dimension of an array, letting numpy do array-wise operations over the “unwanted” dimensions. You can only really have one ellipsis in any given indexing expression, or else the expression would be ambiguous about how many ‘:’ should be put in each.
- glib - superficial, shallow, persuasive but insincere in nature.
- retrodict - Wiktionary - to attempt to estimate the previous state from the present.
- Also interesting is postdiction - Wiktionary, the construction of past conditions by relying on the present.
German RE / AW
Outlook. What is the meaning of “AW” in an email header? – AW == RE in most other languages