python - Count number of "True" values in boolean Tensor

Question

I understand that tf.where will return the locations of True values, so that I could use the result's shape[0] to get the number of Trues.

However, when I try and use this, the dimension is unknown (which makes sense as it needs to be computed at runtime). So my question is, how can I access a dimension and use it in an operation like a sum?

For example:

myOtherTensor = tf.constant([[True, True], [False, True]])
myTensor = tf.where(myOtherTensor)
myTensor.get_shape() #=> [None, 2]
sum = 0
sum += myTensor.get_shape().as_list()[0] # Well defined at runtime but considered None until then.

question from:https://stackoverflow.com/questions/34598371/count-number-of-true-values-in-boolean-tensor

Answer 1

You can cast the values to floats and compute the sum on them: tf.reduce_sum(tf.cast(myOtherTensor, tf.float32))

Depending on your actual use case you can also compute sums per row/column if you specify the reduce dimensions of the call.