CODEWITHSUNDEEP
pythontensorflow
Stormsson
Stormsson

Reputation: 1551

Manually create 3+ rank tensor in tensorflow

I'd like to create a [ ?, ?, n ] tensor at runtime. The data is as follow:

1) each element i'm examining is a vector of n elements (so [1,2,...,n])

2) each "group" is an unknown amount of elements of the previous type (so basically a matrix)

3) i don't know how many groups i will receive.

I tried manually, with something like this:

shape3 = [
[ [ .111,.112,.113 ], [ .121,.122,.123 ], [ .131,.132,.133 ] ],
[ [ .211,.212,.213 ], [ .221,.222,.223 ] ]
]

var_shape3 = tf.Variable(shape3, name="var_shape_3")
with tf.Session() as session:
    session.run(init_op)
    print var_shape3.eval()
    print var_shape3.get_shape()

but i receive the error

Argument must be a dense tensor: [[[0.111, 0.112, 0.113], [0.121, 0.122, 0.123], [0.131, 0.132, 0.133]], [[0.211, 0.212, 0.213], [0.221, 0.222, 0.223]]] - got shape [2], but wanted [2, 3, 3].

some help on what i'm doing wrong please?

on other words: how do i put those data in a tensor?

thank you

Upvotes: 3

Views: 1315

Answers (1)

Fematich
Fematich

Reputation: 1618

In TensorFlow you can have dynamic dimensions, represented by the ? sign. But these dimensions must be inferred during execution, which means that it needs to be represented by a number once you execute your code.

In your example (with variable number of groups and elements in the groups), this will not work. E.g. what will work is:

shape3 = [
[ [ .111,.112,.113 ], [ .121,.122,.123 ], [ .131,.132,.133 ] ],
[ [ .211,.212,.213 ], [ .221,.222,.223 ], [ .000,.000,.000 ] ]
]

Your two options are:

  1. Define the maximum number of groups and elements in the groups and use padding to fill missing data points. You could also use bucketing to group similar sized examples (more info here).
  2. Change your code / data structure to work with variable length sequences. This would probably require using TensorFlow scan op. Note that this can be extremely slow, so I wouldn't recommend it, unless it's really required, more info here.

Upvotes: 3

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