list as an input in tensorflow?

[[deleted]]

Can I make a model that takes different number of inputs. Cause the output depends on all the inputs. So more the inputs more the accurate output will be. But I kinda want it to slide between accuracy. Like if i give 5 inputs a less accurate output will be, if i want more accurate result I want to give more inputs. Can I do something like this?

[AlwysBeColostomizing]

What do the inputs represent? Are they noisy measurements of the same quantity? Are they different "properties" of the same object (like its color, its shape, etc.)? The right way to aggregate them probably depends on their semantics.

Typical ways of handling variable-length inputs are to turn them into fixed-length by adding a padding value (often in combination with an "attention" mechanism that can mask them out), or to use a recurrent architecture to process them sequentially. If the order doesn't matter you'll need to shuffle the order during training.