Closed mattdangerw closed 11 months ago
Alternately, we could show a (unbuilt)
status.
Model: "res_net_2"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Layer (type) ┃ Output Shape ┃ Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ dense_6 (Dense) │ ? │ 0 (unbuilt) │
├────────────────────────────────────────────┼─────────────────────────────────────┼───────────────┤
│ dense_7 (Dense) │ ? │ 0 (unbuilt) │
├────────────────────────────────────────────┼─────────────────────────────────────┼───────────────┤
│ dense_8 (Dense) │ ? │ 0 (unbuilt) │
└────────────────────────────────────────────┴─────────────────────────────────────┴───────────────┘
Total params: 0 (0.00 B)
Trainable params: 0 (0.00 B)
Non-trainable params: 0 (0.00 B)
Optimizer params: 0 (0.00 B) (unbuilt)
In some ways this is more consistent maybe? But would also mean most people will see an unbuilt
optimizer in the standard usage and not be sure how to build it.
Seemed potentially least confusing to just leave it off, but open to suggestions!
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Most people will call
summary()
beforefit()
. Doing so will usually mean the optimizer would show up as 0 parameters, which is misleading.