BatchNormalization -> Relu -> ... -> BatchNormalization -> Relu -> Conv -> ...
Furthermore,
common backbones have repeating subgraphs that may not be of concern to the
user. Wouldn’t it be nice to “tuck them away”?
We’d also like to introduce APIs / SDKs in the future where “Expand / Collapse
by default” can be annotated in model code as Python decorators or something
similar.
[256 x 64 x 1 x 1]
”.
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protobuf
, and protobuf
has a hard size limit of 2GB. Depending on how you’re setting up a large AI
model/pipeline, you may find yourself partitioning them into more than one
subgraph and would like to visualize them separately. That’s what we’d like to
build too!
Sample Output Values tab