For this example, let’s download a ResNet-18 ONNX file
and upload it as your first model.Click on the ”+ New Model” button at the bottom right your dashboard
then upload it in the modal form
It may take a while before the model shows up in the table view as our
backend workers furiously unroll the ONNX model protobuf. We’re working
on improvements to make it faster so stay tuned for more!
Congrats! you’ve uploaded your first model onto the Cellulose platform!
Let’s move on to the fun part - visualizing it :)Click on the model name to proceed.
You’ll now see the ONNX graph being rendered, where an output of a given node
serve as input(s) to others in a graph runtime.
Let’s dive a little deeper into all the inputs and outputs associated with a
BatchNormalization operation below as an example.We tried to make this a little simpler by organizing them into tabs. As of this
writing, these are Inputs, Outputs, Attributes, Sample Output Values and
Fused.
We’ll go into each of them in the sections below.Each operator will always have a set of input(s) and output(s). The input(s)
of a node may consist of:
Tensor initializers with real values, and/or
An input that happen to also be the output of an upstream node.
Input tab
Output tab
Some nodes / operators will also have attributes like in this BatchNormalization
example:
This should bring up a modal overlay with even more details about that
particular initializer.
Well done! Now you’ve dabbled with the core functionalities of the Cellulose
dashboard. Feel free to browse the other documentation sections for more details.