feat: added checks for support of activations on target

[novak-vaclav]

Summary

Introduces stricter checks for activation support on the target.
The updated validation logic applies to: clamp, hardtanh, leaky_relu, relu, sigmoid, tanh.

Test plan

tests can be manually run using pytest -c /dev/null backends/nxp/tests/

cc @robert-kalmar @JakeStevens @digantdesai @MartinPavella @roman-janik-nxp

[pytorch-bot]

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[novak-vaclav]

@pytorchbot label "release notes: nxp"

[novak-vaclav]

@pytorchbot label "module: nxp"

[MartinPavella]

This is incorrect.

You call this function in every activation converter's is_supported_on_target() method. So this condition has to always be satisfied to delegate an activation. But operators which can use the Custom Activation feature of Neutron aren't restricted like this.

For example test_leaky_relu_converter.py contained tests with input shape (23, ), and it delegated successfully.

Your task was aimed only at solving the issue when the activations were the only ops in the model. But here you are introducing a check which effects every case (including models with multiple nodes), and it breaks existing working functionality.

I see you changed all existing tests to satisfy this condition. But the tests were passing, and they should still be passing if Neutron supports them.

Our goal is to delegate as many operators to Neutron as possible. Therefore, we cannot introduce arbitrary restrictions like this. Every single test that started failing when you introduced this change must still be passing. You cannot just modify the tests and pretend it didn't happen. If a test fails -> there is an issue. In this case, the issue was caused by your changes.

---

It appears you have misunderstood the task. In clamp_converter.py, you have removed the method supports_partitioning_result(). What was the motivation for this? Instead, you should have added this method to every "activation_converter" and used it to prohibit delegation if the activation was the only node in the partition (and perhaps consider some operator-specific conditions).

Unless I'm missing something, a complete rework is required.

[novak-vaclav]

As I told you and the team multiple times at the regular meetups, I noticed that the converters did NOT check whether the node is delegable. Such functionality was not implemented, when in my opinion it should have been. I also believe that the absence of such functionality was the root cause of ReLU not being delegated when there are no other nodes in the partition (aside from QDQ nodes of course).
In the Neutron Converter documentation, there is a list of conditions, such as num_channels % num_macs == 0 that are not being checked. That is the whole motivation behind all these changes.
The tests needed to be modified to correctly reflect the newly imposed restrictions. I wanted to adhere to the documentation the Neutron team provided, however if you think it is better to start checking the requirements only when we encounter a situation when it stops working, that is fine by me. Just wanted to do the due dilligence of properly implementing the conversion of one of the most important operators there are, such as ReLU or Sigmoid.
As I am looking at it right now, some of the code is quite old, for example the functionality concerning ReLU. Maybe the restrictions did not exist back then.

[MartinPavella]

Let's not escalate this.

The bottom line is this:

• You wanted to adhere to the Neutron documentation, even in cases when we have working implementation which contradicts the documentation. So you prohibited these cases, which solved the issue of your ticket, but it also broke some supported cases.
• I think we should support as many cases as possible. We know the Neutron documentation is not 100% accurate, so I think prohibiting working cases just because they contradict the docs is not the way to go. Based on this opinion, the solution should have been different.

We can discuss it tomorrow if you want.

P.S.
I didn't mean to sound aggressive in my first comment. I apologize if my phrasing was inappropriate.