Enable 16-bit activations in Cadence Quantizer For fully_connected and linear

[RahulC7]

Summary:

Context

We currently only support 8-bit for most operators. We would like to add generic ops for 16-bit activations, for the following ops:

• quantized_fully_connected
• quantized_linear
• quantized_conv (all flavors)
• quantized_matmul

This Diff

Here, we add support for quantized_linear and quantized_fully_connected. We need to do the following:

1. Allow 16-bit activations in quantized_fully_connected_out.cpp and quantized_linear_out.cpp.
2. Allow 16-bit activations in ref_implementations.py, so tests can run with 16-bit activations to validate the quantization is correct.
3. Add a quantizer(CadenceWith16BitLinearActivationsQuantizer) for checking this works and create a unit test.

Differential Revision: D84284794

[meta-codesync]

@RahulC7 has exported this pull request. If you are a Meta employee, you can view the originating Diff in D84284794.

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❌ 2 New Failures

As of commit 388201c with merge base a12219d ():

NEW FAILURES - The following jobs have failed:

• pull / test-samsung-models-linux / linux-job (gh)
  RuntimeError: Command docker exec -t 31314cecc9534dad8f4f834fe21038ce04bccfb9a58186e5d8f1b9a3191c0589 /exec failed with exit code 1
• Test CUDA Builds / export-voxtral-cuda-artifact / linux-job (gh)
  RuntimeError: Command docker exec -t 9b9934ca3ceb4a204a6184927133162750dab52ec05e67c0d989a23f9afbca36 /exec failed with exit code 2

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