Multiplication following a int8 transposed convolutions isn't constant folded

[pkgoogle]

Description of the bug:

Original Issue: tensorflow/tensorflow#57680
Opening on behalf of @lgeiger

When converting a model that used int8 quantization aware training, conversion of transposed convolutions followed by a scalar multiplication fails.

The converter isn't able to correctly constant fold the per-tensor fake quantized weights and the scalar multiplication which is a common patter when using transposed convolutions followed by batch normalisation layers. This is a follow-up issue to #53766

1. System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): macOS / Ubuntu
• TensorFlow installation (pip package or built from source): pip
• TensorFlow library (version, if pip package or github SHA, if built from source): 2.10.0 / 2.11.0-dev20220913

2. Code

A minimal reproduction of the issue is available in this notebook. Re-run the notebook to show netron visualisations showing the conversion problem.

Actual vs expected behavior:

No response

Any other information you'd like to share?

No response

[gaikwadrahul8]

This issue originally reported by @lgeiger has been moved to this dedicated repository for ai-edge-torch to enhance issue tracking and prioritization. To ensure continuity, we have created this new issue on your behalf.

We appreciate your understanding and look forward to your continued involvement.