[TF-TRT QAT Explicit precision] Assertion outScales.size() == 1 when converting QAT TF model
One additional thing I noticed when debugging: If I am to multiply the quantization or dequantization scale by a constant, the issue goes away and the engine can be built. For example, changing [these lines](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/compiler/tf2tensorrt/convert/ops/quantization_ops.cc#L69-L77) to this: 
```cpp
  if (scale_from_min_side < scale_from_max_side) {
    scales.quantize_scale[0] = scale_from_min_side;
    scales.dequantize_scale[0] = *min_range / min_quantized;
    *max_range = max_quantized * scales.dequantize_scale[0] * 2.0f;
  } else {
    scales.quantize_scale[0] = scale_from_max_side;
    scales.dequantize_scale[0] = *max_range / max_quantized;
    *min_range = min_quantized * scales.dequantize_scale[0] * 2.0f;
  }
```
I suspect it's some sort of overflow problem when the scale factors are actually correct. Will keep digging. Second update, it still works when I update the scaling factors to a very small adjustment, like `1.00001` or `0.99999`, but not when we keep the original value (no adjustment).   Third update: The issue was resolved by ensuring that `narrow_range=False` on the tensorflow side, and retraining the QAT model with that setting. The warning should be an error on the TF-TRT side. I will close this issue as I no longer need support.  Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/60168">Yes</a>
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<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

### Have you reproduced the bug with TF nightly?

No

### Source

source

### Tensorflow Version

2.9

### Custom Code

Yes

### OS Platform and Distribution

Linux Ubuntu 20.04

### Mobile device

_No response_

### Python version

3.8

### Bazel version

_No response_

### GCC/Compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current Behaviour?
I am currently working through supporting TF-TRT with explicit quant / dequant nodes, and am in the final stages of making it work. Here is a summary of the fixes I landed: 
- Implement a explicit convert for `FakeQuantWithMinMaxVars` keras API
- Support Conv2D with a tensor input in explicit conversion (transpose 2nd input to `KCRS` format) to be compatible with TRT conv layer

The conversion actually runs through, but I get an error when building the engine almost immediately: 
```shell
Internal Error (Assertion outScales.size() == 1 failed. )
```


### Standalone code to reproduce the issue

I am building the code from a custom TF-TRT branch off of r2.9, with minimal non-breaking changes. I can clean up my changes and open a PR on r2.9 so people can understand the changes better.


### Relevant log output

```shell
W20230329 16:29:04.094142 99658 quantization_ops.cc:309] FakeQuantWithMinMaxVars has narrow_range=true, but for TensorRT conversion, narrow_range=false is recommended.
W20230329 16:29:04.138859 99658 quantization_ops.cc:309] FakeQuantWithMinMaxVars has narrow_range=true, but for TensorRT conversion, narrow_range=false is recommended.
E20230329 16:29:05.544306 99658 convert_nodes.cc:7274] use_explicit_precision: 1
E20230329 16:29:05.544360 99658 convert_nodes.cc:7280] Build cuda engine
E20230329 16:29:05.545313 99658 convert_nodes.cc:1287] Setting TensorRT network name to TF:2.9.1, TRT:8.5.1-Precision:INT8, Calibration:0, Max-Batch-Size:1, Max-Workspace-Size:4294967296
E20230329 16:29:12.417982 99658 trt_logger.cc:40] DefaultLogger 2: [pointWiseV2Builder.cpp::toExpr::279] Error Code 2: Internal Error (Assertion outScales.size() == 1 failed. )
W20230329 16:29:12.464977 99658 trt_engine_op.cc:1047] TF-TRT Warning: Engine creation for TRTEngineOp_000_000 failed. The native segment will be used instead. Reason: INTERNAL: Failed to build TensorRT engine
W20230329 16:29:12.465102 99658 trt_engine_op.cc:888] TF-TRT Warning: Engine retrieval for input shapes: [[1,7,12], [1,7,15], [1,7,12], [1,6,5,550400], [7,3,1208,1920], [1,15,1,1]] failed. Running native segment for TRTEngineOp_000_000
```
</details>

Following up from this issue: https://github.com/tensorflow/tensorflow/issues/59711
It can possibly help solve both. 