Hello everyone,
I want to experiment INT8 quantization-aware training supported by TF-TRT (TRT5).
So I trained a deep convolutional NN model by adding quantization node (tf.quantization.quantize_and_dequantize) after each convolutional block as mentioned in the documentation.
Here is a segment of the model summary:
Layer (type) ###Output Shape### Param ### Connected to
block_1/conv2d_1 (Conv2D)###(6, 800, 800, 32) ### 9248 ### tf_op_layer_QuantizeAndDequantize
block_1/activation_1 (Activatio ###(6, 800, 800, 32) ### 0 ### block_1/conv2d_1[0][0]
tf_op_layer_QuantizeAndDequanti ###[(6, 800, 800, 32)] ### 0 ### block_1/activation_1[0][0]
res_block_2/conv2d_0 (Conv2D) ### (6, 400, 400, 24) ### 6936### tf_op_layer_QuantizeAndDequantize
res_block_2/activation_0 ###(Activ (6, 400, 400, 24)### 0 ### res_block_2/conv2d_0[0][0]
tf_op_layer_QuantizeAndDequanti ###[(6, 400, 400, 24)]### 0 ### res_block_2/activation_0[0][0]
However, when I run the TRT5 converter with use_calibration = False, I get an error from TRT as follows: Quantization range was not found for res_block_2/activation_0/Relu
Why am I getting this error even if I added the quantization nodes in the right place?
Best,