Hello everyone,
I am using Python3 + Tensorflow 1.12 + TensorRT 3.0.2 in order to quantize a DNN for object detection.
The quantization work fine for me. However, I want to generate and read the calibration table in order to understand if my calibration dataset is good enough or not.
I want to ask also if I can generate the histograms of activation as shown in these slides?
http://on-demand.gputechconf.com/gtc/2017/presentation/s7310-8-bit-inference-with-tensorrt.pdf
I found the following python code in NVIDIA tutorial to extract the TensorRT calibration table after the calibration is done: https://docs.nvidia.com/deeplearning/frameworks/tf-trt-user-guide/index.html#post-train
for n in trt_graph.node:
if n.op == “TRTEngineOp”:
print(“Node: %s, %s” % (n.op, n.name.replace("/", “")))
with tf.gfile.GFile("%s.calib_table" % (n.name.replace("/", "”)), ‘wb’) as f:
f.write(n.attr[“calibration_data”].s)
This code generates a file for each node in the trt_graph. I get something like this:
Up_sample_6/conv2d_25/Relu: 3f556f06
InputPH_1: 3e0324b6
Up_sample_6/conv2d_26/Relu: 3eee7366
OutputPH_0: 3e59daba
Up_sample_6/conv2d_27/Relu: 3dc77c91
InputPH_0: 3f41b751
Thank you in advance,
Fares Charfi
Can you please explain these files and how to read these files?