Getting up to the Jetson inference performance

Autonomous Machines Jetson & Embedded Systems Jetson AGX Xavier
,
14

Hi,

Sorry for keeping you waiting.

We can convert your model into TensorRT engine with following steps and config.py file.

$ sudo python3 /usr/lib/python3.6/dist-packages/uff/bin/convert_to_uff.py [your/pb/file] -o test.uff -O NMS -p config.py
$ /usr/src/tensorrt/bin/trtexec --uff=test.uff --uffInput=Input,3,300,300 --output=NMS

config.py

import graphsurgeon as gs
import tensorflow as tf
import numpy as np

Input = gs.create_node("Input",
    op="Placeholder",
    dtype=tf.float32,
    shape=[1, 3, 300, 300])
PriorBox = gs.create_plugin_node(name="GridAnchor", op="GridAnchor_TRT",
    numLayers=6,
    minSize=0.2,
    maxSize=0.95,
    aspectRatios=[1.0, 2.0, 0.5, 3.0, 0.33],
    variance=[0.1,0.1,0.2,0.2],
    featureMapShapes=[19, 10, 5, 3, 2, 1])
NMS = gs.create_plugin_node(name="NMS", op="NMS_TRT",
    shareLocation=1,
    varianceEncodedInTarget=0,
    backgroundLabelId=0,
    confidenceThreshold=1e-8,
    nmsThreshold=0.6,
    topK=100,
    keepTopK=100,
    numClasses=3,
    inputOrder= [0, 2, 1],
    confSigmoid=1,
    isNormalized=1)
concat_priorbox = gs.create_node(name="concat_priorbox", op="ConcatV2", dtype=tf.float32, axis=2)
concat_box_loc = gs.create_plugin_node("concat_box_loc", op="FlattenConcat_TRT", dtype=tf.float32, axis=1, ignoreBatch=0)
concat_box_conf = gs.create_plugin_node("concat_box_conf", op="FlattenConcat_TRT", dtype=tf.float32, axis=1, ignoreBatch=0)
dummy_const = gs.create_node(name="dummy_const", op="Const", dtype=tf.float32, value=np.array([1, 1], dtype=np.float32))

namespace_plugin_map = {
    "Concatenate": concat_priorbox,
    "MultipleGridAnchorGenerator": PriorBox,
    "Postprocessor": NMS,
    "image_tensor": Input,
    "Cast": Input,
    "ToFloat": Input,
    "Preprocessor": Input,
    "concat": concat_box_loc,
    "concat_1": concat_box_conf
}

namespace_remove = {
    "ToFloat",
    "image_tensor",
    "Preprocessor/map/TensorArrayStack_1/TensorArrayGatherV3",
}

def preprocess(dynamic_graph):
    dynamic_graph.remove(dynamic_graph.find_nodes_by_path(namespace_remove), remove_exclusive_dependencies=False)
    # Now create a new graph by collapsing namespaces
    dynamic_graph.collapse_namespaces(namespace_plugin_map)
    # Remove the outputs, so we just have a single output node (NMS).
    dynamic_graph.remove(dynamic_graph.graph_outputs, remove_exclusive_dependencies=False)
    dynamic_graph.append(dummy_const)
    dynamic_graph.find_nodes_by_op("GridAnchor_TRT")[0].input.append("dummy_const")

Thanks.

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