i am trying to use tensorRT version 5.0.2 in ngc container TensorRT:19.02-py2 to execute a pretrained tensorflow/models/research/maskRcnn network in TensorRT.
i have successfully converted the frozen graph to uff format using the following command :
convert_to_uff.py -o MyUffGraph --text FrozenModelFilename
when i parse the model using the following python code :
import tensorrt as trt
TRT_LOGGER = trt.Logger(trt.Logger.WARNING)
with trt.Builder(TRT_LOGGER) as builder, builder.create_network() as network, trt.UffParser() as parser:
parser.register_input(“image_tensor:0”, (3, 28, 28))
i get the following error :
UFFParser: Graph error: Cycle graph detected
i have then retried the uff conversion , by adding the --debug flag.
i see that the output nodes have not been deduced correctly,
they are :
and not the expected detection_scores,detection_boxes,detection_masks…
i have tried to explicitly add the expected tensors using the -o flag,
this leads to errors like :
uff.model.exceptions.UffException: detection_boxes was not found in the graph
(and in the generated uffgraph.pbtxt file , i don’t see them)
i have found TF object detection faster rcnn nodes not found
which suggests that i am not the first person to encounter this problem, and that the issue is significantly more complicated then documented.