ERROR: Network must have at least one output

[ghost]

Got the following error:
[TensorRT] ERROR: (Unnamed Layer* 32) [Concatenation]: all concat input tensors must have the same dimensions except on the concatenation axis (0), but dimensions mismatched at input 1 at index 1. Input 0 shape: [128,1216,1216], Input 1 shape: [256,608,608] [TensorRT] ERROR: Network must have at least one output Engine: None Traceback (most recent call last): File "create_trt_engine.py", line 51, in <module> main() File "create_trt_engine.py", line 48, in main save_engine(engine, trt_file) File "create_trt_engine.py", line 31, in save_engine buf = engine.serialize() AttributeError: 'NoneType' object has no attribute 'serialize'

My cfg;

`[net]

Testing

#batch=1
#subdivisions=1

Training

batch=64
subdivisions=16
width=608
height=608
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.001
burn_in=1000
max_batches = 12000
policy=steps
steps=7200,9600
scales=.1,.1

[convolutional]
batch_normalize=1
filters=16
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=1

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[convolutional]
size=1
stride=1
pad=1
filters=18
activation=linear

[yolo]
mask = 3,4,5
anchors = 9,18, 13,27, 21,39, 29,59, 44,101, 70,146
classes=1
num=6
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1

[route]
layers = -4

[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

[upsample]
stride=2

[route]
layers = -1, 8

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[convolutional]
size=1
stride=1
pad=1
filters=18
activation=linear

[yolo]
mask = 0,1,2
anchors = 9,18, 13,27, 21,39, 29,59, 44,101, 70,146
classes=1
num=6
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1

`

[QZ-cmd]

Hello，can you save this problem?i have same error

[Rapternmn]

Can you try with Batch = 1

[Rapternmn]

I have mentioned in README to first try with :
batch=1
width=416
height=416

[wavesCHJ]

I have the same errors. this helps me.
NVIDIA/TensorRT#183 (comment)
the solution is change

with trt.Builder(TRT_LOGGER) as builder, builder.create_network() as network, trt.OnnxParser(network, TRT_LOGGER) as parser:

to

explicit_batch = 1 << (int)(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH)
with trt.Builder(TRT_LOGGER) as builder, builder.create_network(explicit_batch) as network, trt.OnnxParser(network, TRT_LOGGER) as parser: