converting yolov3-tiny got error
minkoo01 opened this issue · comments
The output text is below...
As I can see since last max pool input size is changed from 13 to 12...
I don't understand why its happened...
Please help
0 Tensor("yolov3/net1:0", shape=(?, 416, 416, 3), dtype=float32)
1 Tensor("yolov3/convolutional1/Activation:0", shape=(?, 416, 416, 16), dtype=float32)
2 Tensor("yolov3/maxpool1/MaxPool:0", shape=(?, 208, 208, 16), dtype=float32)
3 Tensor("yolov3/convolutional2/Activation:0", shape=(?, 208, 208, 32), dtype=float32)
4 Tensor("yolov3/maxpool2/MaxPool:0", shape=(?, 104, 104, 32), dtype=float32)
5 Tensor("yolov3/convolutional3/Activation:0", shape=(?, 104, 104, 64), dtype=float32)
6 Tensor("yolov3/maxpool3/MaxPool:0", shape=(?, 52, 52, 64), dtype=float32)
7 Tensor("yolov3/convolutional4/Activation:0", shape=(?, 52, 52, 128), dtype=float32)
8 Tensor("yolov3/maxpool4/MaxPool:0", shape=(?, 26, 26, 128), dtype=float32)
9 Tensor("yolov3/convolutional5/Activation:0", shape=(?, 26, 26, 256), dtype=float32)
10 Tensor("yolov3/maxpool5/MaxPool:0", shape=(?, 13, 13, 256), dtype=float32)
11 Tensor("yolov3/convolutional6/Activation:0", shape=(?, 13, 13, 512), dtype=float32)
12 Tensor("yolov3/maxpool6/MaxPool:0", shape=(?, 12, 12, 512), dtype=float32)
13 Tensor("yolov3/convolutional7/Activation:0", shape=(?, 12, 12, 1024), dtype=float32)
14 Tensor("yolov3/convolutional8/Activation:0", shape=(?, 12, 12, 256), dtype=float32)
15 Tensor("yolov3/convolutional9/Activation:0", shape=(?, 12, 12, 512), dtype=float32)
16 Tensor("yolov3/convolutional10/BiasAdd:0", shape=(?, 12, 12, 30), dtype=float32)
17 Tensor("yolov3/convolutional10/BiasAdd:0", shape=(?, 12, 12, 30), dtype=float32)
18 Tensor("yolov3/route1:0", shape=(?, 12, 12, 256), dtype=float32)
19 Tensor("yolov3/convolutional11/Activation:0", shape=(?, 12, 12, 128), dtype=float32)
20 Tensor("yolov3/upsample1:0", shape=(?, 24, 24, 128), dtype=float32)
Traceback (most recent call last):
File "/home/sg180824/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1589, in _create_c_op
c_op = c_api.TF_FinishOperation(op_desc)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Dimension 1 in both shapes must be equal, but are 24 and 26. Shapes are [?,24,24] and [?,26,26]. for 'yolov3/route2' (op: 'ConcatV2') with input shapes: [?,24,24,128], [?,26,26,128], [] and with computed input tensors: input[2] = <-1>.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "DW2TF/main.py", line 111, in <module>
main(args)
File "DW2TF/main.py", line 52, in main
parse_net(args.layers, args.cfg, args.weights, args.training)
File "DW2TF/main.py", line 32, in parse_net
training=training, const_inits=const_inits, verbose=verbose)
File "/raid/jupyterhub/notebook/sg180824/minkoo/yolo/DW2TF/util/cfg_layer.py", line 197, in get_cfg_layer
layer = _cfg_layer_dict.get(layer_name, cfg_ignore)(B, H, W, C, net, param, weights_walker, stack, output_index, scope, training, const_inits, verbose)
File "/raid/jupyterhub/notebook/sg180824/minkoo/yolo/DW2TF/util/cfg_layer.py", line 131, in cfg_route
net = tf.concat(nets, axis=-1, name=scope)
File "/home/sg180824/.local/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1113, in concat
return gen_array_ops.concat_v2(values=values, axis=axis, name=name)
File "/home/sg180824/.local/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1029, in concat_v2
"ConcatV2", values=values, axis=axis, name=name)
File "/home/sg180824/.local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/sg180824/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3414, in create_op
op_def=op_def)
File "/home/sg180824/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1756, in __init__
control_input_ops)
File "/home/sg180824/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1592, in _create_c_op
raise ValueError(str(e))
ValueError: Dimension 1 in both shapes must be equal, but are 24 and 26. Shapes are [?,24,24] and [?,26,26]. for 'yolov3/route2' (op: 'ConcatV2') with input shapes: [?,24,24,128], [?,26,26,128], [] and with computed input tensors: input[2] = <-1>.
@sjain-stanford Oh I got it! I solved after following you said. I really appreciate it 👍