How to resolve unsupported layer issue for my model
varun-tangoit opened this issue · 7 comments
Hi,
Im currently working on facenet,mtcnn model while i need to optimize my model with TensorRT. I have .pb file for model, when i try to convert with uff model i have some error kind of;
uff_model = uff.from_tensorflow_frozen_model("20180518-115854.pb", ["embeddings"])
Warning: keepdims is ignored by the UFF Parser and defaults to True
Warning: No conversion function registered for layer: QueueDequeueUpToV2 yet.
Converting as custom op QueueDequeueUpToV2 batch_join
name: "batch_join"
op: "QueueDequeueUpToV2"
input: "batch_join/fifo_queue"
input: "batch_size"
attr {
key: "component_types"
value {
list {
type: DT_FLOAT
type: DT_INT64
}
}
}
attr {
key: "timeout_ms"
value {
i: -1
}
}
Warning: No conversion function registered for layer: FIFOQueueV2 yet.
Converting as custom op FIFOQueueV2 batch_join/fifo_queue
name: "batch_join/fifo_queue"
op: "FIFOQueueV2"
attr {
key: "capacity"
value {
i: 1440
}
}
attr {
key: "component_types"
value {
list {
type: DT_FLOAT
type: DT_INT64
}
}
}
attr {
key: "container"
value {
s: ""
}
}
attr {
key: "shapes"
value {
list {
shape {
dim {
size: 160
}
dim {
size: 160
}
dim {
size: 3
}
}
shape {
}
}
}
}
attr {
key: "shared_name"
value {
s: ""
}
}
Traceback (most recent call last):
File "", line 1, in
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 149, in from_tensorflow_frozen_model
return from_tensorflow(graphdef, output_nodes, preprocessor, **kwargs)
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 120, in from_tensorflow
name="main")
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py", line 76, in convert_tf2uff_graph
uff_graph, input_replacements)
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py", line 63, in convert_tf2uff_node
op, name, tf_node, inputs, uff_graph, tf_nodes=tf_nodes)
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py", line 38, in convert_layer
fields = cls.parse_tf_attrs(tf_node.attr)
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py", line 209, in parse_tf_attrs
for key, val in attrs.items()}
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py", line 209, in
for key, val in attrs.items()}
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py", line 204, in parse_tf_attr_value
return cls.convert_tf2uff_field(code, val)
File "/usr/lib/python3.5/dist-packages/uff/converters/tensorflow/converter.py", line 189, in convert_tf2uff_field
'type': 'dtype', 'list': 'list'}[code]
KeyError: 'shape'
I can't proceed further, im stuck on this, pls give me some suggestion how to resolve this issue
The same error with you. Have you solved this problem?
Nope.. If you have resolved, pls let me know.
I tried to use insightface to replace facenet and it works. The technology support in nvidia said that facenet has some un-support layers so that it cannot directly convert to uff unless you have the caffemodel. It seems that the caffemodel has plug-in API.
Can you please help me with more detail or where do refer and resolve this issue.. im stuck on this issue. Thanks in advance
In fact, I use the resnet_v1_50 model in this github: https://github.com/auroua/InsightFace_TF
and then convert .ckpt file to .pd file. Finally use uff.from_tensorflow() to uff. I just entirely give up the facenet. Hope it can help you.
Thanks for the help. i will try.. Once you convert tensorRT please tell me how much fps would reached on jetson tx2.. i need to know performance increased or not for facenet model.
In fact, I use the resnet_v1_50 model in this github: https://github.com/auroua/InsightFace_TF
and then convert .ckpt file to .pd file. Finally use uff.from_tensorflow() to uff. I just entirely give up the facenet. Hope it can help you.
Hi!
Have you solve this issue? I want to convert facenet to trt model too but I ran into a lot of problems