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ModelNotFound Exception while loading SSD Model #11
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@OElesin Currently we have two model zoo, one is imperative model zoo (Engine agnostic) and other one is MXNet symbolic model zoo. The criteria you provided only exists in MxModelZoo.
By the way, you use: |
@frankfliu, import ai.djl.mxnet.zoo.MxModelZoo
MxModelZoo.SSD.loadModel(criteria)
// console output below
[20:37:36] src/nnvm/legacy_json_util.cc:209: Loading symbol saved by previous version v1.5.0. Attempting to upgrade...
[20:37:36] src/nnvm/legacy_json_util.cc:217: Symbol successfully upgraded!
ai.djl.engine.EngineException: MXNet engine call failed: [20:37:36] src/ndarray/ndarray.cc:1725: Check failed: !Imperative::Get()->is_np_shape(): ndarray was not saved in np shape semantics, but being loaded in np shape semantics. Please turn off np shape semantics in Python using `with np_shape(False)` to scope of the code of loading the ndarray.
Stack trace:
[bt] (0) 1 libmxnet.so 0x00000001230f0929 mxnet::op::NDArrayOpProp::~NDArrayOpProp() + 4473
[bt] (1) 2 libmxnet.so 0x00000001230efd19 mxnet::op::NDArrayOpProp::~NDArrayOpProp() + 1385
[bt] (2) 3 libmxnet.so 0x0000000124761147 mxnet::NDArray::Load(dmlc::Stream*) + 5671
[bt] (3) 4 libmxnet.so 0x00000001247616eb mxnet::NDArray::Load(dmlc::Stream*, std::__1::vector<mxnet::NDArray, std::__1::allocator<mxnet::NDArray> >*, std::__1::vector<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > > >*) + 219
[bt] (4) 5 libmxnet.so 0x000000012458ce3f MXNDArrayLoad + 255
[bt] (5) 6 jna6825784435853766349.tmp 0x000000011be6ce74 ffi_call_unix64 + 76
[bt] (6) 7 ??? 0x000070000a1e1818 0x0 + 123145472055320
at ai.djl.mxnet.jna.JnaUtils.checkCall(JnaUtils.java:1750)
at ai.djl.mxnet.jna.JnaUtils.loadNdArray(JnaUtils.java:377)
at ai.djl.mxnet.engine.MxModel.loadParameters(MxModel.java:386)
at ai.djl.mxnet.engine.MxModel.load(MxModel.java:126)
at ai.djl.Model.load(Model.java:93)
at ai.djl.repository.zoo.BaseModelLoader.loadModel(BaseModelLoader.java:97)
at ai.djl.repository.zoo.BaseModelLoader.loadModel(BaseModelLoader.java:85)
at ai.djl.repository.zoo.ModelLoader.loadModel(ModelLoader.java:41)
... 36 elided |
@OElesin
And also please collect debug logs for your project, to turn on debug log add -Dai.djl.logging.level=debug. It looks like you are using an incompatible version of MXNet, seems it comes from your pip mxnet package.
|
@OElesin , if you could respond to @frankfliu's question - please do so and reopen this issue. |
* Separate WorkLoadManager This separates the WorkLoadManagement functionality from the main djl-serving into a separate module. The module first enables isolated usage without serving. It also helps convert the wlm to focus on CompletableFutures rather than netty. This makes it easier to leverage from pure Java. As a particular case, it also enables Translators to leverage the wlm. * Update gradle build script * Move anonymous block into function Co-authored-by: Frank Liu <frankfliu2000@gmail.com>
Description
I am attempting to reproduce this ObjectDetection example in Scala. However, when I specify the model criteria as illustrated in the example code, I get an error that the model is not found.
Expected Behavior
Model should be loaded and objects in image should be detected as in example
Error Message
See error message below:
How to Reproduce?
To reproduce:
build.sbt file
sbt import log
Steps to reproduce
(Paste the commands you ran that produced the error.)
What have you tried to solve it?
Environment Info
Please provide the following information:
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