You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@mxnet.apache.org by GitBox <gi...@apache.org> on 2020/12/04 06:27:47 UTC
[GitHub] [incubator-mxnet] lsdustc opened a new issue #19628: CTC loss in mxnet 2.0 not work when use half precision
lsdustc opened a new issue #19628:
URL: https://github.com/apache/incubator-mxnet/issues/19628
## Description
(A clear and concise description of what the bug is.)
### Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=100` before running your script.)
`[14:22:42] /home/super/software/incubator-mxnet/src/storage/storage.cc:199: Using Pooled (Naive) StorageManager for GPU
Traceback (most recent call last):
File "/data/workspace/mxnet_project/ime/test.py", line 53, in <module>
mx.nd.waitall()
File "/home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/ndarray/ndarray.py", line 240, in waitall
check_call(_LIB.MXNDArrayWaitAll())
File "/home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/base.py", line 246, in check_call
raise get_last_ffi_error()
mxnet.base.MXNetError: Traceback (most recent call last):
[bt] (13) /lib/x86_64-linux-gnu/libc.so.6(clone+0x3f) [0x7fd72e61d4cf]
[bt] (12) /lib/x86_64-linux-gnu/libpthread.so.0(+0x7fa3) [0x7fd72e87bfa3]
[bt] (11) /lib/x86_64-linux-gnu/libstdc++.so.6(+0xbbb2f) [0x7fd6b1f1db2f]
[bt] (10) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(std::thread::_State_impl<std::thread::_Invoker<std::tuple<std::function<void (std::shared_ptr<dmlc::ManualEvent>)>, std::shared_ptr<dmlc::ManualEvent> > > >::_M_run()+0x33) [0x7fd6fe279b63]
[bt] (9) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(std::_Function_handler<void (std::shared_ptr<dmlc::ManualEvent>), mxnet::engine::ThreadedEnginePerDevice::PushToExecute(mxnet::engine::OprBlock*, bool)::{lambda()#4}::operator()() const::{lambda(std::shared_ptr<dmlc::ManualEvent>)#1}>::_M_invoke(std::_Any_data const&, std::shared_ptr<dmlc::ManualEvent>&&)+0x37) [0x7fd6fe27e3e7]
[bt] (8) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(void mxnet::engine::ThreadedEnginePerDevice::GPUWorker<(dmlc::ConcurrentQueueType)0>(mxnet::Context, bool, mxnet::engine::ThreadedEnginePerDevice::ThreadWorkerBlock<(dmlc::ConcurrentQueueType)0>*, std::shared_ptr<dmlc::ManualEvent> const&)+0x17e) [0x7fd6fe27e12e]
[bt] (7) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(mxnet::engine::ThreadedEngine::ExecuteOprBlock(mxnet::RunContext, mxnet::engine::OprBlock*)+0x111) [0x7fd6fe27a9b1]
[bt] (6) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(+0x1e095b0) [0x7fd6fe26f5b0]
[bt] (5) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(std::_Function_handler<void (mxnet::RunContext), mxnet::imperative::PushFCompute(std::function<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)> const&, nnvm::Op const*, nnvm::NodeAttrs const&, mxnet::Context const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::Resource, std::allocator<mxnet::Resource> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<unsigned int, std::allocator<unsigned int> > const&, std::vector<mxnet::OpReqType
, std::allocator<mxnet::OpReqType> > const&)::{lambda(mxnet::RunContext)#1}>::_M_invoke(std::_Any_data const&, mxnet::RunContext&&)+0x17) [0x7fd6fe2f0867]
[bt] (4) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(mxnet::imperative::PushFCompute(std::function<void (nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)> const&, nnvm::Op const*, nnvm::NodeAttrs const&, mxnet::Context const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::engine::Var*, std::allocator<mxnet::engine::Var*> > const&, std::vector<mxnet::Resource, std::allocator<mxnet::Resource> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<mxnet::NDArray*, std::allocator<mxnet::NDArray*> > const&, std::vector<unsigned int, std::allocator<unsigned int> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&)::{la
mbda(mxnet::RunContext)#1}::operator()(mxnet::RunContext) const+0x9f2) [0x7fd6fe2eff02]
[bt] (3) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(void mxnet::op::CTCLossOpForward<mshadow::gpu>(nnvm::NodeAttrs const&, mxnet::OpContext const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&, std::vector<mxnet::OpReqType, std::allocator<mxnet::OpReqType> > const&, std::vector<mxnet::TBlob, std::allocator<mxnet::TBlob> > const&)+0x121c) [0x7fd7042c8072]
[bt] (2) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(mshadow::Tensor<mshadow::gpu, 3, float> mxnet::TBlob::get<mshadow::gpu, 3, float>(mshadow::Stream<mshadow::gpu>*) const+0xf7) [0x7fd7038cc645]
[bt] (1) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(float* mxnet::TBlob::dptr<float>() const+0x11d) [0x7fd6fe21e5ed]
[bt] (0) /home/super/python-latest/lib/python3.9/site-packages/mxnet-2.0.0-py3.9.egg/mxnet/libmxnet.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x6b) [0x7fd6fe05d72b]
File "/home/super/software/incubator-mxnet/include/mxnet/././tensor_blob.h", line 256
MXNetError: Check failed: mshadow: :DataType<DType>::kFlag == type_flag_: TBlob.get_with_shape: data type do not match specified type.Expected: half v.s. given float`
## To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
***We recommend using our script for collecting the diagnostic information with the following command***
`curl --retry 10 -s https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py | python3`
<details>
<summary>Environment Information</summary>
```
# Paste the diagnose.py command output here
```
</details>
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@mxnet.apache.org
For additional commands, e-mail: issues-help@mxnet.apache.org
[GitHub] [incubator-mxnet] github-actions[bot] commented on issue #19628: CTC loss in mxnet 2.0 not work when use half precision
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on issue #19628:
URL: https://github.com/apache/incubator-mxnet/issues/19628#issuecomment-738594839
Welcome to Apache MXNet (incubating)! We are on a mission to democratize AI, and we are glad that you are contributing to it by opening this issue.
Please make sure to include all the relevant context, and one of the @apache/mxnet-committers will be here shortly.
If you are interested in contributing to our project, let us know! Also, be sure to check out our guide on [contributing to MXNet](https://mxnet.apache.org/community/contribute) and our [development guides wiki](https://cwiki.apache.org/confluence/display/MXNET/Developments).
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@mxnet.apache.org
For additional commands, e-mail: issues-help@mxnet.apache.org