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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/06/07 23:47:18 UTC
[GitHub] [incubator-mxnet] charlieyou commented on issue #15166: asnumpy()
fails on float16 gradient
charlieyou commented on issue #15166: asnumpy() fails on float16 gradient
URL: https://github.com/apache/incubator-mxnet/issues/15166#issuecomment-500072064
@leleamol This is my bad... I was attempting to post an issue that got at the root issue, but I now realize I posted something with a different cause, which is as you have pointed out, not a bug.
Here is a MRE and stack trace for the actual issue I am facing. I can post it as a separate issue and close this one if desired.
## MRE
```
import mxnet as mx
from mxnet.gluon.rnn import LSTM
fake_data = mx.nd.random.uniform(shape=(1, 32, 32), dtype="float16").as_in_context(mx.gpu(0))
fake_label = mx.nd.random.uniform(shape=(1, 32), dtype="float16").as_in_context(mx.gpu(0))
lstm_layer = LSTM(32, dtype='float16')
lstm_layer.initialize(ctx=mx.gpu(0))
ctc_loss = mx.gluon.loss.CTCLoss()
with mx.autograd.record():
x = lstm_layer(fake_data)
loss = ctc_loss(x, fake_label)
loss.backward()
l = mx.nd.mean(loss).asnumpy()
```
## Stack trace
```
---------------------------------------------------------------------------
MXNetError Traceback (most recent call last)
<ipython-input-69-6bfc070aed48> in <module>()
13
14 loss.backward()
---> 15 l = mx.nd.mean(loss).asnumpy()
~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/ndarray/ndarray.py in asnumpy(self)
1994 self.handle,
1995 data.ctypes.data_as(ctypes.c_void_p),
-> 1996 ctypes.c_size_t(data.size)))
1997 return data
1998
~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/base.py in check_call(ret)
251 """
252 if ret != 0:
--> 253 raise MXNetError(py_str(_LIB.MXGetLastError()))
254
255
MXNetError: [23:39:12] include/mxnet/././tensor_blob.h:236: Check failed: mshadow::DataType<DType>::kFlag == type_flag_: TBlob.get_with_shape: data type do not match specified type.Expected: 2 v.s. given 0
Stack trace:
[bt] (0) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x4ac1eb) [0x7ff57de371eb]
[bt] (1) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x30c8972) [0x7ff580a53972]
[bt] (2) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x31dc115) [0x7ff580b67115]
[bt] (3) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/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&)::{lambda(mxnet::RunContext)#1}::operator()(mxnet::RunContext) const+0x307) [0x7ff57ffd9f47]
[bt] (4) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x259adf4) [0x7ff57ff25df4]
[bt] (5) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25a8789) [0x7ff57ff33789]
[bt] (6) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25abbf0) [0x7ff57ff36bf0]
[bt] (7) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25abe86) [0x7ff57ff36e86]
[bt] (8) /home/ec2-user/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/libmxnet.so(+0x25a6f94) [0x7ff57ff31f94]
```
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