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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2020/04/10 23:39:07 UTC
[GitHub] [incubator-mxnet] sxjscience commented on issue #18022: [Numpy]
Weird bug with mixed dtype
sxjscience commented on issue #18022: [Numpy] Weird bug with mixed dtype
URL: https://github.com/apache/incubator-mxnet/issues/18022#issuecomment-612266886
For this bug, the most weird thing is that it won't raise an error if I commented two lines, i.e., the following one will run well (commented two lines).
```python
import mxnet as mx
from mxnet.gluon import nn
import os
os.environ['MXNET_EXEC_INPLACE_GRAD_SUM_CAP'] = '4'
os.environ['DMLC_LOG_STACK_TRACE_DEPTH'] = '20'
mx.npx.set_np()
ctx = mx.cpu()
batch_size = 2
sequence_length = 10
mask = mx.np.random.randint(0, 2, (batch_size, sequence_length), ctx=ctx)
contextual_embeddings = mx.np.random.normal(0, 1, (2, sequence_length, 256), ctx=ctx, dtype=mx.np.float32)
p_mask = 1 - mask
l_start_scores = nn.Dense(1, flatten=False)
l_end_scores = nn.Dense(1, flatten=False)
l_start_scores.initialize(ctx=ctx)
l_end_scores.initialize(ctx=ctx)
with mx.autograd.record():
# start_scores = mx.np.squeeze(l_start_scores(contextual_embeddings), -1)
# start_logits = start_scores * p_mask + (1 - p_mask) * (-1e18)
contextual_embeddings = mx.np.expand_dims(contextual_embeddings, axis=1) # (B, 1, T, C)
end_scores = l_end_scores(contextual_embeddings)
end_scores = mx.np.squeeze(end_scores, -1)
p_mask = mx.np.expand_dims(p_mask, axis=-1)
end_logits = p_mask * end_scores + (1 - p_mask) * -1e18
end_logits = end_logits * p_mask + (1 - p_mask) * -1e18
loss = end_logits.sum()
loss.backward()
mx.npx.waitall()
```
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