[GitHub] [incubator-mxnet] TaoLv commented on issue #15930: Fix dtype inference in arange_like operator

2019-08-16 Thread GitBox 
TaoLv commented on issue #15930: Fix dtype inference in arange_like operator
URL: https://github.com/apache/incubator-mxnet/pull/15930#issuecomment-522049857
 
 
   @eric-haibin-lin @fhieber 


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[GitHub] [incubator-mxnet] TaoLv commented on issue #15930: Fix dtype inference in arange_like operator

2019-08-17 Thread GitBox 
TaoLv commented on issue #15930: Fix dtype inference in arange_like operator
URL: https://github.com/apache/incubator-mxnet/pull/15930#issuecomment-522246438
 
 
   @eric-haibin-lin Did you observe any crash with fp16 input? With below code 
snippet, it doesn't seem to crash but just gives numpy.float32 output:
   
   ```python
   import mxnet as mx
   import numpy as np
   
   x = mx.sym.Variable('x', dtype=np.float16)
   y = mx.sym.reshape(x, shape=(0, 0, -1))
   z = mx.sym.contrib.arange_like(y, axis=-1)
   
   mod = z.simple_bind(ctx=mx.gpu(0), x=(3, 4, 5, 6), graph_req='null')
   
   mod.arg_arrays[0][:] = 
np.random.normal(size=mod.arg_arrays[0].shape).astype(np.float16)
   out = mod.forward(is_train=False)
   print(out[0].dtype)
   ```


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[GitHub] [incubator-mxnet] TaoLv commented on issue #15930: Fix dtype inference in arange_like operator

2019-08-20 Thread GitBox 
TaoLv commented on issue #15930: Fix dtype inference in arange_like operator
URL: https://github.com/apache/incubator-mxnet/pull/15930#issuecomment-523068244
 
 
   @eric-haibin-lin  do you think the below code snippet can be used as a test 
case?
   
   ```python
   import mxnet as mx
   import numpy as np
   
   dtypes = [np.float16, np.float32, np.float64]
   
   for t in dtypes:
   x = mx.sym.Variable('x', dtype=t)
   y = mx.sym.reshape(x, shape=(0, 0, -1))
   z = mx.sym.contrib.arange_like(y, axis=-1)
   
   mod = z.simple_bind(ctx=mx.gpu(0), x=(3, 4, 5, 6), graph_req='null')
   
   mod.arg_arrays[0][:] = 
np.random.normal(size=mod.arg_arrays[0].shape).astype(t)
   out = mod.forward(is_train=False)
   assert out[0].dtype == np.float32
   ```


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[GitHub] [incubator-mxnet] TaoLv commented on issue #15930: Fix dtype inference in arange_like operator

2019-08-25 Thread GitBox 
TaoLv commented on issue #15930: Fix dtype inference in arange_like operator
URL: https://github.com/apache/incubator-mxnet/pull/15930#issuecomment-524635000
 
 
   > I hope to reserve the dtype attribution, and there is a default action 
when dtype is None.
   
   Just want to provide the same user experience for `ones_like`, `zeros_like` 
and `arange_like`.


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