[GitHub] [incubator-mxnet] ThomasDelteil commented on a change in pull request #15230: Updating SymbolBlock.imports to support different dtypes

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ThomasDelteil commented on a change in pull request #15230: Updating SymbolBlock.imports to support different dtypes
URL: https://github.com/apache/incubator-mxnet/pull/15230#discussion_r293515130
 
 

 ##########
 File path: tests/python/unittest/test_gluon.py
 ##########
 @@ -2750,6 +2775,17 @@ def test_gluon_param_load():
     net.cast('float16')
     net.load_parameters('test_gluon_param_load.params', cast_dtype=True)
     mx.nd.waitall()
+    
+@with_seed()
+def test_gluon_param_load_dtype_source():
+    net = mx.gluon.nn.Dense(10, in_units=10)
+    net.initialize()
+    net.cast('float16')
 
 Review comment:
   @pengzhao-intel @xinyu-intel, thanks for the suggestion, I'm actually unable to find a single layer in Gluon that supports `int8` or `uint8`. 
   
   ```python
   net = mx.gluon.nn.Conv2D(channels=4, kernel_size=3, in_channels=3)
   net.initialize()
   net.cast(np.uint8)
   net(mx.nd.ones((1,3,224,224), dtype=np.uint8))
   ```
   
   gives me a 
   ```text
   MXNetError: std::exception
   ```
   
   Any suggestions without resorting to symbolically fused graphs?

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