[singa] branch dev-postgresql updated: Add the SumErrorLayer implementation

[wa...@apache.org]

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wangwei pushed a commit to branch dev-postgresql
in repository https://gitbox.apache.org/repos/asf/singa.git


The following commit(s) were added to refs/heads/dev-postgresql by this push:
     new 2cf2a5be Add the SumErrorLayer implementation
     new e6cb95f7 Merge pull request #1088 from liuchangshiye/model-selection-psql-msmlp
2cf2a5be is described below

commit 2cf2a5be9c855693f77c09cee87647f20e53874f
Author: liuchangshiye <li...@gmail.com>
AuthorDate: Wed Sep 6 16:40:56 2023 +0800

    Add the SumErrorLayer implementation
---
 examples/model_selection_psql/msmlp/model.py | 25 ++++++++++++++++---------
 1 file changed, 16 insertions(+), 9 deletions(-)

diff --git a/examples/model_selection_psql/msmlp/model.py b/examples/model_selection_psql/msmlp/model.py
index 81ccd5b0..be898b29 100644
--- a/examples/model_selection_psql/msmlp/model.py
+++ b/examples/model_selection_psql/msmlp/model.py
@@ -32,9 +32,7 @@ np_dtype = {"float16": np.float16, "float32": np.float32}
 
 singa_dtype = {"float16": tensor.float16, "float32": tensor.float32}
 
-#### self-defined loss begin
-
-### reference from autograd.py
+### refer to autograd.py
 class SumError(Operator):
 
     def __init__(self):
@@ -52,7 +50,7 @@ class SumError(Operator):
         #     self.n *= s
         # loss /= self.n
         return loss
-
+    
     def backward(self, dy=1.0):
         # dx = self.err
         dev = device.get_default_device()
@@ -62,12 +60,21 @@ class SumError(Operator):
         dx *= dy
         return dx
 
-### called in the MSMLP class for sum error loss gradients
 def se_loss(x):
-    # assert x.shape == t.shape, "input and target shape different: %s, %s" % (
-    #     x.shape, t.shape)
     return SumError()(x)[0]
 
+### refer to layer.py
+class SumErrorLayer(Layer):
+    """
+    Generate a SumError Layer
+    """
+
+    def __init__(self):
+        super(SumErrorLayer, self).__init__()
+
+    def forward(self, x):
+        return se_loss(x)
+
 class MSMLP(model.Model):
 
     def __init__(self, data_size=10, perceptron_size=100, num_classes=10):
@@ -79,8 +86,8 @@ class MSMLP(model.Model):
         self.linear1 = layer.Linear(perceptron_size)
         self.linear2 = layer.Linear(num_classes)
         self.softmax_cross_entropy = layer.SoftMaxCrossEntropy()
-        self.sum_error = SumErrorLayer()
-
+        self.sum_error = SumErrorLayer()  # for synflow backward
+    
     def forward(self, inputs):
         y = self.linear1(inputs)
         y = self.relu(y)