added classes for ReduceSum, ExpandDims, Dot and Repeat layers in CNNNet

src/main/resources/templates/gluon/CNNNet.ftl

@@ -40,6 +40,40 @@ class Concatenate(gluon.HybridBlock):
     def hybrid_forward(self, F, *x):
         return F.concat(*x, dim=self.dim)
 
+class Repeat(gluon.HybridBlock):
+    def __init__(self, repeats, axis=1, **kwargs):
+        super(Repeat, self).__init__(**kwargs)
+        with self.name_scope():
+            self.axis = axis
+            self.repeats = repeats
+
+    def hybrid_forward(self, F, x):
+        return F.repeat(data=x, axis=self.axis, repeats=self.repeats)
+
+class Dot(gluon.HybridBlock):
+    def __init__(self, **kwargs):
+        super(Dot, self).__init__(**kwargs)
+
+    def hybrid_forward(self, F, *x):
+        return F.dot(*x)
+
+class ExpandDims(gluon.HybridBlock):
+    def __init__(self, dim=1, **kwargs):
+        super(ExpandDims, self).__init__(**kwargs)
+        with self.name_scope():
+            self.dim = dim
+
+    def hybrid_forward(self, F, x):
+        return F.expand_dims(data=x, axis=self.dim)
+
+class ReduceSum(gluon.HybridBlock):
+    def __init__(self, axis=1, **kwargs):
+        super(ReduceSum, self).__init__(**kwargs)
+        with self.name_scope():
+            self.axis = axis
+
+    def hybrid_forward(self, F, x):
+        return F.sum(data=x, axis=self.axis)
 
 class ZScoreNormalization(gluon.HybridBlock):
     def __init__(self, data_mean, data_std, **kwargs):

src/main/resources/templates/gluon/elements/Dot.ftl

-<#if mode == "FORWARD_FUNCTION">
-        ${element.name} = mx.symbol.dot(${element.inputs[0]}, ${element.inputs[1]})
-<#elseif mode == "PYTHON_INLINE">
-                    ${element.name} = mx.symbol.dot(${element.inputs[0]}, ${element.inputs[1]})
+<#if mode == "ARCHITECTURE_DEFINITION">
+            self.${element.name} = Dot()
+            <#include "OutputShape.ftl">
+<#elseif mode == "FORWARD_FUNCTION">
+        ${element.name} = self.${element.name}(${tc.join(element.inputs, ", ")})
 </#if>
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src/main/resources/templates/gluon/elements/ExpandDims.ftl

 <#assign dim = element.dim?c>
-<#if mode == "FORWARD_FUNCTION">
-        ${element.name} = mx.symbol.expand_dims(data = ${element.inputs[0]}, axis=${dim})
-<#elseif mode == "PYTHON_INLINE">
-                    ${element.name} = mx.symbol.expand_dims(data = ${element.inputs[0]}, axis=${dim})
+<#if mode == "ARCHITECTURE_DEFINITION">
+            self.${element.name} = ExpandDims(dim=${dim})
+            <#include "OutputShape.ftl">
+<#elseif mode == "FORWARD_FUNCTION">
+        ${element.name} = self.${element.name}(${element.inputs[0]})
 </#if>
\ No newline at end of file

src/main/resources/templates/gluon/elements/ReduceSum.ftl

 <#assign axis = element.axis?c>
-<#if mode == "FORWARD_FUNCTION">
-        ${element.name} = mx.symbol.sum(data = ${element.inputs[0]}, axis=${axis})
-<#elseif mode == "PYTHON_INLINE">
-                    ${element.name} = mx.symbol.sum(data = ${element.inputs[0]}, axis=${axis})
+<#if mode == "ARCHITECTURE_DEFINITION">
+            self.${element.name} = ReduceSum(axis=${axis})
+            <#include "OutputShape.ftl">
+<#elseif mode == "FORWARD_FUNCTION">
+        ${element.name} = self.${element.name}(${element.inputs[0]})
 </#if>
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src/main/resources/templates/gluon/elements/Repeat.ftl

-<#assign repeats = element.repeats?c>
 <#assign axis = element.axis?c>
-<#if mode == "FORWARD_FUNCTION">
-        ${element.name} = mx.symbol.repeat(repeats=${repeats}, axis=${axis})
-<#elseif mode == "PYTHON_INLINE">
-                    ${element.name} = mx.symbol.repeat(repeats=${repeats}, axis=${axis})
+<#assign repeats = element.repeats?c>
+<#if mode == "ARCHITECTURE_DEFINITION">
+            self.${element.name} = Repeat(repeats=${repeats}, axis=${axis})
+            <#include "OutputShape.ftl">
+<#elseif mode == "FORWARD_FUNCTION">
+        ${element.name} = self.${element.name}(${element.inputs[0]})
 </#if>
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