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Improve presentation of CNN. #1

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33 changes: 15 additions & 18 deletions tutorial/cnn.sac
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Original file line number Diff line number Diff line change
Expand Up @@ -155,32 +155,29 @@ float[*], float[*] BackConv2( float[*] d_output, float[*] weights, float[*] inpu
#endif
//------------------------------------------------------------------------------


inline float[*] >--conv-> (float[*] in, float[*] weights) { return Conv (in, weights); }
inline float[*] >--logistics-> (float[*] in, int _) { return Logistic (in); }
inline float[*] >--avgpool-> (float[*] in, int[.] filter) { return AveragePool (in, filter, []); }
inline float[*] >--reshape-> (float[*] in, int[.] s) { return reshape (s, in); }

int main()
{
in = genarray( [28,28], 0f);
in[6,6] = 42f;

print( in);

k1 = genarray( [5,5,6], 1f/25f);
c1 = Logistic( Conv( in, k1 ));
print( shape(c1));

s1 = AveragePool( c1, [2,2], []);
print( shape( s1));

k2 = genarray( [5,5,6,12], 1f/150f);
c2 = Logistic( Conv( s1, k2));

print( shape( c2));

s2 = AveragePool( c2, [2,2], []);
print( shape( s2));

fc = genarray( [4,4,1,12,10], 1f/192f);
out = reshape( [10], Conv( s2, fc));
print( out);
_ = 0;

out = in // Input Layer
>--conv-> k1 >--logistics-> _ // Convolution Layer C1
>--avgpool-> [2,2] // Pooling Layer S1
>--conv-> k2 >--logistics-> _ // Convolution Layer C2
>--avgpool-> [2,2] // Pooling Layer S2
>--conv-> fc >--reshape-> [10]; // Fully connection layer FC

print (out);
return 0;
}