Definition and test scripts for dscnn layer 1

Author: AnirudhBHarish

c_reference/include/dscnn.h

@@ -0,0 +1,14 @@
+#ifndef __DSCNN__
+#define __DSCNN__
+
+#include"conv1d.h"
+#include"conv_utils.h"
+#include<stdlib.h>
+#include<math.h>
+
+int DSCNN_LR(float* output_signal, float* input_signal, unsigned in_T, unsigned in_channels, float* mean, float* var,
+    unsigned affine, float* gamma, float* beta, unsigned in_place, unsigned cnn_hidden, int cnn_padding, unsigned cnn_kernel_size,
+    const void* cnn_params, int cnn_activations);
+
+
+#endif

c_reference/src/dscnn.c

@@ -0,0 +1,23 @@
+#include"dscnn.h"
+#include"conv1d.h"
+#include"conv_utils.h"
+
+int DSCNN_LR(float* output_signal, float* input_signal, unsigned in_T, unsigned in_channels, float* mean, float* var,
+    unsigned affine, float* gamma, float* beta, unsigned in_place, unsigned cnn_hidden, int cnn_padding, unsigned cnn_kernel_size,
+    const void* cnn_params, int cnn_activations){
+    
+    float out_T;
+    
+    // BatchNorm
+    float* norm_out = (float*)malloc(in_T*in_channels*sizeof(float));
+    BatchNorm1d(norm_out, input_signal, in_T, in_channels, 
+    mean, var, affine, gamma, beta, in_place);
+
+    // CNN
+    out_T = in_T - cnn_kernel_size + 2*cnn_padding + 1;
+    Conv1D_LR(output_signal, out_T, cnn_hidden, norm_out, 
+    in_T, in_channels, cnn_padding, cnn_kernel_size, 
+    cnn_params, cnn_activations);
+    free(norm_out);
+    return 0;
+}

c_reference/tests/dscnn/dscnn_lr.h

@@ -0,0 +1,36 @@
+#include<stdio.h>
+#include<stdlib.h>
+
+#include"dscnn_lr.h"
+#include"conv1d.h"
+#include"dscnn.h"
+#include"conv_utils.h"
+
+int main(){
+    
+    ConvLayers_LR_Params conv_params = {
+        .W1 = CNN1_W1,
+        .W2 = CNN1_W2,
+        .B = CNN1_BIAS,
+        .rank = LOW_RANK
+    };
+
+    float pred[O_T * O_F] = {};
+    // int DSCNN_LR(float* output_signal, float* input_signal, unsigned in_T, unsigned in_channels, float* mean, float* stddev,
+    // unsigned affine, float* gamma, float* beta, unsigned in_place, unsigned cnn_hidden, int cnn_padding, unsigned cnn_kernel_size,
+    // const void* cnn_params, int cnn_activations)
+    DSCNN_LR(pred, INPUT, I_T, I_F, BNORM_CNN1_MEAN, BNORM_CNN1_VAR,
+    0, 0, 0, 0, O_F, 2, FILT,
+    &conv_params, 0);
+    float error = 0;
+    for(int t = 0 ; t < O_T ; t++){
+        for(int d = 0 ; d < O_F ; d++){
+            error += ((pred[t * O_F + d] - OUTPUT[t * O_F + d]) * (pred[t * O_F + d] - OUTPUT[t * O_F + d]));
+        }
+    }
+    float avg_error = error/(O_T*O_F);
+    printf("DSCNN K5 Block\n");
+    printf("Aggregate Squared Error : %f   ;   Mean Sqaured Error : %f  \n", error, avg_error);
+
+    return 0 ;
+}