Adjust pseudocode types to account for zero point

When reading tensor values with zero point, the returned value
has one more bit than the original to account for zero point.

Update cases of apply_clip to properly represent the types
involved.

Change-Id: I60c17b1b244c34b4f04f042807936ae0f282ce93

1 files changed, 14 insertions, 14 deletions

diff --git a/chapters/tensor_ops.adoc b/chapters/tensor_ops.adoc
index 341f51d..b006c71 100644
--- a/chapters/tensor_ops.adoc
+++ b/chapters/tensor_ops.adoc
@@ -99,7 +99,7 @@ for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W, 0 <= c < C ) {
     for_each(0 <= ky < kernel_y, 0 <= kx < kernel_x) {
         y = iy + ky;
         x = ix + kx;
-        in_t value = tensor_read<in_t>(input, [N,IH,IW,IC], [n,y,x,c], input_zp, pad);
+        acc_t value = tensor_read<in_t>(input, [N,IH,IW,IC], [n,y,x,c], input_zp, pad);
         acc = apply_add<acc_t>(acc, value);
         if (0 <= y < IH and 0 <= x < IW) count++
     }
@@ -108,7 +108,7 @@ for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W, 0 <= c < C ) {
     } else {
         scale_t scale = reciprocal_scale(count);
         acc = apply_scale_32(acc, scale.multiplier, scale.shift, false);
-        output_val = apply_clip<in_t>(acc + output_zp, minimum<in_t>, maximum<in_t>)
+        output_val = (in_t)apply_clip<acc_t>(acc + output_zp, minimum<in_t>, maximum<in_t>)
     }
     tensor_write<in_t>(output, [N,H,W,OC], [n,oy,ox,oc], output_val);
 }
@@ -164,8 +164,8 @@ for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W; 0 <= oc < OC) {
     for_each(0 <= ky < KH, 0 <= kx < KW, 0 <= ic < IC) {
         y = iy + ky * dilation_y;
         x = ix + kx * dilation_x;
-        in_t value  = tensor_read<in_t>(input, [N,IH,IW,IC], [n,y,x,ic], input_zp, pad);
-        weight_t weight = tensor_read<weight_t>(weight, [OC,KH,KW,IC], [oc,ky,kx,ic], weight_zp);
+        acc_t value  = tensor_read<in_t>(input, [N,IH,IW,IC], [n,y,x,ic], input_zp, pad);
+        acc_t weight = tensor_read<weight_t>(weight, [OC,KH,KW,IC], [oc,ky,kx,ic], weight_zp);
         acc = apply_add<acc_t>(acc, value * weight);
     }
     acc = apply_add<acc_t>(acc, bias[oc]);
@@ -227,8 +227,8 @@ for_each(0 <= n < N, 0 <= od < D, 0 <= oy < H, 0 <= ox < W; 0 <= oc < OC) {
         d = id + kd * dilation_d;
         y = iy + ky * dilation_y;
         x = ix + kx * dilation_x;
-        in_t value  = tensor_read<in_t>(input, [N,ID,IH,IW,IC], [n,d,y,x,ic], input_zp, pad);
-        weight_t weight = tensor_read<weight_t>(weight,[OC,KD,KH,KW,IC],[oc,kd,ky,kx,ic], weight_zp);
+        acc_t value  = tensor_read<in_t>(input, [N,ID,IH,IW,IC], [n,d,y,x,ic], input_zp, pad);
+        acc_t weight = tensor_read<weight_t>(weight,[OC,KD,KH,KW,IC],[oc,kd,ky,kx,ic], weight_zp);
         acc = apply_add<acc_t>(acc, value * weight);
     }
     acc = apply_add<acc_t>(acc, bias[oc]);
@@ -289,8 +289,8 @@ for_each(0 <= n<N, 0 <= oy < H, 0 <= ox < W; 0 <= c < (C * M), 0 <= m < M) {
     for_each(0 <= ky < KH, 0 <= kx < KW) {
         y = iy + ky * dilation_y;
         x = ix + kx * dilation_x;
-        in_t value  = tensor_read<in_t>(input, [N,H,W,C], [n,y,x,c], input_zp, pad);
-        weight_t weight = tensor_read<weight_t>(weight, [KH,KW,C,M], [ky,kx,c,m], weight_zp);
+        acc_t value  = tensor_read<in_t>(input, [N,H,W,C], [n,y,x,c], input_zp, pad);
+        acc_t weight = tensor_read<weight_t>(weight, [KH,KW,C,M], [ky,kx,c,m], weight_zp);
         acc = apply_add<acc_t>(acc, value * weight);
     }
     acc = apply_add<acc_t>(acc, bias[(c * M) + m]);
@@ -342,8 +342,8 @@ assert(weight_t == int8_t || weight_zp == 0);
 for_each(0 <= n < N, 0 <= oc < OC) {
     acc_t acc = 0;
     for_each(0 <= ic < IC) {
-        in_t value  = tensor_read<in_t>(input, [N,IC], [n,ic], input_zp);
-        weight_t weight = tensor_read<weight_t>(weight, [OC,IC], [oc,ic], weight_zp);
+        acc_t value  = tensor_read<in_t>(input, [N,IC], [n,ic], input_zp);
+        acc_t weight = tensor_read<weight_t>(weight, [OC,IC], [oc,ic], weight_zp);
         acc = apply_add<acc_t>(acc, value * weight);
     }
     acc = apply_add<acc_t>(acc, bias[oc]);
@@ -392,8 +392,8 @@ assert(in_t == int8_t || (A_zp == 0 && B_zp == 0)); // Zero point only for int8_
 for_each(0 <= n < N, 0 <= h < H, 0 <= w < W) {
     acc_t acc = 0;
     for_each(0 <= c < C) {
-        in_t value1 = tensor_read<in_t>(A, [N,H,C], [n,h,c], A_zp);
-        in_t value2 = tensor_read<in_t>(B, [N,C,W], [n,c,w], B_zp);
+        acc_t value1 = tensor_read<in_t>(A, [N,H,C], [n,h,c], A_zp);
+        acc_t value2 = tensor_read<in_t>(B, [N,C,W], [n,c,w], B_zp);
         acc = apply_add<acc_t>(acc, value1 * value2);
     }
     tensor_write<acc_t>(output, [N,H,W], [n,h,w], acc);
@@ -500,8 +500,8 @@ for_each(0 <= n < N, 0 <= iy < IH, 0 <= ix < IW, 0 <= oc < OC,
     ox = ix * stride_x - out_pad_left + kx;
     if (oy >= 0 && oy < OH && ox >= 0 && ox < OW) {
         acc_t acc = tensor_read<acc_t>(output, [N,OH,OW,OC], [n,oy,ox,oc]);
-        in_t value = tensor_read<in_t>(input, [N,IH,IW,IC], [n,iy,ix,ic], input_zp);
-        weight_t weight = tensor_read<weight_t>(weight, [OC,KH,KW,IC], [oc,ky,kx,ic], weight_zp);
+        acc_t value = tensor_read<in_t>(input, [N,IH,IW,IC], [n,iy,ix,ic], input_zp);
+        acc_t weight = tensor_read<weight_t>(weight, [OC,KH,KW,IC], [oc,ky,kx,ic], weight_zp);
         acc = apply_add<acc_t>(acc, value * weight);
         tensor_write<acc_t>(output, [N,OH,OW,OC], [n,oy,ox,oc], acc);
     }