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Diffstat (limited to 'chapters/appendix_a.adoc')
| -rw-r--r-- | chapters/appendix_a.adoc | 34 |
1 files changed, 29 insertions, 5 deletions
diff --git a/chapters/appendix_a.adoc b/chapters/appendix_a.adoc index d4235e8..ba3b6bb 100644 --- a/chapters/appendix_a.adoc +++ b/chapters/appendix_a.adoc @@ -37,7 +37,10 @@ This function takes the following arguments: * S is the test set number which identifies which generator is used * KS is the kernel size -* p is the parameter number of 0 for the first input (usually data) and 1 for the second input (usually weights) +* p is the parameter number of: +** 0 for the first input (usually data) +** 1 for the second input (usually weights) +** 2 for the third input if present (usually bias) * k is the index within the kernel in the range 0 \<= k < KS * i is the index within the tensor to write @@ -61,6 +64,7 @@ The aim of this generator is to check that sum of products with zero gives zero | p | tosa_mi_data(S, KS, p, k, i) = | 0 | set_data(2*S, i) < 0 ? 0.0 : set_data(2*S+1, i) | 1 | set_data(2*S, i) < 0 ? set_data(2*S+1, i) : 0.0 +| 2 | 0.0 |=== ==== Test set S=1 @@ -70,8 +74,9 @@ The aim of this test set is to check values with large exponents. [cols="1,9"] |=== | p | tosa_mi_data(S, KS, p, k, i) = -| 0 | (B/sqrt(KS))*(0.75 + 0.25*set_data(2*S+0, i)) -| 1 | (B/sqrt(KS))*(0.75 + 0.25*set_data(2*S+1, i)) +| 0 | (B/sqrt(KS+1))*(0.75 + 0.25*set_data(3*S+0, i)) +| 1 | (B/sqrt(KS+1))*(0.75 + 0.25*set_data(3*S+1, i)) +| 2 | (B*B/(KS+1))*(0.75 + 0.25*set_data(3*S+2, i)) |=== ==== Test set S=2 @@ -85,6 +90,7 @@ If the implementation changes the order of the sum, then the test data must also | p | tosa_mi_data(S, KS, p, k, i) = | 0 | (k==0) ? 1.0 : set_data(2*S+0, i)/sqrt(KS) | 1 | (k==0) ? 1.0 : set_data(2*S+1, i)/sqrt(KS) +| 2 | 0.0 |=== ==== Test set S=3 @@ -98,6 +104,7 @@ If the implementation changes the order of the sum, then the test data must also | p | tosa_mi_data(S, KS, p, k, i) = | 0 | (k==0) ? 16.0 : exp(2*set_data(2*S+0, 2*i+0)) * set_data(2*S+0, 2*i+1) | 1 | (k==0) ? 16.0 : exp(2*set_data(2*S+1, 2*i+0)) * set_data(2*S+1, 2*i+1) +| 2 | 0.0 |=== ==== Test set S=4 @@ -109,6 +116,7 @@ The aim of this test set is to check a mixture of zero and non-zero products. | p | tosa_mi_data(S, KS, p, k, i) = | 0 | (k==KS/2) ? +0.5 : (set_data(2*S, i) < 0 ? 0.0 : (B/sqrt(KS))*set_data(2*S+1, i)) | 1 | (k==KS/2) ? -0.5 : (set_data(2*S, i) < 0 ? (B/sqrt(KS))*set_data(2*S+1, i) : 0.0) +| 2 | 0.0 |=== ==== Test set S=5 @@ -118,8 +126,9 @@ The aim of this test set is to check signed inputs of large range. [cols="1,9"] |=== | p | tosa_mi_data(S, KS, p, k, i) = -| 0 | (B/sqrt(KS))*set_data(2*S+0, i) -| 1 | (B/sqrt(KS))*set_data(2*S+1, i) +| 0 | (B/sqrt(KS+1))*set_data(3*S+0, i) +| 1 | (B/sqrt(KS+1))*set_data(3*S+1, i) +| 2 | (B*B/(KS+1))*set_data(3*S+2, i) |=== === Main Inference operator test data @@ -145,6 +154,9 @@ for (0 <= n < N, 0 <= iy < IH, 0 <= ix < IW, 0 <= ic < IC) { for (0 <= oc < OC, 0 <= ky < KH, 0 <= kx < KW, 0 <= ic < IC) { weight[oc, ky, kx, ic] = tosa_mi_data(S, KS, 1, (ky*KW+kx)*IC+ic, ((oc*KH+ky)*KW+kx)*IC+ic); } +for (0 <= oc < OC) { + bias[oc] = tosa_mi_data(S, KS, 2, oc) +} ---- ==== CONV3D @@ -162,6 +174,9 @@ for (0 <= n < N, 0 <= id < UD, 0 <= iy < IH, 0 <= ix < IW, 0 <= ic < IC) { for (0 <= oc < OC, 0 <= kd < KD, 0 <= ky < KH, 0 <= kx < KW, 0 <= ic < IC) { weight[oc, kd, ky, kx, ic] = tosa_mi_data(S, KS, 1, ((kd*KH+ky)*KW+kx)*IC+ic, (((oc*KD+kd)*KH+ky)*KW+kx)*IC+ic); } +for (0 <= oc < OC) { + bias[oc] = tosa_mi_data(S, KS, 2, oc) +} ---- ==== DEPTHWISE_CONV2D @@ -179,6 +194,9 @@ for (0 <= n < N, 0 <= iy < IH, 0 <= ix < IW, 0 <= c < C) { for (0 <= ky < KH, 0 <= kx < KW, 0 <= c < C, 0 <= m < M) { weight[ky, kx, c, m] = tosa_mi_data(S, KS, 1, (ky*KW+kx), ((ky*KW+kx)*C+c)*M+m); } +for (0 <= oc < C*M) { + bias[oc] = tosa_mi_data(S, KS, 2, oc) +} ---- ==== FULLY_CONNECTED @@ -196,6 +214,9 @@ for (0 <= n < N, 0 <= ic < IC) { for (0 <= oc < OC, 0 <= ic < IC) { weight[oc, ic] = tosa_mi_data(S, KS, 1, ic, oc*IC+ic); } +for (0 <= oc < OC) { + bias[oc] = tosa_mi_data(S, KS, 2, oc) +} ---- ==== MATMUL @@ -230,6 +251,9 @@ for (0 <= n < N, 0 <= iy < IH, 0 <= ix < IW, 0 <= ic < IC) { for (0 <= oc < OC, 0 <= ky < KH, 0 <= kx < KW, 0 <= ic < IC) { weight[oc, ky, kx, ic] = tosa_mi_data(S, KS, 1, (ky*KW+kx)*IC+ic, ((oc*KH+ky)*KW+kx)*IC+ic); } +for (0 <= oc < OC) { + bias[oc] = tosa_mi_data(S, KS, 2, oc) +} ---- ==== FFT2D |