diff options
| -rw-r--r-- | chapters/tensor_ops.adoc | 16 | ||||
| -rw-r--r-- | tosa.xml | 10 |
2 files changed, 16 insertions, 10 deletions
diff --git a/chapters/tensor_ops.adoc b/chapters/tensor_ops.adoc index 656af85..6387790 100644 --- a/chapters/tensor_ops.adoc +++ b/chapters/tensor_ops.adoc @@ -110,6 +110,7 @@ ERROR_IF(stride_y < 1 || stride_x < 1); ERROR_IF(dilation_y < 1 || dilation_x < 1); ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1); ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1); +ERROR_IF(BC != OC && BC != 1); for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= oc < OC) { out_t acc = 0; @@ -126,7 +127,7 @@ for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= oc < OC) { acc = apply_add<out_t>(acc, value * weight); } } - acc = apply_add<out_t>(acc, bias[oc]); + acc = apply_add<out_t>(acc, bias[(BC == 1) ? 0 : oc]); tensor_write<out_t>(output, [N,OH,OW,OC], [n,oy,ox,oc], acc); } ---- @@ -147,6 +148,7 @@ ERROR_IF(dilation_d < 1 || dilation_y < 1 || dilation_x < 1); ERROR_IF(OD != idiv_check(ID - 1 + pad_d0 + pad_d1 - (KD - 1) * dilation_d, stride_d) + 1); ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1); ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1); +ERROR_IF(BC != OC && BC != 1); for_each(0 <= n < N, 0 <= od < OD, 0 <= oy < OH, 0 <= ox < OW; 0 <= oc < OC) { out_t acc = 0; @@ -165,7 +167,7 @@ for_each(0 <= n < N, 0 <= od < OD, 0 <= oy < OH, 0 <= ox < OW; 0 <= oc < OC) { acc = apply_add<out_t>(acc, value * weight); } } - acc = apply_add<out_t>(acc, bias[oc]); + acc = apply_add<out_t>(acc, bias[(BC == 1) ? 0 : oc]); tensor_write<out_t>(output, [N,OD,OH,OW,OC], [n,od,oy,ox,oc], acc); } ---- @@ -185,6 +187,7 @@ ERROR_IF(stride_y < 1 || stride_x < 1); ERROR_IF(dilation_y < 1 || dilation_x < 1); ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1); ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1); +ERROR_IF(BC != C*M && BC != 1); for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= c < C, 0 <= m < M) { out_t acc = 0; @@ -201,7 +204,7 @@ for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= c < C, 0 <= m < M) { acc = apply_add<out_t>(acc, value * weight); } } - acc = apply_add<out_t>(acc, bias[(c * M) + m]); + acc = apply_add<out_t>(acc, bias[(BC == 1) ? 0 : (c * M) + m]); tensor_write<out_t>(output, [N,OH,OW,C * M], [n,oy,ox,c * M + m], acc); } ---- @@ -261,6 +264,8 @@ include::{generated}/operators/FULLY_CONNECTED.adoc[] ---- ERROR_IF(in_t != int8_t && input_zp != 0); // Zero point only for int8_t ERROR_IF(weight_t != int8_t && weight_zp != 0); +ERROR_IF(BC != OC && BC != 1); + for_each(0 <= n < N, 0 <= oc < OC) { out_t acc = 0; for_each(0 <= ic < IC) { @@ -270,7 +275,7 @@ for_each(0 <= n < N, 0 <= oc < OC) { weight = weight - weight_zp; acc = apply_add<out_t>(acc, value * weight); } - acc = apply_add<out_t>(acc, bias[oc]); + acc = apply_add<out_t>(acc, bias[(BC == 1) ? 0 : oc]); tensor_write<out_t>(output, [N,OC], [n,oc], acc); } ---- @@ -378,9 +383,10 @@ ERROR_IF(out_pad_left <= -KW || out_pad_right <= -KW); ERROR_IF(stride_y < 1 || stride_x < 1); ERROR_IF(OH != (IH - 1) * stride_y + out_pad_top + out_pad_bottom + KH); ERROR_IF(OW != (IW - 1) * stride_x + out_pad_left + out_pad_right + KW); +ERROR_IF(BC != OC && BC != 1); for_each(index in out_shape) { - tensor_write<out_t>(output, [N,OH,OW,OC], index, bias[index[3]]) + tensor_write<out_t>(output, [N,OH,OW,OC], index, bias[(BC == 1) ? 0 : index[3]]) } for_each(0 <= n < N, 0 <= iy < IH, 0 <= ix < IW, 0 <= oc < OC, 0 <= ic < IC, 0 <= ky < KH, 0 <= kx < KW) { @@ -129,7 +129,7 @@ <levellimit value="dilation_x * KW" limit="MAX_KERNEL"/> <rank min="4" max="4"/> </argument> - <argument category="input" name="bias" type="tensor_t" shape="[OC]" tensor-element-type="out_t"> + <argument category="input" name="bias" type="tensor_t" shape="[BC]" tensor-element-type="out_t"> <description>Per output channel bias data.</description> <rank min="1" max="1"/> </argument> @@ -203,7 +203,7 @@ <levellimit value="dilation_x * KW" limit="MAX_KERNEL"/> <rank min="5" max="5"/> </argument> - <argument category="input" name="bias" type="tensor_t" shape="[OC]" tensor-element-type="out_t"> + <argument category="input" name="bias" type="tensor_t" shape="[BC]" tensor-element-type="out_t"> <description>Per output channel bias data.</description> <rank min="1" max="1"/> </argument> @@ -279,7 +279,7 @@ <levellimit value="dilation_x * KW" limit="MAX_KERNEL"/> <rank min="4" max="4"/> </argument> - <argument category="input" name="bias" type="tensor_t" shape="[C*M]" tensor-element-type="out_t"> + <argument category="input" name="bias" type="tensor_t" shape="[BC]" tensor-element-type="out_t"> <description>Per output channel bias data.</description> <rank min="1" max="1"/> </argument> @@ -384,7 +384,7 @@ <description>Weights</description> <rank min="2" max="2"/> </argument> - <argument category="input" name="bias" type="tensor_t" shape="[OC]" tensor-element-type="out_t"> + <argument category="input" name="bias" type="tensor_t" shape="[BC]" tensor-element-type="out_t"> <description>Per output channel bias data.</description> <rank min="1" max="1"/> </argument> @@ -562,7 +562,7 @@ <levellimit value="KW" limit="MAX_KERNEL"/> <rank min="4" max="4"/> </argument> - <argument category="input" name="bias" type="tensor_t" shape="[OC]" tensor-element-type="out_t"> + <argument category="input" name="bias" type="tensor_t" shape="[BC]" tensor-element-type="out_t"> <description>Per output channel bias data.</description> <rank min="1" max="1"/> </argument> |