diff options
Diffstat (limited to 'tosa.xml')
| -rw-r--r-- | tosa.xml | 814 |
1 files changed, 281 insertions, 533 deletions
@@ -1,33 +1,29 @@ <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE tosa SYSTEM "tosa.dtd"> <tosa> - <version major="0" minor="70" patch="0" draft="false"/> + <version major="0" minor="60" patch="0" draft="false"/> <profiles> <profile name="BI">Base Inference</profile> <profile name="MI">Main Inference</profile> <profile name="MT">Main Training</profile> </profiles> <levels> - <level name="none" max_rank="32" max_kernel="2147483647" max_stride="2147483647" max_scale="2048" max_log2_size="63">No level</level> - <level name="8K" max_rank="6" max_kernel="8192" max_stride="8192" max_scale="64" max_log2_size="31">Level 8K</level> + <level name="none" max_rank="32" max_kernel="2147483647" max_stride="2147483647" max_scale="2048">No level</level> + <level name="8K" max_rank="6" max_kernel="8192" max_stride="8192" max_scale="64" >Level 8K</level> </levels> <operators> <operatorgroup name="tensor"> <operator> <name>ARGMAX</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape1" tensor-element-type="in_t"> - <description>Input tensor</description> - <levellimit value="rank(shape1)" limit="MAX_RANK"/> - <rank min="1" max="MAX_RANK"/> + <argument category="input" name="input" type="in_t*" shape="shape1"> + <description>Input tensor with rank from 1 to 4</description> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> - <description>Axis in range from 0 to rank(shape1) - 1</description> - <rank min="0" max="0"/> + <argument category="attribute" name="axis" type="int32_t" shape="-"> + <description>Axis in range from 0 to rank(shape1)-1</description> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> - <description>Output tensor, with rank = rank(shape1) - 1</description> - <rank min="0" max="MAX_RANK - 1"/> + <argument category="output" name="output" type="out_t*" shape="shape"> + <description>Output tensor, with rank = rank(shape1)-1</description> </argument> </arguments> <types> @@ -52,45 +48,37 @@ <operator> <name>AVG_POOL2D</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,IH,IW,C]" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="4" max="4"/> + <argument category="input" name="input" type="in_out_t*" shape="[N,IH,IW,C]"> + <description>Input tensor 4D</description> </argument> - <argument category="attribute" name="kernel" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="kernel" type="int32_t*" shape="[2]"> <description>[kernel_y, kernel_x]</description> <levellimit value="kernel_y" limit="MAX_KERNEL"/> <levellimit value="kernel_x" limit="MAX_KERNEL"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="stride" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="stride" type="int32_t*" shape="[2]"> <description>[stride_y, stride_x]</description> <levellimit value="stride_y" limit="MAX_STRIDE"/> <levellimit value="stride_x" limit="MAX_STRIDE"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="pad" type="tensor_t" shape="[4]" tensor-element-type="int32_t"> + <argument category="attribute" name="pad" type="int32_t*" shape="[4]"> <description>[pad_top, pad_bottom, pad_left, pad_right]</description> <levellimit value="pad_top" limit="MAX_KERNEL"/> <levellimit value="pad_bottom" limit="MAX_KERNEL"/> <levellimit value="pad_left" limit="MAX_KERNEL"/> <levellimit value="pad_right" limit="MAX_KERNEL"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="acc_size" type="tensor_t" shape="-" tensor-element-type="acc_size_t"> + <argument category="attribute" name="acc_size" type="acc_t" shape="-"> <description>Enumerated type, must be one of INT32, FP16, FP32, as defined in the Supported Data Types table for this operation</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="input_zp" type="tensor_t" shape="-" tensor-element-type="in_out_t"> + <argument category="attribute" name="input_zp" type="in_out_t" shape="-"> <description>Input tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="output_zp" type="tensor_t" shape="-" tensor-element-type="in_out_t"> + <argument category="attribute" name="output_zp" type="in_out_t" shape="-"> <description>Output tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,OH,OW,C]" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="[N,OH,OW,C]"> <description>Output tensor 4D</description> - <rank min="4" max="4"/> </argument> </arguments> <types> @@ -119,49 +107,40 @@ <operator> <name>CONV2D</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,IH,IW,IC]" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t*" shape="[N,IH,IW,IC]"> <description>Input tensor</description> - <rank min="4" max="4"/> </argument> - <argument category="input" name="weight" type="tensor_t" shape="[OC,KH,KW,IC]" tensor-element-type="weight_t"> + <argument category="input" name="weight" type="weight_t*" shape="[OC,KH,KW,IC]"> <description>Weight kernel size KH x KW</description> <levellimit value="dilation_y * KH" limit="MAX_KERNEL"/> <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="out_t*" shape="[OC]"> <description>Per output channel bias data.</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="pad" type="tensor_t" shape="[4]" tensor-element-type="int32_t"> + <argument category="attribute" name="pad" type="int32_t*" shape="[4]"> <description>[pad_top, pad_bottom, pad_left, pad_right]</description> <levellimit value="pad_top" limit="MAX_KERNEL"/> <levellimit value="pad_bottom" limit="MAX_KERNEL"/> <levellimit value="pad_left" limit="MAX_KERNEL"/> <levellimit value="pad_right" limit="MAX_KERNEL"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="stride" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="stride" type="int32_t*" shape="[2]"> <description>[stride_y, stride_x]</description> <levellimit value="stride_y" limit="MAX_STRIDE"/> <levellimit value="stride_x" limit="MAX_STRIDE"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="dilation" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="dilation" type="int32_t*" shape="[2]"> <description>[dilation_y, dilation_x]</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="input_zp" type="tensor_t" shape="-" tensor-element-type="in_t"> + <argument category="attribute" name="input_zp" type="in_t" shape="-"> <description>Input tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="weight_zp" type="tensor_t" shape="-" tensor-element-type="weight_t"> + <argument category="attribute" name="weight_zp" type="weight_t" shape="-"> <description>Weight zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,OH,OW,OC]" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="[N,OH,OW,OC]"> <description>Output tensor</description> - <rank min="4" max="4"/> </argument> </arguments> <types> @@ -192,22 +171,19 @@ <operator> <name>CONV3D</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,ID,IH,IW,IC]" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t*" shape="[N,ID,IH,IW,IC]"> <description>Input tensor</description> - <rank min="5" max="5"/> </argument> - <argument category="input" name="weight" type="tensor_t" shape="[OC,KD,KH,KW,IC]" tensor-element-type="weight_t"> + <argument category="input" name="weight" type="weight_t*" shape="[OC,KD,KH,KW,IC]"> <description>Weight kernel size KDxKHxKW</description> <levellimit value="dilation_d * KD" limit="MAX_KERNEL"/> <levellimit value="dilation_y * KH" limit="MAX_KERNEL"/> <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="out_t*" shape="[OC]"> <description>Per output channel bias data.</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="pad" type="tensor_t" shape="[6]" tensor-element-type="int32_t"> + <argument category="attribute" name="pad" type="int32_t*" shape="[6]"> <description>[pad_d0, pad_d1, pad_top, pad_bottom, pad_left, pad_right]</description> <levellimit value="pad_d0" limit="MAX_KERNEL"/> <levellimit value="pad_d1" limit="MAX_KERNEL"/> @@ -215,30 +191,24 @@ <levellimit value="pad_bottom" limit="MAX_KERNEL"/> <levellimit value="pad_left" limit="MAX_KERNEL"/> <levellimit value="pad_right" limit="MAX_KERNEL"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="stride" type="tensor_t" shape="[3]" tensor-element-type="int32_t"> + <argument category="attribute" name="stride" type="int32_t*" shape="[3]"> <description>[stride_d, stride_y, stride_x]</description> <levellimit value="stride_y" limit="MAX_STRIDE"/> <levellimit value="stride_x" limit="MAX_STRIDE"/> <levellimit value="stride_d" limit="MAX_STRIDE"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="dilation" type="tensor_t" shape="[3]" tensor-element-type="int32_t"> + <argument category="attribute" name="dilation" type="int32_t*" shape="[3]"> <description>[dilation_d, dilation_y, dilation_x]</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="input_zp" type="tensor_t" shape="-" tensor-element-type="in_t"> + <argument category="attribute" name="input_zp" type="in_t" shape="-"> <description>Input tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="weight_zp" type="tensor_t" shape="-" tensor-element-type="weight_t"> + <argument category="attribute" name="weight_zp" type="weight_t" shape="-"> <description>Weight zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,OD,OH,OW,OC]" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="[N,OD,OH,OW,OC]"> <description>Output tensor</description> - <rank min="5" max="5"/> </argument> </arguments> <types> @@ -269,49 +239,40 @@ <operator> <name>DEPTHWISE_CONV2D</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,H,W,C]" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t*" shape="[N,H,W,C]"> <description>Input tensor</description> - <rank min="4" max="4"/> </argument> - <argument category="input" name="weight" type="tensor_t" shape="[KH,KW,C,M]" tensor-element-type="weight_t"> + <argument category="input" name="weight" type="weight_t*" shape="[KH,KW,C,M]"> <description>Weight kernel size KH x KW</description> <levellimit value="dilation_y * KH" limit="MAX_KERNEL"/> <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="out_t*" shape="[C*M]"> <description>Per output channel bias data.</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="pad" type="tensor_t" shape="[4]" tensor-element-type="int32_t"> + <argument category="attribute" name="pad" type="int32_t*" shape="[4]"> <description>[pad_top, pad_bottom, pad_left, pad_right]</description> <levellimit value="pad_top" limit="MAX_KERNEL"/> <levellimit value="pad_bottom" limit="MAX_KERNEL"/> <levellimit value="pad_left" limit="MAX_KERNEL"/> <levellimit value="pad_right" limit="MAX_KERNEL"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="stride" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="stride" type="int32_t*" shape="[2]"> <description>[stride_y, stride_x]</description> <levellimit value="stride_y" limit="MAX_STRIDE"/> <levellimit value="stride_x" limit="MAX_STRIDE"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="dilation" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="dilation" type="int32_t*" shape="[2]"> <description>[dilation_y, dilation_x]</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="input_zp" type="tensor_t" shape="-" tensor-element-type="in_t"> + <argument category="attribute" name="input_zp" type="in_t" shape="-"> <description>Input tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="weight_zp" type="tensor_t" shape="-" tensor-element-type="weight_t"> + <argument category="attribute" name="weight_zp" type="weight_t" shape="-"> <description>Weight zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,OH,OW,C*M]" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="[N,OH,OW,C*M]"> <description>Output tensor</description> - <rank min="4" max="4"/> </argument> </arguments> <types> @@ -342,27 +303,22 @@ <operator> <name>FFT2D</name> <arguments> - <argument category="input" name="input_real" type="tensor_t" shape="[N,H,W]" tensor-element-type="in_out_t"> + <argument category="input" name="input_real" type="in_out_t*" shape="[N,H,W]"> <description>Real part of the complex input. H,W must be powers of two.</description> <levellimit value="H" limit="MAX_KERNEL"/> <levellimit value="W" limit="MAX_KERNEL"/> - <rank min="3" max="3"/> </argument> - <argument category="input" name="input_imag" type="tensor_t" shape="[N,H,W]" tensor-element-type="in_out_t"> + <argument category="input" name="input_imag" type="in_out_t*" shape="[N,H,W]"> <description>Imaginary part of the complex input. H,W must be powers of two.</description> - <rank min="3" max="3"/> </argument> - <argument category="attribute" name="inverse" type="tensor_t" shape="-" tensor-element-type="bool_t"> + <argument category="attribute" name="inverse" type="bool_t" shape="-"> <description>false for forward FFT, true for inverse FFT</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output_real" type="tensor_t" shape="[N,H,W]" tensor-element-type="in_out_t"> + <argument category="output" name="output_real" type="in_out_t*" shape="[N,H,W]"> <description>Real part of the complex output.</description> - <rank min="3" max="3"/> </argument> - <argument category="output" name="output_imag" type="tensor_t" shape="[N,H,W]" tensor-element-type="in_out_t"> + <argument category="output" name="output_imag" type="in_out_t*" shape="[N,H,W]"> <description>Imaginary part of the complex output.</description> - <rank min="3" max="3"/> </argument> </arguments> <types> @@ -376,29 +332,23 @@ <operator> <name>FULLY_CONNECTED</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,IC]" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t*" shape="[N,IC]"> <description>Input tensor</description> - <rank min="2" max="2"/> </argument> - <argument category="attribute" name="weight" type="tensor_t" shape="[OC,IC]" tensor-element-type="weight_t"> + <argument category="attribute" name="weight" type="weight_t*" shape="[OC,IC]"> <description>Weights</description> - <rank min="2" max="2"/> </argument> - <argument category="attribute" name="bias" type="tensor_t" shape="[OC]" tensor-element-type="out_t"> + <argument category="attribute" name="bias" type="out_t*" shape="[OC]"> <description>Per output channel bias data.</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="input_zp" type="tensor_t" shape="-" tensor-element-type="in_t"> + <argument category="attribute" name="input_zp" type="in_t" shape="-"> <description>Input tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="weight_zp" type="tensor_t" shape="-" tensor-element-type="weight_t"> + <argument category="attribute" name="weight_zp" type="weight_t" shape="-"> <description>Weight zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,OC]" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="[N,OC]"> <description>Output tensor</description> - <rank min="2" max="2"/> </argument> </arguments> <types> @@ -429,25 +379,20 @@ <operator> <name>MATMUL</name> <arguments> - <argument category="input" name="A" type="tensor_t" shape="[N,H,C]" tensor-element-type="in_t"> + <argument category="input" name="A" type="in_t*" shape="[N,H,C]"> <description>Input tensor A, N matrices of size HxC</description> - <rank min="3" max="3"/> </argument> - <argument category="input" name="B" type="tensor_t" shape="[N,C,W]" tensor-element-type="in_t"> + <argument category="input" name="B" type="in_t*" shape="[N,C,W]"> <description>Input tensor B, N matrices of size CxW</description> - <rank min="3" max="3"/> </argument> - <argument category="attribute" name="A_zp" type="tensor_t" shape="-" tensor-element-type="in_t"> + <argument category="attribute" name="A_zp" type="in_t" shape="-"> <description>Input tensor A zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="B_zp" type="tensor_t" shape="-" tensor-element-type="in_t"> + <argument category="attribute" name="B_zp" type="in_t" shape="-"> <description>Input tensor B zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,H,W]" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="[N,H,W]"> <description>Output tensor, N matrices of size HxW</description> - <rank min="3" max="3"/> </argument> </arguments> <types> @@ -476,33 +421,28 @@ <operator> <name>MAX_POOL2D</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,IH,IW,C]" tensor-element-type="in_out_t"> + <argument category="input" name="input" type="in_out_t*" shape="[N,IH,IW,C]"> <description>Input tensor 4D</description> - <rank min="4" max="4"/> </argument> - <argument category="attribute" name="kernel" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="kernel" type="int32_t*" shape="[2]"> <description>[kernel_y, kernel_x]</description> <levellimit value="kernel_y" limit="MAX_KERNEL"/> <levellimit value="kernel_x" limit="MAX_KERNEL"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="stride" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="stride" type="int32_t*" shape="[2]"> <description>[stride_y, stride_x]</description> <levellimit value="stride_y" limit="MAX_STRIDE"/> <levellimit value="stride_x" limit="MAX_STRIDE"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="pad" type="tensor_t" shape="[4]" tensor-element-type="int32_t"> + <argument category="attribute" name="pad" type="int32_t*" shape="[4]"> <description>[pad_top, pad_bottom, pad_left, pad_right]</description> <levellimit value="pad_top" limit="MAX_KERNEL"/> <levellimit value="pad_bottom" limit="MAX_KERNEL"/> <levellimit value="pad_left" limit="MAX_KERNEL"/> <levellimit value="pad_right" limit="MAX_KERNEL"/> - <rank min="1" max="1"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,OH,OW,C]" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="[N,OH,OW,C]"> <description>Output tensor 4D</description> - <rank min="4" max="4"/> </argument> </arguments> <types> @@ -526,19 +466,16 @@ <operator> <name>RFFT2D</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,H,W]" tensor-element-type="in_out_t"> + <argument category="input" name="input" type="in_out_t*" shape="[N,H,W]"> <description>Real input. H,W must be powers of two.</description> <levellimit value="H" limit="MAX_KERNEL"/> <levellimit value="W" limit="MAX_KERNEL"/> - <rank min="3" max="3"/> </argument> - <argument category="output" name="output_real" type="tensor_t" shape="[N,H,W/2 + 1]" tensor-element-type="in_out_t"> + <argument category="output" name="output_real" type="in_out_t*" shape="[N,H,W/2 + 1]"> <description>Real part of the complex output</description> - <rank min="3" max="3"/> </argument> - <argument category="output" name="output_imag" type="tensor_t" shape="[N,H,W/2 + 1]" tensor-element-type="in_out_t"> + <argument category="output" name="output_imag" type="in_out_t*" shape="[N,H,W/2 + 1]"> <description>Imaginary part of the complex output.</description> - <rank min="3" max="3"/> </argument> </arguments> <types> @@ -552,49 +489,40 @@ <operator> <name>TRANSPOSE_CONV2D</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,IH,IW,IC]" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t*" shape="[N,IH,IW,IC]"> <description>Input tensor</description> - <rank min="4" max="4"/> </argument> - <argument category="input" name="weight" type="tensor_t" shape="[OC,KH,KW,IC]" tensor-element-type="weight_t"> + <argument category="input" name="weight" type="weight_t*" shape="[OC,KH,KW,IC]"> <description>Weight kernel size KH x KW</description> <levellimit value="KH" limit="MAX_KERNEL"/> <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="out_t*" shape="[OC]"> <description>Per output channel bias data.</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="out_pad" type="tensor_t" shape="[4]" tensor-element-type="int32_t"> + <argument category="attribute" name="out_pad" type="int32_t*" shape="[4]"> <description>[out_pad_top, out_pad_bottom, out_pad_left, out_pad_right]</description> <levellimit value="out_pad_top" limit="MAX_KERNEL"/> <levellimit value="out_pad_bottom" limit="MAX_KERNEL"/> <levellimit value="out_pad_left" limit="MAX_KERNEL"/> <levellimit value="out_pad_right" limit="MAX_KERNEL"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="stride" type="tensor_t" shape="[2]" tensor-element-type="int32_t"> + <argument category="attribute" name="stride" type="int32_t*" shape="[2]"> <description>[stride_y, stride_x]</description> <levellimit value="stride_y" limit="MAX_STRIDE"/> <levellimit value="stride_x" limit="MAX_STRIDE"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="out_shape" type="tensor_t" shape="[4]" tensor-element-type="int32_t"> + <argument category="attribute" name="out_shape" type="int32_t*" shape="[4]"> <description>[N,OH,OW,OC]</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="input_zp" type="tensor_t" shape="-" tensor-element-type="in_t"> + <argument category="attribute" name="input_zp" type="in_t" shape="-"> <description>Input tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="weight_zp" type="tensor_t" shape="-" tensor-element-type="weight_t"> + <argument category="attribute" name="weight_zp" type="weight_t" shape="-"> <description>Weight zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,OH,OW,OC]" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="[N,OH,OW,OC]"> <description>Output tensor</description> - <rank min="4" max="4"/> </argument> </arguments> <types> @@ -627,22 +555,18 @@ <operator> <name>CLAMP</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="attribute" name="min_val" type="tensor_t" shape="-" tensor-element-type="in_out_t"> + <argument category="attribute" name="min_val" type="in_out_t" shape="-"> <description>Minimum clip value</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="max_val" type="tensor_t" shape="-" tensor-element-type="in_out_t"> + <argument category="attribute" name="max_val" type="in_out_t" shape="-"> <description>Maximum clip value</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type and shape as input</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -666,14 +590,12 @@ <operator> <name>SIGMOID</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type and shape as input</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -695,14 +617,12 @@ <operator> <name>TANH</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type and shape as input</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -726,18 +646,15 @@ <operator> <name>ADD</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -760,22 +677,18 @@ <operator> <name>ARITHMETIC_RIGHT_SHIFT</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="attribute" name="round" type="tensor_t" shape="-" tensor-element-type="bool_t"> + <argument category="attribute" name="round" type="bool_t" shape="-"> <description>If true then the shift is rounded</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -788,18 +701,15 @@ <operator> <name>BITWISE_AND</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -812,18 +722,15 @@ <operator> <name>BITWISE_OR</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -836,18 +743,15 @@ <operator> <name>BITWISE_XOR</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -860,18 +764,15 @@ <operator> <name>INTDIV</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -882,18 +783,15 @@ <operator> <name>LOGICAL_AND</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -904,18 +802,15 @@ <operator> <name>LOGICAL_LEFT_SHIFT</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -928,18 +823,15 @@ <operator> <name>LOGICAL_RIGHT_SHIFT</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -952,18 +844,15 @@ <operator> <name>LOGICAL_OR</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -974,18 +863,15 @@ <operator> <name>LOGICAL_XOR</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -996,18 +882,15 @@ <operator> <name>MAXIMUM</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1030,18 +913,15 @@ <operator> <name>MINIMUM</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1064,22 +944,18 @@ <operator> <name>MUL</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_t"> + <argument category="input" name="input1" type="in_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_t"> + <argument category="input" name="input2" type="in_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input(MT)|attribute(BI,MI)" name="shift" type="tensor_t" shape="-" tensor-element-type="int8_t"> + <argument category="input(MT)|attribute(BI,MI)" name="shift" type="uint6_t" shape="-"> <description>Result right shift (int32_t data type only)</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1105,18 +981,15 @@ <operator> <name>POW</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1138,18 +1011,15 @@ <operator> <name>SUB</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1172,18 +1042,15 @@ <operator> <name>TABLE</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t*" shape="shape"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input(MT)|attribute(BI,MI)" name="table" type="tensor_t" shape="[TABLE_SIZE]" tensor-element-type="table_t"> + <argument category="input(MT)|attribute(BI,MI)" name="table" type="table_t*" shape="[TABLE_SIZE]"> <description>Lookup table tensor</description> - <rank min="1" max="1"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="shape"> <description>Output tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1200,14 +1067,12 @@ <operator> <name>ABS</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1230,14 +1095,12 @@ <operator> <name>BITWISE_NOT</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1250,14 +1113,12 @@ <operator> <name>CEIL</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1279,14 +1140,12 @@ <operator> <name>CLZ</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1297,14 +1156,12 @@ <operator> <name>EXP</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1326,14 +1183,12 @@ <operator> <name>FLOOR</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1355,14 +1210,12 @@ <operator> <name>LOG</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1384,14 +1237,12 @@ <operator> <name>LOGICAL_NOT</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1402,22 +1253,17 @@ <operator> <name>NEGATE</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> - <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="attribute" name="input1_zp" type="tensor_t" shape="-" tensor-element-type="in_out_t"> + <argument category="attribute" name="input1_zp" type="in_out_t" shape="-"> <description>Input 1 zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="output_zp" type="tensor_t" shape="-" tensor-element-type="in_out_t"> + <argument category="attribute" name="output_zp" type="in_out_t" shape="-"> <description>Output zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1443,14 +1289,12 @@ <operator> <name>RECIPROCAL</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1472,14 +1316,12 @@ <operator> <name>RSQRT</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1503,22 +1345,18 @@ <operator> <name>SELECT</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="bool_t"> + <argument category="input" name="input1" type="bool_t" shape="shape1"> <description>Input selector tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_out_t"> + <argument category="input" name="input2" type="in_out_t*" shape="shape2"> <description>Input value tensor if input1 is True</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input3" type="tensor_t" shape="shape3" tensor-element-type="in_out_t"> + <argument category="input" name="input3" type="in_out_t*" shape="shape3"> <description>Input value tensor if input1 is False</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type as input2 and input3, with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1546,18 +1384,15 @@ <operator> <name>EQUAL</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_t"> + <argument category="input" name="input1" type="in_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_t"> + <argument category="input" name="input2" type="in_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1581,18 +1416,15 @@ <operator> <name>GREATER</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_t"> + <argument category="input" name="input1" type="in_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_t"> + <argument category="input" name="input2" type="in_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1616,18 +1448,15 @@ <operator> <name>GREATER_EQUAL</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_t"> + <argument category="input" name="input1" type="in_t*" shape="shape1"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="input" name="input2" type="tensor_t" shape="shape2" tensor-element-type="in_t"> + <argument category="input" name="input2" type="in_t*" shape="shape2"> <description>Input tensor with the same rank as input1</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="shape"> <description>Output tensor with broadcast shape if necessary</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1653,17 +1482,14 @@ <operator> <name>REDUCE_ALL</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="4"/> + <argument category="input" name="input" type="in_out_t*" shape="shape1"> + <description>Input tensor with rank from 1 to 4</description> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> + <argument category="attribute" name="axis" type="int32_t" shape="-"> <description>Axis to reduce, in range from 0 to rank(shape1)-1</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor. Same rank as the input tensor.</description> - <rank min="1" max="4"/> </argument> </arguments> <types> @@ -1674,17 +1500,14 @@ <operator> <name>REDUCE_ANY</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="4"/> + <argument category="input" name="input" type="in_out_t*" shape="shape1"> + <description>Input tensor with rank from 1 to 4</description> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> + <argument category="attribute" name="axis" type="int32_t" shape="-"> <description>Axis to reduce, in range from 0 to rank(shape1)-1</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor. Same rank as the input tensor.</description> - <rank min="1" max="4"/> </argument> </arguments> <types> @@ -1695,17 +1518,14 @@ <operator> <name>REDUCE_MAX</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="4"/> + <argument category="input" name="input" type="in_out_t*" shape="shape1"> + <description>Input tensor with rank from 1 to 4</description> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> + <argument category="attribute" name="axis" type="int32_t" shape="-"> <description>Axis to reduce, in range from 0 to rank(shape1)-1</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor. Same rank as the input tensor.</description> - <rank min="1" max="4"/> </argument> </arguments> <types> @@ -1730,17 +1550,14 @@ <operator> <name>REDUCE_MIN</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="4"/> + <argument category="input" name="input" type="in_out_t*" shape="shape1"> + <description>Input tensor with rank from 1 to 4</description> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> + <argument category="attribute" name="axis" type="int32_t" shape="-"> <description>Axis to reduce, in range from 0 to rank(shape1)-1</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor. Same rank as the input tensor.</description> - <rank min="1" max="4"/> </argument> </arguments> <types> @@ -1765,17 +1582,14 @@ <operator> <name>REDUCE_PRODUCT</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="4"/> + <argument category="input" name="input" type="in_out_t*" shape="shape1"> + <description>Input tensor with rank from 1 to 4</description> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> + <argument category="attribute" name="axis" type="int32_t" shape="-"> <description>Axis to reduce, in range from 0 to rank(shape1)-1</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor. Same rank as the input tensor.</description> - <rank min="1" max="4"/> </argument> </arguments> <types> @@ -1797,17 +1611,14 @@ <operator> <name>REDUCE_SUM</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input" type="in_out_t*" shape="shape1"> <description>Input tensor with rank from 1 to 4</description> - <rank min="1" max="4"/> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> + <argument category="attribute" name="axis" type="int32_t" shape="-"> <description>Axis to reduce, in range from 0 to rank(shape1)-1</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor. Same rank as the input tensor.</description> - <rank min="1" max="4"/> </argument> </arguments> <types> @@ -1832,18 +1643,16 @@ <operator> <name>CONCAT</name> <arguments> - <argument category="input" name="input1" type="tensor_list_t" shape="shapes1" tensor-element-type="in_out_t"> + <!-- FIXME express list of tensors better --> + <argument category="input" name="input1" type="in_out_t*" shape="shapes1[]"> <description>List of input tensors. All inputs must have the same rank and data type</description> - <rank min="1" max="MAX_RANK"/> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> + <argument category="attribute" name="axis" type="int32_t" shape="-"> <description>Axis along which concatenation is to occur, in range from 0 to rank(shape)-1</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="1" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1869,22 +1678,18 @@ <operator> <name>PAD</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="MAX_RANK"/> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> + <description>Input tensor with minimum rank of one.</description> </argument> - <argument category="attribute" name="padding" type="tensor_t" shape="[rank(shape1),2]" tensor-element-type="int32_t"> + <argument category="attribute" name="padding" type="int32_t" shape="[rank(shape1),2]"> <description>Number of pad elements at the start and end of each dimension</description> - <rank min="2" max="2"/> </argument> - <argument category="attribute" name="pad_const" type="tensor_t" shape="-" tensor-element-type="in_out_t"> + <argument category="attribute" name="pad_const" type="in_out_t" shape="-"> <description>Constant value to be used as padding</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type as the input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="1" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1910,19 +1715,16 @@ <operator> <name>RESHAPE</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> <description>Input tensor</description> <levellimit value="rank(shape1)" limit="MAX_RANK"/> - <rank min="1" max="MAX_RANK"/> </argument> - <argument category="attribute" name="new_shape" type="tensor_t" shape="[rank(shape)]" tensor-element-type="int32_t"> + <argument category="attribute" name="new_shape" type="int32_t" shape="[rank(shape)]"> <description>List of values, with each element giving the size of the result tensor for the given dimension. At most one dimension may be given as -1 to automatically calculate the dimension size.</description> - <rank min="1" max="1"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, size as the input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="1" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1948,18 +1750,15 @@ <operator> <name>REVERSE</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> - <description>Input tensor</description> + <argument category="input" name="input" type="in_out_t*" shape="shape"> + <description>Input tensor with minimum rank of one.</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="1" max="MAX_RANK"/> </argument> - <argument category="attribute" name="axis" type="tensor_t" shape="-" tensor-element-type="int32_t"> + <argument category="attribute" name="axis" type="int32_t" shape="-"> <description>Axis to reverse, in range from 0 to rank(shape)-1</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor. Same shape as input tensor</description> - <rank min="1" max="MAX_RANK"/> </argument> </arguments> <types> @@ -1985,23 +1784,19 @@ <operator> <name>SLICE</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="MAX_RANK"/> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> + <description>Input tensor with minimum rank of one.</description> </argument> - <argument category="attribute" name="start" type="tensor_t" shape="[rank(shape1)]" tensor-element-type="index_t"> + <argument category="attribute" name="start" type="int32_t" shape="[rank(shape1)]"> <description>List of integer coordinates, of length equal to the rank of input1. Start coordinate for slicing.</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="size" type="tensor_t" shape="[rank(shape1)]" tensor-element-type="index_t"> + <argument category="attribute" name="size" type="int32_t" shape="[rank(shape1)]"> <description>List of integer size values, of length equal to the rank of input1. Size of the input to be used.</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="1" max="1"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type as the input tensor</description> - <rank min="1" max="MAX_RANK"/> </argument> </arguments> <types> @@ -2027,18 +1822,15 @@ used.</description> <operator> <name>TILE</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="MAX_RANK"/> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> + <description>Input tensor with minimum rank of one.</description> </argument> - <argument category="attribute" name="multiples" type="tensor_t" shape="[rank(shape1)]" tensor-element-type="int32_t"> + <argument category="attribute" name="multiplies" type="int32_t" shape="[rank(shape1)]"> <description>Number of times to replicate input1 in each dimension</description> - <rank min="1" max="1"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, rank as the input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="1" max="MAX_RANK"/> </argument> </arguments> <types> @@ -2064,18 +1856,15 @@ used.</description> <operator> <name>TRANSPOSE</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape1" tensor-element-type="in_out_t"> - <description>Input tensor</description> - <rank min="1" max="MAX_RANK"/> + <argument category="input" name="input1" type="in_out_t*" shape="shape1"> + <description>Input tensor with minimum rank of one.</description> </argument> - <argument category="attribute" name="perms" type="tensor_t" shape="[rank(shape1)]" tensor-element-type="int32_t"> + <argument category="attribute" name="perms" type="int32_t" shape="[rank(shape1)]"> <description>List of integers of length equal to the rank of input1. Values must be valid dimensions within shape1, and may not be repeated.</description> - <rank min="1" max="1"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of same type, rank as the input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="1" max="MAX_RANK"/> </argument> </arguments> <types> @@ -2103,34 +1892,31 @@ used.</description> <operator> <name>GATHER</name> <arguments> - <argument category="input" name="values" type="tensor_t" shape="[N,K,C]" tensor-element-type="in_out_t"> + <argument category="input" name="values" type="value_t*" shape="[N,K,C]"> <description>3D value tensor</description> - <rank min="3" max="3"/> </argument> - <argument category="input" name="indices" type="tensor_t" shape="[N,W]" tensor-element-type="index_t"> + <argument category="input" name="indices" type="index_t*" shape="[N,W]"> <description>2D index tensor</description> - <rank min="2" max="2"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,W,C]" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="value_t*" shape="[N,W,C]"> <description>3D output tensor</description> - <rank min="3" max="3"/> </argument> </arguments> <types> - <type name='in_out_t'/> + <type name='value_t'/> </types> - <typesupport mode="signed 8" in_out_t="int8_t"/> - <typesupport mode="signed 16" in_out_t="int16_t"/> - <typesupport mode="signed 32" in_out_t="int32_t"/> - <typesupport mode="fp16" in_out_t="fp16_t"> + <typesupport mode="signed 8" value_t="int8_t"/> + <typesupport mode="signed 16" value_t="int16_t"/> + <typesupport mode="signed 32" value_t="int32_t"/> + <typesupport mode="fp16" value_t="fp16_t"> <profile name="MI"/> <profile name="MT"/> </typesupport> - <typesupport mode="bf16" in_out_t="bf16_t"> + <typesupport mode="bf16" value_t="bf16_t"> <profile name="MI"/> <profile name="MT"/> </typesupport> - <typesupport mode="fp32" in_out_t="fp32_t"> + <typesupport mode="fp32" value_t="fp32_t"> <profile name="MI"/> <profile name="MT"/> </typesupport> @@ -2138,38 +1924,34 @@ used.</description> <operator> <name>SCATTER</name> <arguments> - <argument category="input" name="values_in" type="tensor_t" shape="[N,K,C]" tensor-element-type="in_out_t"> + <argument category="input" name="values_in" type="value_t*" shape="[N,K,C]"> <description>3D values in tensor</description> - <rank min="3" max="3"/> </argument> - <argument category="input" name="indices" type="tensor_t" shape="[N,W]" tensor-element-type="index_t"> + <argument category="input" name="indices" type="index_t*" shape="[N,W]"> <description>2D index tensor</description> - <rank min="2" max="2"/> </argument> - <argument category="input" name="input" type="tensor_t" shape="[N,W,C]" tensor-element-type="in_out_t"> + <argument category="input" name="input" type="value_t*" shape="[N,W,C]"> <description>3D input tensor</description> - <rank min="3" max="3"/> </argument> - <argument category="output" name="values_out" type="tensor_t" shape="[N,K,C]" tensor-element-type="in_out_t"> + <argument category="output" name="values_out" type="value_t*" shape="[N,K,C]"> <description>3D output tensor</description> - <rank min="3" max="3"/> </argument> </arguments> <types> - <type name='in_out_t'/> + <type name='value_t'/> </types> - <typesupport mode="signed 8" in_out_t="int8_t"/> - <typesupport mode="signed 16" in_out_t="int16_t"/> - <typesupport mode="signed 32" in_out_t="int32_t"/> - <typesupport mode="fp16" in_out_t="fp16_t"> + <typesupport mode="signed 8" value_t="int8_t"/> + <typesupport mode="signed 16" value_t="int16_t"/> + <typesupport mode="signed 32" value_t="int32_t"/> + <typesupport mode="fp16" value_t="fp16_t"> <profile name="MI"/> <profile name="MT"/> </typesupport> - <typesupport mode="bf16" in_out_t="bf16_t"> + <typesupport mode="bf16" value_t="bf16_t"> <profile name="MI"/> <profile name="MT"/> </typesupport> - <typesupport mode="fp32" in_out_t="fp32_t"> + <typesupport mode="fp32" value_t="fp32_t"> <profile name="MI"/> <profile name="MT"/> </typesupport> @@ -2179,31 +1961,25 @@ used.</description> <operator> <name>RESIZE</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="[N,IH,IW,C]" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t*" shape="[N,IH,IW,C]"> <description>Input tensor</description> - <rank min="4" max="4"/> </argument> - <argument category="attribute" name="scale" type="tensor_t" shape="[4]" tensor-element-type="int16_t"> + <argument category="attribute" name="scale" type="int16_t*" shape="[4]"> <description>[scale_y_n, scale_y_d, scale_x_n, scale_x_d]</description> <levellimit value="scale_y_n/scale_y_d" limit="MAX_SCALE"/> <levellimit value="scale_x_n/scale_x_d" limit="MAX_SCALE"/> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="offset" type="tensor_t" shape="[2]" tensor-element-type="int16_t"> + <argument category="attribute" name="offset" type="int16_t*" shape="[2]"> <description>[offset_y, offset_x]</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="border" type="tensor_t" shape="[2]" tensor-element-type="int16_t"> + <argument category="attribute" name="border" type="int16_t*" shape="[2]"> <description>[border_y, border_x]</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="mode" type="tensor_t" shape="-" tensor-element-type="resize_mode_t"> + <argument category="attribute" name="mode" type="mode_t" shape="-"> <description>BILINEAR or NEAREST</description> - <rank min="0" max="0"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="[N,OH,OW,C]" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="[N,OH,OW,C]"> <description>Output tensor</description> - <rank min="4" max="4"/> </argument> </arguments> <types> @@ -2233,14 +2009,12 @@ used.</description> <operator> <name>CAST</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t" shape="shape"> <description>Output tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -2351,42 +2125,33 @@ used.</description> <operator> <name>RESCALE</name> <arguments> - <argument category="input" name="input" type="tensor_t" shape="shape" tensor-element-type="in_t"> + <argument category="input" name="input" type="in_t" shape="shape"> <description>Input tensor</description> <levellimit value="rank(shape)" limit="MAX_RANK"/> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t" shape="shape"> <description>Output tensor with the same shape as input</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="attribute" name="input_zp" type="tensor_t" shape="-" tensor-element-type="in_t"> + <argument category="attribute" name="input_zp" type="in_t" shape="-"> <description>Input tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="output_zp" type="tensor_t" shape="-" tensor-element-type="out_t"> + <argument category="attribute" name="output_zp" type="out_t" shape="-"> <description>Output tensor zero point. Must be zero for non-int8 types.</description> - <rank min="0" max="0"/> </argument> - <argument category="input(MT)|attribute(BI,MI)" name="multiplier" type="tensor_t" shape="[NC]" tensor-element-type="mul_t"> + <argument category="input(MT)|attribute(BI,MI)" name="multiplier" type="mul_t*" shape="[NC]"> <description>Scaling multiplier array</description> - <rank min="1" max="1"/> </argument> - <argument category="input(MT)|attribute(BI,MI)" name="shift" type="tensor_t" shape="[NC]" tensor-element-type="int8_t"> + <argument category="input(MT)|attribute(BI,MI)" name="shift" type="uint6_t*" shape="[NC]"> <description>Scaling shift array</description> - <rank min="1" max="1"/> </argument> - <argument category="attribute" name="scale32" type="tensor_t" shape="-" tensor-element-type="bool_t"> + <argument category="attribute" name="scale32" type="bool_t" shape="-"> <description>if (scale32) mul_t=int32_t else mul_t=int16_t</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="double_round" type="tensor_t" shape="-" tensor-element-type="bool_t"> + <argument category="attribute" name="double_round" type="bool_t" shape="-"> <description>Select double round mode</description> - <rank min="0" max="0"/> </argument> - <argument category="attribute" name="per_channel" type="tensor_t" shape="-" tensor-element-type="bool_t"> + <argument category="attribute" name="per_channel" type="bool_t" shape="-"> <description>if (per_channel) NC=shape[rank(shape)-1] else NC=1</description> - <rank min="0" max="0"/> </argument> </arguments> <types> @@ -2417,13 +2182,11 @@ used.</description> <operator> <name>CONST</name> <arguments> - <argument category="attribute" name="values" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="attribute" name="values" type="out_t*" shape="shape"> <description>Constant values</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="out_t"> + <argument category="output" name="output" type="out_t*" shape="shape"> <description>Output tensor of the same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -2450,13 +2213,11 @@ used.</description> <operator> <name>IDENTITY</name> <arguments> - <argument category="input" name="input1" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="input" name="input1" type="in_out_t*" shape="shape"> <description>Input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> - <argument category="output" name="output" type="tensor_t" shape="shape" tensor-element-type="in_out_t"> + <argument category="output" name="output" type="in_out_t*" shape="shape"> <description>Output tensor of the same type, size as the input tensor</description> - <rank min="0" max="MAX_RANK"/> </argument> </arguments> <types> @@ -2484,20 +2245,19 @@ used.</description> <operator> <name>COND_IF</name> <arguments> - <argument category="input" name="condition" type="tensor_t" shape="shape" tensor-element-type="bool_t"> - <description>Input condition as a size 1 tensor</description> - <rank min="1" max="MAX_RANK"/> - </argument> - <argument category="input" name="input_list" type="tensor_list_t" shape="-" tensor-element-type="-"> + <argument category="input" name="input_list" type="tensor_list_t" shape="-"> <description>List of input tensors</description> </argument> - <argument category="attribute" name="then_graph" type="tosa_graph_t" shape="-" tensor-element-type="-"> + <argument category="input" name="condition" type="bool_t*" shape="shape"> + <description>Input condition as a size 1 tensor</description> + </argument> + <argument category="attribute" name="then_graph" type="tosa_graph_t" shape="-"> <description>TOSA graph to execute if condition is true</description> </argument> - <argument category="attribute" name="else_graph" type="tosa_graph_t" shape="-" tensor-element-type="-"> + <argument category="attribute" name="else_graph" type="tosa_graph_t" shape="-"> <description>TOSA graph to execute if condition is false</description> </argument> - <argument category="output" name="output_list" type="tensor_list_t" shape="-" tensor-element-type="-"> + <argument category="output" name="output_list" type="tensor_list_t" shape="-"> <description>List of output tensors</description> </argument> </arguments> @@ -2505,32 +2265,20 @@ used.</description> <operator> <name>WHILE_LOOP</name> <arguments> - <argument category="input" name="input_list" type="tensor_list_t" shape="-" tensor-element-type="-"> + <argument category="input" name="input_list" type="tensor_list_t" shape="-"> <description>List of input tensors</description> </argument> - <argument category="attribute" name="cond_graph" type="tosa_graph_t" shape="-" tensor-element-type="-"> + <argument category="attribute" name="cond_graph" type="tosa_graph_t" shape="-"> <description>TOSA graph to evaluate the condition</description> </argument> - <argument category="attribute" name="body_graph" type="tosa_graph_t" shape="-" tensor-element-type="-"> + <argument category="attribute" name="body_graph" type="tosa_graph_t" shape="-"> <description>TOSA graph to execute the loop body</description> </argument> - <argument category="output" name="output_list" type="tensor_list_t" shape="-" tensor-element-type="-"> + <argument category="output" name="output_list" type="tensor_list_t" shape="-"> <description>List of output tensors</description> </argument> </arguments> </operator> </operatorgroup> </operators> - - <enum name="resize_mode_t" description="Valid resize types"> - <enumval value="0" name="NEAREST_NEIGHBOR" description="Nearest neighbor resize"/> - <enumval value="1" name="BILINEAR" description="Bilinear resize"/> - </enum> - - <enum name="acc_size_t" description="Allowed accumulator sizes"> - <enumval value="0" name="INT32" description="32-bit integer"/> - <enumval value="1" name="FP16" description="16-bit floating-point"/> - <enumval value="2" name="FP32" description="32-bit floating-point"/> - </enum> - </tosa> |