Base Inference Main Inference Main Training No level Level 8K ARGMAX Input tensor with rank from 1 to 4 Axis in range from 0 to rank(shape1)-1 Output tensor, with rank = rank(shape1)-1 AVG_POOL2D Input tensor 4D [kernel_y, kernel_x] [stride_y, stride_x] [pad_top, pad_bottom, pad_left, pad_right] Input tensor zero point. Must be zero for non-int8 types. Output tensor zero point. Must be zero for non-int8 types. Output tensor 4D CONV2D Input tensor Weight kernel size KH x KW Per output channel bias data. [pad_top, pad_bottom, pad_left, pad_right] [stride_y, stride_x] [dilation_y, dilation_x] Input tensor zero point. Must be zero for non-int8 types. Weight zero point. Must be zero for non-int8 types. Output tensor CONV3D Input tensor Weight kernel size KDxKHxKW Per output channel bias data. [pad_d0, pad_d1, pad_top, pad_bottom, pad_left, pad_right] [stride_d, stride_y, stride_x] [dilation_d, dilation_y, dilation_x] Input tensor zero point. Must be zero for non-int8 types. Weight zero point. Must be zero for non-int8 types. Output tensor DEPTHWISE_CONV2D Input tensor Weight kernel size KH x KW Per output channel bias data. [pad_top, pad_bottom, pad_left, pad_right] [stride_y, stride_x] [dilation_y, dilation_x] Input tensor zero point. Must be zero for non-int8 types. Weight zero point. Must be zero for non-int8 types. Output tensor FFT2D Real part of the complex input. H,W must be powers of two. Imaginary part of the complex input. H,W must be powers of two. false for forward FFT, true for inverse FFT Real part of the complex output. Imaginary part of the complex output. FULLY_CONNECTED Input tensor Weights Per output channel bias data. Input tensor zero point. Must be zero for non-int8 types. Weight zero point. Must be zero for non-int8 types. Output tensor MATMUL Input tensor A, N matrices of size HxC Input tensor B, N matrices of size CxW Input tensor A zero point. Must be zero for non-int8 types. Input tensor B zero point. Must be zero for non-int8 types. Output tensor, N matrices of size HxW MAX_POOL2D Input tensor 4D [kernel_y, kernel_x] [stride_y, stride_x] [pad_top, pad_bottom, pad_left, pad_right] Output tensor 4D RFFT2D Real input. H,W must be powers of two. Real part of the complex output Imaginary part of the complex output. TRANSPOSE_CONV2D Input tensor Weight kernel size KH x KW Per output channel bias data. [out_pad_top, out_pad_bottom, out_pad_left, out_pad_right] [stride_y, stride_x] [N,OH,OW,OC] Input tensor zero point. Must be zero for non-int8 types. Weight zero point. Must be zero for non-int8 types. Output tensor CLAMP Input tensor Minimum clip value Maximum clip value Output tensor of same type and shape as input SIGMOID Input tensor Output tensor of same type and shape as input TANH Input tensor Output tensor of same type and shape as input ADD Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary ARITHMETIC_RIGHT_SHIFT Input tensor Input tensor with the same rank as input1 If true then the shift is rounded Output tensor with broadcast shape if necessary BITWISE_AND Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary BITWISE_OR Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary BITWISE_XOR Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary INTDIV Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary LOGICAL_AND Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary LOGICAL_LEFT_SHIFT Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary LOGICAL_RIGHT_SHIFT Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary LOGICAL_OR Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary LOGICAL_XOR Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary MAXIMUM Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary MINIMUM Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary MUL Input tensor Input tensor with the same rank as input1 Result right shift (int32_t data type only) Output tensor with broadcast shape if necessary POW Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary SUB Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary TABLE Input tensor Lookup table tensor Output tensor ABS Input tensor Output tensor of same type, size as the input tensor BITWISE_NOT Input tensor Output tensor of same type, size as the input tensor CEIL Input tensor Output tensor of same type, size as the input tensor CLZ Input tensor Output tensor of same type, size as the input tensor EXP Input tensor Output tensor of same type, size as the input tensor FLOOR Input tensor Output tensor of same type, size as the input tensor LOG Input tensor Output tensor of same type, size as the input tensor LOGICAL_NOT Input tensor Output tensor of same type, size as the input tensor NEGATE Input tensor Input 1 zero point. Must be zero for non-int8 types. Output zero point. Must be zero for non-int8 types. Output tensor of same type, size as the input tensor RECIPROCAL Input tensor Output tensor of same type, size as the input tensor RSQRT Input tensor Output tensor of same type, size as the input tensor SELECT Input selector tensor Input value tensor if input1 is True Input value tensor if input1 is False Output tensor of same type as input2 and input3, with broadcast shape if necessary EQUAL Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary GREATER Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary GREATER_EQUAL Input tensor Input tensor with the same rank as input1 Output tensor with broadcast shape if necessary REDUCE_ALL Input tensor with rank from 1 to 4 Axis to reduce, in range from 0 to rank(shape1)-1 Output tensor. Same rank as the input tensor. REDUCE_ANY Input tensor with rank from 1 to 4 Axis to reduce, in range from 0 to rank(shape1)-1 Output tensor. Same rank as the input tensor. REDUCE_MAX Input tensor with rank from 1 to 4 Axis to reduce, in range from 0 to rank(shape1)-1 Output tensor. Same rank as the input tensor. REDUCE_MIN Input tensor with rank from 1 to 4 Axis to reduce, in range from 0 to rank(shape1)-1 Output tensor. Same rank as the input tensor. REDUCE_PRODUCT Input tensor with rank from 1 to 4 Axis to reduce, in range from 0 to rank(shape1)-1 Output tensor. Same rank as the input tensor. REDUCE_SUM Input tensor with rank from 1 to 4 Axis to reduce, in range from 0 to rank(shape1)-1 Output tensor. Same rank as the input tensor. CONCAT List of input tensors. All inputs must have the same rank and data type Axis along which concatenation is to occur, in range from 0 to rank(shape)-1 Output tensor PAD Input tensor Number of pad elements at the start and end of each dimension Constant value to be used as padding Output tensor of same type as the input tensor RESHAPE Input tensor 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. Output tensor of same type, size as the input tensor REVERSE Input tensor with rank from 1 to 4 Axis to reverse, in range from 0 to rank(shape)-1 Output tensor. Same shape as input tensor SLICE Input tensor with rank from 1 to 4 List of integer coordinates, of length equal to the rank of input1. Start coordinate for slicing. List of integer size values, of length equal to the rank of input1. Size of the input to be used. Output tensor of same type as the input tensor TILE Input tensor with rank from 1 to 4 Number of times to replicate input1 in each dimension Output tensor of same type, rank as the input tensor TRANSPOSE Input tensor with minimum rank of one. List of integers of length equal to the rank of input1. Values must be valid dimensions within shape1, and may not be repeated. Output tensor of same type, rank as the input tensor GATHER 3D value tensor 2D index tensor 3D output tensor SCATTER 3D values in tensor 2D index tensor 3D input tensor 3D output tensor RESIZE Input tensor [scale_y_n, scale_y_d, scale_x_n, scale_x_d] [offset_y, offset_x] [border_y, border_x] BILINEAR or NEAREST Output tensor CAST Input tensor Output tensor RESCALE Input tensor Output tensor with the same shape as input Input tensor zero point. Must be zero for non-int8 types. Output tensor zero point. Must be zero for non-int8 types. Scaling multiplier array Scaling shift array if (scale32) mul_t=int32_t else mul_t=int16_t Select double round mode if (per_channel) NC=shape[rank(shape)-1] else NC=1 CONST Constant values Output tensor of the same type, size as the input tensor IDENTITY Input tensor Output tensor of the same type, size as the input tensor COND_IF List of input tensors Input condition as a size 1 tensor TOSA graph to execute if condition is true TOSA graph to execute if condition is false List of output tensors WHILE_LOOP List of input tensors TOSA graph to evaluate the condition TOSA graph to execute the loop body List of output tensors