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]
Enumerated type, must be one of INT32, FP16, FP32, as defined in the Supported Data Types table for this operation
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 with minimum rank of one.
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 minimum rank of one.
Axis to reverse, in range from 0 to rank(shape)-1
Output tensor. Same shape as input tensor
SLICE
Input tensor with minimum rank of one.
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 minimum rank of one.
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