Define ARM_NN_BROADCAST_WALK_NHWC

Define Documentation

ARM_NN_BROADCAST_WALK_NHWC(IN_TYPE, OUT_TYPE, in_1, dims_1, in_2, dims_2, out, dims_out, FULL, SCALAR_1, SCALAR_2)

Walk an NHWC broadcast of two operands, calling a contiguous kernel on each run.

Each input is indexed by its own dims: a dimension of 1 has stride 0 and is broadcast, any other dimension equals the output dimension and strides normally. The longest contiguous run whose shapes agree is handed to the caller’s kernels, so the common cases (identical shapes, a single scalar, per-batch, per-row, per-channel) each cost one call per run.

Preconditions: arm_nn_broadcast_dims_valid(dims_1, dims_2, dims_out) is non-zero.

Parameters:

  • IN_TYPE – element type of the inputs

  • OUT_TYPE – element type of the output

  • in_1 – const IN_TYPE * first input

  • dims_1 – const cmsis_nn_dims * dims of in_1

  • in_2 – const IN_TYPE * second input

  • dims_2 – const cmsis_nn_dims * dims of in_2

  • out – OUT_TYPE * output, sized by dims_out

  • dims_out – const cmsis_nn_dims * broadcast output dims (see arm_nn_broadcast_dims_valid)

  • FULL – FULL(const IN_TYPE *a, const IN_TYPE *b, OUT_TYPE *o, int32_t n) elementwise kernel over n elements of a and b

  • SCALAR_1 – SCALAR_1(const IN_TYPE *scalar, const IN_TYPE *vec, OUT_TYPE *o, int32_t n) kernel where *scalar is one element of in_1 broadcast against n elements of in_2

  • SCALAR_2 – SCALAR_2(const IN_TYPE *scalar, const IN_TYPE *vec, OUT_TYPE *o, int32_t n) kernel where *scalar is one element of in_2 broadcast against n elements of in_1; note the operands arrive in reversed order, so an asymmetric kernel must swap them