chapters/reduction.adoc

//
// This confidential and proprietary software may be used only as
// authorised by a licensing agreement from ARM Limited
// (C) COPYRIGHT 2020-2023 ARM Limited
// ALL RIGHTS RESERVED
// The entire notice above must be reproduced on all authorised
// copies and copies may only be made to the extent permitted
// by a licensing agreement from ARM Limited.

=== Reduction Operators

==== REDUCE_ALL

Reduce a tensor along the given axis with a logical AND operation

include::{generated}/operators/REDUCE_ALL.adoc[]

[source,c]
----
ERROR_IF(axis < 0  || axis >= rank(shape1));
ERROR_IF(shape[axis] != 1);

// Initialize output state to true
for_each(index in shape) {
    tensor_write<in_out_t>(output, shape, index, true);
}
for_each(index in shape1) {
    dim_t out_index = index;
    out_index[axis] = 0;
    in_out_t value = tensor_read<in_out_t>(input, shape1, index);
    in_out_t state = tensor_read<in_out_t>(output, shape, out_index);
    state      = state && value;
    tensor_write<in_out_t>(output, shape, out_index, state);
}
----

==== REDUCE_ANY

Reduce a tensor along the given axis with a logical OR operation

include::{generated}/operators/REDUCE_ANY.adoc[]

[source,c]
----
ERROR_IF(axis < 0  || axis >= rank(shape1));
ERROR_IF(shape[axis] != 1);

// Initialize output state to false
for_each(index in shape) {
    tensor_write<in_out_t>(output, shape, index, false);
}
for_each(index in shape1) {
    dim_t out_index = index;
    out_index[axis] = 0;
    in_out_t value = tensor_read<in_out_t>(input, shape1, index);
    in_out_t state = tensor_read<in_out_t>(output, shape, out_index);
    state      = state || value;
    tensor_write<in_out_t>(output, shape, out_index, state);
}
----

==== REDUCE_MAX

Reduce a tensor along the given axis with a maximum operation

include::{generated}/operators/REDUCE_MAX.adoc[]

[source,c]
----
ERROR_IF(axis < 0  || axis >= rank(shape1));
ERROR_IF(shape[axis] != 1);
for_each(index in shape) {
    tensor_write<in_out_t>(output, shape, index, minimum<in_out_t>);
}
for_each(index in shape1) {
    dim_t out_index = index;
    out_index[axis] = 0;
    in_out_t value = tensor_read<in_out_t>(input, shape1, index);
    in_out_t state = tensor_read<in_out_t>(output, shape, out_index);
    state      = apply_max_s<in_out_t>(state, value);
    tensor_write<in_out_t>(output, shape, out_index, state);
}
----

==== REDUCE_MIN

Reduce a tensor along the given axis with a minimum operation

include::{generated}/operators/REDUCE_MIN.adoc[]

[source,c]
----
ERROR_IF(axis < 0  || axis >= rank(shape1));
ERROR_IF(shape[axis] != 1);
for_each(index in shape) {
    tensor_write<in_out_t>(output, shape, index, maximum<in_out_t>);
}
for_each(index in shape1) {
    dim_t out_index = index;
    out_index[axis] = 0;
    in_out_t value = tensor_read<in_out_t>(input, shape1, index);
    in_out_t state = tensor_read<in_out_t>(output, shape, out_index);
    state      = apply_min_s<in_out_t>(state, value);
    tensor_write<in_out_t>(output, shape, out_index, state);
}
----

==== REDUCE_PRODUCT

Reduce a tensor along the given axis by computing the product of the axis.

include::{generated}/operators/REDUCE_PRODUCT.adoc[]

[source,c]
----
ERROR_IF(axis < 0  || axis >= rank(shape1));
ERROR_IF(shape[axis] != 1);
for_each(index in shape) {
    tensor_write<in_out_t>(output, shape, index, 1.0);
}
for_each(index in shape1) {
    dim_t out_index = index;
    out_index[axis] = 0;
    in_out_t value = tensor_read<in_out_t>(input, shape1, index);
    in_out_t state = tensor_read<in_out_t>(output, shape, out_index);
    state      = apply_mul_s<in_out_t>(state, value);
    tensor_write<in_out_t>(output, shape, out_index, state);
}
----

==== REDUCE_SUM

Reduce a tensor along the given axis by computing the sum of the axis.

include::{generated}/operators/REDUCE_SUM.adoc[]

[source,c]
----
ERROR_IF(axis < 0  || axis >= rank(shape1));
ERROR_IF(shape[axis] != 1);
for_each(index in shape) {
    tensor_write<in_out_t>(output, shape, index, 0);
}
for_each(index in shape1) {
    dim_t out_index = index;
    out_index[axis] = 0;
    in_out_t value = tensor_read<in_out_t>(input, shape1, index);
    in_out_t state = tensor_read<in_out_t>(output, shape, out_index);
    state          = apply_add_s<in_out_t>(state, value);
    tensor_write<in_out_t>(output, shape, out_index, state);
}
----