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//
// This confidential and proprietary software may be used only as
// authorised by a licensing agreement from ARM Limited
// (C) COPYRIGHT 2020-2021 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[]
*Operation Function:*
[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[]
*Operation Function:*
[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[]
*Operation Function:*
[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<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[]
*Operation Function:*
[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<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[]
*Operation Function:*
[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 = 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[]
*Operation Function:*
[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<in_out_t>(state, value);
tensor_write<in_out_t>(output, shape, out_index, state);
}
----
|
