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//
// This confidential and proprietary software may be used only as
// authorised by a licensing agreement from ARM Limited
// (C) COPYRIGHT 2020-2024 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.
if (in_out_t == shape_t) {
ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
shape_t value1 = tensor_read<shape_t>(input1, [], []);
shape_t value2 = tensor_read<shape_t>(input2, [], []);
shape_t result = value1 * value2;
tensor_write<shape_t>(output, [], [], result);
} else {
REQUIRE(0 <= shift && shift <= 63);
REQUIRE(in_t == int32_t || shift == 0);
ERROR_IF(shape != broadcast_shape(shape1, shape2));
for_each(index in shape) {
dim_t index1 = apply_broadcast(shape, shape1, index);
dim_t index2 = apply_broadcast(shape, shape2, index);
in_t value1 = tensor_read<in_t>(input1, shape1, index1);
in_t value2 = tensor_read<in_t>(input2, shape2, index2);
out_t result;
if (in_t == i32_t && shift > 0) {
int64_t product = sign_extend<int64_t>(value1) * sign_extend<int64_t>(value2);
int64_t round = static_cast<int64_t>(1) << (shift - 1);
product = (product + round) >> shift;
REQUIRE(product >= minimum_s<i32_t> && product <= maximum_s<i32_t>)
result = product;
} else {
result = apply_mul_s(value1, value2); // low 32-bits of result for i32_t
}
tensor_write<out_t>(output, shape, index, result);
}
}
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