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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);
+ }
+}