| // |
| // 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. |
| |
| REQUIRE(0 <= shift && shift <= 63); |
| REQUIRE(in_t == int32_t || shift == 0); |
| ERROR_IF(shape != broadcast_shape(shape1, shape2)); |
| for_each(index in shape) { |
| shape_t index1 = apply_broadcast(shape, shape1, index); |
| shape_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); |
| } |