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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, [], []);
+ REQUIRE(value2 != 0);
+ shape_t result = value1 / value2;
+ tensor_write<shape_t>(output, [], [], result);
+} else {
+ 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_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+ in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+ REQUIRE(value2 != 0);
+ // This catches the case where we divide minimum<in_out_t> by -1
+ // which is not representable in two's complement
+ REQUIRE(static_cast<int64_t>(value1) / static_cast<int64_t>(value2) <= maximum_s<in_out_t>);
+ in_out_t result = apply_intdiv_s<in_out_t>(value1, value2);
+ tensor_write<in_out_t>(output, shape, index, result);
+ }
+}