MLBEDSW-7231: MLCE: Fixed assert caused by multiple reshape op's
Fixed an assert that was caused by a model that has a reshape operator
followed by another reshape operator. This structure has never been
thought of. However, since there is no need for the first reshape just
remove it from the path while traversing the graph.
Change-Id: I2a939df37502028ffc07115ac87e85375484efee
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
diff --git a/ethosu/vela/graph_optimiser_util.py b/ethosu/vela/graph_optimiser_util.py
index 4e233c4..d90c06b 100644
--- a/ethosu/vela/graph_optimiser_util.py
+++ b/ethosu/vela/graph_optimiser_util.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2021-2022 Arm Limited and/or its affiliates <open-source-office@arm.com>
+# SPDX-FileCopyrightText: Copyright 2021-2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
#
# SPDX-License-Identifier: Apache-2.0
#
@@ -312,6 +312,19 @@
if not op.run_on_npu or op.type not in memory_only_ops:
return op
+ prev_op = op.ifm.ops[0]
+ while prev_op is not None and prev_op.run_on_npu and prev_op.type in memory_only_ops:
+ # Current op is preceded by another memory only op.
+ # Replace current op's ifm with the preceding op's ifm. By doing
+ # this the preceding op is removed from current path.
+ next_prev_op = prev_op.ifm.ops[0]
+ if next_prev_op is not None and next_prev_op.run_on_npu and next_prev_op.type in memory_only_ops:
+ # Preceding op also have a preceding memory only op
+ prev_op = next_prev_op
+ else:
+ op.set_input_tensor(prev_op.ifm, 0)
+ break
+
# For the memory only operators we want to remove, tensors are removed.
# But in order to to do this, they cannot be outputs of the sg,
# this need to be fixed prior to the removal.
@@ -359,6 +372,8 @@
# IFM need to persist due to multiple consumers and copy op is needed
# OFM will replace IFM for the memory only op
insert_copy_op_before_op(op)
+ # One copy added so no need to check for another copy further down
+ return op
elif not (ofm_is_sg_ofm or ofm_is_cpu_consumed):
# Only one consumer and OFM is not subgraph output or cpu consumed,
# safe to replace ifm.shape by ofm.shape