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| author | Tim Hall <tim.hall@arm.com> | 2022-05-04 16:20:43 +0100 |
|---|---|---|
| committer | Tim Hall <tim.hall@arm.com> | 2022-05-04 16:26:09 +0100 |
| commit | b5df773e92051004158046b0ed2c7b802198de6e (patch) | |
| tree | 7d738a28a63b66a20f379acbdfc6c3e7c4a98a61 /ethosu/vela/cascade_builder.py | |
| parent | 95b07c1c0fed6a985607131e59a593786d40b389 (diff) | |
| download | ethos-u-vela-b5df773e92051004158046b0ed2c7b802198de6e.tar.gz | |
Revert "MLBEDSW-6263: Use separate tensors for double buffering"
This reverts commit cc5f4de1c35ba44fca7ff6295c6ae846f8242344.
Signed-off-by: Tim Hall <tim.hall@arm.com>
Change-Id: I0fa5babfe9ad9ec668720d04fe1c16d9a9092131
Diffstat (limited to 'ethosu/vela/cascade_builder.py')
| -rw-r--r-- | ethosu/vela/cascade_builder.py | 12 |
1 files changed, 8 insertions, 4 deletions
diff --git a/ethosu/vela/cascade_builder.py b/ethosu/vela/cascade_builder.py index 0d25ec64..4c3f75b7 100644 --- a/ethosu/vela/cascade_builder.py +++ b/ethosu/vela/cascade_builder.py @@ -144,8 +144,10 @@ class CascadeBuilder: # Keep track of which Ops are in the proposed cascade as well as the best cascade so far ops_in_cascade = [op] ops_in_best_cascade = [op] - # Get the size of the weight buffer(s) - weight_buffer = sum(tens.storage_size() for tens in ref_cost[op].buffered_weight_tensors) + # Get the size of the weight buffer + weight_buffer = 0 + if ref_cost[op].buffered_weight_tensor: + weight_buffer = ref_cost[op].buffered_weight_tensor.storage_size() # The first IFM needs to be stored in full cascade_ifm_size = op.ifm_size_in_bytes() if not self.spilling else 0 @@ -188,8 +190,10 @@ class CascadeBuilder: op_full_ofm = current_op.ofm_size_in_bytes() _, op_ifm_buffer = buffers.get_buffer(producer, current_op, ref_cost) - # Get the size of the weight buffer(s) - op_weight_buffer = sum(tens.storage_size() for tens in ref_cost[current_op].buffered_weight_tensors) + # Get the size of the weight buffer + op_weight_buffer = 0 + if ref_cost[current_op].buffered_weight_tensor: + op_weight_buffer = ref_cost[current_op].buffered_weight_tensor.storage_size() # Calculate the uncascaded memory requirement for current Op uncascaded_sram_usage = op_full_ifm + op_full_ofm + self.non_local_mem_usage.get(current_op, 0) |