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author | Johan Alfven <johan.alfven@arm.com> | 2024-04-20 08:04:27 +0200 |
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committer | Johan Alfven <johan.alfven@arm.com> | 2024-04-24 12:16:57 +0200 |
commit | f49370003956d4f6f7d177114a68edb07b364fe9 (patch) | |
tree | fcd614f6f8293a44e789b723b5dee663aa3957c1 | |
parent | f9194e11b2d2f1e813e347cad2d863a26115fa7e (diff) | |
download | ethos-u-vela-f49370003956d4f6f7d177114a68edb07b364fe9.tar.gz |
- Fully connected with batch shape will use the weights
more than once. Models with these type of fully connected
will benefit from weight buffering.
- If a fully connected op with this shape is detected it is
changed to a conv2d and the normal weight buffering
flow will be used.
Change-Id: I272741a32390e036d5e04bd5af41d4538162e86e
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
-rw-r--r-- | ethosu/vela/tflite_graph_optimiser.py | 9 |
1 files changed, 8 insertions, 1 deletions
diff --git a/ethosu/vela/tflite_graph_optimiser.py b/ethosu/vela/tflite_graph_optimiser.py index 687e5d4..3af8588 100644 --- a/ethosu/vela/tflite_graph_optimiser.py +++ b/ethosu/vela/tflite_graph_optimiser.py @@ -827,7 +827,7 @@ def convert_batched_fc_shape(op: Operation, arch, nng) -> Operation: if op.type == Op.FullyConnected: # Check if the first dimension indicates batching if op.ifm_shapes[0].batch > 1: - batching_split = {4: (2, 2), 8: (2, 4), 16: (4, 4)} + batching_split = {4: (2, 2), 6: (2, 3), 8: (2, 4), 9: (3, 3), 12: (3, 4), 16: (4, 4)} n = op.ifm_shapes[0].batch h, w = batching_split.get(n, (1, n)) op.ifm_shapes[0] = Shape4D([1, h, w, op.ifm_shapes[0].depth]) @@ -840,6 +840,13 @@ def convert_batched_fc_shape(op: Operation, arch, nng) -> Operation: n = op.ofm_shapes[0].batch h, w = batching_split.get(n, (1, n)) op.ofm_shapes[0] = Shape4D([1, h, w, op.ofm_shapes[0].depth]) + if h == 1 and w > 4: + # If batch can not be found in the split set the weights are going to be + # read from memory several times. Convert op to conv2d since this + # enables weight buffering. + op.type = Op.Conv2DBias + op.attrs["padding"] = Padding.SAME + DebugDatabase.add_optimised(op, op) return op |