optim: Fix issue with IFM streaming of LUT
Signed-off-by: Michael McGeagh <michael.mcgeagh@arm.com>
Change-Id: I3c3ed73a6db39615ddf5987dc5696b6b09682be0
diff --git a/ethosu/vela/high_level_command_stream_generator.py b/ethosu/vela/high_level_command_stream_generator.py
index 50b913d..8486dad 100644
--- a/ethosu/vela/high_level_command_stream_generator.py
+++ b/ethosu/vela/high_level_command_stream_generator.py
@@ -272,18 +272,21 @@
if (
intermediate is not None
and intermediate.shape != []
- and intermediate.purpose == TensorPurpose.FeatureMap
+ and intermediate.purpose in (TensorPurpose.FeatureMap, TensorPurpose.LUT)
):
- intermediate_box, _, _ = ofm_box.transform_with_strides_and_skirt(
- strides,
- skirt,
- intermediate.shape,
- npu_block_type,
- concat_axis,
- concat_offset,
- split_offsets[0],
- upscaling,
- )
+ if intermediate.purpose is TensorPurpose.FeatureMap:
+ intermediate_box, _, _ = ofm_box.transform_with_strides_and_skirt(
+ strides,
+ skirt,
+ intermediate.shape,
+ npu_block_type,
+ concat_axis,
+ concat_offset,
+ split_offsets[0],
+ upscaling,
+ )
+ else:
+ intermediate_box = Box([0] * len(intermediate.shape), list(intermediate.shape))
yield from dma_if_necessary(ps, intermediate_box, intermediate)
ifm_y_needed = 1