MLBEDSW-1998: Add support for new_axis_mask
-Added support for new_axis_mask
-Added support for more than 1 bit set in new/shrink_axis mask
-Added checks for strided slice in supported operator check
-Added assert if nothing has been put on NPU
Change-Id: I66e2d04784f14d7ad82371f5d649a455d576a818
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
diff --git a/ethosu/vela/graph_optimiser.py b/ethosu/vela/graph_optimiser.py
index f0afcf8..a4ed39f 100644
--- a/ethosu/vela/graph_optimiser.py
+++ b/ethosu/vela/graph_optimiser.py
@@ -208,23 +208,49 @@
if op.type in set(("Unpack", "StridedSlice")):
# Unpack is also referred to as Unstack
# Requires the rewrite_split function to be called on the op afterwards
+
+ reshape_input_shape = tens.shape
if op.type == "StridedSlice":
+ new_axis_mask = op.attrs["new_axis_mask"]
shrink_axis_mask = op.attrs["shrink_axis_mask"]
- if shrink_axis_mask == 0:
+ ellipsis_mask = op.attrs["ellipsis_mask"]
+
+ if (new_axis_mask != 0 and shrink_axis_mask != 0) or ellipsis_mask != 0:
+ # Not supported, will be put on CPU
+ return tens
+ if shrink_axis_mask == 0 and new_axis_mask == 0:
# Equal Rank StridedSlice, no need to insert reshape
return tens
+ elif shrink_axis_mask != 0:
+ n = 0
+ axis = 0
+ while shrink_axis_mask:
+ prev_mask = shrink_axis_mask
+ n += 1
+ shrink_axis_mask &= shrink_axis_mask - 1
+ axis = int(math.log2(prev_mask - shrink_axis_mask))
+ reshape_input_shape = reshape_input_shape[:axis] + [1] + reshape_input_shape[axis:]
- # Only allow shrinking 1 axis for now
- assert shrink_axis_mask & (shrink_axis_mask - 1) == 0
- assert len(tens.shape) == (len(op.inputs[0].shape) - 1)
+ assert len(tens.shape) == (len(op.inputs[0].shape) - n)
+ op.attrs["shrink_axis_mask"] = 0
- axis = int(math.log2(shrink_axis_mask))
- op.attrs["shrink_axis_mask"] = 0
+ elif new_axis_mask != 0:
+ n = 0
+ axis = 0
+ while new_axis_mask:
+ prev_mask = new_axis_mask
+ n += 1
+ new_axis_mask &= new_axis_mask - 1
+ axis = int(math.log2(prev_mask - new_axis_mask))
+ reshape_input_shape = reshape_input_shape[:axis] + reshape_input_shape[(axis + 1):]
+ new_axis_mask >>= 1
+
+ assert len(tens.shape) == (len(op.inputs[0].shape) + n)
+ op.attrs["new_axis_mask"] = 0
else:
axis = int(op.attrs["axis"])
op.type = "UnpackReshaped"
-
- desired_shape = tens.shape[:axis] + [1] + tens.shape[axis:]
+ reshape_input_shape = tens.shape[:axis] + [1] + tens.shape[axis:]
# Construct 1 shape tensor to be used by all inserted reshape ops
new_shape_name = op.name + "_reshape_shape"
@@ -239,7 +265,7 @@
reshape_op = Operation("Reshape", reshape_name)
reshape_op.outputs = [out_tens]
reshape_in = out_tens.clone("_reshaped")
- reshape_in.shape = reshape_in.storage_shape = reshape_in.bandwidth_shape = desired_shape
+ reshape_in.shape = reshape_in.storage_shape = reshape_in.bandwidth_shape = reshape_input_shape
reshape_in.ops = [op]
out_tens.ops = [reshape_op]
reshape_op.inputs = [reshape_in, new_shape_tens]