MLBEDSW-1498: Add Resize_Bilinear operator support
This patch adds support for the ResizeBilinear operator.
It is implemented using a 2x2 Nearest Neighbor upscale
followed by a 2x2 Average Pool.
Depending on the argument align_corners
the output is either of shape:
- (2 * M, 2 * N) when align_corners == True, or
- (2 * M - 1, 2 * N - 1) when align_corners == False
where (M, N) is the input shape.
The padding mode is SAME when align_corners == True
and VALID when align_corners == False.
The argument half_pixel_centers is out of scope and is
as of now ignored.
Note that only upscaling by a factor of 2 is supported.
Change-Id: Ia6d6d010c4f1bb13f5f839bc8d16872a626d9a3b
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
diff --git a/ethosu/vela/graph_optimiser.py b/ethosu/vela/graph_optimiser.py
index b29a382..fdd6fc6 100644
--- a/ethosu/vela/graph_optimiser.py
+++ b/ethosu/vela/graph_optimiser.py
@@ -283,7 +283,7 @@
if "Conv" in op.type:
kernel_size = op.inputs[1].shape[:2]
input_shape = op.inputs[0].shape
- elif "Pool" in op.type:
+ elif "Pool" in op.type or "ResizeBilinear" == op.type:
kernel_size = op.attrs["ksize"][1:3]
input_shape = op.inputs[0].shape
elif op.type == "ExtractImagePatches":
@@ -314,7 +314,7 @@
)
)
depthwise_op = set(("DepthwiseConv2dNative", "DepthwiseConv2dBiasAct",))
-pool_op = set(("AvgPool", "MaxPool", "QuantizedAvgPool", "QuantizedMaxPool", "AvgPoolAct", "MaxPoolAct"))
+pool_op = set(("AvgPool", "MaxPool", "QuantizedAvgPool", "QuantizedMaxPool", "AvgPoolAct", "MaxPoolAct", "ResizeBilinear",))
elementwise_op = set(("AddAct", "MulAct", "SubAct", "Maximum", "Minimum", "LeakyRelu", "Abs"))
activation_ops = set(("Relu", "Relu6", "ReluN1To1", "Sigmoid", "Tanh"))
memory_only_ops = set(("Reshape",))