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| author | Dwight Lidman <dwight.lidman@arm.com> | 2020-04-30 11:54:48 +0200 |
|---|---|---|
| committer | Tim Hall <tim.hall@arm.com> | 2020-06-18 17:53:52 +0100 |
| commit | 3ec04ac9e38d26193e0081a8e0fa3b8b667bb688 (patch) | |
| tree | d4c961583bbe7ff47a9a0313d72ff0871a44b72d /ethosu/vela/graph_optimiser.py | |
| parent | 1629f331810de8ebff018259c75ee024857472e5 (diff) | |
| download | ethos-u-vela-3ec04ac9e38d26193e0081a8e0fa3b8b667bb688.tar.gz | |
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>
Diffstat (limited to 'ethosu/vela/graph_optimiser.py')
| -rw-r--r-- | ethosu/vela/graph_optimiser.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/ethosu/vela/graph_optimiser.py b/ethosu/vela/graph_optimiser.py index b29a3823..fdd6fc61 100644 --- a/ethosu/vela/graph_optimiser.py +++ b/ethosu/vela/graph_optimiser.py @@ -283,7 +283,7 @@ def add_padding_fields(op, arch): 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 @@ fc_op = set( ) ) 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",)) |