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authorDwight Lidman <dwight.lidman@arm.com>2020-04-30 11:54:48 +0200
committerTim Hall <tim.hall@arm.com>2020-06-18 17:53:52 +0100
commit3ec04ac9e38d26193e0081a8e0fa3b8b667bb688 (patch)
treed4c961583bbe7ff47a9a0313d72ff0871a44b72d /ethosu/vela/tflite_reader.py
parent1629f331810de8ebff018259c75ee024857472e5 (diff)
downloadethos-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/tflite_reader.py')
-rw-r--r--ethosu/vela/tflite_reader.py16
1 files changed, 16 insertions, 0 deletions
diff --git a/ethosu/vela/tflite_reader.py b/ethosu/vela/tflite_reader.py
index 4456d5a0..aa0ec4d8 100644
--- a/ethosu/vela/tflite_reader.py
+++ b/ethosu/vela/tflite_reader.py
@@ -156,6 +156,22 @@ class TFLiteSubgraph:
if opt_serializer is not None:
op.attrs = opt_serializer.deserialize(op_data.BuiltinOptions(), op_data.CustomOptionsAsNumpy())
+ if op_type.startswith("ResizeBilinear"):
+ upscaled_shape = [op.inputs[0].shape[1] * 2, op.inputs[0].shape[2] * 2]
+ out_shape = op.outputs[0].shape[1:3]
+ if not op.attrs['align_corners'] and out_shape == upscaled_shape:
+ # this means the output is supposed to be a x2 upscale,
+ # so we need to do SAME padding
+ op.attrs.update({'padding': b'SAME'})
+ elif (op.attrs['align_corners']
+ and out_shape == [upscaled_shape[0] - 1, upscaled_shape[1] - 1]):
+ # here we can just run the avg pool without padding and
+ # produce a (M * 2 - 1, N * 2 - 1) sized output
+ op.attrs.update({'padding': b'VALID'})
+ else:
+ assert False, "Only 2x upscaling is supported"
+ op.attrs.update({'filter_width': 2, 'filter_height': 2, 'stride_w': 1, 'stride_h': 1,})
+
if "stride_w" in op.attrs:
op.attrs["strides"] = (1, op.attrs["stride_h"], op.attrs["stride_w"], 1)
if "filter_width" in op.attrs: