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| author | Jacob Bohlin <jacob.bohlin@arm.com> | 2020-06-11 15:09:57 +0200 |
|---|---|---|
| committer | Tim Hall <tim.hall@arm.com> | 2020-06-18 17:53:52 +0100 |
| commit | 611fcdf8f0e33dabba4486eb78ce482c189248e5 (patch) | |
| tree | f2265bb694b901d6ff6a57bd616fd0ead0ddc950 /ethosu/vela/high_level_command_stream_generator.py | |
| parent | 749d92115e8ac7d0cc755ce93ea8a8c53fd6e474 (diff) | |
| download | ethos-u-vela-611fcdf8f0e33dabba4486eb78ce482c189248e5.tar.gz | |
MLBEDSW-2435: Fix for cascading upscaling operators
Fixed a coordinate issue which caused the compiler to crash when
cascading upscaling operators such as ResizeBilinear.
Signed-off-by: Jacob Bohlin <jacob.bohlin@arm.com>
Change-Id: I982863573b0e5829e6d0c255dbbc308cb332a37a
Diffstat (limited to 'ethosu/vela/high_level_command_stream_generator.py')
| -rw-r--r-- | ethosu/vela/high_level_command_stream_generator.py | 14 |
1 files changed, 9 insertions, 5 deletions
diff --git a/ethosu/vela/high_level_command_stream_generator.py b/ethosu/vela/high_level_command_stream_generator.py index 0cd3ad22..ab72fbcd 100644 --- a/ethosu/vela/high_level_command_stream_generator.py +++ b/ethosu/vela/high_level_command_stream_generator.py @@ -75,9 +75,13 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id strides = None skirt = None + upscaling = 1 if ps.primary_op is not None: strides = ps.primary_op.attrs.get("strides", None) skirt = ps.primary_op.attrs.get("skirt", None) + if ps.primary_op.type in set(("Conv2DBackpropInputSwitchedBias", "ResizeBilinear")): + upscaling = ofm_tensor.shape[-3] // ifm_tensor.shape[-3] + assert ofm_tensor.shape[-2] == (ifm_tensor.shape[-2] * upscaling) concat_axis = 0 concat_offset = 0 @@ -113,13 +117,13 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id if ifm_tensor.shape != []: ifm_box, _, _ = ofm_box.transform_with_strides_and_skirt( - strides, skirt, ifm_tensor.shape, npu_block_type, concat_axis, concat_offset, split_offsets[0] + strides, skirt, ifm_tensor.shape, npu_block_type, concat_axis, concat_offset, split_offsets[0], upscaling ) else: ifm_box = Box([], []) if ifm2_tensor is not None and ifm2_tensor.shape != []: ifm2_box, _, _ = ofm_box.transform_with_strides_and_skirt( - strides, skirt, ifm2_tensor.shape, npu_block_type, concat_axis, concat_offset, split_offsets[1] + strides, skirt, ifm2_tensor.shape, npu_block_type, concat_axis, concat_offset, split_offsets[1], upscaling ) else: ifm2_box = Box([], []) @@ -127,7 +131,7 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id for intermediate in ps.intermediates: if intermediate != None and intermediate.shape != [] and intermediate.purpose == 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] + strides, skirt, intermediate.shape, npu_block_type, concat_axis, concat_offset, split_offsets[0], upscaling ) yield from dma_if_necessary(ps, intermediate_box, intermediate) @@ -214,13 +218,13 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id k_height = weight_tensor.shape[0] ifm_box, pad_top, pad_bottom = ofm_box.transform_with_strides_and_skirt( - strides, skirt, ifm_tensor.shape, npu_block_type, concat_axis, concat_offset, split_offsets[0], k_height + strides, skirt, ifm_tensor.shape, npu_block_type, concat_axis, concat_offset, split_offsets[0], k_height, upscaling ) for intermediate in ps.intermediates: if intermediate != None and intermediate.shape != [] and intermediate.purpose == 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] + strides, skirt, intermediate.shape, npu_block_type, concat_axis, concat_offset, split_offsets[0], upscaling ) yield from dma_if_necessary(ps, intermediate_box, intermediate) |