diff options
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) |