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| author | Louis Verhaard <louis.verhaard@arm.com> | 2021-03-11 14:59:06 +0100 |
|---|---|---|
| committer | Louis Verhaard <louis.verhaard@arm.com> | 2021-03-16 10:37:20 +0100 |
| commit | c822d62ba27b874a130e9d8d434c12b419d10d62 (patch) | |
| tree | 4450a032513b537ffd3545cb2bdb6e052339beb2 /ethosu/vela/high_level_command_stream_generator.py | |
| parent | 8ba0792731d47de64a59d93359340f3c88fc4a62 (diff) | |
| download | ethos-u-vela-c822d62ba27b874a130e9d8d434c12b419d10d62.tar.gz | |
MLBEDSW-4223: Full support for PAD operator
- Added full support for PAD operator
- Hardware padding is still used whenever possible
- Bug fix Pad followed by max pool if IFM contains negative values
Change-Id: Ifc64d1943737d94466f5e2821009dab12a49a965
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
Diffstat (limited to 'ethosu/vela/high_level_command_stream_generator.py')
| -rw-r--r-- | ethosu/vela/high_level_command_stream_generator.py | 45 |
1 files changed, 12 insertions, 33 deletions
diff --git a/ethosu/vela/high_level_command_stream_generator.py b/ethosu/vela/high_level_command_stream_generator.py index 1ce7e7e3..23d3a4fc 100644 --- a/ethosu/vela/high_level_command_stream_generator.py +++ b/ethosu/vela/high_level_command_stream_generator.py @@ -79,19 +79,14 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id elif ps.primary_op.type == Op.ResizeBilinear: upscaling = round_up_divide(ofm_shape.height, ifm_shape.height) - concat_axis = 0 - concat_offset = 0 + concat_offset = [0, 0, 0, 0] for op in ps.ops: - if op.attrs.get("concat_axis", None) is not None: - concat_axis = op.attrs["concat_axis"] - concat_start = op.attrs["concat_start"] - concat_end = op.attrs["concat_end"] - - ofm_start[concat_axis] = concat_start - ofm_end[concat_axis] = concat_end - concat_offset = concat_start - elif op.type.is_relu_op() or op.type in (Op.Tanh, Op.Sigmoid): + if op.write_offset is not None: + concat_offset = op.write_offset.as_list() + ofm_start = concat_offset + ofm_end = (op.write_offset + op.write_shape).as_list() + if op.type.is_relu_op() or op.type in (Op.Tanh, Op.Sigmoid): ps.primary_op.activation = create_activation_function(op.type) if strat == SchedulingStrategy.WeightStream: @@ -109,13 +104,13 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id if ifm_shape is not None: ifm_box, _, _ = ofm_box.transform_with_strides_and_skirt( - strides, skirt, ifm_shape, npu_block_type, concat_axis, concat_offset, split_offsets[0], upscaling, + strides, skirt, ifm_shape, npu_block_type, concat_offset, split_offsets[0], upscaling, ) else: ifm_box = Box([], []) if ifm2_shape is not None: ifm2_box, _, _ = ofm_box.transform_with_strides_and_skirt( - strides, skirt, ifm2_shape, npu_block_type, concat_axis, concat_offset, split_offsets[1], upscaling, + strides, skirt, ifm2_shape, npu_block_type, concat_offset, split_offsets[1], upscaling, ) else: ifm2_box = Box([], []) @@ -132,7 +127,6 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id skirt, Shape4D(intermediate.shape), npu_block_type, - concat_axis, concat_offset, split_offsets[0], upscaling, @@ -143,11 +137,9 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id weight_box = None if weight_tensor is not None: - weight_oc_start = start - weight_oc_end = end - if concat_axis - len(weight_tensor.shape) == -1: - weight_oc_start -= concat_offset - weight_oc_end -= concat_offset + weight_offset = concat_offset[len(weight_tensor.shape) - 1] + weight_oc_start = start - weight_offset + weight_oc_end = end - weight_offset weight_box = Box.make_weight_box( weight_tensor.shape, @@ -172,8 +164,6 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id weight_tensor, weight_box, scale_tensor, - concat_axis, - concat_offset, ifm2_tensor=ifm2_tensor, ifm2_box=ifm2_box, ) @@ -222,15 +212,7 @@ 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_shape, - npu_block_type, - concat_axis, - concat_offset, - split_offsets[0], - k_height, - upscaling, + strides, skirt, ifm_shape, npu_block_type, concat_offset, split_offsets[0], k_height, upscaling, ) ifm_y_needed = 1 @@ -257,7 +239,6 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id skirt, Shape4D(intermediate.shape), npu_block_type, - concat_axis, concat_offset, split_offsets[0], upscaling, @@ -294,8 +275,6 @@ def generate_high_level_command_stream_for_pass(strat, passes, block_configs, id weight_tensor, weight_box, scale_tensor, - concat_axis, - concat_offset, None, None, pad_top, |