MLBEDSW-3491: Fix index out of range in code gen
Usage of shape[-2] could cause index out of range.
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
Change-Id: I1b64b117f8236ce9ba321ca03bdb25e5a03a6589
diff --git a/ethosu/vela/high_level_command_to_npu_op.py b/ethosu/vela/high_level_command_to_npu_op.py
index 7750121..812e8e9 100644
--- a/ethosu/vela/high_level_command_to_npu_op.py
+++ b/ethosu/vela/high_level_command_to_npu_op.py
@@ -44,6 +44,7 @@
from .api import NpuShape3D
from .api import NpuTileBox
from .architecture_features import ArchitectureFeatures
+from .architecture_features import Block
from .data_type import DataType
from .high_level_command_stream import Box
from .high_level_command_stream import Command
@@ -148,22 +149,20 @@
def create_padding(cmd: NpuStripe, primary_op: Operation) -> NpuPadding:
if primary_op.type.npu_block_type == NpuBlockType.VectorProduct:
return NpuPadding(top=0, left=0, bottom=0, right=0)
- explicit_padding = list(primary_op.attrs["explicit_padding"]) # (top, left, bottom, right)
+ top, left, bottom, right = primary_op.attrs["explicit_padding"]
# Check if this is for horizontal ifm streaming
if not (cmd.is_first_h_stripe and cmd.is_last_h_stripe):
- explicit_padding[0] = cmd.pad_top
- explicit_padding[2] = cmd.pad_bottom
+ top = cmd.pad_top
+ bottom = cmd.pad_bottom
# Indexing from end since a 1x1 Avgpool might have been added with non 4-dimensional input/output,
# because of activation function needed to be fused.
if cmd.ifm_box.start_coord[-2] > 0:
- explicit_padding[1] = 0
- if cmd.ifm_box.end_coord[-2] < cmd.ifm_tensor.shape[-2]:
- explicit_padding[3] = 0
- return NpuPadding(
- top=explicit_padding[0], left=explicit_padding[1], bottom=explicit_padding[2], right=explicit_padding[3]
- )
+ left = 0
+ if cmd.ifm_box.end_coord[-2] < Block.from_shape(cmd.ifm_tensor.shape).width:
+ right = 0
+ return NpuPadding(top=top, left=left, bottom=bottom, right=right)
def get_region(tens: Tensor, arch: ArchitectureFeatures) -> int:
@@ -197,10 +196,10 @@
def get_ifm_depth(npu_block_type: NpuBlockType, ifm_box: Box, ofm_box: Box) -> int:
if npu_block_type in (NpuBlockType.ConvolutionMxN, NpuBlockType.VectorProduct, NpuBlockType.ReduceSum):
- shape = ifm_box.get_size_shape()
+ block = ifm_box.get_block()
else:
- shape = ofm_box.get_size_shape()
- return shape[-1]
+ block = ofm_box.get_block()
+ return block.depth
def use_zero_point_0(ps, tens: Tensor, is_ifm_tensor: bool) -> bool:
@@ -335,22 +334,18 @@
"""Sets common fields of the given operation"""
ps = cmd.ps
op = ps.primary_op
- in_shape = cmd.ifm_box.get_size_shape()
- out_shape = cmd.ofm_box.get_size_shape()
- ofm_height = out_shape[-3] if len(out_shape) >= 4 else 1
- ofm_width = out_shape[-2] if len(out_shape) >= 2 else 1
- ofm_depth = out_shape[-1] if len(out_shape) >= 1 else 1
- ifm_height = in_shape[-3] if len(in_shape) >= 4 else 1
- if op.type.npu_block_type in (NpuBlockType.ConvolutionMxN, NpuBlockType.VectorProduct, NpuBlockType.ReduceSum):
- ifm_depth = in_shape[-1] if len(in_shape) >= 1 else 1
- else:
- ifm_depth = ofm_depth
+
+ ifm_height = cmd.ifm_box.get_block().height
+ ifm_width = Block.from_shape(cmd.ifm_tensor.shape).width
+ ifm_depth = get_ifm_depth(op.type.npu_block_type, cmd.ifm_box, cmd.ofm_box)
npu_op.ifm = create_feature_map(cmd.ifm_tensor, cmd.ifm_box, arch)
- npu_op.ifm.shape = NpuShape3D(height=ifm_height, width=cmd.ifm_tensor.shape[-2], depth=ifm_depth)
+ npu_op.ifm.shape = NpuShape3D(height=ifm_height, width=ifm_width, depth=ifm_depth)
npu_op.ifm.quantization = get_ifm_or_ifm2_quantization(ps, cmd.ifm_tensor)
+
+ out_block = cmd.ofm_box.get_block()
npu_op.ofm = create_feature_map(cmd.ofm_tensor, cmd.ofm_box, arch)
- npu_op.ofm.shape = NpuShape3D(height=ofm_height, width=ofm_width, depth=ofm_depth)
+ npu_op.ofm.shape = NpuShape3D(height=out_block.height, width=out_block.width, depth=out_block.depth)
npu_op.ofm.quantization = get_ofm_quantization(ps, cmd.ofm_tensor)
if cmd.weight_tensor is not None:
@@ -429,9 +424,9 @@
npu_op.ifm2_scalar = cmd.ifm2_tensor.values.item(0)
npu_op.ifm2.shape = NpuShape3D(height=0, width=0, depth=0)
else:
- box_shp = cmd.ifm2_box.get_size_shape()
- height = box_shp[-3] if len(box_shp) >= 3 else 1
- npu_op.ifm2.shape = NpuShape3D(height=height, width=cmd.ifm2_tensor.shape[-2], depth=box_shp[-1])
+ ifm2_blk = cmd.ifm2_box.get_block()
+ ifm2_width = Block.from_shape(cmd.ifm2_tensor.shape).width
+ npu_op.ifm2.shape = NpuShape3D(height=ifm2_blk.height, width=ifm2_width, depth=ifm2_blk.depth)
set_common_op_fields(npu_op, cmd, arch)
# Check if output scale needs to be overridden
output_scale = None