MLBEDSW-3903: Bug fix PAD operator
- Added checks for unsupported pad sizes in PAD operator
- Bug fix right pad/bottom pad calculation when replacing PAD operator
by hardware padding
Change-Id: Ib84be711277d987052f14352ab386e0e0b774987
Signed-off-by: Louis Verhaard <louis.verhaard@arm.com>
diff --git a/ethosu/vela/supported_operators.py b/ethosu/vela/supported_operators.py
index 99a4ba1..505d4d1 100644
--- a/ethosu/vela/supported_operators.py
+++ b/ethosu/vela/supported_operators.py
@@ -1,4 +1,4 @@
-# Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved.
+# Copyright (C) 2020-2021 Arm Limited or its affiliates. All rights reserved.
#
# SPDX-License-Identifier: Apache-2.0
#
@@ -260,6 +260,7 @@
self.specific_constraints[Op.Pad].append(SupportedOperators.constraint_pad_type)
self.specific_constraints[Op.Pad].append(SupportedOperators.constraint_pad_constant)
self.specific_constraints[Op.Pad].append(SupportedOperators.constraint_pad_ofm)
+ self.specific_constraints[Op.Pad].append(SupportedOperators.constraint_pad_size)
# HardSwish specific checks:
self.specific_constraints[Op.HardSwish].append(SupportedOperators.constraint_input_8bit)
@@ -844,6 +845,39 @@
return valid, f"PAD operator is followed by: {_optype_formatter(unsupported_consumers)+none_string}"
@staticmethod
+ def __leading_pad_ok(leading_pad, stride, kernel_size):
+ # If kernel size // 2 > stride, then (left, top) padding must be a multiple of stride,
+ # otherwise replacing PAD by hardware padding would iterate the wrong IFM rows/columns
+ max_size = kernel_size // 2
+ return leading_pad == max_size or max_size <= stride or leading_pad % stride == 0
+
+ @staticmethod
+ def constraint_pad_size(op):
+ "Padding must be at most kernel size divided by 2"
+ if SupportedOperators.constraint_pad_ofm(op)[0]:
+ padding = op.inputs[1].values # 4x2 tensor, first dimension is N, H, W, C
+ top, left, bottom, right = (padding[1][0], padding[2][0], padding[1][1], padding[2][1])
+ for cons in op.ofm.consumers():
+ if cons is not None:
+ # Note: pre-order graph traversal removes inputs of operators that are in traversal,
+ # which makes it impossible to calculate kernel size, hence use cached _kernel for those operators
+ k = cons.kernel if cons.inputs else cons._kernel
+ k_w, k_h = k.dilated_wh()
+ if left > k_w // 2:
+ return False, f"Left padding is {left}, kernel width is {k_w}"
+ if right > k_w // 2:
+ return False, f"Right padding is {right}, kernel width is {k_w}"
+ if top > k_h // 2:
+ return False, f"Top padding is {top}, kernel height is {k_h}"
+ if bottom > k_h // 2:
+ return False, f"Bottom padding is {bottom}, kernel height is {k_h}"
+ if not SupportedOperators.__leading_pad_ok(top, k.stride.y, k_h):
+ return False, f"Top padding is {top}, must be {k_h // 2} or multiple of {k.stride.y}"
+ if not SupportedOperators.__leading_pad_ok(left, k.stride.x, k_w):
+ return False, f"Left padding is {left}, must be {k_w // 2} or multiple of {k.stride.x}"
+ return True, "Pad size is ok"
+
+ @staticmethod
def constraint_stridedslice_inputs_const(op):
"Begin, End and Stride Input tensors must be constant"
valid = True