diff options
Diffstat (limited to 'ethosu/vela/supported_operators.py')
| -rw-r--r-- | ethosu/vela/supported_operators.py | 36 |
1 files changed, 35 insertions, 1 deletions
diff --git a/ethosu/vela/supported_operators.py b/ethosu/vela/supported_operators.py index 99a4ba10..505d4d16 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 @@ class SupportedOperators: 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 @@ class SupportedOperators: 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 |