diff options
Diffstat (limited to 'ethosu/vela/operation.py')
| -rw-r--r-- | ethosu/vela/operation.py | 24 |
1 files changed, 6 insertions, 18 deletions
diff --git a/ethosu/vela/operation.py b/ethosu/vela/operation.py index de35dcc7..f85cb4bb 100644 --- a/ethosu/vela/operation.py +++ b/ethosu/vela/operation.py @@ -1,4 +1,4 @@ -# SPDX-FileCopyrightText: Copyright 2020-2022 Arm Limited and/or its affiliates <open-source-office@arm.com> +# SPDX-FileCopyrightText: Copyright 2020-2023 Arm Limited and/or its affiliates <open-source-office@arm.com> # # SPDX-License-Identifier: Apache-2.0 # @@ -458,19 +458,6 @@ def create_activation_function(op_type: Op, min=None, max=None) -> ActivationFun return act -def get_slice_offsets(input_shape: List[int], offset_tens: Tensor, offset_mask: int, is_begin: bool = True): - # For strided slice operator: get start or end offsets - offsets = len(input_shape) * [0] if is_begin else input_shape[:] - for idx in range(len(input_shape)): - # If the i:th bit in the mask is set then the value on offset_tens[i] should be ignored - if (offset_mask & (1 << idx)) == 0: - offsets[idx] = offset_tens.values[idx] - if offsets[idx] < 0: - # Convert offset to positive value - offsets[idx] += input_shape[idx] - return offsets - - class Operation: """Class representing a Neural Network operation. Has a name, a type, input and output tensors, as well as an attribute dictionary.""" @@ -775,17 +762,18 @@ class Operation: outputs = self.outputs # Extract masks - begin_mask = self.attrs["begin_mask"] ellipsis_mask = self.attrs["ellipsis_mask"] - end_mask = self.attrs["end_mask"] new_axis_mask = self.attrs["new_axis_mask"] shrink_axis_mask = self.attrs["shrink_axis_mask"] # shrink_axis_mask/new_axis_mask/ellipsis_mask is not supported by the Operation class but the operation # may have the attribute modified and handled in the graph optimization phase. assert shrink_axis_mask == new_axis_mask == ellipsis_mask == 0 - offset_start = get_slice_offsets(input_tens.shape, begin_tens, begin_mask, is_begin=True) - offset_end = get_slice_offsets(input_tens.shape, end_tens, end_mask, is_begin=False) + # use the begin and end values that were calculated in the model semantic check. this is because the end + # values can be affected (ignored) by the shrink_axis_mask and this mask may have been changed in the graph + # optimizer (see assert above) + offset_start = self.attrs["offset_begin"] + offset_end = self.attrs["offset_end"] elif self.type == Op.UnpackReshaped: # Requires fixup_unpack_output to be called before this point input_tens = self.inputs[0] |