Pavel Esir
22169a05b9
* fix ss * successfully converted * successfully run moved infer and normalizer unit-tests * successfully rewritten StridedSlice infer unittests * int64 array * Successfully converter crash-when-loading, xj_feauture and toy nets (cherry-picked maxpoolV4 and tf_broadcast_ext) * successfully moved PermuteAttrs to general mechanism * successfully converted xj_feauture and crash when loading with the new rewritten SS infer * fixed get_shape_from_slice and moved to common utils * fixed extending masks and some other * some refactoring * fixed extending masks in extractor, fixed licence year and some other code clearing * corrected a couple of unittests * fox permute for 5 rank slice and 4 rank inputs/ * WIP * Added comments * fixed StridedSlice in ProposalMutation.py * rechecked shape_infer unittests added some new cases * added shape_infer unit-tests after StridedSliceNormalizer pass and Permute unit-tests * corrected unittests * Applied review comments * general permutations for inputs implemented, corrected ellipsis unrolling when shrink_axis is at the beginning, some other corrections * removed code duplication in infer and normalizer, moved 'slices' attr normalizing to StridedSliceNormalizer.py * removed some code duplication and other minor improvements * Added tests * minor corrections * wider range of unittests added (froze the number) * review comments applied * enabled skipped unit-test * comment corrections * applied review comments: changed op -> type, added some asserts, corrected comments and other minor corrections * sorted inputs, updated Supported_Frameworks_Layers.md, some minor
72 lines
2.3 KiB
Python
72 lines
2.3 KiB
Python
"""
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Copyright (C) 2018-2021 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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from mo.front.caffe.extractors.utils import get_canonical_axis_index
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import numpy as np
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from mo.utils.error import Error
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def slice_axis_ext(attrs):
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axis = attrs.int("axis", 0)
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begin = attrs.int("begin", 0)
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end = attrs.int("end", None)
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node_attrs = {
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'type': 'Crop',
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'axis': axis,
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'offset': begin,
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'dim': end,
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'infer': mxnet_slice_axis_infer
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}
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return node_attrs
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def mxnet_slice_axis_infer(node):
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in_shape = node.in_port(0).data.get_shape()
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node.axis = get_canonical_axis_index(in_shape, node.axis)
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slice_axis = node.axis
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new_shape = np.array(in_shape, dtype=np.int64)
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new_shape[slice_axis] = new_shape[slice_axis] / len(node.out_nodes())
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axis_size = in_shape[slice_axis]
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if node.offset < 0:
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node.offset += axis_size
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if not node.dim:
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node.dim = axis_size
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elif node.dim < 0:
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node.dim += axis_size
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input_dim = in_shape.size
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node.dim = (node.dim - node.offset)
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if node.dim > in_shape[slice_axis]:
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raise Error(
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'{0} node dimension value is bigger than the corresponding value in the input shape {1}. ' +
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'\nIn particular {2} is bigger than {3}. The Model Optimizer does not support this case. ' +
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'\nTo overcome, try to edit the original model "end" property of the {0} layer.',
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node.name, ','.join(str(i) for i in in_shape), str(node.dim), str(in_shape[slice_axis])
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)
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for i in range(0, input_dim):
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if i == slice_axis:
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new_shape[i] = node.dim
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else:
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new_shape[i] = in_shape[i]
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for i in range(0, len(node.out_nodes())):
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node.out_node(i)['shape'] = new_shape
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