""" Copyright (c) 2018-2019 Intel Corporation Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import numpy as np from mo.front.caffe.extractors.utils import embed_input, weights_biases from mo.front.common.partial_infer.elemental import copy_shape_infer from mo.utils.utils import NamedAttrsClass def scale_ext(pl, ml): param = pl.scale_param attrs = { 'op': 'ScaleShift', 'type': 'ScaleShift', 'axis': param.axis, 'infer': copy_shape_infer } if ml is None and len(pl.bottom) == 1: # default weights and biases for scale layer if the caffemodel file doesn't contain them ml = NamedAttrsClass({'blobs': np.array([NamedAttrsClass({'data': np.array([1])}), NamedAttrsClass({'data': np.array([0])})])}) # scale with 1 input and 1 or 2 blobs if ml and len(ml.blobs) != 0 and len(pl.bottom) == 1: attrs.update(weights_biases(param.bias_term, ml)) # 2 inputs + bias elif len(pl.bottom) == 2 and param.bias_term: if ml is None or len(ml.blobs) == 0: # default bias for scale layer with 2 inputs if the caffemodel file doesn't contain them ml = NamedAttrsClass({'blobs': np.array([NamedAttrsClass({'data': np.array([0])})])}) embed_input(attrs, 1, 'biases', ml.blobs[0].data) return attrs