""" 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 get_spatial_attr from mo.front.common.extractors.utils import layout_attrs from mo.front.extractor import FrontExtractorOp from mo.ops.pooling import Pooling class PoolingFrontExtractor(FrontExtractorOp): op = 'pooling' enabled = True @staticmethod def extract(node): proto_layer = node.pb param = proto_layer.pooling_param method = 'max' exclude_pad = 'true' kernel = [0, 0] stride = [1, 1] padding = [0, 0] global_pooling = False if hasattr(param, 'global_pooling') and param.global_pooling: global_pooling = param.global_pooling else: kernel = get_spatial_attr(kernel, 'kernel_size', 'kernel', param) padding = get_spatial_attr(padding, 'pad', 'pad', param) stride = get_spatial_attr(stride, 'stride', 'stride', param) if param.pool == 0: method = 'max' exclude_pad = 'true' elif param.pool == 1: method = 'avg' exclude_pad = 'false' else: raise ValueError('Unknown Pooling Method!') pooling_convention = 'full' # for Caffe rounding type should be ceil rt = 'ceil' if hasattr(param, 'ceil_mode') and not param.ceil_mode: # If pooling has ceil_mode and ceil_mode is False using floor for rounding shapes in partial_infer pooling_convention = 'valid' rt = 'floor' attrs = { 'window': np.array([1, 1, kernel[1], kernel[0]], dtype=np.int64), 'stride': np.array([1, 1, stride[1], stride[0]], dtype=np.int64), 'pad': np.array([[0, 0], [0, 0], [padding[1], padding[1]], [padding[0], padding[0]]], dtype=np.int64), 'pad_spatial_shape': np.array([[padding[1], padding[1]], [padding[0], padding[0]]], dtype=np.int64), 'pool_method': method, 'exclude_pad': exclude_pad, 'global_pool': global_pooling, 'output_spatial_shape': None, 'rounding_type': rt } attrs.update(layout_attrs()) attrs['pooling_convention'] = pooling_convention # update the attributes of the node Pooling.update_node_stat(node, attrs) return __class__.enabled