""" Copyright (C) 2018-2020 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.graph.graph import Node, Graph from mo.ops.op import Op class TensorArray(Op): op = "TensorArrayV3" def __init__(self, graph: Graph, attrs: dict): mandatory_props = { 'type': None, 'op': __class__.op, 'infer': TensorArray.array_infer, } super().__init__(graph, mandatory_props, attrs) @staticmethod def array_infer(node: Node): size = node.in_node(0) assert size.value is not None # 0 port: handle if 0 in node.out_nodes().keys(): if node.has_valid('element_shape'): element_shape = node['element_shape'] else: element_shape = None out_node = node.out_node(0).id output_value = node.out_node(0).id node.graph.node[out_node]['value'] = np.array(output_value) output_shape = node.graph.node[out_node]['value'].shape node.graph.node[out_node]['shape'] = np.array(output_shape) node.graph.node[out_node]['element_shape'] = np.array(element_shape) node.graph.node[out_node]['size'] = size.value # 1 port flow if 1 in node.out_nodes().keys(): output_value = None out_node = node.out_node(1).id node.graph.node[out_node]['value'] = None if output_value is None else np.array(output_value) node.graph.node[out_node]['shape'] = np.array(output_shape)