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"""
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.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': __class__.op,
'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)