Files
openvino/model-optimizer/extensions/ops/TensorIterator_ops.py

104 lines
2.9 KiB
Python

"""
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.
"""
from mo.graph.graph import Node, Graph
from mo.ops.op import Op
# TODO: check all supported attributes in this file
class TensorIteratorInput(Op):
op = "TensorIteratorInput"
def __init__(self, graph: Graph, attrs: dict):
mandatory_props = {
'op': __class__.op,
'axis': None,
'start': None,
'end': None,
'stride': None,
'part_size': None,
'in_ports_count': 3,
'out_ports_count': 1,
'infer': TensorIteratorInput.input_infer,
}
super().__init__(graph, mandatory_props, attrs)
def supported_attrs(self):
return ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size']
@staticmethod
def input_infer(node: Node):
pass
class TensorIteratorOutput(Op):
op = "TensorIteratorOutput"
def __init__(self, graph: Graph, attrs: dict):
mandatory_props = {
'op': __class__.op,
'axis': None,
'start': None,
'end': None,
'stride': None,
'part_size': None,
'in_ports_count': 3,
'out_ports_count': 1,
'infer': TensorIteratorOutput.input_infer,
}
super().__init__(graph, mandatory_props, attrs)
def supported_attrs(self):
return ['external_port_id', 'internal_layer_id', 'internal_port_id', 'axis', 'start', 'stride', 'part_size']
@staticmethod
def input_infer(node: Node):
pass
class TensorIteratorCondition(Op):
op = "TensorIteratorCondition"
def __init__(self, graph: Graph, attrs: dict):
mandatory_props = {
'op': __class__.op,
'in_ports_count': 2,
'out_ports_count': 2,
'infer': TensorIteratorCondition.input_infer,
}
super().__init__(graph, mandatory_props, attrs)
@staticmethod
def input_infer(node: Node):
pass
class TensorIteratorBackEdge(Op):
op = 'TensorIteratorBackEdge'
def __init__(self, graph: Graph, attrs: dict):
mandatory_props = {
'op': __class__.op,
'in_ports_count': 3,
'out_ports_count': 1,
'infer': TensorIteratorBackEdge.input_infer,
}
super().__init__(graph, mandatory_props, attrs)
@staticmethod
def input_infer(node: Node):
pass