83 lines
2.6 KiB
Python
83 lines
2.6 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.
|
|
"""
|
|
import numpy as np
|
|
|
|
from extensions.ops.RNN import rnn_infer
|
|
from mo.graph.graph import Node, Graph
|
|
from mo.ops.op import Op
|
|
|
|
|
|
class GRU(Op):
|
|
op = 'GRU'
|
|
|
|
def __init__(self, graph: Graph, attrs: dict):
|
|
mandatory_props = {
|
|
'type': 'RNNSequence', # should be never emitted to IR; for debugging purposes
|
|
'op': __class__.op,
|
|
'blobs_wrb': False,
|
|
'has_num_directions': False,
|
|
'direction': 'forward',
|
|
'infer': __class__.infer,
|
|
'multiplier': 3,
|
|
'multilayers': False,
|
|
'gate_order': np.array([0, 1, 2]), # TODO: change it later
|
|
'normalized': False,
|
|
|
|
'activation_alpha': None,
|
|
'activation_beta': None,
|
|
'activations': None,
|
|
'clip': None,
|
|
'linear_before_reset': None,
|
|
'in_ports_count': 6,
|
|
'out_ports_count': 2,
|
|
}
|
|
super().__init__(graph, mandatory_props, attrs)
|
|
|
|
@staticmethod
|
|
def supported_attrs():
|
|
return [
|
|
'hidden_size', # number of the elements in hidden cell size
|
|
'direction', # one of 'forward', 'reverse', or 'bidirectional'
|
|
'axis',
|
|
|
|
'activation_alpha',
|
|
'activation_beta',
|
|
'activations',
|
|
'clip',
|
|
'linear_before_reset',
|
|
]
|
|
|
|
def backend_attrs(self):
|
|
return [
|
|
'hidden_size', # number of the elements in hidden cell size
|
|
'direction', # one of 'forward', 'reverse', or 'bidirectional'
|
|
'axis',
|
|
|
|
'activation_alpha',
|
|
'activation_beta',
|
|
('activations', lambda node: ','.join(node.activations) if node.activations is not None else None),
|
|
'clip',
|
|
'linear_before_reset',
|
|
]
|
|
|
|
@staticmethod
|
|
def infer(node: Node):
|
|
assert len(node.in_nodes()) >= 3 # X, W and R
|
|
assert len(node.in_nodes()) <= 5
|
|
assert len(node.out_nodes()) <= 2
|
|
|
|
rnn_infer(node, [1])
|