def _create_sub(graph: Graph, input_1: Node, port_1: int, input_2: Node,
port_2: int):
negate = Power(graph, dict(scale=-1, name=input_2.name + '/negate_'))
add = Eltwise(graph, dict(operation='sum',
name=input_1.name + '/add_'))
out_node = add.create_node([(input_1, port_1),
negate.create_node([(input_2, port_2)])])
return out_node
def replace_op(self, graph: nx.MultiDiGraph, node: Node):
negate = Power(graph, dict(scale=-1, name=node.name + '/negate_'))
add = Eltwise(graph, dict(operation='sum', name=node.name + '/add_'))
out_node = add.create_node([
(node.in_node(0), node.in_edge(0)['out']),
negate.create_node([(node.in_node(1), node.in_edge(1)['out'])])
])
# Replace edge from out port 0 of the matched node with a edge from node out_node.id with port 0.
# The "explicit" version of the return value is: [(out_node.id, 0)])
return [out_node.id]
def replace_op(self, graph: Graph, node: Node):
out_node = node.in_node(0)
operation = node.operation
for ind in range(1, len(node.in_nodes())):
eltwise_op = Eltwise(
graph,
dict(operation=operation,
name=node.name + '/' + operation + '_' + str(ind)))
out_node = eltwise_op.create_node([out_node, node.in_node(ind)])
return [out_node.id]
def replace_sub_graph(self, graph: Graph, match: dict):
fbn = match['fbn']
input = fbn.in_node(0)
log.debug('Found potential MVN pattern after {} with name {}'.format(
input.op, input.name))
if input.id != match['mean'].in_node(
0).id or input.id != match['sqdiff'].in_node(0).id:
return
log.debug('Confirmed MVN pattern after {} with name {}'.format(
input.op, input.name))
MVN = Op.get_op_class_by_name('MVN')
mvn = MVN(
graph,
dict(name=fbn.name + '/MVN_',
eps=fbn.eps,
required_reduction_indices=[1, 2]
if fbn.data_format == b'NHWC' else [2, 3]))
mvn.attrs['old_infer'] = mvn.attrs['infer']
mvn.attrs['infer'] = __class__.infer
mul = Eltwise(graph, dict(operation='mul', name=fbn.name + '/Mul_'))
add = Eltwise(graph, dict(operation='sum', name=fbn.name + '/Add_'))
input_gamma = fbn.in_node(1)
input_beta = fbn.in_node(2)
mean_reduction = match['mean'].in_node(1)
variance_reduction = match['variance'].in_node(1)
new_subgraph = add.create_node([
mul.create_node([
mvn.create_node([input, mean_reduction, variance_reduction]),
input_gamma
]), input_beta
])
fbn.replace_node(new_subgraph)
def replace_op(self, graph: nx.MultiDiGraph, node: Node):
reciprocal = Power(
graph,
dict(scale=1,
power=np.float64(-1),
shift=0,
name=node.name + '/reciprocal_'))
mul = Eltwise(graph, dict(operation='mul', name=node.name + '/mul_'))
out_node = mul.create_node([
(node.in_node(0), node.in_edge(0)['out']),
reciprocal.create_node([(node.in_node(1), node.in_edge(1)['out'])])
])
# Replace edge from out port 0 of the matched node with a edge from node out_node.id with port 0.
# The "explicit" version of the return value is: [(out_node.id, 0)])
return [out_node.id]