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 = MVN(graph, dict(
name=fbn.name + '/MVN_',
eps=fbn.eps,
eps_mode='outside_sqrt',
normalize_variance=1
))
mvn.attrs['old_infer'] = mvn.attrs['infer']
mvn.attrs['infer'] = __class__.infer
mul = Mul(graph, dict(operation='mul', name=fbn.name + '/Mul_'))
add = Add(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: Graph, node: Node):
prefix = node.name + '/InstanceNormalization'
mvn = MVN(graph, dict(name=prefix + '/MVN', eps=node.epsilon))
mul = Mul(graph, dict(name=prefix + '/Mul', axis=1))
add = Add(graph, dict(name=prefix + '/Add', axis=1))
new_subgraph = add.create_node([
mul.create_node(
[mvn.create_node([node.in_node(0)]),
node.in_node(1)]),
node.in_node(2)
])
return [new_subgraph.id]
def replace_sub_graph(graph: Graph, match: dict):
mvn = MVN(graph, dict(
name=match['truediv'].name + '/MVN_',
eps_mode='outside_sqrt',
normalize_variance=1
))
mvn.attrs['old_infer'] = mvn.attrs['infer']
mvn.attrs['infer'] = __class__.infer
mean_reduction = match['mean'].in_node(1)
variance_reduction = match['variance'].in_node(1)
pow2 = match['pow'].in_node(1)
eps = match['add'].in_node(0 if match['add'].in_node(0).id != match['variance'].id else 1)
new_subgraph = mvn.create_node([match['mean'].in_node(0), mean_reduction, variance_reduction, pow2, eps])
match['truediv'].replace_node(new_subgraph)
def replace_sub_graph(graph: Graph, match: dict):
mvn = MVN(
graph,
dict(name=match['truediv'].name + '/MVN_',
required_reduction_indices=[1, 2]
if graph.graph['layout'] == 'NHWC' else [2, 3]))
mvn.attrs['old_infer'] = mvn.attrs['infer']
mvn.attrs['infer'] = __class__.infer
mean_reduction = match['mean'].in_node(1)
variance_reduction = match['variance'].in_node(1)
pow2 = match['pow'].in_node(1)
eps = match['add'].in_node(
0 if match['add'].in_node(0).id != match['variance'].id else 1)
new_subgraph = mvn.create_node([
match['mean'].in_node(0), mean_reduction, variance_reduction, pow2,
eps
])
match['truediv'].replace_node(new_subgraph)
