def replace_pattern(self, graph: Graph, match: dict):
node = match['op']
if (node.data_format != b'NHWC' or len(node.in_nodes()) != 5
or node.in_node(0).value is not None or # input
node.in_node(1).value is None or # scale
node.in_node(2).value is None or # offset
node.in_node(3).value is not None or # mean
node.in_node(4).value is not None or # variance
node.in_node(1).value.ndim != 1 or
node.in_node(2).value.ndim != 1):
return
scale_mul = Eltwise(
graph, dict(operation='mul', name=node.name + '/scale_mul_'))
shift_add = Eltwise(
graph, dict(operation='sum', name=node.name + '/shift_add_'))
mean_add = Eltwise(
graph, dict(operation='sum', name=node.name + '/mean_add_'))
variance_mul = Eltwise(
graph, dict(operation='mul', name=node.name + '/variance_mul_'))
mean_negate = Power(graph,
dict(scale=-1, name=node.name + '/mean_negate_'))
mean_arg = mean_add.create_node_with_data([
node.in_node(0),
mean_negate.create_node_with_data([node.in_node(3)])
])
variance_square = Power(
graph, dict(power=2, name=node.name + '/variance_square_'))
variance_denom = Power(
graph,
dict(shift=node.eps,
power=-0.5,
name=node.name + '/variance_denom_'))
variance_arg = variance_mul.create_node_with_data([
mean_arg,
variance_denom.create_node_with_data([node.in_node(4)])
])
shift_add.create_node_with_data([
scale_mul.create_node_with_data([variance_arg,
node.in_node(1)]),
node.in_node(2)
],
data_nodes=node.out_node())
node.graph.remove_node(node.id)
def replace_pattern(self, graph: Graph, match: dict):
node = match['minimum']
# Constant propagation case
if node.in_node(0).value is not None and node.in_node(1).value is not None:
return
negate_1 = Power(graph, dict(scale=-1, name=node.name + '/negate1_'))
negate_2 = Power(graph, dict(scale=-1, name=node.name + '/negate2_'))
maximum = Eltwise(graph, dict(operation='max', name=node.name + '/Max_'))
negate_output = Power(graph, dict(scale=-1, name=node.name + '/negate_out_'))
negate_output.create_node_with_data(
inputs=[maximum.create_node_with_data([negate_1.create_node_with_data([node.in_node(0)]),
negate_2.create_node_with_data([node.in_node(1)])])],
data_nodes=node.out_node())
# Delete minimum vertex
node.graph.remove_node(node.id)