def placeholder_scales(self, placeholder: Node):
"""
Helper function to get scales for prior boxes out of input image size:
[1 / im_width, 1 / im_height, 1 / im_width, 1 / im_height]
"""
graph = placeholder.graph
name = placeholder.soft_get('name', placeholder.id)
shape_value = placeholder.soft_get('shape', None)
assert shape_value is not None, \
"[ {} replacer ] Placeholder `{}` should have shape attribute".format(self.replacement_id, name)
assert isinstance(shape_value, np.ndarray), \
"[ {} replacer ] Placeholder `{}` shape attribute should be np.ndarray".format(self.replacement_id, name)
assert shape_value.size == 4, \
"[ {} replacer ] Placeholder `{}` should be 4D. Shape: {}".format(self.replacement_id, name, shape_value)
shape = Shape(graph, {'name': 'input_image_shape'}).create_node()
shape.in_port(0).connect(placeholder.out_port(0))
begin = Const(graph, {'value': int64_array([1])}).create_node()
end = Const(graph, {'value': int64_array([3])}).create_node()
stride = Const(graph, {'value': int64_array([1])}).create_node()
spatial = StridedSlice(graph, {'name': name + '/get_h_w', 'begin_mask': int64_array([1]),
'end_mask': int64_array([1]), 'new_axis_mask': int64_array([0]),
'shrink_axis_mask': int64_array([0]), 'ellipsis_mask': int64_array([0])}).create_node()
spatial.in_port(0).connect(shape.out_port(0))
spatial.in_port(1).connect(begin.out_port(0))
spatial.in_port(2).connect(end.out_port(0))
spatial.in_port(3).connect(stride.out_port(0))
power = Const(graph, {'value': float32_array([-1.])}).create_node()
spatial_scale = Pow(graph, {}).create_node()
spatial_scale.in_port(0).connect(spatial.out_port(0))
spatial_scale.in_port(1).connect(power.out_port(0))
# Power `type_infer` requires inputs to have equal data type
convert_to_fp32 = Cast(graph, {'dst_type': np.float32}).create_node()
spatial_scale.in_port(0).get_connection().insert_node(convert_to_fp32)
order = Const(graph, {'value': int64_array([1, 0])}).create_node()
axis_const = Const(graph, {'value': int64_array(0)}).create_node()
reverse = Gather(graph, {}).create_node()
reverse.in_port(0).connect(spatial_scale.out_port(0))
reverse.in_port(1).connect(order.out_port(0))
axis_const.out_port(0).connect(reverse.in_port(2))
priors_scale_node = Concat(graph, {'axis': 0, 'in_ports_count': 2}).create_node()
priors_scale_node.add_input_port(0, skip_if_exist=True)
priors_scale_node.add_input_port(1, skip_if_exist=True)
priors_scale_node.in_port(0).connect(reverse.out_port(0))
priors_scale_node.in_port(1).connect(reverse.out_port(0))
return priors_scale_node
def replace_sub_graph(self, graph: Graph, match: dict):
node = match['op']
name = node.soft_get('name', node.id)
assert node.has_valid('axis')
axis = Const(graph, {'name': name + '/axis', 'value': int64_array(node.axis)}).create_node()
gather = Gather(graph, {'name': name}).create_node()
node.in_port(0).get_connection().set_destination(gather.in_port(0))
node.in_port(1).get_connection().set_destination(gather.in_port(1))
axis.out_port(0).connect(gather.in_port(2))
node.out_port(0).get_connection().set_source(gather.out_port(0))
def get_shape_values_by_indices_node(shape_node: Node,
indices_node: Node) -> Node:
"""
The function returns a node that produces values of the specified indices node of the input node 'shape_node'
:param shape_node: the node of 1D output shape to get elements from
:param indices_node: the node of 1D output shape with the list of element indices to get
:return: node producing required elements of the node
"""
graph = shape_node.graph
axis = Const(graph, {
'value': int64_array(0),
'name': shape_node.name + '/Axis'
}).create_node()
gather_node = Gather(graph, {
'name': shape_node.name + '/Gather'
}).create_node()
shape_node.out_port(0).connect(gather_node.in_port(0))
indices_node.out_port(0).connect(gather_node.in_port(1))
axis.out_port(0).connect(gather_node.in_port(2))
return gather_node
