Ejemplo n.º 1
0
    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
Ejemplo n.º 2
0
    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))