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How to use _create_sub method in localstack

Best Python code snippet using localstack_python

RetinaNetFilteredDetectionsReplacement.py

Source:RetinaNetFilteredDetectionsReplacement.py

...33    equal to "caffe.PriorBoxParameter.CORNER" produces the same result as the post-processing in the original topology.34    """35    replacement_id = 'RetinaNetFilteredDetectionsReplacement'36    @staticmethod37    def _create_sub(graph: nx.MultiDiGraph, input_1: Node, port_1: int, input_2: Node, port_2: int):38        negate = Power(graph, dict(scale=-1, name=input_2.name + '/negate_'))39        add = Eltwise(graph, dict(operation='sum', name=input_1.name + '/add_'))40        out_node = add.create_node([(input_1, port_1), negate.create_node([(input_2, port_2)])])41        return out_node42    def output_edges_match(self, graph: nx.DiGraph, match: SubgraphMatch, new_sub_graph: dict):43        return {match.output_node(0)[0].id: new_sub_graph['detection_output_node'].id}44    def nodes_to_remove(self, graph: nx.MultiDiGraph, match: SubgraphMatch):45        new_nodes_to_remove = match.matched_nodes_names()46        new_nodes_to_remove.remove(match.single_input_node(0)[0].id)47        new_nodes_to_remove.remove(match.single_input_node(1)[0].id)48        new_nodes_to_remove.remove(match.single_input_node(2)[0].id)49        return new_nodes_to_remove50    def generate_sub_graph(self, graph: nx.MultiDiGraph, match: SubgraphMatch):51        reshape_classes_op = Reshape(graph, {'dim': np.array([0, -1])})52        reshape_classes_node = reshape_classes_op.create_node([match.single_input_node(1)[0]],53                                                              dict(name='do_reshape_classes'))54        priors_node = match.single_input_node(2)[0]55        placeholder = [Node(graph, node_id) for node_id in graph.nodes() if Node(graph, node_id).op == 'Placeholder'][0]56        im_height = placeholder.shape[1]57        im_width = placeholder.shape[2]58        # scale prior boxes to the [0, 1] interval59        priors_scale_const_node = Const(graph, {'value': np.array([1 / im_width,60                                                                   1 / im_height,61                                                                   1 / im_width,62                                                                   1 / im_height])}).create_node([])63        priors_scale_node = Eltwise(graph, {'name': 'scale_priors', 'operation': 'mul'}).create_node(64            [priors_node, priors_scale_const_node])65        # calculate prior boxes widths and heights66        split_node = SplitV(graph, {'axis': 2, 'size_splits': [1, 1, 1, 1]}).create_node([priors_scale_node])67        priors_width_node = __class__._create_sub(graph, split_node, 2, split_node, 0)68        priors_height_node = __class__._create_sub(graph, split_node, 3, split_node, 1)69        # concat weights and heights into a single tensor and multiple with the box coordinates regression values70        concat_width_height_node = Concat(graph, {'name': 'concat_priors_width_height', 'axis': -1}).create_node(71            [priors_width_node, priors_height_node, priors_width_node, priors_height_node])72        applied_width_height_regressions_node = Eltwise(graph, {'name': 'final_regressions', 'operation': 'mul'}). \73            create_node([concat_width_height_node, match.single_input_node(0)[0]])74        # reshape to 2D tensor as Inference Engine Detection Output layer expects75        reshape_regression_op = Reshape(graph, {'dim': np.array([0, -1])})76        reshape_regression_node = reshape_regression_op.create_node([applied_width_height_regressions_node],77                                                                    {'name': 'reshape_regression'})78        detection_output_op = DetectionOutput(graph, match.custom_replacement_desc.custom_attributes)79        detection_output_op.attrs['old_infer'] = detection_output_op.attrs['infer']80        detection_output_op.attrs['infer'] = __class__.do_infer81        detection_output_node = detection_output_op.create_node(82            [reshape_regression_node, reshape_classes_node, priors_scale_node],...

menu.py

Source:menu.py

...19    def _close_sub_janel(self):20        self.sub_window.destroy()21        self.sub_window = None22        self.sub_menu = None23    def _create_sub(self, text, function):24        if self.sub_window is not None:25            self.sub_window.lift()26        else:27            self.sub_window = front_page("200x200", self._close_sub_janel, self)28            self.sub_menu = SubMenu(text, function, self.sub_window)29    def _button_create(self):30        self._create_sub((31            "Create Room",32            "Name Player: ",33            "Name Room: ",34            "Password: "35        ), self.intergame.game_to_server.create_room)36    def _button_enter(self):37        self._create_sub((38            "Enter Room",39            "Name Player: ",40            "Id Room: ",41            "Password: "42        ), self.intergame.game_to_server.enter_room)43    def destroy(self):44        if self.sub_window is not None:45            self.sub_window.destroy()46        self.label = self.button_create = self.button_enter \47            = self.sub_window = self.sub_menu = None...

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