def emit_Pool()

in mmdnn/conversion/coreml/coreml_emitter.py [0:0]

• 56 lines of code
• 6 McCabe index (conditional complexity)

    def emit_Pool(self, IR_node):
        """
        Convert pooling layer to coreml.
        """
        # Get input and output names
        input_name = self.IR_graph.get_node(IR_node.in_edges[0]).real_name

        # Pooling layer type
        pooling_type = IR_node.get_attr('pooling_type')
        if pooling_type == 'MAX':
            layer_type_str = 'MAX'
        elif pooling_type == 'AVG':
            layer_type_str = 'AVERAGE'
        else:
            raise TypeError("Pooling type %s not supported" % pooling_type)


        # if it's global, set the global flag
        global_pooling = IR_node.get_attr('global_pooling', False)
        dim = len(IR_node.get_attr('strides')) - 2


        if global_pooling:
            if dim == 2:



                stride_height, stride_width = tuple(IR_node.get_attr('strides')[1:-1])
                height, width = 1, 1

                # TODO  global pooling modification

                # Padding
                padding = self._get_padding(IR_node)

                if isinstance(padding, list):
                    padding_type = "VALID"
                    # see protobuf
                    padding_top, padding_left, padding_bottom, padding_right = padding[1], padding[2], padding[5], padding[6]
                else:
                    padding_type = "SAME"
                    padding_top, padding_left, padding_bottom, padding_right = 0, 0, 0, 0


            elif dim == 1:
                raise NotImplementedError()
                global_pooling = False
                _, width, channels = keras_layer.input_shape
                height = 1
                stride_height, stride_width = height, width
                padding_type = 'VALID'
            else:
                raise NotImplementedError()

        else:

            height, width = tuple(IR_node.get_attr('kernel_shape')[1:-1])
            stride_height, stride_width = tuple(IR_node.get_attr('strides')[1:-1])

            # Padding
            padding = self._get_padding(IR_node)
            if isinstance(padding, list):

                padding_type = "VALID"
                # see protobuf
                padding_top, padding_left, padding_bottom, padding_right = padding[1], padding [2], padding[5], padding [6]
            else:
                padding_type = "SAME"
                padding_top, padding_left, padding_bottom, padding_right = 0, 0, 0, 0


        self.builder.add_pooling(name=IR_node.name,
                                    height=height,
                                    width=width,
                                    stride_height=stride_height,
                                    stride_width=stride_width,
                                    layer_type=layer_type_str,
                                    padding_type=padding_type,
                                    padding_top= padding_top,
                                    padding_left= padding_left,
                                    padding_bottom= padding_bottom,
                                    padding_right= padding_right,
                                    input_name=input_name,
                                    output_name=IR_node.name,
                                    exclude_pad_area=True,
                                    is_global=global_pooling)