[MO][Opset13] NMSRotated-13 support in MO IR Reader (#20354)
* nms_rotated mo ir read init * Fix type infer and clean up * Update tests * Update tests * update package BOM file * Update type_infer * Avoid files collision in tests --------- Co-authored-by: Michal Lukaszewski <michal.lukaszewski@intel.com>
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Katarzyna Mitrus
GitHub
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@ -934,6 +934,7 @@ openvino/tools/mo/ops/mxfft.py
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openvino/tools/mo/ops/mxrepeat.py
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openvino/tools/mo/ops/mxrepeat.py
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openvino/tools/mo/ops/mxreshape.py
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openvino/tools/mo/ops/mxreshape.py
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openvino/tools/mo/ops/NextIteration.py
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openvino/tools/mo/ops/NextIteration.py
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openvino/tools/mo/ops/nms_rotated.py
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openvino/tools/mo/ops/non_max_suppression.py
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openvino/tools/mo/ops/non_max_suppression.py
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openvino/tools/mo/ops/non_zero.py
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openvino/tools/mo/ops/non_zero.py
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openvino/tools/mo/ops/normalize.py
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openvino/tools/mo/ops/normalize.py
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79
tools/mo/openvino/tools/mo/ops/nms_rotated.py
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79
tools/mo/openvino/tools/mo/ops/nms_rotated.py
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# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import logging as log
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import numpy as np
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from openvino.tools.mo.front.common.partial_infer.utils import shape_array, dynamic_dimension_value
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from openvino.tools.mo.front.extractor import bool_to_str
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from openvino.tools.mo.graph.graph import Node, Graph
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from openvino.tools.mo.middle.passes.convert_data_type import np_data_type_to_destination_type
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from openvino.tools.mo.ops.op import Op
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from openvino.tools.mo.utils.error import Error
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class NMSRotated(Op):
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op = 'NMSRotated'
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enabled = False
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def __init__(self, graph: Graph, attrs: dict):
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mandatory_props = {
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'type': self.op,
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'op': self.op,
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'version': 'opset13',
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'infer': self.infer,
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'type_infer': self.type_infer,
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'sort_result_descending': True,
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'output_type': np.int64,
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'clockwise': True,
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'in_ports_count': 5,
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'out_ports_count': 3,
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}
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super().__init__(graph, mandatory_props, attrs)
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def backend_attrs(self):
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return [('sort_result_descending', lambda node: bool_to_str(node, 'sort_result_descending')),
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'output_type',
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('clockwise', lambda node: bool_to_str(node, 'clockwise'))]
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def supported_attrs(self):
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return [
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'sort_result_descending',
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'output_type',
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'clockwise',
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]
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@staticmethod
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def infer(node: Node):
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num_of_inputs = len(node.in_ports())
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opset = node.get_opset()
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required_num_inputs = 5
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input_msg_fmt = 'NMSRotated node {} from {} must have {} inputs'
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node_name = node.soft_get('name', node.id)
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inputs_msg = input_msg_fmt.format(
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node_name, opset, required_num_inputs)
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assert num_of_inputs == required_num_inputs, inputs_msg
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node.out_port(0).data.set_shape(
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shape_array([dynamic_dimension_value, 3]))
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num_of_outputs = len(
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[port for port in node.out_ports().values() if not port.disconnected()])
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if num_of_outputs >= 2 and node.has_port('out', 1):
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node.out_port(1).data.set_shape(
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shape_array([dynamic_dimension_value, 3]))
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if num_of_outputs >= 3 and node.has_port('out', 2):
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node.out_port(2).data.set_shape(shape_array([1]))
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@staticmethod
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def type_infer(node: Node):
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node.out_port(1).set_data_type(np.float32)
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if node.has_valid('output_type') and node['output_type'].lower() == 'i32':
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node.out_port(0).set_data_type(np.int32)
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node.out_port(2).set_data_type(np.int32)
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else:
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node.out_port(0).set_data_type(np.int64)
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node.out_port(2).set_data_type(np.int64)
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@ -357,3 +357,103 @@ class TestOps(unittest.TestCase):
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self.assertEqual(loaded_model.get_output_element_type(0), Type.i64)
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self.assertEqual(loaded_model.get_output_element_type(0), Type.i64)
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self.assertEqual(loaded_model.get_output_partial_shape(
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self.assertEqual(loaded_model.get_output_partial_shape(
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0), PartialShape([2, 3]))
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0), PartialShape([2, 3]))
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def test_nms_rotated_13_attrs_false_i32(self):
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boxes_shape = [1, 100, 5]
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scores_shape = [1, 2, 100]
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max_output_boxes_val = 5
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iou_threshold_val = 0.5
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score_threshold_val = 0.4
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boxes_parameter = opset13.parameter(
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boxes_shape, name="Boxes", dtype=np.float32)
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scores_parameter = opset13.parameter(
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scores_shape, name="Scores", dtype=np.float32)
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max_output_boxes = opset13.constant([max_output_boxes_val], np.int64)
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iou_threshold = opset13.constant([iou_threshold_val], np.float32)
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score_threshold = opset13.constant([score_threshold_val], np.float32)
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sort_result_descending = False
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output_type = "i32"
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clockwise = False
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node = opset13.nms_rotated(boxes_parameter, scores_parameter, max_output_boxes, iou_threshold,
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score_threshold, sort_result_descending, output_type, clockwise)
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model = Model(node, [boxes_parameter, scores_parameter])
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graph, loaded_model = TestOps.check_graph_can_save(
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model, 'nms_rotated_model_1')
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ir_node = graph.get_op_nodes(op="NMSRotated")[0]
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self.assertListEqual(ir_node.out_port(
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0).data.get_shape().tolist(), [None, 3])
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self.assertListEqual(ir_node.out_port(
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1).data.get_shape().tolist(), [None, 3])
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self.assertListEqual(ir_node.out_port(
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2).data.get_shape().tolist(), [1])
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self.assertEqual(ir_node["version"], "opset13")
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self.assertEqual(ir_node['sort_result_descending'], False)
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self.assertEqual(ir_node['output_type'], "i32")
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self.assertEqual(ir_node['clockwise'], False)
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self.assertEqual(loaded_model.get_output_element_type(0), Type.i32)
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self.assertEqual(loaded_model.get_output_element_type(1), Type.f32)
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self.assertEqual(loaded_model.get_output_element_type(2), Type.i32)
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self.assertEqual(loaded_model.get_output_partial_shape(
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0), PartialShape([Dimension(-1, 10), 3]))
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self.assertEqual(loaded_model.get_output_partial_shape(
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1), PartialShape([Dimension(-1, 10), 3]))
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self.assertEqual(loaded_model.get_output_partial_shape(
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2), PartialShape([1]))
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def test_nms_rotated_13_attrs_true_i64(self):
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boxes_shape = [1, 100, 5]
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scores_shape = [1, 3, 100]
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max_output_boxes_val = 5
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iou_threshold_val = 0.5
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score_threshold_val = 0.4
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boxes_parameter = opset13.parameter(
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boxes_shape, name="Boxes", dtype=np.float32)
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scores_parameter = opset13.parameter(
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scores_shape, name="Scores", dtype=np.float32)
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max_output_boxes = opset13.constant([max_output_boxes_val], np.int64)
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iou_threshold = opset13.constant([iou_threshold_val], np.float32)
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score_threshold = opset13.constant([score_threshold_val], np.float32)
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sort_result_descending = True
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output_type = "i64"
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clockwise = True
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node = opset13.nms_rotated(boxes_parameter, scores_parameter, max_output_boxes, iou_threshold,
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score_threshold, sort_result_descending, output_type, clockwise)
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model = Model(node, [boxes_parameter, scores_parameter])
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graph, loaded_model = TestOps.check_graph_can_save(
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model, 'nms_rotated_model_2')
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ir_node = graph.get_op_nodes(op="NMSRotated")[0]
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self.assertListEqual(ir_node.out_port(
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0).data.get_shape().tolist(), [None, 3])
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self.assertListEqual(ir_node.out_port(
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1).data.get_shape().tolist(), [None, 3])
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self.assertListEqual(ir_node.out_port(
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2).data.get_shape().tolist(), [1])
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self.assertEqual(ir_node["version"], "opset13")
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self.assertEqual(ir_node['sort_result_descending'], True)
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self.assertEqual(ir_node['output_type'], "i64")
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self.assertEqual(ir_node['clockwise'], True)
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self.assertEqual(loaded_model.get_output_element_type(0), Type.i64)
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self.assertEqual(loaded_model.get_output_element_type(1), Type.f32)
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self.assertEqual(loaded_model.get_output_element_type(2), Type.i64)
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self.assertEqual(loaded_model.get_output_partial_shape(
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0), PartialShape([Dimension(-1, 15), 3]))
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self.assertEqual(loaded_model.get_output_partial_shape(
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1), PartialShape([Dimension(-1, 15), 3]))
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self.assertEqual(loaded_model.get_output_partial_shape(
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2), PartialShape([1]))
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