def test_proposal_ext_ideal_numbers(self, merge_attrs):
params = {
'feat_stride': 1,
'base_size': 16,
'min_size': 16,
'ratio': 1,
'scale': 2,
'pre_nms_topn': 6000,
'post_nms_topn': 300,
'nms_thresh': 0.7
}
merge_attrs.return_value = {**params}
fake_pl = FakeProposalProtoLayer(FakeMultiParam(params))
fake_node = FakeNode(fake_pl, None)
fake_node.graph.graph['cmd_params'] = FakeAttr(
generate_experimental_IR_V10=False)
ProposalFrontExtractor.extract(fake_node)
exp_res = {
'type': "Proposal",
'feat_stride': 1,
'base_size': 16,
'min_size': 16,
'ratio': 1,
'scale': 2,
'pre_nms_topn': 6000,
'post_nms_topn': 300,
'nms_thresh': 0.7,
'infer': ProposalOp.proposal_infer
}
for key in exp_res.keys():
self.assertEqual(fake_node[key], exp_res[key])
def test_proposal_ext_scale(self):
params = {
'param_str':
"'feat_stride': 16, 'scale': [1,2,3], 'ratio':[5, 6,7]"
}
fake_pl = FakeProposalPythonProtoLayer(FakeMultiParam(params))
fake_node = FakeNode(fake_pl, None)
fake_node.graph.graph['cmd_params'] = FakeAttr(
generate_experimental_IR_V10=False)
ProposalPythonFrontExtractor.extract(fake_node)
exp_res = {
'type': "Proposal",
'feat_stride': 16,
'base_size': 16,
'min_size': 16,
'ratio': [5, 6, 7],
'scale': [1, 2, 3],
'pre_nms_topn': 6000,
'post_nms_topn': 300,
'nms_thresh': 0.7,
'infer': ProposalOp.proposal_infer
}
for key in exp_res.keys():
self.assertEqual(fake_node[key], exp_res[key])
def test_nms_infer_v10_opset1(self):
self.graph.graph['cmd_params'] = FakeAttr(ir_version=10)
nms_node = Node(self.graph, 'nms')
nms_node['version'] = 'opset1'
NonMaxSuppression.infer(nms_node)
NonMaxSuppression.type_infer(nms_node)
self.assertTrue(np.array_equal(nms_node.out_port(0).data.get_shape(), [100, 3]))
self.assertTrue(nms_node.out_port(0).get_data_type() == np.int64)
def test_nms_infer_v7(self):
self.graph.graph['cmd_params'] = FakeAttr(generate_experimental_IR_V10=False, ir_version=7)
nms_node = Node(self.graph, 'nms')
nms_node['version'] = 'opset1'
NonMaxSuppression.infer(nms_node)
NonMaxSuppression.type_infer(nms_node)
self.assertTrue(np.array_equal(nms_node.out_port(0).data.get_shape(), [100, 3]))
self.assertTrue(nms_node.out_port(0).get_data_type() == np.int32)
def test_topk_infer_v10_opset1(self):
self.graph.graph['cmd_params'] = FakeAttr(ir_version=10)
topk_node = Node(self.graph, 'topk')
topk_node['version'] = 'opset1'
TopK.infer(topk_node)
TopK.type_infer(topk_node)
self.assertTrue(np.array_equal(topk_node.out_port(0).data.get_shape(), int64_array([20, 10, 4])))
self.assertTrue(np.array_equal(topk_node.out_port(1).data.get_shape(), int64_array([20, 10, 4])))
self.assertTrue(topk_node.out_port(0).get_data_type() == np.float32)
self.assertTrue(topk_node.out_port(1).get_data_type() == np.int32)
def test_topk_infer_v10_i32_opset3(self):
self.graph.graph['cmd_params'] = FakeAttr(
generate_experimental_IR_V10=True, ir_version=10)
topk_node = Node(self.graph, 'topk')
topk_node['version'] = 'opset3'
topk_node['index_element_type'] = np.int32
TopK.infer(topk_node)
TopK.type_infer(topk_node)
self.assertTrue(
np.array_equal(
topk_node.out_port(0).data.get_shape(),
int64_array([20, 10, 4])))
self.assertTrue(
np.array_equal(
topk_node.out_port(1).data.get_shape(),
int64_array([20, 10, 4])))
self.assertTrue(topk_node.out_port(0).get_data_type() == np.float32)
self.assertTrue(topk_node.out_port(1).get_data_type() == np.int32)