Yegor Kruglovandyegor.kruglov
abb1ca657e
* implement argmin extractors * reconsidering argmax to topk * arg ops refactoring * rename ArgMaxToTopK * added unittests * update docs * move unittest file to new folder * conversations resolving * revert changes with argmax.py, move argmin op to a new file * rename ArgMaxSqueeze * updated BOM file * little fix * code refactoring in ArgMaxOp, updated unittests Co-authored-by: yegor.kruglov <ykruglov@nnlvdp-mkaglins.inn.intel.com>
139 lines
5.5 KiB
Python
139 lines
5.5 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import unittest
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import numpy as np
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from extensions.ops.argmax import arg_ops_infer
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from mo.graph.graph import Node
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from unit_tests.utils.graph import build_graph
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nodes_attributes = {
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'op_input': {'kind': 'op', 'op': 'Parameter'},
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'node_1': {'kind': 'data'},
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'argmax': {'op': 'ArgMax', 'kind': 'op'},
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'node_3': {'kind': 'data', 'value': None},
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'op_output': {'kind': 'op', 'op': 'Result'}
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}
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class TestArgMaxOp(unittest.TestCase):
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def test_caffe_argmax_axis(self):
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graph = build_graph(nodes_attributes,
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[
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('op_input', 'node_1'),
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('node_1', 'argmax'),
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('argmax', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3, 1025, 2049])},
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'argmax': {
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'out_max_val': True,
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'top_k': 100,
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'axis': 2
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}
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})
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argmax_node = Node(graph, 'argmax')
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arg_ops_infer(argmax_node)
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exp_shape = np.array([1, 3, 100, 2049])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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def test_caffe_argmax_axis_negative(self):
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graph = build_graph(nodes_attributes,
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[
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('op_input', 'node_1'),
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('node_1', 'argmax'),
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('argmax', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3, 1025, 2049])},
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'argmax': {
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'out_max_val': True,
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'top_k': 100,
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'axis': -1
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}
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})
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argmax_node = Node(graph, 'argmax')
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arg_ops_infer(argmax_node)
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exp_shape = np.array([1, 3, 1025, 100])
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res_shape = graph.node['node_3']['shape']
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self.assertEqual(argmax_node.axis, 3)
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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def test_caffe_argmax_no_axis(self):
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graph = build_graph(nodes_attributes,
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[
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('op_input', 'node_1'),
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('node_1', 'argmax'),
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('argmax', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3, 1025, 2049])},
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'argmax': {
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'out_max_val': True,
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'top_k': 100
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}
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})
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argmax_node = Node(graph, 'argmax')
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arg_ops_infer(argmax_node)
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exp_shape = np.array([1, 2, 100, 1])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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def test_caffe_argmax_extend_shape(self):
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graph = build_graph(nodes_attributes,
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[
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('op_input', 'node_1'),
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('node_1', 'argmax'),
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('argmax', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3])},
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'argmax': {
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'out_max_val': True,
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'top_k': 100
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}
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})
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argmax_node = Node(graph, 'argmax')
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arg_ops_infer(argmax_node)
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exp_shape = np.array([1, 2, 100])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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def test_caffe_argmax_out_max_val_false(self):
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graph = build_graph(nodes_attributes,
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[
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('op_input', 'node_1'),
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('node_1', 'argmax'),
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('argmax', 'node_3'),
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('node_3', 'op_output')
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],
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{'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3])},
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'argmax': {
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'out_max_val': False,
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'top_k': 100
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}
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})
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argmax_node = Node(graph, 'argmax')
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arg_ops_infer(argmax_node)
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exp_shape = np.array([1, 1, 100])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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