Evgeny Lazarev
f3d1aa6490
* Removed test-generator from all MO requirement files except the dev one * Moved all MO unit tests files to a separate directory * Added __init__.py files to the tests directory. Fixed importing paths for some unit tests * Fixed imports in all unit tests. Moved all unit test related files from the MO code to the dedicated directory * Renamed directory with unit test utils * Updated imports in unit tests
268 lines
17 KiB
Python
268 lines
17 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
|
|
import unittest
|
|
|
|
import numpy as np
|
|
from generator import generator, generate
|
|
|
|
from extensions.ops.interpolate import Interpolate
|
|
from mo.front.common.partial_infer.utils import int64_array
|
|
from mo.graph.graph import Node
|
|
from unit_tests.utils.graph import build_graph
|
|
|
|
|
|
graph_node_attrs_without_axes = {
|
|
'input': {'type': 'Parameter', 'kind': 'op'},
|
|
'input_data': {'kind': 'data', 'shape': None, 'value': None},
|
|
'sizes': {'type': 'Const', 'kind': 'op', 'shape': None, 'value': None},
|
|
'sizes_data': {'kind': 'data', 'shape': None, 'value': None},
|
|
'scales': {'type': 'Const', 'kind': 'op', 'shape': None, 'value': None},
|
|
'scales_data': {'kind': 'data', 'shape': None, 'value': None},
|
|
'interpolate': {
|
|
'type': 'Interpolate', 'kind': 'op', 'mode': 'nearest', 'shape_calculation_mode': 'sizes',
|
|
'coordinate_transformation_mode': 'half_pixel', 'version': 'opset4',
|
|
'nearest_mode': 'round_prefer_floor', 'antialias': 0,
|
|
},
|
|
'interpolate_data': {'kind': 'data', 'value': None, 'shape': None},
|
|
'op_output': {'kind': 'op', 'op': 'Result'},
|
|
}
|
|
|
|
graph_edges_without_axes = [
|
|
('input', 'input_data'),
|
|
('sizes', 'sizes_data'),
|
|
('scales', 'scales_data'),
|
|
('input_data', 'interpolate', {'in': 0}),
|
|
('sizes_data', 'interpolate', {'in': 1}),
|
|
('scales_data', 'interpolate', {'in': 2}),
|
|
('interpolate', 'interpolate_data'),
|
|
('interpolate_data', 'op_output'),
|
|
]
|
|
|
|
|
|
graph_nodes_attrs = {
|
|
'input': {'type': 'Parameter', 'kind': 'op'},
|
|
'input_data': {'kind': 'data', 'shape': None, 'value': None},
|
|
'sizes': {'type': 'Const', 'kind': 'op', 'shape': None, 'value': None},
|
|
'sizes_data': {'kind': 'data', 'shape': None, 'value': None},
|
|
'scales': {'type': 'Const', 'kind': 'op', 'shape': None, 'value': None},
|
|
'scales_data': {'kind': 'data', 'shape': None, 'value': None},
|
|
'axes': {'type': 'Const', 'kind': 'op', 'shape': None, 'value': None},
|
|
'axes_data': {'kind': 'data', 'shape': None, 'value': None},
|
|
'interpolate': {
|
|
'type': 'Interpolate', 'kind': 'op', 'mode': 'nearest', 'shape_calculation_mode': 'sizes',
|
|
'coordinate_transformation_mode': 'half_pixel', 'version': 'opset4',
|
|
'nearest_mode': 'round_prefer_floor', 'antialias': 0,
|
|
},
|
|
'interpolate_data': {'kind': 'data', 'value': None, 'shape': None},
|
|
'op_output': {'kind': 'op', 'op': 'Result'},
|
|
}
|
|
|
|
graph_edges = [
|
|
('input', 'input_data'),
|
|
('sizes', 'sizes_data'),
|
|
('scales', 'scales_data'),
|
|
('axes', 'axes_data'),
|
|
('input_data', 'interpolate', {'in': 0}),
|
|
('sizes_data', 'interpolate', {'in': 1}),
|
|
('scales_data', 'interpolate', {'in': 2}),
|
|
('axes_data', 'interpolate', {'in': 3}),
|
|
('interpolate', 'interpolate_data'),
|
|
('interpolate_data', 'op_output'),
|
|
]
|
|
|
|
|
|
@generator
|
|
class TestInterpolateOp(unittest.TestCase):
|
|
@generate(*[([0], [0], [1, 3, 100, 200], [1, 3, 350, 150], [350, 150], [3.5, 150 / 200], [2, 3]),
|
|
([0, 3, 10, 10], [0], [16, 7, 190, 400], [8, 10, 390, 600],
|
|
[8, 390, 600], [0.5, 390 / 200, 600 / 410], [0, 2, 3]),
|
|
([10, 5, 0, 10], [0, 4, 16, 18], [4, 33, 1024, 8000], [56, 42, 520, 8028],
|
|
[56, 520], [4.0, 0.5], [0, 2]),
|
|
([0], [0], [1, 16, 85, 470, 690], [20, 16, 40, 470, 1380],
|
|
[20, 40, 1380], [20.0, 40.0 / 85.0, 1380.0 / 690.0], [0, 2, 4]),
|
|
([4, 3, 11, 22, 5], [1, 3, 4, 8, 5], [1, 16, 85, 470, 690], [60, 22, 430, 500, 345],
|
|
[60, 430, 345], [10.0, 4.3, 345.0 / 700.0], [0, 2, 4]),
|
|
([0], [0], [5, 77, 444, 88, 6050], [100, 308, 4440, 44, 6050],
|
|
[100, 308, 4440, 44], [20.0, 4.0, 10.0, 0.5], [0, 1, 2, 3]),
|
|
([0], [0], [1, 100, 200], [1, 350, 150], [350, 150], [3.5, 150 / 200], [1, 2]),
|
|
([0, 3, 10], [0], [16, 7, 190], [8, 10, 390], [8, 390], [0.5, 390 / 200], [0, 2]),
|
|
([10, 0, 10], [0, 16, 18], [4, 1024, 8000], [56, 520, 8028], [56, 520], [4.0, 0.5], [0, 1]),
|
|
([0], [0], [1, 690], [20, 1380], [20, 1380], [20.0, 1380.0 / 690.0], [0, 1]),
|
|
([4, 3, 11, 22, 5, 0], [1, 3, 4, 8, 5, 0], [1, 16, 85, 470, 690, 349], [60, 22, 430, 500, 345, 349],
|
|
[60, 430, 345], [10.0, 4.3, 345.0 / 700.0], [0, 2, 4])
|
|
])
|
|
def test_interpolate4_using_sizes(self, pads_begin, pads_end, input_shape, output_shape, sizes, scales, axes):
|
|
graph = build_graph(nodes_attrs=graph_nodes_attrs,
|
|
edges=graph_edges,
|
|
update_attributes={
|
|
'input_data': {'shape': input_shape},
|
|
'sizes': {'shape': int64_array(sizes).shape, 'value': int64_array(sizes)},
|
|
'sizes_data': {'shape': int64_array(sizes).shape, 'value': int64_array(sizes)},
|
|
'scales': {'shape': np.array(scales).shape, 'value': np.array(scales)},
|
|
'scales_data': {'shape': np.array(scales).shape, 'value': np.array(scales)},
|
|
'axes': {'shape': int64_array(axes).shape, 'value': int64_array(axes)},
|
|
'axes_data': {'shape': int64_array(axes).shape, 'value': int64_array(axes)},
|
|
'interpolate': {'pads_begin': int64_array(pads_begin),
|
|
'pads_end': int64_array(pads_end)}
|
|
})
|
|
|
|
node = Node(graph, 'interpolate')
|
|
tested_class = Interpolate(graph=graph, attrs=node.attrs())
|
|
tested_class.infer(node)
|
|
|
|
msg = "Interpolate-4 infer failed for case: sizes={}, scales={}, pads_begin={}, pads_end={}, axes={}," \
|
|
" expected_shape={}, actual_shape={}"
|
|
|
|
self.assertTrue(np.array_equal(graph.node['interpolate_data']['shape'], int64_array(output_shape)),
|
|
msg.format(sizes, scales, pads_begin, pads_end, axes, output_shape,
|
|
graph.node['interpolate_data']['shape']))
|
|
|
|
@generate(*[([0], [0], [1, 3, 100, 200], [1, 3, 350, 150], [350, 150], [3.5, 150 / 200], [2, 3]),
|
|
([0, 3, 10, 10], [0], [16, 7, 190, 400], [8, 10, 390, 600],
|
|
[8, 390, 600], [0.5, 390 / 200, 600 / 410], [0, 2, 3]),
|
|
([10, 5, 0, 10], [0, 4, 16, 18], [4, 33, 1024, 8000], [56, 42, 520, 8028],
|
|
[56, 520], [4.0, 0.5], [0, 2]),
|
|
([0], [0], [1, 16, 85, 470, 690], [20, 16, 40, 470, 1380],
|
|
[20, 40, 1380], [20.0, 40.0 / 85.0, 1380.0 / 690.0], [0, 2, 4]),
|
|
([4, 3, 11, 22, 5], [1, 3, 4, 8, 5], [1, 16, 85, 470, 690], [60, 22, 430, 500, 345],
|
|
[60, 430, 345], [10.0, 4.3, 345.0 / 700.0], [0, 2, 4]),
|
|
([0], [0], [5, 77, 444, 88, 6050], [100, 308, 4440, 44, 6050],
|
|
[100, 308, 4440, 44], [20.0, 4.0, 10.0, 0.5], [0, 1, 2, 3]),
|
|
([0], [0], [1, 100, 200], [1, 350, 150], [350, 150], [3.5, 150 / 200], [1, 2]),
|
|
([0, 3, 10], [0], [16, 7, 190], [8, 10, 390], [8, 390], [0.5, 390 / 200], [0, 2]),
|
|
([10, 0, 10], [0, 16, 18], [4, 1024, 8000], [56, 520, 8028], [56, 520], [4.0, 0.5], [0, 1]),
|
|
([0], [0], [1, 690], [20, 1380], [20, 1380], [20.0, 1380.0 / 690.0], [0, 1]),
|
|
([4, 3, 11, 22, 5, 0], [1, 3, 4, 8, 5, 0], [1, 16, 85, 470, 690, 349], [60, 22, 430, 500, 345, 349],
|
|
[60, 430, 345], [10.0, 4.3, 345.0 / 700.0], [0, 2, 4]),
|
|
([4, 3, 11, 22, 5, 0, 0], [1, 3, 4, 8, 5, 0, 0], [1, 16, 85, 470, 690, 349, 3],
|
|
[60, 22, 430, 500, 345, 349, 1],
|
|
[60, 430, 345, 1], [10.0, 4.3, 345.0 / 700.0, 1 / 3], [0, 2, 4, 6]),
|
|
([4, 3, 11, 22, 5, 0, 0], [1, 3, 4, 8, 5, 0, 0], [1, 16, 85, 470, 690, 349, 3],
|
|
[60, 22, 430, 500, 345, 349, 1],
|
|
[60, 430, 345, 1], [10.0, 4.3, 345.0 / 700.0, 0.3333333], [0, 2, 4, 6]),
|
|
])
|
|
def test_interpolate4_using_scales(self, pads_begin, pads_end, input_shape, output_shape, sizes, scales, axes):
|
|
graph = build_graph(nodes_attrs=graph_nodes_attrs,
|
|
edges=graph_edges,
|
|
update_attributes={
|
|
'input_data': {'shape': input_shape},
|
|
'sizes': {'shape': int64_array(sizes).shape, 'value': int64_array(sizes)},
|
|
'sizes_data': {'shape': int64_array(sizes).shape, 'value': int64_array(sizes)},
|
|
'scales': {'shape': np.array(scales).shape, 'value': np.array(scales)},
|
|
'scales_data': {'shape': np.array(scales).shape, 'value': np.array(scales)},
|
|
'axes': {'shape': int64_array(axes).shape, 'value': int64_array(axes)},
|
|
'axes_data': {'shape': int64_array(axes).shape, 'value': int64_array(axes)},
|
|
'interpolate': {'pads_begin': int64_array(pads_begin),
|
|
'pads_end': int64_array(pads_end),
|
|
'shape_calculation_mode': 'scales'}
|
|
})
|
|
|
|
node = Node(graph, 'interpolate')
|
|
tested_class = Interpolate(graph=graph, attrs=node.attrs())
|
|
tested_class.infer(node)
|
|
|
|
msg = "Interpolate-4 infer failed for case: sizes={}, scales={}, pads_begin={}, pads_end={}, axes={}," \
|
|
" expected_shape={}, actual_shape={}"
|
|
|
|
self.assertTrue(np.array_equal(graph.node['interpolate_data']['shape'], int64_array(output_shape)),
|
|
msg.format(sizes, scales, pads_begin, pads_end, axes, output_shape,
|
|
graph.node['interpolate_data']['shape']))
|
|
|
|
@generate(*[([0], [0], [1, 3, 100, 200], [1, 3, 350, 150], [1, 3, 350, 150], [1.0, 1.0, 3.5, 150 / 200]),
|
|
([0, 3, 10, 10], [0], [16, 7, 190, 400], [8, 10, 390, 600],
|
|
[8, 10, 390, 600], [0.5, 1.0, 390 / 200, 600 / 410]),
|
|
([10, 5, 0, 10], [0, 4, 16, 18], [4, 33, 1024, 8000], [56, 42, 520, 8028],
|
|
[56, 42, 520, 8028], [4.0, 1.0, 0.5, 1.0]),
|
|
([0], [0], [1, 16, 85, 470, 690], [20, 16, 40, 470, 1380],
|
|
[20, 16, 40, 470, 1380], [20.0, 1.0, 40.0 / 85.0, 1.0, 1380.0 / 690.0]),
|
|
([4, 3, 11, 22, 5], [1, 3, 4, 8, 5], [1, 16, 85, 470, 690], [60, 22, 430, 500, 345],
|
|
[60, 22, 430, 500, 345], [10.0, 1.0, 4.3, 1.0, 345.0 / 700.0]),
|
|
([0], [0], [5, 77, 444, 88, 6050], [100, 308, 4440, 44, 6050],
|
|
[100, 308, 4440, 44, 6050], [20.0, 4.0, 10.0, 0.5, 1.0]),
|
|
([0], [0], [1, 100, 200], [1, 350, 150], [1, 350, 150], [1.0, 3.5, 150 / 200]),
|
|
([0, 3, 10], [0], [16, 7, 190], [8, 10, 390], [8, 10, 390], [0.5, 1.0, 390 / 200]),
|
|
([10, 0, 10], [0, 16, 18], [4, 1024, 8000], [56, 520, 8028], [56, 520, 8028], [4.0, 0.5, 1.0]),
|
|
([0], [0], [1, 690], [20, 1380], [20, 1380], [20.0, 1380.0 / 690.0]),
|
|
([4, 3, 11, 22, 5, 0], [1, 3, 4, 8, 5, 0], [1, 16, 85, 470, 690, 349], [60, 22, 430, 500, 345, 349],
|
|
[60, 22, 430, 500, 345, 349], [10.0, 1.0, 4.3, 1.0, 345.0 / 700.0, 1.0]),
|
|
([4, 3, 11, 22, 5, 0, 0], [1, 3, 4, 8, 5, 0, 0], [1, 16, 85, 470, 690, 349, 3],
|
|
[60, 22, 430, 500, 345, 349, 1],
|
|
[60, 22, 430, 500, 345, 349, 1], [10.0, 1.0, 4.3, 1.0, 345.0 / 700.0, 1.0, 1 / 3]),
|
|
])
|
|
def test_interpolate4_using_sizes_without_axes(self, pads_begin, pads_end, input_shape, output_shape, sizes,
|
|
scales):
|
|
graph = build_graph(nodes_attrs=graph_node_attrs_without_axes,
|
|
edges=graph_edges_without_axes,
|
|
update_attributes={
|
|
'input_data': {'shape': input_shape},
|
|
'sizes': {'shape': int64_array(sizes).shape, 'value': int64_array(sizes)},
|
|
'sizes_data': {'shape': int64_array(sizes).shape, 'value': int64_array(sizes)},
|
|
'scales': {'shape': np.array(scales).shape, 'value': np.array(scales)},
|
|
'scales_data': {'shape': np.array(scales).shape, 'value': np.array(scales)},
|
|
'interpolate': {'pads_begin': int64_array(pads_begin),
|
|
'pads_end': int64_array(pads_end),
|
|
'shape_calculation_mode': 'sizes'}
|
|
})
|
|
|
|
node = Node(graph, 'interpolate')
|
|
tested_class = Interpolate(graph=graph, attrs=node.attrs())
|
|
tested_class.infer(node)
|
|
|
|
msg = "Interpolate-4 infer failed for case: sizes={}, scales={}, pads_begin={}, pads_end={}," \
|
|
" expected_shape={}, actual_shape={}"
|
|
|
|
self.assertTrue(np.array_equal(graph.node['interpolate_data']['shape'], int64_array(output_shape)),
|
|
msg.format(sizes, scales, pads_begin, pads_end, output_shape,
|
|
graph.node['interpolate_data']['shape']))
|
|
|
|
@generate(*[([0], [0], [1, 3, 100, 200], [1, 3, 350, 150], [1, 3, 350, 150], [1.0, 1.0, 3.5, 150 / 200]),
|
|
([0, 3, 10, 10], [0], [16, 7, 190, 400], [8, 10, 390, 600],
|
|
[8, 10, 390, 600], [0.5, 1.0, 390 / 200, 600 / 410]),
|
|
([10, 5, 0, 10], [0, 4, 16, 18], [4, 33, 1024, 8000], [56, 42, 520, 8028],
|
|
[56, 42, 520, 8028], [4.0, 1.0, 0.5, 1.0]),
|
|
([0], [0], [1, 16, 85, 470, 690], [20, 16, 40, 470, 1380],
|
|
[20, 16, 40, 470, 1380], [20.0, 1.0, 40.0 / 85.0, 1.0, 1380.0 / 690.0]),
|
|
([4, 3, 11, 22, 5], [1, 3, 4, 8, 5], [1, 16, 85, 470, 690], [60, 22, 430, 500, 345],
|
|
[60, 22, 430, 500, 345], [10.0, 1.0, 4.3, 1.0, 345.0 / 700.0]),
|
|
([0], [0], [5, 77, 444, 88, 6050], [100, 308, 4440, 44, 6050],
|
|
[100, 308, 4440, 44, 6050], [20.0, 4.0, 10.0, 0.5, 1.0]),
|
|
([0], [0], [1, 100, 200], [1, 350, 150], [1, 350, 150], [1.0, 3.5, 150 / 200]),
|
|
([0, 3, 10], [0], [16, 7, 190], [8, 10, 390], [8, 10, 390], [0.5, 1.0, 390 / 200]),
|
|
([10, 0, 10], [0, 16, 18], [4, 1024, 8000], [56, 520, 8028], [56, 520, 8028], [4.0, 0.5, 1.0]),
|
|
([0], [0], [1, 690], [20, 1380], [20, 1380], [20.0, 1380.0 / 690.0]),
|
|
([4, 3, 11, 22, 5, 0], [1, 3, 4, 8, 5, 0], [1, 16, 85, 470, 690, 349], [60, 22, 430, 500, 345, 349],
|
|
[60, 22, 430, 500, 345, 349], [10.0, 1.0, 4.3, 1.0, 345.0 / 700.0, 1.0]),
|
|
([4, 3, 11, 22, 5, 0, 0], [1, 3, 4, 8, 5, 0, 0], [1, 16, 85, 470, 690, 349, 3],
|
|
[60, 22, 430, 500, 345, 349, 1],
|
|
[60, 22, 430, 500, 345, 349, 1], [10.0, 1.0, 4.3, 1.0, 345.0 / 700.0, 1.0, 1 / 3]),
|
|
([4, 3, 11, 22, 5, 0, 0], [1, 3, 4, 8, 5, 0, 0], [1, 16, 85, 470, 690, 349, 3],
|
|
[60, 22, 430, 500, 345, 349, 1],
|
|
[60, 22, 430, 500, 345, 349, 1], [10.0, 1.0, 4.3, 1.0, 345.0 / 700.0, 1.0, 0.3333333]),
|
|
])
|
|
def test_interpolate4_using_scales_without_axes(self, pads_begin, pads_end, input_shape, output_shape, sizes,
|
|
scales):
|
|
graph = build_graph(nodes_attrs=graph_node_attrs_without_axes,
|
|
edges=graph_edges_without_axes,
|
|
update_attributes={
|
|
'input_data': {'shape': input_shape},
|
|
'sizes': {'shape': int64_array(sizes).shape, 'value': int64_array(sizes)},
|
|
'sizes_data': {'shape': int64_array(sizes).shape, 'value': int64_array(sizes)},
|
|
'scales': {'shape': np.array(scales).shape, 'value': np.array(scales)},
|
|
'scales_data': {'shape': np.array(scales).shape, 'value': np.array(scales)},
|
|
'interpolate': {'pads_begin': int64_array(pads_begin),
|
|
'pads_end': int64_array(pads_end),
|
|
'shape_calculation_mode': 'scales'}
|
|
})
|
|
|
|
node = Node(graph, 'interpolate')
|
|
tested_class = Interpolate(graph=graph, attrs=node.attrs())
|
|
tested_class.infer(node)
|
|
|
|
msg = "Interpolate-4 infer failed for case: sizes={}, scales={}, pads_begin={}, pads_end={}," \
|
|
" expected_shape={}, actual_shape={}"
|
|
|
|
self.assertTrue(np.array_equal(graph.node['interpolate_data']['shape'], int64_array(output_shape)),
|
|
msg.format(sizes, scales, pads_begin, pads_end, output_shape,
|
|
graph.node['interpolate_data']['shape']))
|