openvino/model-optimizer/extensions/middle/SliceConvert_test.py

403 lines
22 KiB
Python

"""
Copyright (C) 2018-2020 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import unittest
import numpy as np
from extensions.middle.SliceConverter import ConvertSlice
from mo.front.common.partial_infer.utils import int64_array
from mo.graph.graph import Node
from mo.ops.slice import Slice
from mo.utils.ir_engine.compare_graphs import compare_graphs
from mo.utils.unittest.graph import build_graph
nodes_attributes = {
# input data
'placeholder_1': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
'placeholder_2': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
'placeholder_3': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
'placeholder_1_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
'placeholder_2_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
'placeholder_3_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
# Slice layer
'slice': {'type': 'Slice', 'kind': 'op', 'op': 'Slice', 'name': 'slice_node'},
'slice_data': {'value': None, 'shape': None, 'kind': 'data'},
# Output operation
'output_op': {'type': 'Const', 'value': None, 'kind': 'op', 'op': 'Const'},
'output_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
'op_output': { 'kind': 'op', 'op': 'Result'},
# Crop layer
'crop': {'type': 'Crop', 'kind': 'op', 'op': 'Crop', 'axis': None, 'offset': None, 'dim': None},
'dim': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
# StridedSlice layer
'strided_slice': {'kind': 'op', 'op': 'StridedSlice', 'slices': None, 'shrink_axis_mask': None}
}
class ConvertSliceTests(unittest.TestCase):
def test_1(self):
"""
Testing case with non-constant path and multiple
slicing dimensions
:return:
"""
graph = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'slice'),
('slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': np.array([4, 5, 6])},
'slice': {'start': np.array([1, 2, 3]), 'end': np.array([3, 4, 4]), 'axis': None},
}, nodes_with_edges_only=True,
)
slice_node = Node(graph, 'slice')
Slice.infer(slice_node)
pattern = ConvertSlice()
pattern.find_and_replace_pattern(graph)
graph.clean_up()
ss_node = Node(graph, graph.get_node_id_by_name('slice_node'))
assert ss_node.type == 'Crop', 'Something wrong with transformed Slice node'
graph_ref = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'crop'),
('crop', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': np.array([4, 5, 6])},
'crop': {'axis': np.array([0, 1, 2]), 'offset': np.array([1, 2, 3]),
'dim': np.array([2, 2, 1])},
}, nodes_with_edges_only=True,
)
(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
self.assertTrue(flag, resp)
def test_2(self):
"""
Testing case with constant path and one
slicing dimension
"""
graph = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'slice'),
('slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': np.array([4, 5, 6])},
'slice': {'start': np.array([1]), 'end': np.array([3]), 'axis': None}
}, nodes_with_edges_only=True,
)
graph.graph['layout'] = 'NHWC'
slice_node = Node(graph, 'slice')
Slice.infer(slice_node)
pattern = ConvertSlice()
pattern.find_and_replace_pattern(graph)
graph.clean_up()
ss_node = Node(graph, graph.get_node_id_by_name('slice_node'))
assert ss_node.type == 'StridedSlice', 'Something wrong with transformed Slice node'
graph_ref = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_2', 'placeholder_2_data'),
('placeholder_3', 'placeholder_3_data'),
('placeholder_1_data', 'strided_slice'),
('placeholder_2_data', 'strided_slice'),
('placeholder_3_data', 'strided_slice'),
('strided_slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': np.array([4, 5, 6])},
'strided_slice': {'slices': np.array([slice(1, 3, 1),slice(0, 5, 1),slice(0, 6, 1)]),
'shrink_axis_mask': np.array([False, False, False])},
}, nodes_with_edges_only=True,
)
(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
self.assertTrue(flag, resp)
def test_3(self):
"""
Testing case with constant path and one
slicing dimension
"""
graph = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'slice'),
('slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': np.array([1, 5, 6])},
'slice': {'start': np.array([1]), 'end': np.array([3]), 'axis': np.array([1])}
}, nodes_with_edges_only=True,
)
graph.graph['layout'] = 'NHWC'
slice_node = Node(graph, 'slice')
Slice.infer(slice_node)
pattern = ConvertSlice()
pattern.find_and_replace_pattern(graph)
graph.clean_up()
ss_node = Node(graph, graph.get_node_id_by_name('slice_node'))
assert ss_node.type == 'StridedSlice', 'Something wrong with transformed Slice node'
graph_ref = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_2', 'placeholder_2_data'),
('placeholder_3', 'placeholder_3_data'),
('placeholder_1_data', 'strided_slice'),
('placeholder_2_data', 'strided_slice'),
('placeholder_3_data', 'strided_slice'),
('strided_slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': np.array([1, 5, 6])},
'strided_slice': {'slices': np.array([slice(0, 1, 1),slice(1, 3, 1),slice(0, 6, 1)]),
'shrink_axis_mask': np.array([False, False, False])},
}, nodes_with_edges_only=True,
)
(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
self.assertTrue(flag, resp)
class ConvertSliceONNXOpset10Tests(unittest.TestCase):
nodes_attributes = {
# input data
'placeholder_1': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
'placeholder_1_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
# Slice layer inputs
'starts': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
'starts_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
'ends': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
'ends_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
'strides': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
'strides_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
'axes': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
'axes_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
'steps': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
'steps_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
# Slice layer
'slice': {'type': 'Slice', 'kind': 'op', 'op': 'Slice', 'format': 'onnx', 'end': None, 'name': 'slice_node'},
'slice_data': {'value': None, 'shape': None, 'kind': 'data'},
# Output operation
'output_op': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
'output_data': {'shape': None, 'kind': 'data', 'data_type': None},
'op_output': {'kind': 'op', 'op': 'Result'},
# StridedSlice layer
'strided_slice': {'kind': 'op', 'op': 'StridedSlice', 'slices': None, 'shrink_axis_mask': None}
}
def test_no_steps_no_axes(self):
input_shape = int64_array([5, 10, 20])
starts_value = int64_array([3, 2, 7])
ends_value = int64_array([5, 8, 15])
steps_value = int64_array([1, 1, 1])
masks_value = np.zeros([len(input_shape)], dtype=np.int64)
graph = build_graph(self.nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'slice', {'in': 0}),
('starts', 'starts_data'),
('starts_data', 'slice', {'in': 1}),
('ends', 'ends_data'),
('ends_data', 'slice', {'in': 2}),
('slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': input_shape},
'starts': {'shape': starts_value.shape, 'value': starts_value},
'starts_data': {'shape': starts_value.shape, 'value': starts_value},
'ends': {'shape': ends_value.shape, 'value': ends_value},
'ends_data': {'shape': ends_value.shape, 'value': ends_value},
}, nodes_with_edges_only=True
)
slice_node = Node(graph, 'slice')
Slice.infer(slice_node)
pattern = ConvertSlice()
pattern.find_and_replace_pattern(graph)
ss_node = Node(graph, graph.get_node_id_by_name('slice_node'))
assert ss_node.type == 'StridedSlice', 'Something wrong with transformed Slice node'
graph_ref = build_graph(self.nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'strided_slice', {'in': 0}),
('starts', 'starts_data'),
('starts_data', 'strided_slice', {'in': 1}),
('ends', 'ends_data'),
('ends_data', 'strided_slice', {'in': 2}),
('strides', 'strides_data'),
('strides_data', 'strided_slice', {'in': 3}),
('strided_slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': input_shape},
'strided_slice': {'new_axis_mask': masks_value, 'shrink_axis_mask': masks_value,
'ellipsis_mask': masks_value, 'begin_mask': np.ones([3]),
'end_mask': np.ones([3])},
'slice_data': {'shape': int64_array([2, 6, 8])}
}, nodes_with_edges_only=True
)
(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
self.assertTrue(flag, resp)
def test_no_axes(self):
input_shape = int64_array([5, 10, 20])
starts_value = int64_array([3, 2, 7])
ends_value = int64_array([5, 8, 15])
steps_value = int64_array([2, 3, 1])
masks_value = np.zeros([len(input_shape)], dtype=np.int64)
graph = build_graph(self.nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'slice', {'in': 0}),
('starts', 'starts_data'),
('starts_data', 'slice', {'in': 1}),
('ends', 'ends_data'),
('ends_data', 'slice', {'in': 2}),
('steps', 'steps_data'),
('steps_data', 'slice', {'in': 4}),
('slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': input_shape},
'starts': {'shape': starts_value.shape, 'value': starts_value},
'starts_data': {'shape': starts_value.shape, 'value': starts_value},
'ends': {'shape': ends_value.shape, 'value': ends_value},
'ends_data': {'shape': ends_value.shape, 'value': ends_value},
'steps': {'shape': steps_value.shape, 'value': steps_value},
'steps_data': {'shape': steps_value.shape, 'value': steps_value},
}, nodes_with_edges_only=True
)
slice_node = Node(graph, 'slice')
Slice.infer(slice_node)
pattern = ConvertSlice()
pattern.find_and_replace_pattern(graph)
ss_node = Node(graph, graph.get_node_id_by_name('slice_node'))
assert ss_node.type == 'StridedSlice', 'Something wrong with transformed Slice node'
graph_ref = build_graph(self.nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'strided_slice', {'in': 0}),
('starts', 'starts_data'),
('starts_data', 'strided_slice', {'in': 1}),
('ends', 'ends_data'),
('ends_data', 'strided_slice', {'in': 2}),
('strides', 'strides_data'),
('strides_data', 'strided_slice', {'in': 3}),
('strided_slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': input_shape},
'strided_slice': {'new_axis_mask': masks_value, 'shrink_axis_mask': masks_value,
'ellipsis_mask': masks_value, 'begin_mask': np.ones([3]),
'end_mask': np.ones([3])},
'slice_data': {'shape': int64_array([1, 2, 8])}
}, nodes_with_edges_only=True
)
(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
self.assertTrue(flag, resp)
def test_no_steps(self):
input_shape = int64_array([5, 10, 20])
starts_value = int64_array([4, 2])
ends_value = int64_array([15, 8])
axes_value = int64_array([2, 1])
masks_value = np.zeros([len(input_shape)], dtype=np.int64)
graph = build_graph(self.nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'slice', {'in': 0}),
('starts', 'starts_data'),
('starts_data', 'slice', {'in': 1}),
('ends', 'ends_data'),
('ends_data', 'slice', {'in': 2}),
('axes', 'axes_data'),
('axes_data', 'slice', {'in': 3}),
('slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': input_shape},
'starts': {'shape': starts_value.shape, 'value': starts_value},
'starts_data': {'shape': starts_value.shape, 'value': starts_value},
'ends': {'shape': ends_value.shape, 'value': ends_value},
'ends_data': {'shape': ends_value.shape, 'value': ends_value},
'axes': {'shape': axes_value.shape, 'value': axes_value},
'axes_data': {'shape': axes_value.shape, 'value': axes_value},
}, nodes_with_edges_only=True
)
slice_node = Node(graph, 'slice')
Slice.infer(slice_node)
pattern = ConvertSlice()
pattern.find_and_replace_pattern(graph)
ss_node = Node(graph, graph.get_node_id_by_name('slice_node'))
assert ss_node.type == 'StridedSlice', 'Something wrong with transformed Slice node'
graph_ref = build_graph(self.nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'strided_slice', {'in': 0}),
('starts', 'starts_data'),
('starts_data', 'strided_slice', {'in': 1}),
('ends', 'ends_data'),
('ends_data', 'strided_slice', {'in': 2}),
('strides', 'strides_data'),
('strides_data', 'strided_slice', {'in': 3}),
('strided_slice', 'slice_data'),
('slice_data', 'output_op'),
('output_op', 'output_data'),
('output_data', 'op_output')
],
{'placeholder_1_data': {'shape': input_shape},
'strided_slice': {'new_axis_mask': masks_value, 'shrink_axis_mask': masks_value,
'ellipsis_mask': masks_value, 'begin_mask': int64_array([0, 1, 1]),
'end_mask': int64_array([0, 1, 1])},
'slice_data': {'shape': int64_array([5, 6, 11])}
}, nodes_with_edges_only=True
)
(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
self.assertTrue(flag, resp)