381 lines
20 KiB
Python
381 lines
20 KiB
Python
"""
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Copyright (c) 2018-2019 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import unittest
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import numpy as np
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from extensions.middle.SliceConverter import ConvertSlice
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from mo.front.common.partial_infer.utils import int64_array
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from mo.graph.graph import Node
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from mo.utils.unittest.graph import build_graph, compare_graphs
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from mo.ops.slice import Slice
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nodes_attributes = {
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# input data
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'placeholder_1': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
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'placeholder_2': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
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'placeholder_3': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
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'placeholder_1_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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'placeholder_2_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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'placeholder_3_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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# Slice layer
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'slice': {'type': 'Slice', 'kind': 'op', 'op': 'Slice'},
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'slice_data': {'value': None, 'shape': None, 'kind': 'data'},
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# Output operation
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'output_op': {'type': 'Const', 'value': None, 'kind': 'op', 'op': 'Const'},
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'output_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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'op_output': { 'kind': 'op', 'op': 'Result'},
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# Crop layer
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'crop': {'type': 'Crop', 'kind': 'op', 'op': 'Crop', 'axis': None, 'offset': None, 'dim': None},
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'dim': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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# StridedSlice layer
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'strided_slice': {'kind': 'op', 'op': 'StridedSlice', 'slices': None,
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'shrink_axis_mask': None}
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}
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class ConvertSliceTests(unittest.TestCase):
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def test_1(self):
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"""
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Testing case with non-constant path and multiple
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slicing dimensions
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:return:
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"""
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graph = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'slice'),
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('slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': np.array([4, 5, 6])},
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'slice': {'start': np.array([1, 2, 3]), 'end': np.array([3, 4, 4]), 'axis': None},
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}
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)
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slice_node = Node(graph, 'slice')
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Slice.infer(slice_node)
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pattern = ConvertSlice()
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pattern.find_and_replace_pattern(graph)
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graph_ref = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'crop'),
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('crop', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': np.array([4, 5, 6])},
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'crop': {'axis': np.array([0, 1, 2]), 'offset': np.array([1, 2, 3])},
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'dim': {'dim': np.array([2, 2, 1])},
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}
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)
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(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
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self.assertTrue(flag, resp)
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def test_2(self):
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"""
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Testing case with constant path and one
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slicing dimension
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"""
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graph = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'slice'),
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('slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': np.array([4, 5, 6])},
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'slice': {'start': np.array([1]), 'end': np.array([3]), 'axis': None}
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}
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)
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graph.graph['layout'] = 'NHWC'
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slice_node = Node(graph, 'slice')
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Slice.infer(slice_node)
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pattern = ConvertSlice()
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pattern.find_and_replace_pattern(graph)
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graph_ref = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_2', 'placeholder_2_data'),
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('placeholder_3', 'placeholder_3_data'),
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('placeholder_1_data', 'strided_slice'),
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('placeholder_2_data', 'strided_slice'),
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('placeholder_3_data', 'strided_slice'),
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('strided_slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': np.array([4, 5, 6])},
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'strided_slice': {'slices': np.array([slice(1, 3, 1),slice(0, 5, 1),slice(0, 6, 1)]),
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'shrink_axis_mask': np.array([False, False, False])},
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}
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)
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(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
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self.assertTrue(flag, resp)
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def test_3(self):
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"""
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Testing case with constant path and one
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slicing dimension
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"""
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graph = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'slice'),
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('slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': np.array([1, 5, 6])},
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'slice': {'start': np.array([1]), 'end': np.array([3]), 'axis': np.array([1])}
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}
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)
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graph.graph['layout'] = 'NHWC'
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slice_node = Node(graph, 'slice')
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Slice.infer(slice_node)
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pattern = ConvertSlice()
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pattern.find_and_replace_pattern(graph)
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graph_ref = build_graph(nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_2', 'placeholder_2_data'),
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('placeholder_3', 'placeholder_3_data'),
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('placeholder_1_data', 'strided_slice'),
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('placeholder_2_data', 'strided_slice'),
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('placeholder_3_data', 'strided_slice'),
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('strided_slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': np.array([1, 5, 6])},
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'strided_slice': {'slices': np.array([slice(0, 1, 1),slice(1, 3, 1),slice(0, 6, 1)]),
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'shrink_axis_mask': np.array([False, False, False])},
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}
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)
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(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
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self.assertTrue(flag, resp)
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class ConvertSliceONNXOpset10Tests(unittest.TestCase):
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nodes_attributes = {
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# input data
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'placeholder_1': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
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'placeholder_1_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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# Slice layer inputs
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'starts': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
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'starts_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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'ends': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
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'ends_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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'strides': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
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'strides_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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'axes': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
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'axes_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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'steps': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
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'steps_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
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# Slice layer
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'slice': {'type': 'Slice', 'kind': 'op', 'op': 'Slice', 'format': 'onnx', 'end': None},
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'slice_data': {'value': None, 'shape': None, 'kind': 'data'},
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# Output operation
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'output_op': {'type': 'Const', 'kind': 'op', 'op': 'Const'},
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'output_data': {'shape': None, 'kind': 'data', 'data_type': None},
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'op_output': {'kind': 'op', 'op': 'Result'},
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# StridedSlice layer
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'strided_slice': {'kind': 'op', 'op': 'StridedSlice', 'slices': None, 'shrink_axis_mask': None}
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}
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def test_no_steps_no_axes(self):
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input_shape = int64_array([5, 10, 20])
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starts_value = int64_array([3, 2, 7])
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ends_value = int64_array([5, 8, 15])
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steps_value = int64_array([1, 1, 1])
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masks_value = np.zeros([len(input_shape)], dtype=np.int64)
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graph = build_graph(self.nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'slice', {'in': 0}),
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('starts', 'starts_data'),
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('starts_data', 'slice', {'in': 1}),
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('ends', 'ends_data'),
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('ends_data', 'slice', {'in': 2}),
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('slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': input_shape},
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'starts': {'shape': starts_value.shape, 'value': starts_value},
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'starts_data': {'shape': starts_value.shape, 'value': starts_value},
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'ends': {'shape': ends_value.shape, 'value': ends_value},
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'ends_data': {'shape': ends_value.shape, 'value': ends_value},
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}, nodes_with_edges_only=True
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)
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slice_node = Node(graph, 'slice')
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Slice.infer(slice_node)
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pattern = ConvertSlice()
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pattern.find_and_replace_pattern(graph)
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graph_ref = build_graph(self.nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'strided_slice', {'in': 0}),
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('starts', 'starts_data'),
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('starts_data', 'strided_slice', {'in': 1}),
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('ends', 'ends_data'),
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('ends_data', 'strided_slice', {'in': 2}),
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('strides', 'strides_data'),
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('strides_data', 'strided_slice', {'in': 3}),
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('strided_slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': input_shape},
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'strided_slice': {'new_axis_mask': masks_value, 'shrink_axis_mask': masks_value,
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'ellipsis_mask': masks_value, 'begin_mask': np.ones([3]),
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'end_mask': np.ones([3])},
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'slice_data': {'shape': int64_array([2, 6, 8])}
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}, nodes_with_edges_only=True
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)
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(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
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self.assertTrue(flag, resp)
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def test_no_axes(self):
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input_shape = int64_array([5, 10, 20])
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starts_value = int64_array([3, 2, 7])
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ends_value = int64_array([5, 8, 15])
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steps_value = int64_array([2, 3, 1])
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masks_value = np.zeros([len(input_shape)], dtype=np.int64)
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graph = build_graph(self.nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'slice', {'in': 0}),
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('starts', 'starts_data'),
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('starts_data', 'slice', {'in': 1}),
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('ends', 'ends_data'),
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('ends_data', 'slice', {'in': 2}),
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('steps', 'steps_data'),
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('steps_data', 'slice', {'in': 4}),
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('slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': input_shape},
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'starts': {'shape': starts_value.shape, 'value': starts_value},
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'starts_data': {'shape': starts_value.shape, 'value': starts_value},
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'ends': {'shape': ends_value.shape, 'value': ends_value},
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'ends_data': {'shape': ends_value.shape, 'value': ends_value},
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'steps': {'shape': steps_value.shape, 'value': steps_value},
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'steps_data': {'shape': steps_value.shape, 'value': steps_value},
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}, nodes_with_edges_only=True
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)
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slice_node = Node(graph, 'slice')
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Slice.infer(slice_node)
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pattern = ConvertSlice()
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pattern.find_and_replace_pattern(graph)
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graph_ref = build_graph(self.nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'strided_slice', {'in': 0}),
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('starts', 'starts_data'),
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('starts_data', 'strided_slice', {'in': 1}),
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('ends', 'ends_data'),
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('ends_data', 'strided_slice', {'in': 2}),
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('strides', 'strides_data'),
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('strides_data', 'strided_slice', {'in': 3}),
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('strided_slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': input_shape},
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'strided_slice': {'new_axis_mask': masks_value, 'shrink_axis_mask': masks_value,
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'ellipsis_mask': masks_value, 'begin_mask': np.ones([3]),
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'end_mask': np.ones([3])},
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'slice_data': {'shape': int64_array([1, 2, 8])}
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}, nodes_with_edges_only=True
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)
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(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
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self.assertTrue(flag, resp)
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def test_no_steps(self):
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input_shape = int64_array([5, 10, 20])
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starts_value = int64_array([4, 2])
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ends_value = int64_array([15, 8])
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axes_value = int64_array([2, 1])
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masks_value = np.zeros([len(input_shape)], dtype=np.int64)
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graph = build_graph(self.nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'slice', {'in': 0}),
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('starts', 'starts_data'),
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('starts_data', 'slice', {'in': 1}),
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('ends', 'ends_data'),
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('ends_data', 'slice', {'in': 2}),
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('axes', 'axes_data'),
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('axes_data', 'slice', {'in': 3}),
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('slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': input_shape},
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'starts': {'shape': starts_value.shape, 'value': starts_value},
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'starts_data': {'shape': starts_value.shape, 'value': starts_value},
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'ends': {'shape': ends_value.shape, 'value': ends_value},
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'ends_data': {'shape': ends_value.shape, 'value': ends_value},
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'axes': {'shape': axes_value.shape, 'value': axes_value},
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'axes_data': {'shape': axes_value.shape, 'value': axes_value},
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}, nodes_with_edges_only=True
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)
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slice_node = Node(graph, 'slice')
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Slice.infer(slice_node)
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pattern = ConvertSlice()
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pattern.find_and_replace_pattern(graph)
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graph_ref = build_graph(self.nodes_attributes,
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[('placeholder_1', 'placeholder_1_data'),
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('placeholder_1_data', 'strided_slice', {'in': 0}),
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('starts', 'starts_data'),
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('starts_data', 'strided_slice', {'in': 1}),
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('ends', 'ends_data'),
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('ends_data', 'strided_slice', {'in': 2}),
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('strides', 'strides_data'),
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('strides_data', 'strided_slice', {'in': 3}),
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('strided_slice', 'slice_data'),
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('slice_data', 'output_op'),
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('output_op', 'output_data'),
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('output_data', 'op_output')
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],
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{'placeholder_1_data': {'shape': input_shape},
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'strided_slice': {'new_axis_mask': masks_value, 'shrink_axis_mask': masks_value,
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'ellipsis_mask': masks_value, 'begin_mask': int64_array([0, 1, 1]),
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'end_mask': int64_array([0, 1, 1])},
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'slice_data': {'shape': int64_array([5, 6, 11])}
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}, nodes_with_edges_only=True
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)
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(flag, resp) = compare_graphs(graph, graph_ref, 'output_op', check_op_attrs=True)
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self.assertTrue(flag, resp)
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