Pavel Esir
75d2d88b61
* Added Caffe Slice_ext * Added TFSlice, AttributedSlice (both with extractors and replacers), corrected SliceConverter and added unittests for all cases * added comments to each type of Slice operation; optimized shape inference; moved mxlice inside of slice.py; renamed slice_replacers * removed type annotation for get_shape_after_slice routine * replaced zeros_like with zeros * Corrected preserving node names, renamed attributes names, added tests fro slice_replacer onnx phase * Renamed slice_replacers.py * added more unittest cases * added type annotations, moved to more relevant place routines for shape calculation, and some other minor corrections * corrected a typo `normalize_slice_indices` comment * corrected shape calculation for Nonconstant inputs * corrected a few typos * corrected type declarations * corrected shape inference with rounding * refactored unit-tests for front transforms of Slice * added error raising for negative and zero shapes * removed magic_num * corrected AttributedSlice, clarified comments * fixed unit-test for AttributedSliceToSlice * typo in type hints corrected * removed supported_attrs * returned back default None for attrs of Slice
279 lines
14 KiB
Python
279 lines
14 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 mo.front.common.partial_infer.slice import tf_strided_slice_infer, convert_negative_indices, mxnet_slice_axis_infer
|
|
from mo.graph.graph import Node
|
|
from mo.utils.unittest.graph import build_graph
|
|
|
|
nodes_attributes = {'node_1': {'value': None, 'kind': 'data'},
|
|
'Slice_node': {'type': 'Slice', 'kind': 'op'},
|
|
'node_2': {'value': None, 'kind': 'data'},
|
|
'node_3': {'value': None, 'kind': 'data'},
|
|
'node_4': {'value': None, 'kind': 'data'},
|
|
# StridedSlice node with attrs
|
|
'sslice_input': {'value': None, 'shape': None, 'kind': 'data'},
|
|
'sslice_1': {'type': 'StridedSlice', 'value': None, 'kind': 'op', 'op': 'StridedSlice'},
|
|
'sslice_begin_1': {'value': None, 'shape': None, 'kind': 'data'},
|
|
'sslice_end_1': {'value': None, 'shape': None, 'kind': 'data'},
|
|
'sslice_stride_1': {'value': None, 'shape': None, 'kind': 'data'},
|
|
'sslice_data_1': {'value': None, 'shape': None, 'kind': 'data'},
|
|
# TF slice
|
|
'tf_slice_input': {'value': None, 'shape': None, 'kind': 'data'},
|
|
'tf_slice_begin': {'value': None, 'shape': None, 'kind': 'data'},
|
|
'tf_slice_size': {'value': None, 'shape': None, 'kind': 'data'},
|
|
'tf_slice': {'kind': 'op'},
|
|
'tf_slice_output': {'value': None, 'shape': None, 'kind': 'data'},
|
|
'op_output': {'kind': 'op', 'op': 'Result'},
|
|
'op_output_1': {'kind': 'op', 'op': 'Result'},
|
|
'op_output_2': {'kind': 'op', 'op': 'Result'}
|
|
}
|
|
|
|
tf_slice_edges = [('tf_slice_input', 'tf_slice'), ('tf_slice_begin', 'tf_slice'), ('tf_slice_size', 'tf_slice'),
|
|
('tf_slice', 'tf_slice_output')]
|
|
|
|
|
|
class TestTFStridedSliceInfer(unittest.TestCase):
|
|
def build_test_graph2(self):
|
|
return build_graph(nodes_attributes,
|
|
[('sslice_input', 'sslice_1'),
|
|
('sslice_begin_1', 'sslice_1'),
|
|
('sslice_end_1', 'sslice_1'),
|
|
('sslice_stride_1', 'sslice_1'),
|
|
('sslice_1', 'sslice_data_1'),
|
|
('sslice_data_1', 'op_output')
|
|
],
|
|
{
|
|
'sslice_input': {'value': np.array([1, 34, 34, 62]),
|
|
'shape': np.array([3])},
|
|
'sslice_begin_1': {'value': np.array([0]), 'shape': np.array([1])},
|
|
'sslice_end_1': {'value': np.array([4]), 'shape': np.array([1])},
|
|
'sslice_stride_1': {'value': np.array([1]), 'shape': np.array([1])},
|
|
'sslice_1': {'shrink_axis_mask': [0], 'ellipsis_mask': [0], 'new_axis_mask': [0],
|
|
'begin_mask': [1], 'end_mask': [1]},
|
|
})
|
|
|
|
def build_test_graph(self):
|
|
return build_graph(nodes_attributes,
|
|
[('sslice_input', 'sslice_1'),
|
|
('sslice_begin_1', 'sslice_1'),
|
|
('sslice_end_1', 'sslice_1'),
|
|
('sslice_stride_1', 'sslice_1'),
|
|
('sslice_1', 'sslice_data_1'),
|
|
('sslice_data_1', 'op_output')
|
|
],
|
|
{
|
|
'sslice_input': {'value': None, 'shape': np.array([1, 35, 35, 3])},
|
|
'sslice_begin_1': {'value': np.array([0, 0, 0, 0]), 'shape': np.array([4])},
|
|
'sslice_end_1': {'value': np.array([1, 34, 30, 2]), 'shape': np.array([4])},
|
|
'sslice_stride_1': {'value': np.array([1, 1, 1, 1]),
|
|
'shape': np.array([4])},
|
|
'sslice_1': {'shrink_axis_mask': [0], 'ellipsis_mask': [0], 'new_axis_mask': [0],
|
|
'begin_mask': [1], 'end_mask': [1]},
|
|
})
|
|
|
|
def build_test_graph_dim_beg(self):
|
|
return build_graph(nodes_attributes,
|
|
[('sslice_input', 'sslice_1'),
|
|
('sslice_begin_1', 'sslice_1'),
|
|
('sslice_end_1', 'sslice_1'),
|
|
('sslice_stride_1', 'sslice_1'),
|
|
('sslice_1', 'sslice_data_1'),
|
|
('sslice_data_1', 'op_output')
|
|
],
|
|
{
|
|
'sslice_input': {'value': np.array([[1, 34, 34, 62]]),
|
|
'shape': np.array([1, 4])},
|
|
'sslice_begin_1': {'value': np.array([0]), 'shape': np.array([1])},
|
|
'sslice_end_1': {'value': np.array([4]), 'shape': np.array([1])},
|
|
'sslice_stride_1': {'value': np.array([1]), 'shape': np.array([1])},
|
|
'sslice_1': {'shrink_axis_mask': [0], 'ellipsis_mask': [0], 'new_axis_mask': [0],
|
|
'begin_mask': [1], 'end_mask': [1]},
|
|
})
|
|
|
|
def test_slice_infer_1(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([1, 34, 30, 2])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_2(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
node.end_mask = [1, 0, 0, 1] # 6
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([1, 35, 35, 2])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_3(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
node.in_node(1).value = np.array([0, 10, 10, 0])
|
|
node.end_mask = [1, 0, 0, 1] # 6
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([1, 25, 25, 2])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_4(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
node.in_node(1).value = np.array([0, 10, 10, 0])
|
|
node.begin_mask = [1, 0, 0, 1] # 6
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([1, 34, 30, 2])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_5(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
node.in_node(1).value = np.array([0, 10, 10, 0])
|
|
node.begin_mask = [0, 0, 0, 0] # 15
|
|
node.end_mask = [0, 0, 0, 0] # 15
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([1, 35, 35, 3])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_6(self):
|
|
graph = self.build_test_graph2()
|
|
node = Node(graph, 'sslice_1')
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([4])), 'Wrong output shape detected')
|
|
self.assertTrue(np.array_equal(node.out_node().value, np.array([1, 34, 34, 62])), 'Wrong output value detected')
|
|
|
|
def test_slice_infer_7(self):
|
|
graph = self.build_test_graph2()
|
|
node = Node(graph, 'sslice_1')
|
|
node.in_node(1).value = np.array([1])
|
|
node.in_node(2).value = np.array([3])
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([2])), 'Wrong output shape detected')
|
|
self.assertTrue(np.array_equal(node.out_node().value, np.array([34, 34])), 'Wrong output value detected')
|
|
|
|
def test_slice_infer_8(self):
|
|
graph = self.build_test_graph2()
|
|
node = Node(graph, 'sslice_1')
|
|
node.new_axis_mask = [1]
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([1, 4])), 'Wrong output shape detected')
|
|
self.assertTrue(np.array_equal(node.out_node().value, np.array([[1, 34, 34, 62]])),
|
|
'Wrong output value detected')
|
|
|
|
def test_slice_infer_9(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
node.begin_mask = [0, 0, 0, 0] # 15
|
|
node.end_mask = [0, 0, 0, 0] # 15
|
|
node.shrink_axis_mask = [1]
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([35, 35, 3])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_10(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
node.begin_mask = [0, 0, 0, 0] # 15
|
|
node.end_mask = [0, 0, 0, 0] # 15
|
|
node.shrink_axis_mask = [1, 0, 0, 0]
|
|
node.new_axis_mask = [0, 0, 0, 1] # 8
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([35, 35, 1, 3])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_11(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
node.begin_mask = [0, 0, 0, 0] # 15
|
|
node.end_mask = [0, 0, 0, 0] # 15
|
|
node.shrink_axis_mask = [1, 0, 1, 0] # 5
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([35, 3])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_12(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
node.begin_mask = [0, 0, 0, 0] # 15
|
|
node.end_mask = [0, 0, 0, 0] # 15
|
|
node.shrink_axis_mask = [1, 1, 1, 0] # 7
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([3])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_13(self):
|
|
graph = self.build_test_graph2()
|
|
node = Node(graph, 'sslice_1')
|
|
node.in_node(1).value = np.array([1])
|
|
node.shrink_axis_mask = [1]
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([])), 'Wrong output shape detected')
|
|
self.assertTrue(np.array_equal(node.out_node().value, np.array(34)), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_14(self):
|
|
graph = self.build_test_graph2()
|
|
node = Node(graph, 'sslice_1')
|
|
node.in_node(3).value = np.array([-1])
|
|
node.end_mask = [0]
|
|
node.begin_mask = [0]
|
|
node.in_node(0).shape = [4]
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([4])), 'Wrong output shape detected')
|
|
print(node.out_node().value)
|
|
self.assertTrue(np.array_equal(node.out_node().value, np.array([62, 34, 34, 1])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_dim_beg(self):
|
|
graph = self.build_test_graph_dim_beg()
|
|
node = Node(graph, 'sslice_1')
|
|
node.shrink_axis_mask = [1]
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([4])), 'Wrong output shape detected')
|
|
self.assertTrue(np.array_equal(node.out_node().value, np.array([1, 34, 34, 62])), 'Wrong output shape detected')
|
|
|
|
def test_slice_infer_neg_end(self):
|
|
graph = self.build_test_graph()
|
|
node = Node(graph, 'sslice_1')
|
|
end_node = Node(graph, 'sslice_end_1')
|
|
end_node.value = np.array([1, -1, -5, -1])
|
|
tf_strided_slice_infer(node)
|
|
self.assertTrue(np.array_equal(node.out_node().shape, np.array([1, 34, 30, 2])), 'Wrong output shape detected')
|
|
self.assertTrue(np.array_equal(end_node.value, np.array([1, -1, -5, -1])), 'Negative values in end were converted to positive')
|
|
|
|
|
|
class TestConvertNegativeIndices(unittest.TestCase):
|
|
def test_convert_negative_indices(self):
|
|
dimensions = np.array([3, 4, 8, 10])
|
|
indices = np.array([2, 0, -3, -4])
|
|
convert_negative_indices(indices, dimensions)
|
|
self.assertTrue(np.array_equal(indices, np.array([2, 0, 5, 6])), 'Wrong dimension indices')
|
|
|
|
|
|
class TestMXNetSliceAxisInfer(unittest.TestCase):
|
|
def test_slice_axis_infer_layer(self):
|
|
graph = build_graph(
|
|
{'node_1': {'name': 'data', 'type': 'Identity', 'value': None, 'kind': 'op', 'op': 'Parameter'},
|
|
'slice_axis_node': {'name': 'slice_axis_node', 'type': 'sigmoid', 'value': None,
|
|
'kind': 'op', 'op': 'slice_axis', },
|
|
'node_3': {'name': 'node_3', 'type': 'Identity', 'value': None, 'kind': 'op'},
|
|
},
|
|
[
|
|
('node_1', 'slice_axis_node'),
|
|
('slice_axis_node', 'node_3'),
|
|
],
|
|
{
|
|
'node_1': {'shape': np.array([1, 1024, 19, 19])},
|
|
'slice_axis_node': {'axis': 1, 'offset': 10, 'dim': 25},
|
|
})
|
|
|
|
slice_axis_node = Node(graph, 'slice_axis_node')
|
|
mxnet_slice_axis_infer(slice_axis_node)
|
|
res_shape = [1, 15, 19, 19]
|
|
for i in range(0, len(graph.node['node_3']['shape'])):
|
|
self.assertEqual(graph.node['node_3']['shape'][i], res_shape[i])
|