def test6(self):
# Original graph
# data(1,64,1)-->Reduce(axis=-2,keep_dims=True, reduce_type=Sum)-->data(1,1,1)
#
# Reference graph
# data(1,61,1)->Reshape(1,1,64,1)->Pool(1,1,1,1)->Reshape(1,1,1)->Power(scale=64)
#
graph = build_graph(nodes_attributes,
[('placeholder_1_data', 'reduce_1'),
('reduce_1', 'reduce_1_data'),
('reduce_1_data', 'concat'),
],
{'placeholder_1_data': {'shape': np.array([1, 64, 1])},
'reduce_1': {'axis': np.array([-2]), 'keep_dims': True, 'reduce_type': 'Sum'},
'reduce_1_data': {'shape': np.array([1, 1, 1])},
}, nodes_with_edges_only=True)
graph.graph['layout'] = 'NCHW'
graph_ref = build_graph(nodes_attributes,
[('placeholder_1_data', 'reshape_1'),
('reshape_1', 'reshape_1_data'),
('reshape_1_data', 'pooling'),
('pooling', 'pooling_data'),
('pooling_data', 'reshape_2'),
('reshape_2', 'reshape_2_data'),
('reshape_2_data', 'power'),
('power', 'power_data'),
('power_data', 'concat'),
],
{'placeholder_1_data': {'shape': np.array([1, 64, 1])},
'reshape_1': {'dim': np.array([1, 1, 64, 1])},
'reshape_1_data': {'shape': np.array([1, 1, 64, 1])},
'pooling': {'window': np.array([1, 1, 64, 1])},
'pooling_data': {'shape': np.array([1, 1, 1, 1])},
'reshape_2': {'dim': np.array([1, 1, 1])},
'reshape_2_data': {'shape': np.array([1, 1, 1])},
'power': {'scale': 64.0},
'power_data': {'shape': np.array([1, 1, 1])},
}, nodes_with_edges_only=True)
pattern = ReduceReplacer()
pattern.find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, graph_ref, 'concat', check_op_attrs=True)
self.assertTrue(flag, resp)
def test5(self):
# Original graph
# data(1, 16, 64, 64, 64, 4)-->Reduce(axis=[5],keep_dims=False)-->data(1, 16, 64, 64, 64)
#
# Reference graph
# data(1, 16, 64, 64, 64, 4)->Reshape(1*16*64*64, 64, 4, 1)->Pool(1, 1, 4, 1)->Reshape(1, 16, 64, 64, 64)
#
graph = build_graph(nodes_attributes,
[('placeholder_1_data', 'reduce_1'),
('reduce_1', 'reduce_1_data'),
('reduce_1_data', 'concat'),
],
{'placeholder_1_data': {'shape': np.array([1, 16, 64, 64, 64, 4])},
'reduce_1': {'axis': np.array([5]), 'keep_dims': False, 'reduce_type': 'max'},
'reduce_1_data': {'shape': np.array([1, 16, 64, 64, 64])},
}, nodes_with_edges_only=True)
graph.graph['layout'] = 'NCHW'
graph_ref = build_graph(nodes_attributes,
[('placeholder_1_data', 'reshape_1'),
('reshape_1', 'reshape_1_data'),
('reshape_1_data', 'pooling'),
('pooling', 'pooling_data'),
('pooling_data', 'reshape_2'),
('reshape_2', 'reshape_2_data'),
('reshape_2_data', 'concat'),
],
{'placeholder_1_data': {'shape': np.array([1, 16, 64, 64, 64, 4])},
'reshape_1': {'dim': np.array([65536, 64, 4, 1])},
'reshape_1_data': {'shape': np.array([65536, 64, 4, 1])},
'pooling': {'window': np.array([1, 1, 4, 1])},
'pooling_data': {'shape': np.array([65536, 64, 1, 1])},
'reshape_2': {'dim': np.array([1, 16, 64, 64, 64])},
'reshape_2_data': {'shape': np.array([1, 16, 64, 64, 64])},
}, nodes_with_edges_only=True)
pattern = ReduceReplacer()
pattern.find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, graph_ref, 'concat', check_op_attrs=True)
self.assertTrue(flag, resp)