def test_4D_multiple_consumers(self):
input_shape = int64_array([1, 300, 300, 3])
axes = int64_array([1, 2, 3])
weights_value = np.ones(shape=int64_array([input_shape[-1]]), dtype=np.float32)
graph = build_graph_with_attrs(nodes + [
('input', dict(kind='op', shape=input_shape, op='Parameter', data_type=np.float32)),
('input_data', dict(kind='data', shape=input_shape, data_type=np.float32)),
('square_data', dict(kind='data', shape=input_shape)),
('sum_axes_data', dict(kind='data', value=axes, shape=None)),
('result_2', dict(kind='op', op='Result'))
], edges + [('input_data', 'result_2')], nodes_with_edges_only=True)
graph.stage = 'middle'
L2NormToNorm().find_and_replace_pattern(graph)
graph_ref = build_graph_with_attrs(nodes + [
('input', dict(kind='op', shape=input_shape, op='Parameter', data_type=np.float32)),
('input_data', dict(kind='data', shape=input_shape, data_type=np.float32)),
('weights_node_data', dict(kind='data', value=axes.sort())),
('result_2', dict(kind='op', op='Result'))
], edges_after_replacement + [('input_data', 'result_2')], nodes_with_edges_only=True)
(flag, resp) = compare_graphs(graph, graph_ref, 'result', check_op_attrs=True)
self.assertTrue(graph.node[graph.get_nodes_with_attributes(type='NormalizeL2')[0]]['name'] == 'l2_norm_name')
self.assertTrue(flag, resp)
def test_positive(self, input_shape, axes, layout):
graph = build_graph_with_attrs(nodes + [
('input', dict(kind='op', shape=input_shape, op='Parameter', data_type=np.float32)),
('input_data', dict(kind='data', shape=input_shape, data_type=np.float32)),
('square_data', dict(kind='data', shape=input_shape)),
('sum_axes_data', dict(kind='data', value=axes, shape=None)),
], edges, nodes_with_edges_only=True)
graph.stage = 'middle'
graph.graph['layout'] = layout
L2NormToNorm().find_and_replace_pattern(graph)
graph_ref = build_graph_with_attrs(nodes + [
('input', dict(kind='op', shape=input_shape, op='Parameter', data_type=np.float32)),
('input_data', dict(kind='data', shape=input_shape, data_type=np.float32)),
('weights_node_data', dict(kind='data', value=axes.sort())),
], edges_after_replacement, nodes_with_edges_only=True)
(flag, resp) = compare_graphs(graph, graph_ref, 'result', check_op_attrs=True)
self.assertTrue(graph.node[graph.get_nodes_with_attributes(type='NormalizeL2')[0]]['name'] == 'l2_norm_name')
self.assertTrue(flag, resp)
def test_negative(self, input_shape, axes, layout):
graph = build_graph_with_attrs(nodes + [
('input', dict(kind='op', shape=input_shape, op='Parameter', data_type=np.float32)),
('input_data', dict(kind='data', shape=input_shape, data_type=np.float32)),
('square_data', dict(kind='data', shape=input_shape)),
('sum_axes_data', dict(kind='data', value=axes, shape=None)),
], edges, nodes_with_edges_only=True)
graph.stage = 'middle'
graph.graph['layout'] = layout
L2NormToNorm().find_and_replace_pattern(graph)
graph_ref = build_graph_with_attrs(nodes + [
('input', dict(kind='op', shape=input_shape, op='Parameter', data_type=np.float32)),
('input_data', dict(kind='data', shape=input_shape, data_type=np.float32)),
('square_data', dict(kind='data', shape=input_shape)),
('sum_axes_data', dict(kind='data', value=axes, shape=None)),
], edges, nodes_with_edges_only=True)
(flag, resp) = compare_graphs(graph, graph_ref, 'result', check_op_attrs=True)
self.assertTrue(flag, resp)
def test_4D_negative_4(self):
input_shape = int64_array([1, 300, 300, 3])
axes = int64_array([2, 0])
graph = build_graph_with_attrs(nodes + [
('input', dict(kind='op', shape=input_shape, op='Parameter', data_type=np.float32)),
('input_data', dict(kind='data', shape=input_shape, data_type=np.float32)),
('square_data', dict(kind='data', shape=input_shape)),
('sum_axes_data', dict(kind='data', value=axes, shape=None)),
], edges, nodes_with_edges_only=True)
graph.stage = 'middle'
L2NormToNorm().find_and_replace_pattern(graph)
graph_ref = build_graph_with_attrs(nodes + [
('input', dict(kind='op', shape=input_shape, op='Parameter', data_type=np.float32)),
('input_data', dict(kind='data', shape=input_shape, data_type=np.float32)),
('square_data', dict(kind='data', shape=input_shape)),
('sum_axes_data', dict(kind='data', value=axes, shape=None)),
], edges, nodes_with_edges_only=True)
(flag, resp) = compare_graphs(graph, graph_ref, 'result', check_op_attrs=True)
self.assertTrue(flag, resp)