def test_partial_infer(self):
graph = build_graph(nodes_attributes, edges1, inputs1)
sparse_fill_empty_rows_node = Node(graph,
'sparse_fill_empty_rows_node')
SparseFillEmptyRows.infer(sparse_fill_empty_rows_node)
# prepare reference results
ref_output_indices_shape = int64_array([20, 2])
ref_output_values_shape = int64_array([20])
ref_empty_row_indicator_shape = int64_array([4])
# get resulted shapes
res_output_indices_shape = graph.node['output_indices']['shape']
res_output_values_shape = graph.node['output_values']['shape']
res_empty_row_indicator_shape = graph.node['empty_row_indicator'][
'shape']
self.assertTrue(
np.array_equal(ref_output_indices_shape, res_output_indices_shape),
'shapes do not match expected: {} and given: {}'.format(
ref_output_indices_shape, res_output_indices_shape))
self.assertTrue(
np.array_equal(ref_output_values_shape, res_output_values_shape),
'shapes do not match expected: {} and given: {}'.format(
ref_output_values_shape, res_output_values_shape))
self.assertTrue(
np.array_equal(ref_empty_row_indicator_shape,
res_empty_row_indicator_shape),
'shapes do not match expected: {} and given: {}'.format(
ref_empty_row_indicator_shape, res_empty_row_indicator_shape))
def test_partial_infer_for_some_out_ports(self):
edges = [
('input_indices', 'sparse_fill_empty_rows_node', {
'in': 0
}),
('input_values', 'sparse_fill_empty_rows_node', {
'in': 1
}),
('dense_shape', 'sparse_fill_empty_rows_node', {
'in': 2
}),
('default_value', 'sparse_fill_empty_rows_node', {
'in': 3
}),
('sparse_fill_empty_rows_node', 'output_indices', {
'out': 0
}),
('sparse_fill_empty_rows_node', 'empty_row_indicator', {
'out': 2
}),
('output_indices', 'result_indices', {
'out': 0
}),
('empty_row_indicator', 'result_empty_row_indicator', {
'out': 0
}),
]
graph = build_graph(nodes_attributes, edges, inputs1)
sparse_fill_empty_rows_node = Node(graph,
'sparse_fill_empty_rows_node')
SparseFillEmptyRows.infer(sparse_fill_empty_rows_node)
# prepare reference results
ref_output_indices_shape = int64_array([20, 2])
ref_empty_row_indicator_shape = int64_array([4])
# get resulted shapes
res_output_indices_shape = graph.node['output_indices']['shape']
res_empty_row_indicator_shape = graph.node['empty_row_indicator'][
'shape']
self.assertTrue(
np.array_equal(ref_output_indices_shape, res_output_indices_shape),
'shapes do not match expected: {} and given: {}'.format(
ref_output_indices_shape, res_output_indices_shape))
self.assertTrue(
np.array_equal(ref_empty_row_indicator_shape,
res_empty_row_indicator_shape),
'shapes do not match expected: {} and given: {}'.format(
ref_empty_row_indicator_shape, res_empty_row_indicator_shape))
def extract(cls, node):
attrs = {}
SparseFillEmptyRows.update_node_stat(node, attrs)
return cls.enabled
def extract(node):
attrs = {}
SparseFillEmptyRows.update_node_stat(node, attrs)
return __class__.enabled