# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved. # # 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 dygraph_to_static_utils import ( Dy2StTestBase, test_ast_only, ) import paddle # The input of concat_grad is no_need_buffer def concat_net(x): y = x + 1 z = paddle.concat([y, y], axis=0) return z class TestNoNeedBuffer(Dy2StTestBase): @test_ast_only def test_no_need_buffer(self): input = paddle.to_tensor([1, 2]) input.stop_gradient = False static_fn = paddle.jit.to_static(concat_net) static_res = static_fn(input) dygraph_res = concat_net(input) np.testing.assert_allclose(static_res.numpy(), dygraph_res.numpy()) _, partial_program_layer = static_fn.get_concrete_program(input) named_values = ( partial_program_layer.program.forward_program._list_named_vars() ) no_need_buffers_names = partial_program_layer.program.program_attr[ "no_need_buffers_names" ] no_need_buffers = [ value := named_values.get(no_need_buffer_name, None) for no_need_buffer_name in no_need_buffers_names ] for no_need_buffer_value in no_need_buffers: if no_need_buffer_value is None: continue defining_op = no_need_buffer_value.get_defining_op() # y = x + 1, it's defining op is `pd_op.scale` if defining_op is not None and defining_op.name() == 'pd_op.scale': break else: raise AssertionError( "middle var `y` should be no_need_buffer value" ) if __name__ == '__main__': unittest.main()