# Copyright (c) 2022 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 paddle from paddle.distributed.fleet import auto paddle.enable_static() def make_program(): main_program = paddle.fluid.Program() start_program = paddle.fluid.Program() with paddle.static.program_guard(main_program, start_program): x = paddle.static.data(name='x', shape=[4, 4, 8], dtype='float32') x.stop_gradient = False auto.shard_tensor(x, auto.ProcessMesh([0, 1], dim_names=["x"]), ["x", None, None]) shape = paddle.shape(x) return main_program, start_program def parallelizer(program_func, rank): from paddle.distributed.auto_parallel.completion import Completer from paddle.distributed.auto_parallel.partitioner import Partitioner from paddle.distributed.auto_parallel.dist_context import DistributedContext main_program, start_program = program_func() dist_context = DistributedContext() completer = Completer(dist_context) completer.complete_forward_annotation(main_program) dist_context.block_state.parse_forward_blocks(main_program) partitioner = Partitioner(dist_context, rank) dist_main_prog, _, _ = partitioner.partition(main_program, start_program, []) return dist_main_prog, dist_context class TestDistShape(unittest.TestCase): def test_dist_shape(self): dist_main_prog, dist_context = parallelizer(make_program, 0) ops = dist_main_prog.global_block().ops shape_op = ops[0] dist_op = dist_context.get_dist_op_for_program(shape_op) dist_op.dist_attr.impl_type == "shape" dist_op.dist_attr.impl_idx == 0 in_name = shape_op.input_arg_names[0] out_name = shape_op.output_arg_names[0] in_dims_mapping = dist_op.dist_attr.get_input_dims_mapping(in_name) out_dims_mapping = dist_op.dist_attr.get_output_dims_mapping(out_name) assert in_dims_mapping == [0, -1, -1] assert out_dims_mapping == [-1] if __name__ == "__main__": unittest.main()