# Copyright (c) 2018 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 paddle.v2 as paddle import paddle.fluid as fluid import numpy as np prog = fluid.framework.Program() block = prog.current_block() random_reader = block.create_var( type=fluid.core.VarDesc.VarType.READER, name="RandomDataGenerator") random_reader.desc.set_dtypes( [fluid.core.VarDesc.VarType.FP32, fluid.core.VarDesc.VarType.FP32]) create_random_data_generator_op = block.append_op( type="create_random_data_generator", outputs={"Out": random_reader}, attrs={ "shape_concat": [1, 2, 1, 1], "ranks": [2, 2], "min": 0.0, "max": 1.0, 'lod_levels': [0, 0] }) shuffle_reader = block.create_var( type=fluid.core.VarDesc.VarType.READER, name="ShuffleReader") create_shuffle_reader_op = block.append_op( type="create_shuffle_reader", inputs={"UnderlyingReader": random_reader}, outputs={"Out": shuffle_reader}, attrs={"buffer_size": 7}) batch_reader = block.create_var( type=fluid.core.VarDesc.VarType.READER, name="BatchReader") create_batch_reader_op = block.append_op( type="create_batch_reader", inputs={"UnderlyingReader": shuffle_reader}, outputs={"Out": batch_reader}, attrs={"batch_size": 10}) out1 = block.create_var(type=fluid.core.VarDesc.VarType.LOD_TENSOR, name="Out1") out2 = block.create_var(type=fluid.core.VarDesc.VarType.LOD_TENSOR, name="Out2") read_op = block.append_op( type="read", inputs={"Reader": batch_reader}, outputs={"Out": [out1, out2]}) place = fluid.CPUPlace() exe = fluid.Executor(place) [res1, res2] = exe.run(prog, fetch_list=[out1, out2]) if not (res1.shape == (10, 2) and res2.shape == (10, 1)): exit(1) exit(0)