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93 lines
3.1 KiB
93 lines
3.1 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import paddle
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import paddle.fluid as fluid
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import numpy as np
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import sys
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startup_prog = fluid.framework.Program()
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startup_block = startup_prog.current_block()
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random_reader = startup_block.create_var(
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type=fluid.core.VarDesc.VarType.READER, name="RandomDataGenerator")
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random_reader.desc.set_dtypes(
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[fluid.core.VarDesc.VarType.FP32, fluid.core.VarDesc.VarType.FP32])
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random_reader.persistable = True
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shuffle_reader = startup_block.create_var(
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type=fluid.core.VarDesc.VarType.READER, name="ShuffleReader")
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shuffle_reader.persistable = True
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batch_reader = startup_block.create_var(
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type=fluid.core.VarDesc.VarType.READER, name="BatchReader")
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batch_reader.persistable = True
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double_buffer = startup_block.create_var(
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type=fluid.core.VarDesc.VarType.READER, name="DoubleBuffer")
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double_buffer.persistable = True
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main_prog = startup_prog.clone()
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main_block = main_prog.current_block()
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create_random_data_generator_op = startup_block.append_op(
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type="create_random_data_generator",
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outputs={"Out": random_reader},
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attrs={
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"shape_concat": [1, 2, 1, 1],
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"ranks": [2, 2],
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"low": 0.0,
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"high": 1.0,
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'lod_levels': [0, 0]
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})
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create_shuffle_reader_op = startup_block.append_op(
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type="create_shuffle_reader",
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inputs={"UnderlyingReader": random_reader},
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outputs={"Out": shuffle_reader},
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attrs={"buffer_size": 7})
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create_batch_reader_op = startup_block.append_op(
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type="create_batch_reader",
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inputs={"UnderlyingReader": shuffle_reader},
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outputs={"Out": batch_reader},
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attrs={"batch_size": 10})
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create_double_buffer_reader_op = startup_block.append_op(
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type="create_double_buffer_reader",
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inputs={"UnderlyingReader": batch_reader},
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outputs={"Out": double_buffer})
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out1 = main_block.create_var(
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type=fluid.core.VarDesc.VarType.LOD_TENSOR, name="Out1")
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out2 = main_block.create_var(
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type=fluid.core.VarDesc.VarType.LOD_TENSOR, name="Out2")
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main_block.var("DoubleBuffer").desc.set_shapes(double_buffer.desc.shapes())
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main_block.var("DoubleBuffer").desc.set_dtypes(double_buffer.desc.dtypes())
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main_block.var("DoubleBuffer").desc.set_lod_levels(
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double_buffer.desc.lod_levels())
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read_op = main_block.append_op(
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type="read",
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inputs={"Reader": double_buffer},
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outputs={"Out": [out1, out2]})
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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exe.run(startup_prog)
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for i in range(1, 100):
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[res1, res2] = exe.run(main_prog, fetch_list=[out1, out2])
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if not (res1.shape == (10, 2) and res2.shape == (10, 1)):
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exit(1)
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