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test_cpp_reader.py
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94 lines (79 loc) · 3.14 KB
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# 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.
from __future__ import print_function
import paddle
import paddle.fluid as fluid
import numpy as np
import sys
startup_prog = fluid.framework.Program()
startup_block = startup_prog.current_block()
random_reader = startup_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])
random_reader.persistable = True
shuffle_reader = startup_block.create_var(
type=fluid.core.VarDesc.VarType.READER, name="ShuffleReader")
shuffle_reader.persistable = True
batch_reader = startup_block.create_var(
type=fluid.core.VarDesc.VarType.READER, name="BatchReader")
batch_reader.persistable = True
double_buffer = startup_block.create_var(
type=fluid.core.VarDesc.VarType.READER, name="DoubleBuffer")
double_buffer.persistable = True
main_prog = startup_prog.clone()
main_block = main_prog.current_block()
create_random_data_generator_op = startup_block.append_op(
type="create_random_data_generator",
outputs={"Out": random_reader},
attrs={
"shape_concat": [1, 2, 1, 1],
"ranks": [2, 2],
"low": 0.0,
"high": 1.0,
'lod_levels': [0, 0]
})
create_shuffle_reader_op = startup_block.append_op(
type="create_shuffle_reader",
inputs={"UnderlyingReader": random_reader},
outputs={"Out": shuffle_reader},
attrs={"buffer_size": 7})
create_batch_reader_op = startup_block.append_op(
type="create_batch_reader",
inputs={"UnderlyingReader": shuffle_reader},
outputs={"Out": batch_reader},
attrs={"batch_size": 10})
create_double_buffer_reader_op = startup_block.append_op(
type="create_double_buffer_reader",
inputs={"UnderlyingReader": batch_reader},
outputs={"Out": double_buffer})
out1 = main_block.create_var(
type=fluid.core.VarDesc.VarType.LOD_TENSOR, name="Out1")
out2 = main_block.create_var(
type=fluid.core.VarDesc.VarType.LOD_TENSOR, name="Out2")
main_block.var("DoubleBuffer").desc.set_shapes(double_buffer.desc.shapes())
main_block.var("DoubleBuffer").desc.set_dtypes(double_buffer.desc.dtypes())
main_block.var("DoubleBuffer").desc.set_lod_levels(
double_buffer.desc.lod_levels())
read_op = main_block.append_op(
type="read",
inputs={"Reader": double_buffer},
outputs={"Out": [out1, out2]})
place = fluid.CPUPlace()
exe = fluid.Executor(place)
exe.run(startup_prog)
for i in range(1, 100):
[res1, res2] = exe.run(main_prog, fetch_list=[out1, out2])
if not (res1.shape == (10, 2) and res2.shape == (10, 1)):
exit(1)