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add reader dependency pass, test=develop (PaddlePaddle#23301)
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112 changes: 112 additions & 0 deletions
112
paddle/fluid/framework/ir/multi_devices_graph_pass/add_reader_dependency_pass.cc
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// Copyright (c) 2020 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. | ||
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#include <queue> | ||
#include <unordered_set> | ||
#include "paddle/fluid/framework/ir/pass.h" | ||
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namespace paddle { | ||
namespace framework { | ||
namespace ir { | ||
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class AddReaderDependencyPass : public Pass { | ||
protected: | ||
void ApplyImpl(Graph *graph) const override; | ||
}; | ||
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static std::unordered_set<Node *> FindAllPrecedingOpNodes(Node *node) { | ||
std::unordered_set<Node *> result; | ||
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std::queue<Node *> q; | ||
q.push(node); | ||
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while (!q.empty()) { | ||
auto *cur_node = q.front(); | ||
q.pop(); | ||
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for (auto &in_var : cur_node->inputs) { | ||
for (auto &in_op : in_var->inputs) { | ||
if (result.count(in_op) == 0 && in_op != node) { | ||
result.insert(in_op); | ||
q.push(in_op); | ||
} | ||
} | ||
} | ||
} | ||
return result; | ||
} | ||
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void AddReaderDependencyPass::ApplyImpl(Graph *graph) const { | ||
const auto &nodes = graph->Nodes(); | ||
std::unordered_set<Node *> ops; | ||
std::unordered_set<Node *> read_ops; | ||
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for (auto &n : nodes) { | ||
if (n->IsOp() && n->Op()) { | ||
ops.insert(n); | ||
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if (n->Op()->Type() == "read") { | ||
read_ops.insert(n); | ||
} | ||
} | ||
} | ||
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VLOG(10) << "Found " << read_ops.size() << " read op(s)"; | ||
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if (read_ops.empty()) { | ||
return; | ||
} | ||
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// Find all startup ops | ||
std::unordered_set<Node *> out_ops; | ||
for (auto &op : ops) { | ||
for (auto &out_var : op->outputs) { | ||
for (auto &out_op : out_var->outputs) { | ||
out_ops.insert(out_op); | ||
} | ||
} | ||
} | ||
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for (auto &out_op : out_ops) { | ||
ops.erase(out_op); | ||
} | ||
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VLOG(10) << "Found " << ops.size() << " startup ops"; | ||
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for (auto &read_op : read_ops) { | ||
auto preceding_ops = FindAllPrecedingOpNodes(read_op); | ||
for (auto &startup_op : ops) { | ||
if (read_op == startup_op || preceding_ops.count(startup_op) > 0) { | ||
VLOG(10) << "Startup op " << startup_op->Op()->Type() << " is skipped"; | ||
continue; | ||
} | ||
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auto *dep_var = graph->CreateControlDepVar(); | ||
read_op->outputs.push_back(dep_var); | ||
startup_op->inputs.push_back(dep_var); | ||
dep_var->inputs.push_back(read_op); | ||
dep_var->outputs.push_back(startup_op); | ||
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VLOG(10) << "Add dependencies between " << read_op->Op()->Type() | ||
<< " and " << startup_op->Op()->Type(); | ||
} | ||
} | ||
} | ||
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} // namespace ir | ||
} // namespace framework | ||
} // namespace paddle | ||
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REGISTER_PASS(add_reader_dependency_pass, | ||
paddle::framework::ir::AddReaderDependencyPass); |
107 changes: 107 additions & 0 deletions
107
python/paddle/fluid/tests/unittests/test_add_reader_dependency.py
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# Copyright (c) 2020 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. | ||
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import paddle.fluid as fluid | ||
from paddle.fluid.layer_helper import LayerHelper | ||
import unittest | ||
import numpy as np | ||
import time | ||
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def inplace_add(x, bias): | ||
helper = LayerHelper('scale', **locals()) | ||
helper.append_op( | ||
type='scale', | ||
inputs={'X': [x]}, | ||
outputs={'Out': [x]}, | ||
attrs={'bias': bias}) | ||
return x | ||
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class TestAddReaderDependency(unittest.TestCase): | ||
def setUp(self): | ||
self.batch_num = 3 | ||
self.sleep_time = 2 | ||
self.use_double_buffer = True | ||
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def test_main(self): | ||
self.run_main(fluid.CPUPlace()) | ||
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if fluid.is_compiled_with_cuda(): | ||
self.run_main(fluid.CUDAPlace(0)) | ||
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def run_main(self, place): | ||
with fluid.program_guard(fluid.Program(), fluid.Program()): | ||
with fluid.scope_guard(fluid.Scope()): | ||
tmp_in = fluid.data(name='tmp_in', dtype='float32', shape=[1]) | ||
loader = fluid.io.DataLoader.from_generator( | ||
feed_list=[tmp_in], | ||
capacity=16, | ||
iterable=False, | ||
use_double_buffer=self.use_double_buffer) | ||
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def data_source(): | ||
for _ in range(self.batch_num): | ||
time.sleep(self.sleep_time) # sleep some times | ||
yield np.random.uniform( | ||
low=-1, high=1, size=[1]).astype('float32'), | ||
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persistable_in = fluid.data( | ||
name='persistable_in', dtype='float32', shape=[1]) | ||
persistable_in.persistable = True | ||
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persistable_in = inplace_add(persistable_in, bias=1) | ||
prog = fluid.CompiledProgram(fluid.default_main_program()) | ||
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exe = fluid.Executor(place) | ||
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loader.set_batch_generator(data_source) | ||
loader.start() | ||
batch_id = 0 | ||
try: | ||
while True: | ||
if batch_id == 0: | ||
feed = { | ||
persistable_in.name: | ||
np.array([-1]).astype('float32') | ||
} | ||
else: | ||
feed = None | ||
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ret, = exe.run(prog, | ||
feed=feed, | ||
fetch_list=[persistable_in]) | ||
self.assertEqual(ret.shape, (1, )) | ||
self.assertEqual(ret[0], batch_id) | ||
batch_id += 1 | ||
except fluid.core.EOFException: | ||
loader.reset() | ||
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self.assertEqual(batch_id, self.batch_num) | ||
t = fluid.global_scope().find_var( | ||
persistable_in.name).get_tensor() | ||
t_val = np.array(t) | ||
self.assertEqual(t_val.shape, (1, )) | ||
self.assertEqual(t_val[0] + 1, batch_id) | ||
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class TestAddReaderDependencyWithoutDoubleBuffer(TestAddReaderDependency): | ||
def setUp(self): | ||
self.batch_num = 3 | ||
self.sleep_time = 2 | ||
self.use_double_buffer = False | ||
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if __name__ == '__main__': | ||
unittest.main() |