提交 3e917a93 编写于 作者: S sneaxiy

add scope_pool

add module cleanup
test=develop
上级 00dadb07
......@@ -60,7 +60,7 @@ class Float16Transpiler:
raise TypeError("place should be as CPUPlace/CUDAPlace type")
if scope is None:
scope = global_scope()
if not isinstance(scope, core.Scope):
if not isinstance(scope, core._Scope):
raise TypeError("scope should be as Scope type or None")
self.scope = scope
......
......@@ -84,6 +84,7 @@ cc_library(threadpool SRCS threadpool.cc DEPS enforce)
cc_test(threadpool_test SRCS threadpool_test.cc DEPS threadpool)
cc_library(scope SRCS scope.cc DEPS glog threadpool)
cc_library(scope_pool SRCS scope_pool.cc DEPS scope)
cc_test(scope_test SRCS scope_test.cc DEPS scope)
cc_library(data_device_transform SRCS data_device_transform.cc DEPS tensor)
......
// 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.
#include "paddle/fluid/framework/scope_pool.h"
#include "paddle/fluid/framework/threadpool.h"
namespace paddle {
namespace framework {
ScopePool &ScopePool::Instance() { // NOLINT
static ScopePool pool;
return pool;
}
void ScopePool::DeleteScope(Scope *scope) { delete scope; }
void ScopePool::Insert(std::unique_ptr<Scope> &&s) {
std::lock_guard<std::mutex> guard(mtx_);
scopes_.insert(s.release());
}
void ScopePool::Remove(Scope *s) {
size_t has_scope;
{
std::lock_guard<std::mutex> guard(mtx_);
has_scope = scopes_.erase(s);
}
PADDLE_ENFORCE(has_scope > 0, "Delete non-existing global scope");
DeleteScope(s);
}
ScopePool::~ScopePool() { Clear(); }
void ScopePool::Clear() {
std::lock_guard<std::mutex> guard(mtx_);
for (auto *s : scopes_) {
DeleteScope(s);
}
scopes_.clear();
}
} // namespace framework
} // namespace paddle
// 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.
#pragma once
#include <mutex> // NOLINT
#include <unordered_set>
#include "paddle/fluid/framework/scope.h"
namespace paddle {
namespace framework {
class ScopePool {
public:
static ScopePool &Instance(); // NOLINT
void Insert(std::unique_ptr<Scope> &&s);
void Remove(Scope *s);
void Clear();
~ScopePool();
private:
ScopePool() = default;
static void DeleteScope(Scope *scope);
std::unordered_set<Scope *> scopes_;
std::mutex mtx_;
};
} // namespace framework
} // namespace paddle
set(PYBIND_DEPS pybind python proto_desc memory executor async_executor prune feed_fetch_method pass_builder parallel_executor profiler layer)
set(PYBIND_DEPS pybind python proto_desc memory executor async_executor prune feed_fetch_method pass_builder parallel_executor profiler layer scope_pool)
if(WITH_PYTHON)
list(APPEND PYBIND_DEPS py_func_op)
endif()
......
......@@ -32,6 +32,7 @@ limitations under the License. */
#include "paddle/fluid/framework/parallel_executor.h"
#include "paddle/fluid/framework/prune.h"
#include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/framework/scope_pool.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/framework/version.h"
#include "paddle/fluid/imperative/layer.h"
......@@ -117,6 +118,9 @@ PYBIND11_MODULE(core, m) {
return paddle::operators::AppendPythonCallableObjectAndReturnId(py_obj);
});
m.add_object("_cleanup",
py::capsule([]() { ScopePool::Instance().Clear(); }));
py::class_<imperative::VarBase, PyVarBase>(m, "VarBase", R"DOC()DOC")
.def(py::init<>())
.def("_run_backward",
......@@ -454,7 +458,7 @@ All parameter, weight, gradient are variables in Paddle.
},
py::return_value_policy::copy);
py::class_<Scope>(m, "Scope", R"DOC(
py::class_<Scope>(m, "_Scope", R"DOC(
Scope is an association of a name to Variable. All variables belong to Scope.
Variables in a parent scope can be retrieved from local scope.
......@@ -474,17 +478,26 @@ All parameter, weight, gradient are variables in Paddle.
param.set(param_array, place)
)DOC")
.def("_remove_from_pool",
[](Scope &self) { ScopePool::Instance().Remove(&self); })
.def("var",
[](Scope &self, const std::string &name) -> Variable * {
return self.Var(name);
},
py::return_value_policy::reference)
.def("find_var", &Scope::FindVar, py::return_value_policy::reference)
.def(py::init<>())
.def("new_scope", [](Scope &self) -> Scope * { return &self.NewScope(); },
py::return_value_policy::reference)
.def("drop_kids", &Scope::DropKids);
m.def("Scope",
[]() -> Scope * {
auto *s = new Scope();
ScopePool::Instance().Insert(std::unique_ptr<Scope>(s));
return s;
},
py::return_value_policy::reference);
//! @note: Be careful! PyBind will return std::string as an unicode, not
//! Python str. If you want a str object, you should cast them in Python.
m.def("get_all_op_protos", []() -> std::vector<py::bytes> {
......
......@@ -46,7 +46,7 @@ from . import transpiler
from . import distribute_lookup_table
from .param_attr import ParamAttr, WeightNormParamAttr
from .data_feeder import DataFeeder
from .core import LoDTensor, LoDTensorArray, CPUPlace, CUDAPlace, CUDAPinnedPlace, Scope
from .core import LoDTensor, LoDTensorArray, CPUPlace, CUDAPlace, CUDAPinnedPlace, Scope, _Scope
from .transpiler import DistributeTranspiler, \
memory_optimize, release_memory, DistributeTranspilerConfig
from .lod_tensor import create_lod_tensor, create_random_int_lodtensor
......
......@@ -191,7 +191,7 @@ def _fetch_var(name, scope=None, return_numpy=True):
assert isinstance(name, str)
if scope is None:
scope = global_scope()
assert isinstance(scope, core.Scope)
assert isinstance(scope, core._Scope)
var = scope.find_var(name)
assert var is not None, (
......
......@@ -26,7 +26,7 @@ os.environ['CPU_NUM'] = str(dev_cnt)
def dummy_func_with_no_input():
return float(1.0)
return np.array([0], dtype='float32')
def dummy_func_with_no_output(x):
......@@ -105,7 +105,7 @@ def simple_fc_net(img, label, use_py_func_op):
name='test_tmp_var', dtype='float32', shape=[1])
fluid.layers.py_func(
func=dummy_func_with_no_input, x=None, out=dummy_var)
loss += dummy_var
fluid.layers.py_func(func=dummy_func_with_no_output, x=loss, out=None)
loss = fluid.layers.mean(loss)
......@@ -174,7 +174,7 @@ class TestPyFuncOpUseExecutor(unittest.TestCase):
self.assertAlmostEqual(max_diff, 0, delta=1e-3)
class TestPyFuncOpUseParallelExecutor(unittest.TestCase):
class TestPyFuncOpUseParallelExecutor(TestPyFuncOpUseExecutor):
def setUp(self):
self.use_parallel_executor = True
......
......@@ -57,7 +57,7 @@ class InferenceTranspiler(object):
raise TypeError("place should be as CPUPlace/CUDAPlace type")
if scope is None:
scope = global_scope()
if not isinstance(scope, core.Scope):
if not isinstance(scope, core._Scope):
raise TypeError("scope should be as Scope type or None")
use_mkldnn = bool(os.getenv("FLAGS_use_mkldnn", False))
......
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