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未验证 提交 99a4ff8f 编写于 作者: L Leo Chen 提交者： GitHub
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[new-exec] support runing with different scope and the same program using scope_guard (#43962) 

* support scope_guard

* fix test
上级 8279dfea
隐藏空白更改
内联 并排
Showing with 47 addition and 24 deletion
paddle/fluid/framework/new_executor/standalone_executor.cc
浏览文件 @ 99a4ff8f
......@@ -28,44 +28,50 @@ StandaloneExecutor::StandaloneExecutor(const platform::Place& place,
scope_(scope) {
// NOTE(zhiqiu): for startup_program, run once ?
if (startup_prog.Block(0).AllOps().size() > 0) {
auto core = GetInterpreterCore(startup_prog, {}, {}, false);
auto core = GetInterpreterCore(scope, startup_prog, {}, {}, false);
VLOG(4) << "StandaloneExecutor: " << this << ", InterpreterCore: " << core;
core->Run({});
}
}
paddle::framework::FetchList StandaloneExecutor::Run(
Scope* scope,
const std::vector<std::string>& feed_names,
const std::vector<framework::LoDTensor>& feed_tensors,
const std::vector<std::string>& fetch_names) {
platform::RecordEvent record_event(
"StandaloneExecutor::run", platform::TracerEventType::UserDefined, 1);
auto core = GetInterpreterCore(main_prog_, feed_names, fetch_names, true);
auto core =
GetInterpreterCore(scope, main_prog_, feed_names, fetch_names, true);
return core->Run(feed_names, feed_tensors);
}
paddle::framework::FetchList StandaloneExecutor::Run(
Scope* scope,
const std::vector<std::string>& feed_names,
const std::vector<std::string>& fetch_names) {
platform::RecordEvent record_event(
"StandaloneExecutor::run", platform::TracerEventType::UserDefined, 1);
auto core = GetInterpreterCore(main_prog_, feed_names, fetch_names, false);
auto core =
GetInterpreterCore(scope, main_prog_, feed_names, fetch_names, false);
VLOG(4) << "StandaloneExecutor: " << this << ", InterpreterCore: " << core;
return core->Run(feed_names);
}
framework::interpreter::CostInfo StandaloneExecutor::DryRun(
Scope* scope,
const std::vector<std::string>& feed_names,
const std::vector<framework::LoDTensor>& feed_tensors) {
auto core = GetInterpreterCore(main_prog_, feed_names, {}, true);
auto core = GetInterpreterCore(scope, main_prog_, feed_names, {}, true);
return core->DryRun(feed_names, feed_tensors);
}
std::shared_ptr<InterpreterCore> StandaloneExecutor::GetInterpreterCore(
Scope* scope,
const ProgramDesc& prog,
const std::vector<std::string>& feed_names,
const std::vector<std::string>& fetch_names,
......@@ -79,6 +85,7 @@ std::shared_ptr<InterpreterCore> StandaloneExecutor::GetInterpreterCore(
for (auto& fetchname : fetch_names) {
oss << fetchname << ",";
}
oss << "scope:" << scope;
auto iter = interpretercores_.find(oss.str());
......@@ -89,13 +96,13 @@ std::shared_ptr<InterpreterCore> StandaloneExecutor::GetInterpreterCore(
std::shared_ptr<InterpreterCore> core = nullptr;
if (add_fetch_op) {
core = CreateInterpreterCore(place_, prog, scope_, fetch_names);
core = CreateInterpreterCore(place_, prog, scope, fetch_names);
} else {
core = std::make_shared<InterpreterCore>(
place_,
prog.Block(0),
/*skip_gc_vars=*/std::set<std::string>(),
scope_);
scope);
}
interpretercores_.emplace(oss.str(), core);
return core;
......
paddle/fluid/framework/new_executor/standalone_executor.h
浏览文件 @ 99a4ff8f
......@@ -39,6 +39,7 @@ class StandaloneExecutor {
~StandaloneExecutor() {}
paddle::framework::FetchList Run(
Scope* scope,
const std::vector<std::string>& feed_names,
const std::vector<framework::LoDTensor>& feed_tensors,
const std::vector<std::string>& fetch_names);
......@@ -46,15 +47,18 @@ class StandaloneExecutor {
// NOTE(zhiqiu): feed_names are only used for caching interpretercore.
// fetch_names are used for caching interpretercore and inserting fetch ops,
// the latter can be moved to python side.
paddle::framework::FetchList Run(const std::vector<std::string>& feed_names,
paddle::framework::FetchList Run(Scope* scope,
const std::vector<std::string>& feed_names,
const std::vector<std::string>& fetch_names);
framework::interpreter::CostInfo DryRun(
Scope* scope,
const std::vector<std::string>& feed_names,
const std::vector<framework::LoDTensor>& feed_tensors);
private:
std::shared_ptr<InterpreterCore> GetInterpreterCore(
Scope* scope,
const ProgramDesc& prog,
const std::vector<std::string>& feed_names,
const std::vector<std::string>& fetch_names,
......
paddle/fluid/pybind/pybind.cc
浏览文件 @ 99a4ff8f
......@@ -3063,6 +3063,7 @@ All parameter, weight, gradient are variables in Paddle.
Scope *>())
.def("run",
[](StandaloneExecutor &self,
Scope *scope,
const std::unordered_map<std::string, py::array> &input_dict,
std::vector<std::string> fetch_names) {
std::vector<framework::LoDTensor> feed_tensors;
......@@ -3079,12 +3080,13 @@ All parameter, weight, gradient are variables in Paddle.
paddle::framework::FetchList ret;
{
pybind11::gil_scoped_release release;
ret = self.Run(feed_names, feed_tensors, fetch_names);
ret = self.Run(scope, feed_names, feed_tensors, fetch_names);
}
return py::cast(std::move(ret));
})
.def("run",
[](StandaloneExecutor &self,
Scope *scope,
const std::unordered_map<std::string, framework::LoDTensor>
&input_dict,
std::vector<std::string> fetch_names) {
......@@ -3099,23 +3101,25 @@ All parameter, weight, gradient are variables in Paddle.
paddle::framework::FetchList ret;
{
pybind11::gil_scoped_release release;
ret = self.Run(feed_names, feed_tensors, fetch_names);
ret = self.Run(scope, feed_names, feed_tensors, fetch_names);
}
return py::cast(std::move(ret));
})
.def("run",
[](StandaloneExecutor &self,
Scope *scope,
std::vector<std::string> feed_names,
std::vector<std::string> fetch_names) {
paddle::framework::FetchList ret;
{
pybind11::gil_scoped_release release;
ret = self.Run(feed_names, fetch_names);
ret = self.Run(scope, feed_names, fetch_names);
}
return py::cast(std::move(ret));
})
.def("dry_run",
[](StandaloneExecutor &self,
Scope *scope,
const std::unordered_map<std::string, py::array> &input_dict) {
std::vector<framework::LoDTensor> feed_tensors;
std::vector<std::string> feed_names;
......@@ -3131,7 +3135,7 @@ All parameter, weight, gradient are variables in Paddle.
framework::interpreter::CostInfo cost_info;
{
pybind11::gil_scoped_release release;
cost_info = self.DryRun(feed_names, feed_tensors);
cost_info = self.DryRun(scope, feed_names, feed_tensors);
}
return cost_info;
});
......
python/paddle/fluid/executor.py
浏览文件 @ 99a4ff8f
......@@ -537,7 +537,7 @@ class _StandaloneExecutor(object):
self._scope = scope
self._new_exe = self._create_new_executor()
def run(self, feed_names, fetch_list, return_numpy=True):
def run(self, scope, feed_names, fetch_list, return_numpy=True):
"""
Args:
feed_names(list): This parameter represents the input names of the model.
......@@ -549,7 +549,8 @@ class _StandaloneExecutor(object):
"""
fetch_list = self._check_fetch(fetch_list)
tensors = self._new_exe.run(feed_names, fetch_list)._move_to_list()
tensors = self._new_exe.run(scope, feed_names,
fetch_list)._move_to_list()
if return_numpy:
return as_numpy(tensors, copy=True)
else:
......@@ -1470,7 +1471,8 @@ class Executor(object):
cpu_tensor = _as_lodtensor(data, core.CPUPlace())
tensor._copy_from(cpu_tensor, self.place)
return new_exe.run(list(feed.keys()), fetch_list, return_numpy)
return new_exe.run(scope, list(feed.keys()), fetch_list,
return_numpy)
compiled = isinstance(program, compiler.CompiledProgram)
......
python/paddle/fluid/tests/unittests/interpreter/test_standalone_executor.py
浏览文件 @ 99a4ff8f
......@@ -50,27 +50,30 @@ class LinearTestCase(unittest.TestCase):
def test_interp_base(self):
startup_program, main_program, c = self.build_program()
scope = core.Scope()
standaloneexecutor = StandaloneExecutor(self.place,
startup_program.desc,
main_program.desc, core.Scope())
main_program.desc, scope)
out = standaloneexecutor.run(
{"a": np.ones([2, 2], dtype="float32") * 2}, [c.name])
scope, {"a": np.ones([2, 2], dtype="float32") * 2}, [c.name])
for i in range(10):
out = standaloneexecutor.run(
{"a": np.ones([2, 2], dtype="float32") * i}, [c.name])
scope, {"a": np.ones([2, 2], dtype="float32") * i}, [c.name])
for i in range(10):
out = standaloneexecutor.run(
{"a": np.ones([2, 2], dtype="float32") * i}, ['a', c.name])
scope, {"a": np.ones([2, 2], dtype="float32") * i},
['a', c.name])
def test_dry_run(self):
scope = core.Scope()
startup_program, main_program, c = self.build_program()
standaloneexecutor = StandaloneExecutor(self.place,
startup_program.desc,
main_program.desc, core.Scope())
main_program.desc, scope)
# test for cost_info
cost_info = standaloneexecutor.dry_run(
{"a": np.ones([2, 2], dtype="float32")})
scope, {"a": np.ones([2, 2], dtype="float32")})
self.check_cost_info(cost_info)
def check_cost_info(self, cost_info):
......@@ -132,14 +135,15 @@ class ExecutorStatisticsTestCase(unittest.TestCase):
p = core.Place()
p.set_place(self.place)
scope = core.Scope()
executor = StandaloneExecutor(p, startup_program.desc,
main_program.desc, core.Scope())
main_program.desc, scope)
helper_profiler = profiler.Profiler(
targets=[profiler.ProfilerTarget.CPU], scheduler=(1, 2))
helper_profiler.start()
for i in range(self.iter_n):
executor.run({}, fetch_list)
executor.run(scope, {}, fetch_list)
helper_profiler.step()
helper_profiler.stop()
......@@ -251,13 +255,15 @@ class MultiStreamModelTestCase(unittest.TestCase):
p = core.Place()
p.set_place(self.place)
scope = core.Scope()
inter_core = StandaloneExecutor(p, startup_program.desc,
main_program.desc, core.Scope())
main_program.desc, scope)
outs = []
for i in range(self.iter_n):
outs.append(
np.array(inter_core.run({}, fetch_list)._move_to_list()[0]))
np.array(
inter_core.run(scope, {}, fetch_list)._move_to_list()[0]))
return outs
......
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