未验证 提交 d852be7c 编写于 作者: X Xin Pan 提交者: GitHub

Revert "Make variable::GetMutable robust"

上级 ae8b1c32
......@@ -66,7 +66,7 @@ void InitializeVariable(Variable* var, proto::VarType::Type var_type) {
} else if (var_type == proto::VarType::FETCH_LIST) {
var->GetMutable<FeedFetchList>();
} else if (var_type == proto::VarType::STEP_SCOPES) {
var->GetMutable<std::vector<framework::Scope*>>();
var->GetMutable<std::vector<framework::Scope>>();
} else if (var_type == proto::VarType::LOD_RANK_TABLE) {
var->GetMutable<LoDRankTable>();
} else if (var_type == proto::VarType::LOD_TENSOR_ARRAY) {
......
......@@ -27,7 +27,8 @@ void SetFeedVariable(Scope* scope, const LoDTensor& input,
// be created.
VLOG(3) << "SetFeedVariable name=" << var_name << " index=" << index;
Variable* g_feed_value = scope->Var(var_name);
auto& feed_inputs = *(g_feed_value->GetMutable<FeedFetchList>());
auto& feed_inputs =
*(g_feed_value->GetMutable<std::vector<paddle::framework::LoDTensor>>());
if (index >= feed_inputs.size()) {
feed_inputs.resize(index + 1);
}
......
......@@ -37,7 +37,7 @@ static void InitializeVariable(Variable *var, proto::VarType::Type var_type) {
} else if (var_type == proto::VarType::FETCH_LIST) {
var->GetMutable<FeedFetchList>();
} else if (var_type == proto::VarType::STEP_SCOPES) {
var->GetMutable<std::vector<framework::Scope *>>();
var->GetMutable<std::vector<framework::Scope>>();
} else if (var_type == proto::VarType::LOD_RANK_TABLE) {
var->GetMutable<LoDRankTable>();
} else if (var_type == proto::VarType::LOD_TENSOR_ARRAY) {
......
......@@ -38,12 +38,8 @@ class Variable {
template <typename T>
T* GetMutable() {
if (!holder_) {
if (!IsType<T>()) {
holder_.reset(new PlaceholderImpl<T>(new T()));
} else {
PADDLE_ENFORCE(IsType<T>(),
"Variable must be type %s, the holding type is %s",
typeid(T).name(), holder_->Type().name());
}
return static_cast<T*>(holder_->Ptr());
}
......
......@@ -33,10 +33,9 @@ TEST(Variable, GetMutable) {
const Tensor& tt = v->Get<Tensor>();
EXPECT_EQ(1234, tt.content_);
try {
v->GetMutable<std::string>();
} catch (std::exception& e) {
return;
}
EXPECT_TRUE(false);
std::string* s = v->GetMutable<std::string>();
*s = "hello";
const std::string& ss = v->Get<std::string>();
EXPECT_EQ("hello", ss);
}
......@@ -17,6 +17,7 @@ from __future__ import print_function
import paddle
import paddle.fluid as fluid
from paddle.fluid.layers.device import get_places
from paddle.fluid.layers.control_flow import ParallelDo
import unittest
import os
import numpy as np
......@@ -83,7 +84,18 @@ def train(use_cuda, is_sparse, is_parallel, save_dirname, is_local=True):
avg_cost, predict_word = __network__(
[first_word, second_word, third_word, forth_word, next_word])
else:
raise ValueError('is_parallel=True not implemented')
places = get_places()
pd = ParallelDo(places)
with pd.do():
avg_cost, predict_word = __network__(
list(
map(pd.read_input, [
first_word, second_word, third_word, forth_word,
next_word
])))
pd.write_output(avg_cost)
avg_cost = fluid.layers.mean(pd())
sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
sgd_optimizer.minimize(avg_cost)
......@@ -250,7 +262,7 @@ def inject_test_method(use_cuda, is_sparse, is_parallel):
for use_cuda in (False, True):
for is_sparse in (False, True):
for is_parallel in (False, ): # TODO(paddle-dev): Add parallel test.
for is_parallel in (False, True):
inject_test_method(use_cuda, is_sparse, is_parallel)
if __name__ == '__main__':
......
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