提交 22850661 编写于 作者: X Xin Pan

Avoid GetMutable implicitly reset Var Type.

This can cause a lot of problem:
1. Wrong operator implementation, Op can get a wrong type without failure.
2. Anytype can be Get without defined in VarType.

Also fix wrong STEP_SCOPE usage.

test=develop
上级 e1904ac2
......@@ -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) {
......
......@@ -27,8 +27,7 @@ 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<std::vector<paddle::framework::LoDTensor>>());
auto& feed_inputs = *(g_feed_value->GetMutable<FeedFetchList>());
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) {
......
......@@ -38,8 +38,12 @@ class Variable {
template <typename T>
T* GetMutable() {
if (!IsType<T>()) {
if (!holder_) {
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());
}
......
......@@ -33,9 +33,10 @@ TEST(Variable, GetMutable) {
const Tensor& tt = v->Get<Tensor>();
EXPECT_EQ(1234, tt.content_);
std::string* s = v->GetMutable<std::string>();
*s = "hello";
const std::string& ss = v->Get<std::string>();
EXPECT_EQ("hello", ss);
try {
v->GetMutable<std::string>();
} catch (std::exception& e) {
return;
}
EXPECT_TRUE(false);
}
......@@ -56,7 +56,11 @@ def data(name,
Args:
name(str): The name/alias of the function
shape(list): Tuple declaring the shape.
append_batch_size(bool): Whether or not to append the data as a batch.
append_batch_size(bool):
1. If true, it prepends -1 to the shape.
For example if shape=[1], the resulting shape is [-1, 1].
2. If shape contains -1, such as shape=[1, -1],
append_batch_size will be enforced to be be False (ineffective).
dtype(int|float): The type of data : float32, float_16, int etc
type(VarType): The output type. By default it is LOD_TENSOR.
lod_level(int): The LoD Level. 0 means the input data is not a sequence.
......
......@@ -100,7 +100,7 @@ def create_global_var(shape,
force_cpu=False,
name=None):
"""
Create a new variable in the global block(block 0).
Create a new tensor variable with value in the global block(block 0).
Args:
shape(list[int]): shape of the variable
......
......@@ -17,7 +17,6 @@ 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
......@@ -84,18 +83,7 @@ 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:
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())
raise ValueError('is_parallel=True not implemented')
sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
sgd_optimizer.minimize(avg_cost)
......@@ -262,7 +250,7 @@ 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, True):
for is_parallel in (False, ): # TODO(paddle-dev): Add parallel test.
inject_test_method(use_cuda, is_sparse, is_parallel)
if __name__ == '__main__':
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册