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update-doc-pybind
zchen0211 9 years ago
parent 299dcb6715
commit 39d79e6419
5 changed files with 53 additions and 41 deletions
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11
paddle/framework/tensor.h
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@ -78,9 +78,6 @@ class Tensor {
template <typename T>
inline T* mutable_data(DDim dims, platform::Place place);
/*! Size of a single element in data() */
inline size_t element_size() { return holder_->element_size(); }
/*! Return the dimensions of the memory block. */
inline const DDim& dims() const;
@ -132,7 +129,6 @@ class Tensor {
virtual ~Placeholder() {}
virtual void* ptr() const = 0;
virtual size_t size() const = 0;
virtual size_t element_size() const = 0;
virtual std::type_index type() const = 0;
virtual platform::Place place() const = 0;
};
@ -143,8 +139,7 @@ class Tensor {
: ptr_(static_cast<T*>(memory::Alloc(place, size)),
memory::PODDeleter<T, Place>(place)),
place_(place),
size_(size),
element_size_(sizeof(T)) {
size_(size) {
PADDLE_ENFORCE_NOT_NULL(ptr_, "Insufficient %s memory to allocation.",
(is_cpu_place(place_) ? "CPU" : "GPU"));
}
@ -153,7 +148,6 @@ class Tensor {
virtual platform::Place place() const { return place_; }
virtual void* ptr() const { return static_cast<void*>(ptr_.get()); }
virtual std::type_index type() const { return std::type_index(typeid(T)); }
virtual size_t element_size() const { return element_size_; }
/*! the pointer of memory block. */
std::unique_ptr<T, memory::PODDeleter<T, Place>> ptr_;
@ -163,9 +157,6 @@ class Tensor {
/*! the size of memory block. */
size_t size_;
/*! the size of a single element */
size_t element_size_;
};
/*! holds the memory block if allocated. */

8
paddle/framework/tensor_test.cc
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@ -36,7 +36,7 @@ TEST(Tensor, DataAssert) {
} catch (paddle::platform::EnforceNotMet err) {
caught = true;
std::string msg =
"holder_ should not be null\nTenosr holds no memory. Call "
"holder_ should not be null\nTensor holds no memory. Call "
"Tensor::mutable_data first.";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
@ -59,8 +59,6 @@ TEST(Tensor, MutableData) {
// initialization
p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
EXPECT_NE(p1, nullptr);
// check tensor type
EXPECT_EQ(src_tensor.element_size(), sizeof(float));
// set src_tensor a new dim with large size
// momery is supposed to be re-allocated
p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), CPUPlace());
@ -114,7 +112,7 @@ TEST(Tensor, ShareDataWith) {
} catch (paddle::platform::EnforceNotMet err) {
caught = true;
std::string msg =
"holder_ should not be null\nTenosr holds no memory. Call "
"holder_ should not be null\nTensor holds no memory. Call "
"Tensor::mutable_data first.";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
@ -276,4 +274,4 @@ TEST(Tensor, ReshapeToMatrix) {
Tensor res = ReshapeToMatrix<int>(src, 2);
ASSERT_EQ(res.dims()[0], 2 * 3);
ASSERT_EQ(res.dims()[1], 4 * 9);
}
}

3
paddle/operators/CMakeLists.txt
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@ -80,8 +80,7 @@ endfunction()
add_subdirectory(math)
set(DEPS_OPS
recurrent_op)
set(DEPS_OPS
recurrent_op
cond_op)
op_library(recurrent_op SRCS recurrent_op.cc rnn/recurrent_op_utils.cc
DEPS framework_proto tensor net_op)

55
paddle/operators/cond_op.cc
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@ -28,6 +28,7 @@ namespace operators {
using Scope = framework::Scope;
using Variable = framework::Variable;
using Tensor = framework::Tensor;
using LoDTensor = framework::LoDTensor;
using DDim = framework::DDim;
void CondOp::CreateScope(const Scope& scope) const {
@ -41,8 +42,9 @@ void CondOp::CreateScope(const Scope& scope) const {
void CondOp::CreateIndexTensor(const Scope& scope) const {
auto index_tensors_var = scope.FindVar("IndexTensors");
PADDLE_ENFORCE(index_tensors_var != nullptr, "");
auto& index_tensors = *index_tensors_var->GetMutable<std::vector<Tensor>>();
index_tensors.push_back(Tensor());
auto& index_tensors =
*index_tensors_var->GetMutable<std::vector<LoDTensor>>();
index_tensors.push_back(LoDTensor());
}
void CondOp::InferShape(const Scope& scope) const {
@ -65,8 +67,8 @@ void CondOp::InferShape(const Scope& scope) const {
for (auto& input : Inputs("Xs")) {
// Create a new tensor in sub-scope for input-type tensor
Variable* v = sub_scopes[i]->NewVar(input);
Tensor* sub_input = v->GetMutable<Tensor>();
sub_input->Resize(scope.FindVar(input)->GetMutable<Tensor>()->dims());
LoDTensor* sub_input = v->GetMutable<LoDTensor>();
sub_input->Resize(scope.FindVar(input)->GetMutable<LoDTensor>()->dims());
}
for (auto& output : (*sub_net_op_[i]).Outputs()) {
@ -80,33 +82,40 @@ void CondOp::InferShape(const Scope& scope) const {
}
for (auto& output : Outputs("Outs")) {
Tensor* tensor_t_out = sub_scopes[0]->FindVar(output)->GetMutable<Tensor>();
PADDLE_ENFORCE_NOT_NULL(tensor_t_out, "True output should be NULL");
Tensor* tensor_f_out = sub_scopes[1]->FindVar(output)->GetMutable<Tensor>();
PADDLE_ENFORCE_NOT_NULL(tensor_f_out, "True output should be NULL");
LoDTensor* tensor_t_out =
sub_scopes[0]->FindVar(output)->GetMutable<LoDTensor>();
PADDLE_ENFORCE_NOT_NULL(tensor_t_out, "True output should not be NULL");
LoDTensor* tensor_f_out =
sub_scopes[1]->FindVar(output)->GetMutable<LoDTensor>();
PADDLE_ENFORCE_NOT_NULL(tensor_f_out, "False output should not be NULL");
auto* tensor_out_var = scope.FindVar(output);
PADDLE_ENFORCE_NOT_NULL(tensor_out_var, "Output not found");
Tensor* tensor_out = tensor_out_var->GetMutable<Tensor>();
PADDLE_ENFORCE_NOT_NULL(tensor_t_out, "True output should be NULL");
LoDTensor* tensor_out = tensor_out_var->GetMutable<LoDTensor>();
PADDLE_ENFORCE_NOT_NULL(tensor_t_out,
"True output tensor should not be NULL");
// check output size should be same
PADDLE_ENFORCE_EQ(tensor_t_out->dims(), tensor_f_out->dims(),
"Outputs not of the same shape");
tensor_out->Resize(tensor_t_out->dims());
tensor_out->mutable_data<float>(tensor_out->dims(), platform::CPUPlace());
// tensor_out->mutable_data<float>(tensor_out->dims(),
// platform::CPUPlace());
tensor_out->mutable_data<float>(platform::CPUPlace());
}
}
void CondOp::Run(const Scope& scope,
const platform::DeviceContext& dev_ctx) const {
auto sub_scopes = scope.FindVar("SubScopes")->Get<std::vector<Scope*>>();
auto index_tensors =
scope.FindVar("IndexTensors")->Get<std::vector<Tensor>>();
auto* sub_scopes_var = scope.FindVar("SubScopes");
auto sub_scopes = sub_scopes_var->Get<std::vector<Scope*>>();
auto* index_tensors_var = scope.FindVar("IndexTensors");
auto index_tensors = index_tensors_var->Get<std::vector<LoDTensor>>();
std::string cond_name = Input("Cond");
Variable* cond_var = scope.FindVar(cond_name);
PADDLE_ENFORCE_NOT_NULL(cond_var);
const Tensor* cond = cond_var->GetMutable<Tensor>();
const LoDTensor* cond = cond_var->GetMutable<LoDTensor>();
// Step 1: get the true/false index at runtime
// index_[0]: vector<int>, contains all index for cond[i] == true
@ -139,11 +148,11 @@ void CondOp::Run(const Scope& scope,
// find Tensor
Variable* v = scope.FindVar(input);
PADDLE_ENFORCE_NOT_NULL(v);
Tensor* tensor_parent = v->GetMutable<Tensor>();
LoDTensor* tensor_parent = v->GetMutable<LoDTensor>();
v = sub_scopes[i]->FindVar(input);
PADDLE_ENFORCE_NOT_NULL(v);
Tensor* tensor_child = v->GetMutable<Tensor>();
LoDTensor* tensor_child = v->GetMutable<LoDTensor>();
// Resize child
DDim dim = tensor_child->dims();
@ -157,7 +166,9 @@ void CondOp::Run(const Scope& scope,
}
// Step 3: run
for (int i = 0; i < 2; ++i) sub_net_op_[i]->Run(*sub_scopes[i], dev_ctx);
for (int i = 0; i < 2; ++i) {
sub_net_op_[i]->Run(*sub_scopes[i], dev_ctx);
}
// Step 4: merge output results
for (int i = 0; i < 2; ++i) {
@ -166,11 +177,11 @@ void CondOp::Run(const Scope& scope,
// find Tensor
Variable* v = scope.FindVar(output);
PADDLE_ENFORCE_NOT_NULL(v);
Tensor* tensor_parent = v->GetMutable<Tensor>();
LoDTensor* tensor_parent = v->GetMutable<LoDTensor>();
v = sub_scopes[i]->FindVar(output);
PADDLE_ENFORCE_NOT_NULL(v);
Tensor* tensor_child = v->GetMutable<Tensor>();
LoDTensor* tensor_child = v->GetMutable<LoDTensor>();
ScatterUpdate<float>(dev_ctx.GetPlace(), tensor_child, &index_tensors[i],
tensor_parent);
@ -192,7 +203,9 @@ class CondOpProtoAndCheckerMaker : public framework::OpProtoAndCheckerMaker {
AddComment(R"DOC(
Sample dependent Cond Operator:
The equation is: Out[i] = subnet_t[i], if Cond[i] == true
Given Cond[i] as a 1/0 vector to indicate true/false
The equation is:
Out[i] = subnet_t[i], if Cond[i] == true
Out[i] = subnet_t[i], if Cond[i] == false
)DOC");
}

17
paddle/operators/cond_op.h
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@ -24,6 +24,17 @@ limitations under the License. */
namespace paddle {
namespace operators {
/*
* @brief CondOp is a dynamic if-else Operator
*
* It has a input tensor named cond indicating which netop each instance will
* run.
*
* if cond == 1, it will run true_net, which is a NetOp.
*
* if cond == 0, it will run false_net, which is another NetOp.
*/
class CondOp : public framework::OperatorBase {
public:
CondOp(const std::string& type, const framework::VariableNameMap& inputs,
@ -45,18 +56,18 @@ class CondOp : public framework::OperatorBase {
void CreateIndexTensor(const framework::Scope& scope) const;
/**
/*
* InferShape must be called before Run.
*/
void InferShape(const framework::Scope& scope) const override;
// Set True Block
void set_truenet(std::unique_ptr<OperatorBase> net) {
void set_truenet(std::unique_ptr<OperatorBase>&& net) {
sub_net_op_[0] = std::move(net);
}
// Set False Block
void set_falsenet(std::unique_ptr<OperatorBase> net) {
void set_falsenet(std::unique_ptr<OperatorBase>&& net) {
sub_net_op_[1] = std::move(net);
}

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