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Merged
merged 10 commits into from
Apr 4, 2020
Merged

Delete Ref & VectorRef and add GetDataSafely #22997

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fc1bbae
delete invalid check inferface Ref & VectorRef, test=develop
chenwhql Mar 13, 2020
bf3dacd
fix vector ref delete error, test=develop
chenwhql Mar 13, 2020
4edae75
resolve conflict
chenwhql Mar 30, 2020
efd2280
try the new check inferface, test=develop
chenwhql Mar 31, 2020
9cd5c7b
change all related code with new check macro, test=develop
chenwhql Apr 1, 2020
f17b969
remove static assert, test=develop
chenwhql Apr 2, 2020
7b32e15
polish detail, test=develop
chenwhql Apr 2, 2020
6b7ea05
skip coverage problem, test=develop
chenwhql Apr 3, 2020
56d8322
resolve conflict, test=develop
chenwhql Apr 3, 2020
616e030
add new check macro, test=develop
chenwhql Apr 3, 2020
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4 changes: 2 additions & 2 deletions paddle/fluid/operators/activation_cudnn.cu.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -31,8 +31,8 @@ class CudnnActivationKernel
ExtractActivationTensor(context, X, Out);
ActivationDescriptor act_desc;
TensorDescriptor x_desc, out_desc;
x_desc.set(detail::Ref(X));
out_desc.set(detail::Ref(Out));
x_desc.set(GET_DATA_SAFELY(X, "Input", "X", "CudnnActivation"));
out_desc.set(GET_DATA_SAFELY(Out, "Output", "Out", "CudnnActivation");
}
};

Expand Down
11 changes: 7 additions & 4 deletions paddle/fluid/operators/activation_cudnn_op.cu.cc
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Expand Up @@ -37,7 +37,7 @@ struct CudnnActivationFunctor {
act_desc.set(mode_, coef_);
TensorDescriptor x_desc, out_desc;
x_desc.set(x);
out_desc.set(detail::Ref(out));
out_desc.set(GET_DATA_SAFELY(out, "Output", "Out", "CudnnActivation"));
PADDLE_ENFORCE(platform::dynload::cudnnActivationForward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), x_desc.desc(), x.data<T>(),
Expand All @@ -63,7 +63,7 @@ struct CudnnActivationGradFunctor {
x_desc.set(x);
out_desc.set(out);
dout_desc.set(dout);
dx_desc.set(detail::Ref(dx));
dx_desc.set(GET_DATA_SAFELY(dx, "Output", "X@GRAD", "CudnnActivationGrad"));
PADDLE_ENFORCE(platform::dynload::cudnnActivationBackward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), out_desc.desc(), out.data<T>(),
Expand Down Expand Up @@ -141,7 +141,7 @@ class CudnnActivationKernel
Out->mutable_data<T>(context.GetPlace());
auto& dev_ctx = context.template device_context<CUDADeviceContext>();
Functor functor(dev_ctx);
functor(detail::Ref(X), Out);
functor(GET_DATA_SAFELY(X, "Input", "X", "CudnnActivation"), Out);
}
};

Expand All @@ -161,7 +161,10 @@ class CudnnActivationGradKernel
dX->mutable_data<T>(context.GetPlace());
auto& dev_ctx = context.template device_context<CUDADeviceContext>();
Functor functor(dev_ctx);
functor(detail::Ref(X), detail::Ref(Out), detail::Ref(dOut), dX);
functor(GET_DATA_SAFELY(X, "Input", "X", "CudnnActivationGrad"),
GET_DATA_SAFELY(Out, "Input", "Out", "CudnnActivationGrad"),
GET_DATA_SAFELY(dOut, "Input", "Out@GRAD", "CudnnActivationGrad"),
dX);
}
};

Expand Down
100 changes: 66 additions & 34 deletions paddle/fluid/operators/activation_op.h
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Expand Up @@ -26,7 +26,6 @@ limitations under the License. */

#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/platform/float16.h"

Expand Down Expand Up @@ -156,8 +155,10 @@ class ActivationKernel
ExtractActivationTensor(context, &X, &Out);
Out->mutable_data<T>(context.GetPlace());

auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "Activation"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "Activation"));
auto* place =
context.template device_context<DeviceContext>().eigen_device();
Functor functor;
Expand All @@ -182,10 +183,14 @@ class ActivationGradKernel
ExtractActivationGradTensor<Functor::FwdDeps()>(context, &X, &Out, &dOut,
&dX);
dX->mutable_data<T>(context.GetPlace());
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Input", "Out@GRAD", "ActivationGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Input", "Out", "ActivationGrad"));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Input", "X@GRAD", "ActivationGrad"));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "ActivationGrad"));
auto* place =
context.template device_context<DeviceContext>().eigen_device();
Functor functor;
Expand Down Expand Up @@ -1285,10 +1290,13 @@ struct ReluGradGradFunctor : public BaseActivationFunctor<T> {
framework::Tensor* ddOut, framework::Tensor* dOut,
framework::Tensor* dX) const {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "ReluGradGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "ReluGradGrad"));
if (ddOut) {
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DDOut", "ReluGradGrad"));
ddout.device(*d) = ddx * (out > static_cast<T>(0)).template cast<T>();
}
}
Expand All @@ -1308,9 +1316,12 @@ struct LeakyReluGradGradFunctor : public BaseActivationFunctor<T> {
framework::Tensor* dX) const {
if (ddOut) {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "LeakyReluGradGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "LeakyReluGradGrad"));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DOut", "LeakyReluGradGrad"));
ddout.device(*d) = ddx *
((out > static_cast<T>(0)).template cast<T>() +
static_cast<T>(alpha) *
Expand All @@ -1332,18 +1343,23 @@ struct ELUGradGradFunctor : public BaseActivationFunctor<T> {
const framework::Tensor* ddX, framework::Tensor* ddOut,
const framework::Tensor* dOut, framework::Tensor* dX) const {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "ELUGradGrad"));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "ELUGradGrad"));

if (dX) {
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Output", "DX", "ELUGradGrad"));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Output", "DOut", "ELUGradGrad"));
dx.device(*d) = ddx * dout * static_cast<T>(alpha) * x.exp() *
(x < static_cast<T>(0)).template cast<T>();
}

if (ddOut) {
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DDOut", "ELUGradGrad"));
ddout.device(*d) = ddx *
((x > static_cast<T>(0)).template cast<T>() +
static_cast<T>(alpha) * x.exp() *
Expand All @@ -1361,17 +1377,22 @@ struct SqrtGradGradFunctor : public BaseActivationFunctor<T> {
const framework::Tensor* ddX, framework::Tensor* ddOut,
framework::Tensor* dOut, const framework::Tensor* dX) const {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "SqrtGradGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "SqrtGradGrad"));
// sqrt GradGrad: ddy = 0.5 * ddx / y, dy = -1 * dx * ddx
// calculate dy first, so ddy can inplace ddx
if (dOut) {
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Output", "DX", "SqrtGradGrad"));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Output", "DOut", "SqrtGradGrad"));
dout.device(*d) = dx * ddx * static_cast<T>(-1) / out;
}
if (ddOut) {
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DDOut", "SqrtGradGrad"));
ddout.device(*d) = ddx * static_cast<T>(0.5) / out;
}
}
Expand All @@ -1385,17 +1406,22 @@ struct SquareGradGradFunctor : public BaseActivationFunctor<T> {
const framework::Tensor* ddX, framework::Tensor* ddOut,
const framework::Tensor* dOut, framework::Tensor* dX) const {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "SquareGradGrad"));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "SquareGradGrad"));
// square GradGrad: ddy=2x*ddx, dx=2dy*ddx
// calculate dx first, so ddy can inplace ddx
if (dX) {
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Output", "DX", "SquareGradGrad"));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Output", "DOut", "SquareGradGrad"));
dx.device(*d) = ddx * static_cast<T>(2) * dout;
}
if (ddOut) {
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DDOut", "SquareGradGrad"));
ddout.device(*d) = ddx * static_cast<T>(2) * x;
}
}
Expand Down Expand Up @@ -1557,8 +1583,10 @@ class PowKernel : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
ExtractActivationTensor(context, &X, &Out);
Out->mutable_data<T>(context.GetPlace());

auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "Pow"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "Pow"));
auto* place =
context.template device_context<DeviceContext>().eigen_device();
Functor functor;
Expand Down Expand Up @@ -1602,10 +1630,14 @@ class PowGradKernel
ExtractActivationGradTensor<Functor::FwdDeps()>(context, &X, &Out, &dOut,
&dX);
dX->mutable_data<T>(context.GetPlace());
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Input", "Out@GRAD", "PowGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Input", "Out", "PowGrad"));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Output", "X@GRAD", "PowGrad"));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "PowGrad"));
auto* place =
context.template device_context<DeviceContext>().eigen_device();
Functor functor;
Expand Down
1 change: 0 additions & 1 deletion paddle/fluid/operators/add_position_encoding_op.h
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Expand Up @@ -15,7 +15,6 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"

namespace paddle {
namespace operators {
Expand Down
8 changes: 3 additions & 5 deletions paddle/fluid/operators/controlflow/get_places_op.cc
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Expand Up @@ -14,7 +14,6 @@ limitations under the License. */

#include <thread> // NOLINT
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/platform/place.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/gpu_info.h"
Expand Down Expand Up @@ -56,10 +55,9 @@ class GetPlacesOp : public framework::OperatorBase {
is_gpu ? "GPU" : "CPU");

auto out_var_name = Output("Out");
auto &places =
*(detail::Ref(scope.FindVar(out_var_name),
"Output variable %s cannot be found", out_var_name)
.GetMutable<platform::PlaceList>());
auto &places = *(GET_DATA_SAFELY(scope.FindVar(out_var_name), "Output",
"Out", "GetPlaces")
.GetMutable<platform::PlaceList>());
places.reserve(device_count);
if (is_gpu) {
PADDLE_ENFORCE_LE(device_count, CUDADevCount(),
Expand Down
1 change: 0 additions & 1 deletion paddle/fluid/operators/controlflow/tensor_array_read_write_op.cc
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Expand Up @@ -12,7 +12,6 @@ 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/operators/array_operator.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/math_function.h"

namespace paddle {
Expand Down
14 changes: 4 additions & 10 deletions paddle/fluid/operators/controlflow/while_op.cc
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Expand Up @@ -19,7 +19,6 @@
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/var_type.h"
#include "paddle/fluid/operators/controlflow/while_op_helper.h"
#include "paddle/fluid/operators/detail/safe_ref.h"

namespace paddle {
namespace operators {
Expand Down Expand Up @@ -198,23 +197,18 @@ class WhileGradOp : public framework::OperatorBase {
continue;
}

auto &og_outside =
detail::Ref(scope.FindVar(outside_og_name),
"Cannot find Outside Gradient %s", outside_og_name);
auto &og_inside =
detail::Ref(cur_scope.Var(inside_og_name),
"Cannot find inside gradient %s", inside_og_name);
auto &og_outside = *scope.FindVar(outside_og_name);
auto &og_inside = *cur_scope.Var(inside_og_name);
if (og_outside.IsType<framework::LoDTensor>()) {
auto &outside_tensor = og_outside.Get<framework::LoDTensor>();
auto &inside_tensor =
detail::Ref(og_inside.GetMutable<framework::LoDTensor>());
auto &inside_tensor = *og_inside.GetMutable<framework::LoDTensor>();
inside_tensor.set_lod(outside_tensor.lod());
inside_tensor.ShareDataWith(outside_tensor);
} else if (og_outside.IsType<framework::LoDTensorArray>()) {
auto outside_array =
og_outside.GetMutable<framework::LoDTensorArray>();
auto &inside_array =
detail::Ref(og_inside.GetMutable<framework::LoDTensorArray>());
*og_inside.GetMutable<framework::LoDTensorArray>();
inside_array.clear();
inside_array.resize(outside_array->size());
VLOG(8) << outside_og_name << " size = " << outside_array->size();
Expand Down
6 changes: 2 additions & 4 deletions paddle/fluid/operators/conv_op.h
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Expand Up @@ -20,7 +20,6 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/operators/math/depthwise_conv.h"
#include "paddle/fluid/operators/math/im2col.h"
Expand Down Expand Up @@ -674,9 +673,8 @@ class GemmConvDoubleGradKernel : public framework::OpKernel<T> {
Tensor* ddY = ctx.Output<Tensor>("DDOutput");
Tensor* dW = ctx.Output<Tensor>("DFilter");
Tensor* dX = ctx.Output<Tensor>("DInput");
Tensor W = detail::Ref(ctx.Input<Tensor>("Filter"),
"Cannot find input Filter(%s) in scope)",
ctx.InputNames("Filter")[0]);
Tensor W = GET_DATA_SAFELY(ctx.Input<Tensor>("Filter"), "Input", "Filter",
"GemmConvDoubleGrad");
if (!ddY && !dW && !dX) return;

const int groups = ctx.Attr<int>("groups");
Expand Down
13 changes: 5 additions & 8 deletions paddle/fluid/operators/cum_op.h
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Expand Up @@ -18,7 +18,6 @@ limitations under the License. */
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/operators/detail/safe_ref.h"

namespace paddle {
namespace operators {
Expand All @@ -29,13 +28,11 @@ class CumKernel : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
using T = typename Functor::ELEMENT_TYPE;

void Compute(const framework::ExecutionContext& context) const override {
auto& X = detail::Ref(context.Input<framework::Tensor>("X"),
"Cannot get input tensor X, variable name = %s",
context.InputName("X"));
auto& X = GET_DATA_SAFELY(context.Input<framework::Tensor>("X"), "Input",
"X", "Cum");

auto& Out = detail::Ref(context.Output<framework::Tensor>("Out"),
"Cannot get output tensor Out, variable name = %s",
context.OutputName("Out"));
auto& Out = GET_DATA_SAFELY(context.Output<framework::Tensor>("Out"),
"Output", "Out", "Cum");
int axis = context.Attr<int>("axis");
bool exclusive = context.Attr<bool>("exclusive");
bool reverse = context.Attr<bool>("reverse");
Expand All @@ -46,7 +43,7 @@ class CumKernel : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
PADDLE_ENFORCE_LT(
axis, x_dims.size(),
"axis should be less than the dimensiotn of the input tensor");
Out.mutable_data<T>(context.GetPlace());
Out.template mutable_data<T>(context.GetPlace());

int pre = 1;
int post = 1;
Expand Down
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