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未验证 提交 4e23ba32 编写于 作者: A Aurelius84 提交者： GitHub
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[PTen]Migrate Dim and DDim from paddle::framework into pten namespace (#39053) 

* Migrate Dim and DDim from paddle::framework into pten namespace

* fix paddle::framework::Array

* fix framework::Array
上级 cf6516ff
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Showing with 734 addition and 574 deletion
paddle/fluid/framework/CMakeLists.txt
浏览文件 @ 4e23ba32
......@@ -55,14 +55,6 @@ proto_library(trainer_desc_proto SRCS trainer_desc.proto DEPS framework_proto
cc_library(string_array SRCS string_array.cc DEPS utf8proc)
cc_library(ddim SRCS ddim.cc DEPS eigen3 boost enforce)
cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
if(WITH_GPU)
nv_test(dim_test SRCS dim_test.cu DEPS ddim)
elseif(WITH_ROCM)
hip_test(dim_test SRCS dim_test.cu DEPS ddim)
endif()
cc_test(unroll_array_ops_test SRCS unroll_array_ops_test.cc)
cc_library(data_type SRCS data_type.cc DEPS framework_proto ddim device_context)
cc_test(data_type_test SRCS data_type_test.cc DEPS data_type place tensor)
if(WITH_GPU)
......
paddle/fluid/framework/ddim.h
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......@@ -14,237 +14,13 @@ limitations under the License. */
#pragma once
#include <initializer_list>
#include <stdexcept>
#include <string>
#include <vector>
#include "paddle/fluid/framework/dim.h"
#include "paddle/pten/core/ddim.h"
namespace paddle {
namespace framework {
#define PADDLE_VISIT_DDIM_BASE(rank, callback) \
case (rank): { \
constexpr auto kRank = (rank); \
return (callback); \
}
#define PADDLE_VISIT_DDIM(rank, callback) \
switch (rank) { \
PADDLE_VISIT_DDIM_BASE(0, callback); \
PADDLE_VISIT_DDIM_BASE(1, callback); \
PADDLE_VISIT_DDIM_BASE(2, callback); \
PADDLE_VISIT_DDIM_BASE(3, callback); \
PADDLE_VISIT_DDIM_BASE(4, callback); \
PADDLE_VISIT_DDIM_BASE(5, callback); \
PADDLE_VISIT_DDIM_BASE(6, callback); \
PADDLE_VISIT_DDIM_BASE(7, callback); \
PADDLE_VISIT_DDIM_BASE(8, callback); \
PADDLE_VISIT_DDIM_BASE(9, callback); \
default: \
PADDLE_THROW(platform::errors::Unimplemented( \
"Invalid dimension to be accessed. Now only supports access to " \
"dimension 0 to 9, but received dimension is %d.", \
rank)); \
}
template <typename T1, typename T2>
inline void dynamic_dim_assign(const T1* in, T2* out, int n) {
PADDLE_VISIT_DDIM(n, (static_dim_assign<kRank, T1, T2>(in, out)));
}
/**
* \brief A dynamically sized dimension.
*
* The number of dimensions must be between [1, 9].
*/
class DDim {
public:
constexpr static int kMaxRank = 9;
DDim() : rank_(1) { dim_[0] = 0; }
DDim(const DDim& ddim) : dim_() { CopyFrom(ddim); }
DDim(const int* d, int n) : rank_(n) {
dynamic_dim_assign(d, dim_.GetMutable(), n);
}
DDim(const int64_t* d, int n) : rank_(n) {
dynamic_dim_assign(d, dim_.GetMutable(), n);
}
template <int D>
/*implicit*/ DDim(const Dim<D>& in) : rank_(D) { // NOLINT
UnsafeCast<D>() = in;
}
/*implicit*/ DDim(std::initializer_list<int64_t> init_list)
: DDim(init_list.begin(), init_list.size()) {}
inline DDim& operator=(const DDim& ddim) { return CopyFrom(ddim); }
template <int D>
inline DDim& operator=(const Dim<D>& dim) {
rank_ = D;
UnsafeCast<D>() = dim;
return *this;
}
inline int64_t& operator[](int idx) { return dim_[idx]; }
inline int64_t operator[](int idx) const { return dim_[idx]; }
int64_t& at(int idx) {
PADDLE_ENFORCE_GE(idx, 0,
platform::errors::InvalidArgument(
"Invalid DDim index to be accessed. The valid index "
"is between 0 and %d, but received index is %d.",
rank_, idx));
PADDLE_ENFORCE_LT(idx, rank_,
platform::errors::InvalidArgument(
"Invalid DDim index to be accessed. The valid index "
"is between 0 and %d, but received index is %d.",
rank_, idx));
return dim_[idx];
}
int64_t at(int idx) const {
PADDLE_ENFORCE_GE(idx, 0,
platform::errors::InvalidArgument(
"Invalid DDim index to be accessed. The valid index "
"is between 0 and %d, but received index is %d.",
rank_, idx));
PADDLE_ENFORCE_LT(idx, rank_,
platform::errors::InvalidArgument(
"Invalid DDim index to be accessed. The valid index "
"is between 0 and %d, but received index is %d.",
rank_, idx));
return dim_[idx];
}
template <typename Visitor>
typename std::result_of<Visitor(Dim<0>&)>::type apply_visitor(
Visitor&& visitor) {
PADDLE_VISIT_DDIM(rank_, visitor(UnsafeCast<kRank>()));
}
template <typename Visitor>
typename std::result_of<Visitor(const Dim<0>&)>::type apply_visitor(
Visitor&& visitor) const {
PADDLE_VISIT_DDIM(rank_, visitor(UnsafeCast<kRank>()));
}
bool operator==(const DDim& d) const;
bool operator!=(const DDim& d) const;
inline const int64_t* Get() const { return dim_.Get(); }
inline int64_t* GetMutable() { return dim_.GetMutable(); }
inline int size() const { return rank_; }
std::string to_str() const;
DDim reshape(const std::vector<int>& shape) const;
DDim transpose(const std::vector<int>& axis) const;
private:
template <int D>
inline Dim<D>& UnsafeCast() {
static_assert(D >= 0 && D <= kMaxRank, "Invalid rank");
auto* p = static_cast<void*>(&dim_);
return *reinterpret_cast<Dim<D>*>(p);
}
template <int D>
inline const Dim<D>& UnsafeCast() const {
static_assert(D >= 0 && D <= kMaxRank, "Invalid rank");
auto* p = static_cast<const void*>(&dim_);
return *reinterpret_cast<const Dim<D>*>(p);
}
inline DDim& CopyFrom(const DDim& ddim) {
PADDLE_VISIT_DDIM(ddim.rank_, (*this = ddim.UnsafeCast<kRank>()));
}
friend DDim stride(const DDim& ddim);
friend DDim stride_numel(const DDim& ddim);
private:
Dim<kMaxRank> dim_;
int rank_;
};
#undef PADDLE_VISIT_DDIM_BASE
#undef PADDLE_VISIT_DDIM
/**
* \brief Make a DDim from std::vector<int64_t>
*
* \param dims An vector of ints. Must be sized between [1, 9]
*/
DDim make_ddim(const std::vector<int64_t>& dims);
DDim make_ddim(const std::vector<int>& dims);
/**
* \brief Make a DDim from an initializer list
*
* \param dims An initializer list of ints. Must be sized between [1, 9]
*
*/
DDim make_ddim(std::initializer_list<int64_t> dims);
template <typename T = int64_t>
std::vector<T> vectorize(const DDim& ddim) {
std::vector<T> result(DDim::kMaxRank);
dynamic_dim_assign(ddim.Get(), result.data(), ddim.size());
result.resize(ddim.size());
return result;
}
int64_t product(const DDim& ddim);
bool contain_unknown_dim(const DDim& ddim);
/**
* \brief Slice a ddim
*
* Slice dim with [begin, end).
* e.g. DDim d = make_ddim({1,2,3,4,5});
* slice_ddim(d, 1, 3); ====> {2,3}
*/
DDim slice_ddim(const DDim& dim, int begin, int end);
/**
* \brief What is the length of this dimension?
*
* \param Dynamic dimension to inspect
*/
int arity(const DDim& ddim);
std::ostream& operator<<(std::ostream&, const DDim&);
/**
* \brief Flatten dim to 3d
* e.g., DDim d = mak_ddim({1, 2, 3, 4, 5, 6})
* flatten_to_3d(d, 2, 4); ===> {1*2, 3*4, 5*6} ===> {2, 12, 30}
*/
DDim flatten_to_3d(const DDim& src, int num_row_dims, int num_col_dims);
// Reshape a tensor to a matrix. The matrix's first dimension(column length)
// will be the product of tensor's first `num_col_dims` dimensions.
DDim flatten_to_2d(const DDim& src, int num_col_dims);
DDim flatten_to_1d(const DDim& src);
DDim stride(const DDim& ddim);
using DDim = pten::framework::DDim;
using namespace pten::framework; // NOLINT
DDim stride_numel(const DDim& ddim);
} // namespace framework
} // namespace paddle
paddle/fluid/framework/dim.h
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......@@ -12,89 +12,13 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include <iostream>
#include <sstream>
#include <stdexcept>
#include <string>
#include <type_traits>
#include "paddle/fluid/framework/array.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/dim.h"
namespace paddle {
namespace framework {
// Statically sized, statically indexed dimension
template <int D>
class Dim : public Array<int64_t, D> {
public:
static_assert(D >= 0, "D must be not less than 0");
static constexpr int kRank = D;
using BaseClass = Array<int64_t, D>;
inline Dim(int64_t head, const Dim<D - 1>& tail) {
(*this)[0] = head;
new (this->GetMutable() + 1) Dim<D - 1>(tail);
}
template <typename... Args>
HOSTDEVICE explicit Dim(int64_t head, Args... args)
: BaseClass(head, args...) {}
/** Construct a Dim with each dimension set to the given index */
HOSTDEVICE explicit Dim(int64_t idx) { this->Fill(idx); }
HOSTDEVICE Dim() = default;
HOST std::string to_string() const;
};
// Product of a Dim
template <int D>
HOSTDEVICE inline int64_t product(const Dim<D>& a) {
return UnrollProduct<D>::Run(a.Get());
}
/**
* Helper function to create a Dim
*
* \param idxes The type of Dim constructed depends on the number of params
*
*/
template <typename... Args>
HOSTDEVICE inline Dim<sizeof...(Args)> make_dim(Args... idxes) {
return Dim<sizeof...(Args)>(idxes...);
}
// Allows us to output a Dim
template <int D>
inline std::ostream& operator<<(std::ostream& os, const Dim<D>& d) {
os << d[0];
for (int i = 1; i < D; ++i) {
os << ", " << d[i];
}
return os;
}
inline std::ostream& operator<<(std::ostream& os, const Dim<0>& d) {
return os;
}
template <int D>
HOST std::string Dim<D>::to_string() const {
std::stringstream stream;
stream << *this;
return stream.str();
}
template <int D, typename T1, typename T2>
inline void static_dim_assign(const T1* in, T2* out) {
UnrollAssign<D>::Run(in, out);
}
using Dim = pten::framework::Dim<D>;
using namespace pten::framework; // NOLINT
} // namespace framework
} // namespace paddle
paddle/fluid/operators/amp/check_finite_and_unscale_op.h
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......@@ -18,7 +18,7 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/operators/isfinite_op.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/amp/update_loss_scaling_op.h
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......@@ -24,7 +24,7 @@
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/errors.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/bce_loss_op.cu
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......@@ -17,7 +17,7 @@ limitations under the License. */
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/platform/device/gpu/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/bernoulli_op.h
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......@@ -14,7 +14,7 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/bilateral_slice_op.h
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......@@ -13,7 +13,7 @@
#include <string>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/bincount_op.cu
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......@@ -16,7 +16,7 @@ limitations under the License. */
#include "paddle/fluid/operators/bincount_op.h"
#include "paddle/fluid/platform/device/gpu/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/deformable_conv_func.h
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......@@ -24,7 +24,7 @@
#pragma once
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
template <typename T>
HOSTDEVICE T DmcnGetGradientWeight(T argmax_h, T argmax_w, const int h,
......
paddle/fluid/operators/dequantize_log_op.cu
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......@@ -15,7 +15,7 @@ limitations under the License. */
#include "paddle/fluid/operators/dequantize_log_op.h"
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/detection/box_clip_op.cu
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......@@ -16,7 +16,7 @@ limitations under the License. */
#include "paddle/fluid/operators/detection/box_clip_op.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/detection/sigmoid_focal_loss_op.cu
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......@@ -14,7 +14,7 @@ limitations under the License. */
#include "paddle/fluid/operators/detection/sigmoid_focal_loss_op.h"
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/detection/yolo_box_op.h
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......@@ -14,7 +14,7 @@
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/distribution_helper.h
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......@@ -26,7 +26,7 @@ limitations under the License. */
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/for_range.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
#if !defined(_WIN32)
#define UNLIKELY(condition) __builtin_expect(static_cast<bool>(condition), 0)
......
paddle/fluid/operators/elementwise/elementwise_functor.h
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......@@ -14,8 +14,8 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/array.h"
#include "paddle/fluid/platform/complex.h"
#include "paddle/pten/core/array.h"
#include "paddle/pten/kernels/funcs/elementwise_functor.h"
namespace paddle {
......@@ -92,12 +92,12 @@ using Complex = paddle::platform::complex<T>;
template <typename InT, typename OutT>
struct DivGradXYFunctor {
inline HOSTDEVICE paddle::framework::Array<OutT, 2> operator()(const InT a,
const InT b,
const InT c) {
inline HOSTDEVICE pten::framework::Array<OutT, 2> operator()(const InT a,
const InT b,
const InT c) {
// dx = dout / y
// dy = - dout * out / y
paddle::framework::Array<OutT, 2> outs;
pten::framework::Array<OutT, 2> outs;
outs[0] = a / c;
outs[1] = -a * b / c;
return outs;
......@@ -106,9 +106,9 @@ struct DivGradXYFunctor {
template <typename InT, typename OutT>
struct DivGradXYFunctor<Complex<InT>, Complex<OutT>> {
inline HOSTDEVICE paddle::framework::Array<Complex<OutT>, 2> operator()(
inline HOSTDEVICE pten::framework::Array<Complex<OutT>, 2> operator()(
const Complex<InT> a, const Complex<InT> b, const Complex<InT> c) {
paddle::framework::Array<Complex<OutT>, 2> outs;
pten::framework::Array<Complex<OutT>, 2> outs;
Complex<InT> c_conj(c.real, -c.imag);
Complex<InT> out_div_c_conj((b / c).real, -(b / c).imag);
outs[0] = a / c_conj;
......@@ -247,9 +247,9 @@ struct MinGradYFunctor {
template <typename InT, typename OutT>
struct MinGradXYFunctor {
inline HOSTDEVICE paddle::framework::Array<OutT, 2> operator()(
inline HOSTDEVICE pten::framework::Array<OutT, 2> operator()(
const InT& x, const InT& y, const InT& dout) {
paddle::framework::Array<OutT, 2> outs;
pten::framework::Array<OutT, 2> outs;
// dx = dout * (x < y)
outs[0] = static_cast<OutT>(dout * static_cast<InT>(x < y));
// dy = dout * (x >= y)
......@@ -273,10 +273,10 @@ struct MulGradFunctor<Complex<T>> {
template <typename InT, typename OutT>
struct MulGradXYFunctor {
inline HOSTDEVICE paddle::framework::Array<OutT, 2> operator()(const InT a,
const InT b,
const InT c) {
paddle::framework::Array<OutT, 2> outs;
inline HOSTDEVICE pten::framework::Array<OutT, 2> operator()(const InT a,
const InT b,
const InT c) {
pten::framework::Array<OutT, 2> outs;
// dx = dout * y
outs[0] = a * b;
// dy = dout * x
......@@ -287,9 +287,9 @@ struct MulGradXYFunctor {
template <typename InT, typename OutT>
struct MulGradXYFunctor<Complex<InT>, Complex<OutT>> {
inline HOSTDEVICE paddle::framework::Array<Complex<OutT>, 2> operator()(
inline HOSTDEVICE pten::framework::Array<Complex<OutT>, 2> operator()(
const Complex<InT> a, const Complex<InT> b, const Complex<InT> c) {
paddle::framework::Array<Complex<OutT>, 2> outs;
pten::framework::Array<Complex<OutT>, 2> outs;
// dx = dout * y
Complex<InT> b_conj(b.real, -b.imag);
outs[0] = a * b_conj;
......@@ -316,9 +316,9 @@ struct MaxGradYFunctor {
template <typename InT, typename OutT>
struct MaxGradXYFunctor {
inline HOSTDEVICE paddle::framework::Array<OutT, 2> operator()(
inline HOSTDEVICE pten::framework::Array<OutT, 2> operator()(
const InT& x, const InT& y, const InT& dout) {
paddle::framework::Array<OutT, 2> outs;
pten::framework::Array<OutT, 2> outs;
// dx = dout * (x > y)
outs[0] = static_cast<OutT>(dout * static_cast<InT>(x > y));
// dy = dout * (x <= y)
......
paddle/fluid/operators/fake_quantize_op.h
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......@@ -20,8 +20,8 @@ limitations under the License. */
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/memory/malloc.h"
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/fluid/platform/transform.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/grid_sampler_op.h
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......@@ -20,7 +20,7 @@ limitations under the License. */
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/gather.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/histogram_op.cu
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......@@ -16,7 +16,7 @@ limitations under the License. */
#include "paddle/fluid/operators/histogram_op.h"
#include "paddle/fluid/platform/device/gpu/gpu_launch_config.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/huber_loss_op.h
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......@@ -15,7 +15,7 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/interpolate_op.h
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......@@ -15,7 +15,7 @@
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/interpolate_v2_op.h
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......@@ -15,7 +15,7 @@
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/kernel_primitives/datamover_primitives.h
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......@@ -20,6 +20,7 @@
#ifdef PADDLE_WITH_HIP
#include <hip/hip_fp16.h>
#endif
#include "paddle/pten/core/ddim.h"
namespace paddle {
namespace operators {
......@@ -85,7 +86,7 @@ struct FastDivMod {
template <int kDims>
struct BroadcastConfig {
FastDivMod divmoders[kDims];
uint32_t strides[framework::DDim::kMaxRank];
uint32_t strides[pten::framework::DDim::kMaxRank];
HOSTDEVICE BroadcastConfig() {}
HOSTDEVICE BroadcastConfig(const std::vector<int64_t>& out_dims,
......
paddle/fluid/operators/kldiv_loss_op.h
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......@@ -13,7 +13,7 @@
#include <string>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/lstm_unit_op.cu
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......@@ -19,7 +19,7 @@ https://github.com/caffe2/caffe2/blob/master/caffe2/operators/lstm_unit_op_gpu.c
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/cross_entropy_op.h"
#include "paddle/fluid/operators/lstm_unit_op.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math.h
浏览文件 @ 4e23ba32
......@@ -15,7 +15,7 @@
#pragma once
#include "paddle/fluid/platform/float16.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
#include "math.h" // NOLINT
......
paddle/fluid/operators/math/algorithm.h
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......@@ -18,7 +18,7 @@
#include <cstdint> // for int64_t
#include <numeric>
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/complex_functors.h
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......@@ -17,7 +17,7 @@ limitations under the License. */
#include <type_traits>
#include "paddle/fluid/platform/complex.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/cos_sim_functor.h
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......@@ -17,7 +17,7 @@ limitations under the License. */
#include <stdlib.h>
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/cross_entropy.h
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......@@ -16,7 +16,7 @@ limitations under the License. */
#include <limits>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/depthwise_conv.h
浏览文件 @ 4e23ba32
......@@ -16,7 +16,7 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/detail/activation_functions.h
浏览文件 @ 4e23ba32
......@@ -17,7 +17,7 @@ limitations under the License. */
#include <stdexcept>
#include <string>
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/detail/gru_kernel.h
浏览文件 @ 4e23ba32
......@@ -15,7 +15,7 @@ limitations under the License. */
#pragma once
#include <type_traits>
#include "paddle/fluid/operators/math/detail/activation_functions.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
// TODO(guosheng): refine code style in gru_kernel
namespace paddle {
......
paddle/fluid/operators/math/detail/lstm_kernel.h
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......@@ -15,7 +15,7 @@ limitations under the License. */
#pragma once
#include <type_traits>
#include "paddle/fluid/operators/math/detail/activation_functions.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/maxouting.h
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......@@ -15,8 +15,8 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/fluid/platform/macros.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/pooling.h
浏览文件 @ 4e23ba32
......@@ -20,8 +20,8 @@ limitations under the License. */
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/operators/amp/fp16_type_traits.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/fluid/platform/macros.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/modified_huber_loss_op.cu
浏览文件 @ 4e23ba32
......@@ -17,7 +17,7 @@ limitations under the License. */
#include <thrust/tuple.h>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/modified_huber_loss_op.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/modified_huber_loss_op.h
浏览文件 @ 4e23ba32
......@@ -16,7 +16,7 @@ limitations under the License. */
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/multinomial_op.h
浏览文件 @ 4e23ba32
......@@ -18,7 +18,7 @@ limitations under the License. */
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/nll_loss_op.cu
浏览文件 @ 4e23ba32
......@@ -14,7 +14,7 @@ limitations under the License. */
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/operators/nll_loss_op.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/roll_op.cu
浏览文件 @ 4e23ba32
......@@ -13,11 +13,11 @@
// limitations under the License.
#pragma once
#include "paddle/fluid/framework/array.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/roll_op.h"
#include "paddle/fluid/platform/complex.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/pten/core/array.h"
namespace paddle {
namespace operators {
......@@ -28,9 +28,9 @@ using LoDTensor = framework::LoDTensor;
template <typename T, size_t Rank>
__global__ void RollCudaKernel(const T* input, T* output, int64_t N,
paddle::framework::Array<int64_t, Rank> shifts,
paddle::framework::Array<int64_t, Rank> strides,
paddle::framework::Array<int64_t, Rank> sizes) {
pten::framework::Array<int64_t, Rank> shifts,
pten::framework::Array<int64_t, Rank> strides,
pten::framework::Array<int64_t, Rank> sizes) {
int64_t idx = blockIdx.x * blockDim.x + threadIdx.x;
if (idx >= N) {
return;
......@@ -101,9 +101,9 @@ class RollKernel<platform::CUDADeviceContext, T>
#define CALL_ROLL_CUDA_KERNEL(N) \
case N: { \
paddle::framework::Array<int64_t, N> _strides; \
paddle::framework::Array<int64_t, N> _shifts; \
paddle::framework::Array<int64_t, N> _sizes; \
pten::framework::Array<int64_t, N> _strides; \
pten::framework::Array<int64_t, N> _shifts; \
pten::framework::Array<int64_t, N> _sizes; \
for (size_t idx = 0; idx < N; ++idx) { \
_strides[idx] = strides[idx]; \
_shifts[idx] = shifts[idx]; \
......
paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cu
浏览文件 @ 4e23ba32
......@@ -22,7 +22,7 @@ namespace cub = hipcub;
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.h"
#include "paddle/fluid/platform/device/gpu/gpu_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/smooth_l1_loss_op.h
浏览文件 @ 4e23ba32
......@@ -15,7 +15,7 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/unstack_op.h
浏览文件 @ 4e23ba32
......@@ -20,7 +20,6 @@ limitations under the License. */
#if defined(__NVCC__) || defined(__HIPCC__)
#include <thrust/device_vector.h>
#include "paddle/fluid/framework/array.h"
#endif
namespace paddle {
......
paddle/fluid/platform/aligned_vector.h
浏览文件 @ 4e23ba32
......@@ -14,7 +14,7 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace platform {
......
paddle/fluid/platform/eigen_ext.h
浏览文件 @ 4e23ba32
......@@ -17,7 +17,7 @@
#include "paddle/fluid/platform/bfloat16.h"
#include "paddle/fluid/platform/complex.h"
#include "paddle/fluid/platform/float16.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
#include "unsupported/Eigen/CXX11/Tensor"
......
paddle/fluid/platform/transform.h
浏览文件 @ 4e23ba32
......@@ -19,8 +19,8 @@ limitations under the License. */
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/pten/core/hostdevice.h"
#if defined(__NVCC__) || defined(__HIPCC__)
#include <thrust/execution_policy.h>
......
paddle/fluid/platform/transform_test.cu
浏览文件 @ 4e23ba32
......@@ -15,8 +15,8 @@ limitations under the License. */
#include <gtest/gtest.h>
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/memory/memory.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/fluid/platform/transform.h"
#include "paddle/pten/core/hostdevice.h"
template <typename T>
class Scale {
......
paddle/pten/api/include/tensor.h
浏览文件 @ 4e23ba32
......@@ -42,12 +42,12 @@ class DenseTensor;
namespace pten {
class TensorBase;
namespace framework {
class DDim;
} // namespace framework
} // namespace pten
namespace paddle {
namespace framework {
class DDim;
}
namespace experimental {
......@@ -159,9 +159,9 @@ class PADDLE_API Tensor final {
/**
* @brief Return the dimensions of Tensor.
*
* @return paddle::framework::DDim
* @return pten::framework::DDim
*/
paddle::framework::DDim dims() const;
pten::framework::DDim dims() const;
/**
* @brief Return the shape (dimensions) of Tensor.
......
paddle/pten/api/lib/tensor.cc
浏览文件 @ 4e23ba32
......@@ -47,13 +47,13 @@ limitations under the License. */
* In the future, the necessary components will be moved to the this library,
* or the corresponding components will be re-implemented.
*/
#include "paddle/fluid/framework/ddim.h"
#include "paddle/fluid/memory/memory.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/stream/cuda_stream.h"
#include "paddle/pten/common/complex.h"
#include "paddle/pten/common/float16.h"
#include "paddle/pten/core/ddim.h"
namespace paddle {
namespace experimental {
......@@ -94,10 +94,10 @@ int64_t Tensor::numel() const { return impl_->numel(); }
int64_t Tensor::size() const { return impl_->numel(); }
paddle::framework::DDim Tensor::dims() const { return impl_->dims(); }
pten::framework::DDim Tensor::dims() const { return impl_->dims(); }
std::vector<int64_t> Tensor::shape() const {
return paddle::framework::vectorize<int64_t>(impl_->dims());
return pten::framework::vectorize<int64_t>(impl_->dims());
}
void Tensor::reshape(const std::vector<int64_t> &shape) {
......
paddle/pten/core/CMakeLists.txt
浏览文件 @ 4e23ba32
......@@ -15,6 +15,15 @@ cc_library(tensor_meta SRCS tensor_meta.cc DEPS enforce mixed_vector)
cc_library(dense_tensor SRCS dense_tensor.cc DEPS convert_utils tensor_meta tensor_base)
cc_library(pten_device_context SRCS device_context.cc DEPS tensor_base )
cc_test(unroll_array_ops_test SRCS unroll_array_ops_test.cc)
cc_library(ddim SRCS ddim.cc DEPS eigen3 boost enforce)
cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
if(WITH_GPU)
nv_test(dim_test SRCS dim_test.cu DEPS ddim)
elseif(WITH_ROCM)
hip_test(dim_test SRCS dim_test.cu DEPS ddim)
endif()
# Will remove once we implemented MKLDNN_Tensor
if(WITH_MKLDNN)
add_dependencies(dense_tensor mkldnn)
......
paddle/fluid/framework/array.h → paddle/pten/core/array.h
浏览文件 @ 4e23ba32
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -15,10 +15,12 @@
#pragma once
#include <cstdint>
#include "paddle/fluid/framework/unroll_array_ops.h"
#include "paddle/pten/core/unroll_array_ops.h"
// TODO(paddle-dev): Need to modify into pten/core/enforce.h
#include "paddle/fluid/platform/enforce.h"
namespace paddle {
namespace pten {
namespace platform = paddle::platform;
namespace framework {
template <typename T, size_t N>
......@@ -146,4 +148,4 @@ class Array<T, 0> {
};
} // namespace framework
} // namespace paddle
} // namespace pten
paddle/fluid/framework/ddim.cc → paddle/pten/core/ddim.cc
浏览文件 @ 4e23ba32
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
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/framework/ddim.h"
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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/pten/core/ddim.h"
#include <set>
#include "paddle/fluid/platform/enforce.h"
namespace paddle {
namespace pten {
namespace platform = paddle::platform;
namespace framework {
DDim make_ddim(std::initializer_list<int64_t> dims) {
......@@ -82,10 +82,13 @@ bool contain_unknown_dim(const DDim& ddim) {
DDim slice_ddim(const DDim& dim, int begin, int end) {
PADDLE_ENFORCE_EQ(
(begin >= 0 && end <= dim.size()), true,
(begin >= 0 && end <= dim.size()),
true,
platform::errors::InvalidArgument(
"[begin(%d), end(%d)) must be inside [0, %d) in ddim slice.", begin,
end, dim.size()));
"[begin(%d), end(%d)) must be inside [0, %d) in ddim slice.",
begin,
end,
dim.size()));
// Constructor of DDim would check whether end - begin is valid
return DDim(dim.Get() + begin, end - begin);
}
......@@ -108,27 +111,34 @@ std::ostream& operator<<(std::ostream& os, const DDim& ddim) {
}
DDim flatten_to_3d(const DDim& src, int num_row_dims, int num_col_dims) {
PADDLE_ENFORCE_GE(src.size(), 3,
PADDLE_ENFORCE_GE(src.size(),
3,
platform::errors::InvalidArgument(
"The rank of src dim should be at least 3 "
"in flatten_to_3d, but received %d.",
src.size()));
PADDLE_ENFORCE_EQ((num_row_dims >= 1 && num_row_dims < src.size()), true,
PADDLE_ENFORCE_EQ((num_row_dims >= 1 && num_row_dims < src.size()),
true,
platform::errors::InvalidArgument(
"The num_row_dims should be inside [1, %d] "
"in flatten_to_3d, but received %d.",
src.size() - 1, num_row_dims));
PADDLE_ENFORCE_EQ((num_col_dims >= 2 && num_col_dims <= src.size()), true,
src.size() - 1,
num_row_dims));
PADDLE_ENFORCE_EQ((num_col_dims >= 2 && num_col_dims <= src.size()),
true,
platform::errors::InvalidArgument(
"The num_col_dims should be inside [2, %d] "
"in flatten_to_3d, but received %d.",
src.size(), num_col_dims));
src.size(),
num_col_dims));
PADDLE_ENFORCE_GE(
num_col_dims, num_row_dims,
num_col_dims,
num_row_dims,
platform::errors::InvalidArgument(
"The num_row_dims should be less than num_col_dims in flatten_to_3d,"
"but received num_row_dims = %d, num_col_dims = %d.",
num_row_dims, num_col_dims));
num_row_dims,
num_col_dims));
return DDim({product(slice_ddim(src, 0, num_row_dims)),
product(slice_ddim(src, num_row_dims, num_col_dims)),
......@@ -169,13 +179,16 @@ DDim DDim::reshape(const std::vector<int>& shape) const {
out_dims.rank_ = shape.size();
for (size_t i = 0; i < shape.size(); ++i) {
if (shape[i] == copy_dim_val) {
PADDLE_ENFORCE_LT(static_cast<int>(i), in_dims.size(),
PADDLE_ENFORCE_LT(static_cast<int>(i),
in_dims.size(),
platform::errors::InvalidArgument(
"Index %d of shape under which the value of 0 "
"is stored, must be lower than the number of "
"old dimensions. But received shape[%d] = 0, "
"dimensions = %d, shape = [%s].",
i, in_dims.size(), in_dims));
i,
in_dims.size(),
in_dims));
out_dims[i] = in_dims[i];
} else {
out_dims[i] = shape[i];
......@@ -190,19 +203,23 @@ DDim DDim::transpose(const std::vector<int>& axis) const {
size_t axis_size = axis.size();
auto axis_set = std::set<int>(axis.begin(), axis.end());
PADDLE_ENFORCE_EQ(axis_set.size(), axis_size,
PADDLE_ENFORCE_EQ(axis_set.size(),
axis_size,
platform::errors::InvalidArgument(
"In an axis array, elements must be unique."));
PADDLE_ENFORCE_EQ(
in_rank, axis_size,
in_rank,
axis_size,
platform::errors::InvalidArgument("The input dimension's size "
"should be equal to the axis's size. "
"But received dimension is %d, "
"axis's size is %d",
in_rank, axis_size));
in_rank,
axis_size));
PADDLE_ENFORCE_LT(*std::max_element(axis.begin(), axis.end()), axis_size,
PADDLE_ENFORCE_LT(*std::max_element(axis.begin(), axis.end()),
axis_size,
platform::errors::InvalidArgument(
"Axis values must be ranging from 0 to (dims - 1)."));
......@@ -214,4 +231,4 @@ DDim DDim::transpose(const std::vector<int>& axis) const {
}
} // namespace framework
} // namespace paddle
} // namespace pten
\ No newline at end of file
paddle/pten/core/ddim.h 0 → 100644
浏览文件 @ 4e23ba32
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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.
#pragma once
#include <initializer_list>
#include <stdexcept>
#include <string>
#include <vector>
#include "paddle/pten/core/dim.h"
namespace pten {
namespace platform = paddle::platform;
namespace framework {
#define PADDLE_VISIT_DDIM_BASE(rank, callback) \
case (rank): { \
constexpr auto kRank = (rank); \
return (callback); \
}
#define PADDLE_VISIT_DDIM(rank, callback) \
switch (rank) { \
PADDLE_VISIT_DDIM_BASE(0, callback); \
PADDLE_VISIT_DDIM_BASE(1, callback); \
PADDLE_VISIT_DDIM_BASE(2, callback); \
PADDLE_VISIT_DDIM_BASE(3, callback); \
PADDLE_VISIT_DDIM_BASE(4, callback); \
PADDLE_VISIT_DDIM_BASE(5, callback); \
PADDLE_VISIT_DDIM_BASE(6, callback); \
PADDLE_VISIT_DDIM_BASE(7, callback); \
PADDLE_VISIT_DDIM_BASE(8, callback); \
PADDLE_VISIT_DDIM_BASE(9, callback); \
default: \
PADDLE_THROW(platform::errors::Unimplemented( \
"Invalid dimension to be accessed. Now only supports access to " \
"dimension 0 to 9, but received dimension is %d.", \
rank)); \
}
template <typename T1, typename T2>
inline void dynamic_dim_assign(const T1* in, T2* out, int n) {
PADDLE_VISIT_DDIM(n, (static_dim_assign<kRank, T1, T2>(in, out)));
}
/**
* \brief A dynamically sized dimension.
*
* The number of dimensions must be between [1, 9].
*/
class DDim {
public:
constexpr static int kMaxRank = 9;
DDim() : rank_(1) { dim_[0] = 0; }
DDim(const DDim& ddim) : dim_() { CopyFrom(ddim); }
DDim(const int* d, int n) : rank_(n) {
dynamic_dim_assign(d, dim_.GetMutable(), n);
}
DDim(const int64_t* d, int n) : rank_(n) {
dynamic_dim_assign(d, dim_.GetMutable(), n);
}
template <int D>
/*implicit*/ DDim(const Dim<D>& in) : rank_(D) { // NOLINT
UnsafeCast<D>() = in;
}
/*implicit*/ DDim(std::initializer_list<int64_t> init_list)
: DDim(init_list.begin(), init_list.size()) {}
inline DDim& operator=(const DDim& ddim) { return CopyFrom(ddim); }
template <int D>
inline DDim& operator=(const Dim<D>& dim) {
rank_ = D;
UnsafeCast<D>() = dim;
return *this;
}
inline int64_t& operator[](int idx) { return dim_[idx]; }
inline int64_t operator[](int idx) const { return dim_[idx]; }
int64_t& at(int idx) {
PADDLE_ENFORCE_GE(idx,
0,
platform::errors::InvalidArgument(
"Invalid DDim index to be accessed. The valid index "
"is between 0 and %d, but received index is %d.",
rank_,
idx));
PADDLE_ENFORCE_LT(idx,
rank_,
platform::errors::InvalidArgument(
"Invalid DDim index to be accessed. The valid index "
"is between 0 and %d, but received index is %d.",
rank_,
idx));
return dim_[idx];
}
int64_t at(int idx) const {
PADDLE_ENFORCE_GE(idx,
0,
platform::errors::InvalidArgument(
"Invalid DDim index to be accessed. The valid index "
"is between 0 and %d, but received index is %d.",
rank_,
idx));
PADDLE_ENFORCE_LT(idx,
rank_,
platform::errors::InvalidArgument(
"Invalid DDim index to be accessed. The valid index "
"is between 0 and %d, but received index is %d.",
rank_,
idx));
return dim_[idx];
}
template <typename Visitor>
typename std::result_of<Visitor(Dim<0>&)>::type apply_visitor(
Visitor&& visitor) {
PADDLE_VISIT_DDIM(rank_, visitor(UnsafeCast<kRank>()));
}
template <typename Visitor>
typename std::result_of<Visitor(const Dim<0>&)>::type apply_visitor(
Visitor&& visitor) const {
PADDLE_VISIT_DDIM(rank_, visitor(UnsafeCast<kRank>()));
}
bool operator==(const DDim& d) const;
bool operator!=(const DDim& d) const;
inline const int64_t* Get() const { return dim_.Get(); }
inline int64_t* GetMutable() { return dim_.GetMutable(); }
inline int size() const { return rank_; }
std::string to_str() const;
DDim reshape(const std::vector<int>& shape) const;
DDim transpose(const std::vector<int>& axis) const;
private:
template <int D>
inline Dim<D>& UnsafeCast() {
static_assert(D >= 0 && D <= kMaxRank, "Invalid rank");
auto* p = static_cast<void*>(&dim_);
return *reinterpret_cast<Dim<D>*>(p);
}
template <int D>
inline const Dim<D>& UnsafeCast() const {
static_assert(D >= 0 && D <= kMaxRank, "Invalid rank");
auto* p = static_cast<const void*>(&dim_);
return *reinterpret_cast<const Dim<D>*>(p);
}
inline DDim& CopyFrom(const DDim& ddim) {
PADDLE_VISIT_DDIM(ddim.rank_, (*this = ddim.UnsafeCast<kRank>()));
}
friend DDim stride(const DDim& ddim);
friend DDim stride_numel(const DDim& ddim);
private:
Dim<kMaxRank> dim_;
int rank_;
};
#undef PADDLE_VISIT_DDIM_BASE
#undef PADDLE_VISIT_DDIM
/**
* \brief Make a DDim from std::vector<int64_t>
*
* \param dims An vector of ints. Must be sized between [1, 9]
*/
DDim make_ddim(const std::vector<int64_t>& dims);
DDim make_ddim(const std::vector<int>& dims);
/**
* \brief Make a DDim from an initializer list
*
* \param dims An initializer list of ints. Must be sized between [1, 9]
*
*/
DDim make_ddim(std::initializer_list<int64_t> dims);
template <typename T = int64_t>
std::vector<T> vectorize(const DDim& ddim) {
std::vector<T> result(DDim::kMaxRank);
dynamic_dim_assign(ddim.Get(), result.data(), ddim.size());
result.resize(ddim.size());
return result;
}
int64_t product(const DDim& ddim);
bool contain_unknown_dim(const DDim& ddim);
/**
* \brief Slice a ddim
*
* Slice dim with [begin, end).
* e.g. DDim d = make_ddim({1,2,3,4,5});
* slice_ddim(d, 1, 3); ====> {2,3}
*/
DDim slice_ddim(const DDim& dim, int begin, int end);
/**
* \brief What is the length of this dimension?
*
* \param Dynamic dimension to inspect
*/
int arity(const DDim& ddim);
std::ostream& operator<<(std::ostream&, const DDim&);
/**
* \brief Flatten dim to 3d
* e.g., DDim d = mak_ddim({1, 2, 3, 4, 5, 6})
* flatten_to_3d(d, 2, 4); ===> {1*2, 3*4, 5*6} ===> {2, 12, 30}
*/
DDim flatten_to_3d(const DDim& src, int num_row_dims, int num_col_dims);
// Reshape a tensor to a matrix. The matrix's first dimension(column length)
// will be the product of tensor's first `num_col_dims` dimensions.
DDim flatten_to_2d(const DDim& src, int num_col_dims);
DDim flatten_to_1d(const DDim& src);
DDim stride(const DDim& ddim);
DDim stride_numel(const DDim& ddim);
} // namespace framework
} // namespace pten
paddle/fluid/framework/ddim_test.cc → paddle/pten/core/ddim_test.cc
浏览文件 @ 4e23ba32
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
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 <sstream>
#include "gtest/gtest.h"
#include "paddle/fluid/framework/ddim.h"
#include "paddle/pten/core/ddim.h"
TEST(DDim, Equality) {
// construct a DDim from an initialization list
paddle::framework::DDim ddim = paddle::framework::make_ddim({9, 1, 5});
pten::framework::DDim ddim = pten::framework::make_ddim({9, 1, 5});
EXPECT_EQ(ddim[0], 9);
EXPECT_EQ(ddim[1], 1);
EXPECT_EQ(ddim[2], 5);
// construct a DDim from a vector
std::vector<int64_t> vec({9, 1, 5});
paddle::framework::DDim vddim = paddle::framework::make_ddim(vec);
pten::framework::DDim vddim = pten::framework::make_ddim(vec);
EXPECT_EQ(ddim[0], 9);
EXPECT_EQ(ddim[1], 1);
EXPECT_EQ(ddim[2], 5);
......@@ -37,35 +38,33 @@ TEST(DDim, Equality) {
EXPECT_EQ(ddim[0], 6);
// vectorize a DDim
std::vector<int64_t> res_vec = paddle::framework::vectorize(vddim);
std::vector<int64_t> res_vec = pten::framework::vectorize(vddim);
EXPECT_EQ(res_vec[0], 9);
EXPECT_EQ(res_vec[1], 1);
EXPECT_EQ(res_vec[2], 5);
paddle::framework::Dim<3> d(3, 2, 1);
res_vec = paddle::framework::vectorize(paddle::framework::DDim(d));
pten::framework::Dim<3> d(3, 2, 1);
res_vec = pten::framework::vectorize(pten::framework::DDim(d));
EXPECT_EQ(res_vec[0], 3);
EXPECT_EQ(res_vec[1], 2);
EXPECT_EQ(res_vec[2], 1);
// arity of a DDim
EXPECT_EQ(paddle::framework::arity(ddim), 3);
EXPECT_EQ(pten::framework::arity(ddim), 3);
EXPECT_EQ(ddim.size(), 3);
// product of a DDim
EXPECT_EQ(paddle::framework::product(vddim), 45);
EXPECT_EQ(
paddle::framework::product(paddle::framework::make_ddim({3, 2, 5, 3})),
90);
EXPECT_EQ(pten::framework::product(vddim), 45);
EXPECT_EQ(pten::framework::product(pten::framework::make_ddim({3, 2, 5, 3})),
90);
// slice a DDim
paddle::framework::DDim ddim2 =
paddle::framework::make_ddim({1, 2, 3, 4, 5, 6});
paddle::framework::DDim ss = paddle::framework::slice_ddim(ddim2, 2, 5);
pten::framework::DDim ddim2 = pten::framework::make_ddim({1, 2, 3, 4, 5, 6});
pten::framework::DDim ss = pten::framework::slice_ddim(ddim2, 2, 5);
EXPECT_EQ(arity(ss), 3);
EXPECT_EQ(ss[0], 3);
EXPECT_EQ(ss[1], 4);
EXPECT_EQ(ss[2], 5);
paddle::framework::DDim ss2 = paddle::framework::slice_ddim(ddim2, 0, 6);
pten::framework::DDim ss2 = pten::framework::slice_ddim(ddim2, 0, 6);
EXPECT_EQ(arity(ss2), 6);
EXPECT_EQ(ss2[0], 1);
EXPECT_EQ(ss2[1], 2);
......@@ -78,7 +77,7 @@ TEST(DDim, Equality) {
TEST(DDim, Print) {
// print a DDim
std::stringstream ss;
paddle::framework::DDim ddim = paddle::framework::make_ddim({2, 3, 4});
pten::framework::DDim ddim = pten::framework::make_ddim({2, 3, 4});
ss << ddim;
EXPECT_EQ("2, 3, 4", ss.str());
}
paddle/pten/core/dim.h 0 → 100644
浏览文件 @ 4e23ba32
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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.
#pragma once
#include <iostream>
#include <sstream>
#include <stdexcept>
#include <string>
#include <type_traits>
#include "paddle/pten/core/array.h"
#include "paddle/pten/core/hostdevice.h"
namespace pten {
namespace framework {
// Statically sized, statically indexed dimension
template <int D>
class Dim : public Array<int64_t, D> {
public:
static_assert(D >= 0, "D must be not less than 0");
static constexpr int kRank = D;
using BaseClass = Array<int64_t, D>;
inline Dim(int64_t head, const Dim<D - 1>& tail) {
(*this)[0] = head;
new (this->GetMutable() + 1) Dim<D - 1>(tail);
}
template <typename... Args>
HOSTDEVICE explicit Dim(int64_t head, Args... args)
: BaseClass(head, args...) {}
/** Construct a Dim with each dimension set to the given index */
HOSTDEVICE explicit Dim(int64_t idx) { this->Fill(idx); }
HOSTDEVICE Dim() = default;
HOST std::string to_string() const;
};
// Product of a Dim
template <int D>
HOSTDEVICE inline int64_t product(const Dim<D>& a) {
return UnrollProduct<D>::Run(a.Get());
}
/**
* Helper function to create a Dim
*
* \param idxes The type of Dim constructed depends on the number of params
*
*/
template <typename... Args>
HOSTDEVICE inline Dim<sizeof...(Args)> make_dim(Args... idxes) {
return Dim<sizeof...(Args)>(idxes...);
}
// Allows us to output a Dim
template <int D>
inline std::ostream& operator<<(std::ostream& os, const Dim<D>& d) {
os << d[0];
for (int i = 1; i < D; ++i) {
os << ", " << d[i];
}
return os;
}
inline std::ostream& operator<<(std::ostream& os, const Dim<0>& d) {
return os;
}
template <int D>
HOST std::string Dim<D>::to_string() const {
std::stringstream stream;
stream << *this;
return stream.str();
}
template <int D, typename T1, typename T2>
inline void static_dim_assign(const T1* in, T2* out) {
UnrollAssign<D>::Run(in, out);
}
} // namespace framework
} // namespace pten
paddle/fluid/framework/dim_test.cu → paddle/pten/core/dim_test.cu
浏览文件 @ 4e23ba32
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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 <thrust/device_vector.h>
#include <sstream>
#include "gtest/gtest.h"
#include "paddle/fluid/framework/dim.h"
#include "paddle/pten/core/dim.h"
__global__ void test(paddle::framework::Dim<2>* o) {
o[0] = paddle::framework::make_dim(5, 6);
__global__ void test(pten::framework::Dim<2>* o) {
o[0] = pten::framework::make_dim(5, 6);
}
__global__ void dyn_idx_gpu(int64_t* o) {
auto d = paddle::framework::make_dim(5, 6);
auto d = pten::framework::make_dim(5, 6);
o[0] = d[1];
}
TEST(Dim, Equality) {
// construct a Dim on the CPU
auto a = paddle::framework::make_dim(3, 4);
auto a = pten::framework::make_dim(3, 4);
EXPECT_EQ(a[0], 3);
EXPECT_EQ(a[1], 4);
// construct a Dim on the GPU
thrust::device_vector<paddle::framework::Dim<2>> t(2);
thrust::device_vector<pten::framework::Dim<2>> t(2);
#ifdef PADDLE_WITH_HIP
hipLaunchKernelGGL(test, dim3(1), dim3(1), 0, 0,
thrust::raw_pointer_cast(t.data()));
hipLaunchKernelGGL(
test, dim3(1), dim3(1), 0, 0, thrust::raw_pointer_cast(t.data()));
#else
test<<<1, 1>>>(thrust::raw_pointer_cast(t.data()));
#endif
......@@ -45,10 +46,10 @@ TEST(Dim, Equality) {
EXPECT_EQ(a[1], 6);
// product
EXPECT_EQ(paddle::framework::product(a), 30);
EXPECT_EQ(pten::framework::product(a), 30);
// mutate a Dim
auto b = paddle::framework::make_dim(7, 8);
auto b = pten::framework::make_dim(7, 8);
b[1] = 10;
EXPECT_EQ(b[0], 7);
EXPECT_EQ(b[1], 10);
......@@ -61,8 +62,8 @@ TEST(Dim, Equality) {
// dynamic access on GPU
thrust::device_vector<int64_t> r(1);
#ifdef PADDLE_WITH_HIP
hipLaunchKernelGGL(dyn_idx_gpu, dim3(1), dim3(1), 0, 0,
thrust::raw_pointer_cast(r.data()));
hipLaunchKernelGGL(
dyn_idx_gpu, dim3(1), dim3(1), 0, 0, thrust::raw_pointer_cast(r.data()));
#else
dyn_idx_gpu<<<1, 1>>>(thrust::raw_pointer_cast(r.data()));
#endif
......@@ -71,9 +72,9 @@ TEST(Dim, Equality) {
}
TEST(Dim, Bool) {
auto a = paddle::framework::make_dim(3, 4);
auto b = paddle::framework::make_dim(5, 6);
auto c = paddle::framework::make_dim(3, 4);
auto a = pten::framework::make_dim(3, 4);
auto b = pten::framework::make_dim(5, 6);
auto c = pten::framework::make_dim(3, 4);
// comparison
EXPECT_TRUE(a == a);
......@@ -84,13 +85,13 @@ TEST(Dim, Bool) {
TEST(Dim, Print) {
{
std::stringstream ss;
auto a = paddle::framework::make_dim(2, 3);
auto a = pten::framework::make_dim(2, 3);
ss << a;
EXPECT_EQ(ss.str(), "2, 3");
}
{
std::stringstream ss;
ss << paddle::framework::make_dim(8);
ss << pten::framework::make_dim(8);
EXPECT_EQ(ss.str(), "8");
}
}
}
\ No newline at end of file
paddle/fluid/platform/hostdevice.h → paddle/pten/core/hostdevice.h
浏览文件 @ 4e23ba32
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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.
#pragma once
#ifdef __HIPCC__
......
paddle/pten/core/tensor_base.h
浏览文件 @ 4e23ba32
......@@ -14,11 +14,11 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/ddim.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/pten/common/backend.h"
#include "paddle/pten/common/data_type.h"
#include "paddle/pten/common/layout.h"
#include "paddle/pten/core/ddim.h"
#include "paddle/pten/core/storage.h"
#include "paddle/pten/core/utils/type_registry.h"
......@@ -28,7 +28,7 @@ class TensorBase {
public:
using DataType = paddle::experimental::DataType;
using DataLayout = paddle::experimental::DataLayout;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
using Place = paddle::platform::Place;
virtual ~TensorBase() = default;
......
paddle/pten/core/tensor_meta.h
浏览文件 @ 4e23ba32
......@@ -21,7 +21,7 @@ limitations under the License. */
#include "paddle/pten/common/layout.h"
// See Note [ Why still include the fluid headers? ]
#include "paddle/fluid/framework/ddim.h"
#include "paddle/pten/core/ddim.h"
// Note: mixed_vector include many header now, LoD will be
// used on CUDA device? Can we use small_vector here?
......@@ -30,7 +30,7 @@ limitations under the License. */
namespace pten {
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
using LoD = std::vector<paddle::framework::Vector<size_t>>;
/// \brief The meta data of dense tensor. Take the structure type
/// and use all default operations.
......
paddle/fluid/framework/unroll_array_ops.h → paddle/pten/core/unroll_array_ops.h
浏览文件 @ 4e23ba32
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -16,9 +16,9 @@
#include <cstddef>
#include <type_traits>
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/core/hostdevice.h"
namespace paddle {
namespace pten {
namespace framework {
namespace detail {
......@@ -130,4 +130,4 @@ template <size_t N>
using UnrollProduct = detail::UnrollProduct<0, N, N == 0>;
} // namespace framework
} // namespace paddle
} // namespace pten
paddle/fluid/framework/unroll_array_ops_test.cc → paddle/pten/core/unroll_array_ops_test.cc
浏览文件 @ 4e23ba32
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
......@@ -12,12 +12,12 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/framework/unroll_array_ops.h"
#include "paddle/pten/core/unroll_array_ops.h"
#include <gtest/gtest.h>
#include <array>
namespace paddle {
namespace pten {
namespace framework {
template <typename T>
......@@ -79,4 +79,4 @@ TEST(unroll_ops, product) {
}
} // namespace framework
} // namespace paddle
} // namespace pten
\ No newline at end of file
paddle/pten/infermeta/binary.cc
浏览文件 @ 4e23ba32
......@@ -64,8 +64,8 @@ DenseTensorMeta MatmulInferMeta(const DenseTensorMeta& x_meta,
const DenseTensorMeta& y_meta,
bool trans_x,
bool trans_y) {
std::vector<int64_t> dims_x = paddle::framework::vectorize(x_meta.dims);
std::vector<int64_t> dims_y = paddle::framework::vectorize(y_meta.dims);
std::vector<int64_t> dims_x = pten::framework::vectorize(x_meta.dims);
std::vector<int64_t> dims_y = pten::framework::vectorize(y_meta.dims);
auto ndims_x = dims_x.size();
auto ndims_y = dims_y.size();
PADDLE_ENFORCE_GT(ndims_x,
......@@ -125,7 +125,7 @@ DenseTensorMeta MatmulInferMeta(const DenseTensorMeta& x_meta,
new_dims.push_back(1);
}
auto ddim_out = paddle::framework::make_ddim(new_dims);
auto ddim_out = pten::framework::make_ddim(new_dims);
return {x_meta.dtype, ddim_out, x_meta.layout};
}
......@@ -169,7 +169,7 @@ DenseTensorMeta ElementwiseInferMeta(const DenseTensorMeta& x_meta,
out_dims_array.data(),
max_dim,
axis);
return_meta.dims = paddle::framework::make_ddim(out_dims_array);
return_meta.dims = pten::framework::make_ddim(out_dims_array);
}
return_meta.lod = x_meta.lod;
return return_meta;
......
paddle/pten/infermeta/nullary.cc
浏览文件 @ 4e23ba32
......@@ -20,14 +20,14 @@ namespace pten {
DenseTensorMeta CreateInferMeta(const std::vector<int64_t>& shape,
DataType dtype,
DataLayout layout) {
const auto& out_dims = paddle::framework::make_ddim(shape);
const auto& out_dims = pten::framework::make_ddim(shape);
return {dtype, out_dims, layout};
}
DenseTensorMeta CreateInferMeta(const ScalarArray& shape,
DataType dtype,
DataLayout layout) {
const auto& out_dims = paddle::framework::make_ddim(shape.GetData());
const auto& out_dims = pten::framework::make_ddim(shape.GetData());
return {dtype, out_dims, layout};
}
......
paddle/pten/infermeta/unary.cc
浏览文件 @ 4e23ba32
......@@ -23,7 +23,7 @@ DenseTensorMeta UnchangedInferMeta(const DenseTensorMeta& x_meta) {
}
DenseTensorMeta ReductionInferMeta(const DenseTensorMeta& x_meta) {
const auto& out_dims = paddle::framework::make_ddim({1});
const auto& out_dims = pten::framework::make_ddim({1});
DenseTensorMeta return_meta(x_meta.dtype, out_dims, x_meta.layout);
return return_meta;
}
......@@ -63,7 +63,7 @@ DenseTensorMeta FlattenInferMeta(const DenseTensorMeta& x_meta,
for (int i = stop_axis + 1; i < in_dims_size; i++) {
out_shape.push_back(x_dims[i]);
}
const auto& out_dims = paddle::framework::make_ddim(out_shape);
const auto& out_dims = pten::framework::make_ddim(out_shape);
DenseTensorMeta return_meta(x_meta.dtype, out_dims, x_meta.layout);
if (x_dims[0] == return_meta.dims[0]) {
......@@ -89,10 +89,10 @@ DenseTensorMeta CreateLikeInferMeta(const DenseTensorMeta& x_meta,
layout == DataLayout::UNDEFINED ? x_meta.layout : layout};
}
static paddle::framework::DDim ValidateShape(
const std::vector<int64_t> shape, const paddle::framework::DDim& in_dims) {
const int64_t in_size = paddle::framework::product(in_dims);
auto in_dims_vec = paddle::framework::vectorize(in_dims);
static pten::framework::DDim ValidateShape(
const std::vector<int64_t> shape, const pten::framework::DDim& in_dims) {
const int64_t in_size = pten::framework::product(in_dims);
auto in_dims_vec = pten::framework::vectorize(in_dims);
bool all_positive = std::all_of(in_dims_vec.cbegin(),
in_dims_vec.cend(),
[](int64_t i) { return i > 0; });
......@@ -112,7 +112,7 @@ static paddle::framework::DDim ValidateShape(
paddle::platform::errors::InvalidArgument(
"Only one dimension value of 'shape' in ReshapeOp can "
"be -1. But received shape = [%s], shape[%d] is also -1.",
paddle::framework::make_ddim(shape),
pten::framework::make_ddim(shape),
i));
unk_dim_idx = i;
} else if (shape[i] == copy_dim_val) {
......@@ -124,7 +124,7 @@ static paddle::framework::DDim ValidateShape(
"the input tensor X's dimensions. "
"But received shape = [%s], shape[%d] = 0, X's shape = [%s], "
"X's dimensions = %d.",
paddle::framework::make_ddim(shape),
pten::framework::make_ddim(shape),
i,
in_dims,
in_dims.size()));
......@@ -136,7 +136,7 @@ static paddle::framework::DDim ValidateShape(
"Each dimension value of 'shape' in ReshapeOp must not "
"be negative except one unknown dimension. "
"But received shape = [%s], shape[%d] = %d.",
paddle::framework::make_ddim(shape),
pten::framework::make_ddim(shape),
i,
shape[i]));
}
......@@ -165,7 +165,7 @@ static paddle::framework::DDim ValidateShape(
"'shape' is [%s], known capacity of 'shape' is %d.",
in_dims,
in_size,
paddle::framework::make_ddim(shape),
pten::framework::make_ddim(shape),
capacity));
} else {
output_shape[unk_dim_idx] = -1;
......@@ -183,7 +183,7 @@ static paddle::framework::DDim ValidateShape(
"[%s], the capacity of 'shape' is %d.",
in_dims,
in_size,
paddle::framework::make_ddim(shape),
pten::framework::make_ddim(shape),
capacity));
}
}
......@@ -202,11 +202,11 @@ static paddle::framework::DDim ValidateShape(
"capacity of 'Out' is %d.",
in_dims,
in_size,
paddle::framework::make_ddim(shape),
pten::framework::make_ddim(shape),
capacity));
}
return paddle::framework::make_ddim(output_shape);
return pten::framework::make_ddim(output_shape);
}
DenseTensorMeta InferMetaFromVecValue(const DenseTensorMeta& x_meta,
......@@ -267,7 +267,7 @@ DenseTensorMeta ReduceInferMeta(const DenseTensorMeta& x_meta,
out_dim_vector.push_back(1);
}
}
DDim out_dim = paddle::framework::make_ddim(out_dim_vector);
DDim out_dim = pten::framework::make_ddim(out_dim_vector);
DataType out_dtype;
if (dtype != DataType::UNDEFINED) {
......
paddle/pten/kernels/cpu/elementwise.h
浏览文件 @ 4e23ba32
......@@ -583,8 +583,8 @@ void CommonElementwiseBroadcastBackward(const CPUContext& ctx,
}
VLOG(3) << "CommonElementwiseBroadcastBackward xdims:"
<< paddle::framework::make_ddim(x_dims_array)
<< " ydim:" << paddle::framework::make_ddim(y_dims_array);
<< pten::framework::make_ddim(x_dims_array)
<< " ydim:" << pten::framework::make_ddim(y_dims_array);
CommonGradBroadcastCPU<T, DX_OP, DY_OP, Tout>(x,
y,
......
paddle/pten/kernels/cpu/reduce.h
浏览文件 @ 4e23ba32
......@@ -50,13 +50,13 @@ void ReduceFunctor(const DeviceContext& context,
DDim out_dims = output->dims();
if (keep_dim && x_rank > 1) {
const int kDelFlag = -2;
auto dims_vector = paddle::framework::vectorize(out_dims);
auto dims_vector = pten::framework::vectorize(out_dims);
for (size_t i = 0; i < dims_ref.size(); ++i) {
dims_vector[dims_ref[i]] = kDelFlag;
}
dims_vector.erase(remove(dims_vector.begin(), dims_vector.end(), kDelFlag),
dims_vector.end());
out_dims = paddle::framework::make_ddim(dims_vector);
out_dims = pten::framework::make_ddim(dims_vector);
}
auto& place = *context.eigen_device();
Functor functor;
......
paddle/pten/kernels/empty_kernel.cc
浏览文件 @ 4e23ba32
......@@ -24,7 +24,7 @@ template <typename T, typename Context>
void EmptyKernel(const Context& dev_ctx,
const ScalarArray& shape,
DenseTensor* out) {
out->ResizeAndAllocate(paddle::framework::make_ddim(shape.GetData()));
out->ResizeAndAllocate(pten::framework::make_ddim(shape.GetData()));
}
template <typename T, typename Context>
......
paddle/pten/kernels/flatten_grad_kernel.cc
浏览文件 @ 4e23ba32
......@@ -25,8 +25,7 @@ void FlattenGradKernel(const Context& dev_ctx,
const DenseTensor& xshape,
DenseTensor* x_grad) {
auto xshape_dims = xshape.dims();
auto x_dims =
paddle::framework::slice_ddim(xshape_dims, 1, xshape_dims.size());
auto x_dims = pten::framework::slice_ddim(xshape_dims, 1, xshape_dims.size());
pten::Copy(dev_ctx, out_grad, false, x_grad);
x_grad->ResizeAndAllocate(x_dims);
}
......
paddle/pten/kernels/funcs/common_shape.h
浏览文件 @ 4e23ba32
......@@ -26,7 +26,7 @@ inline void SetXShape(const DenseTensor &x, DenseTensor *xshape) {
for (int i = 0; i < in_dims.size(); ++i) {
xshape_dims[i + 1] = in_dims[i];
}
xshape->ResizeAndAllocate(paddle::framework::make_ddim(xshape_dims));
xshape->ResizeAndAllocate(pten::framework::make_ddim(xshape_dims));
xshape->ResetLoD(x.meta().lod);
}
......
paddle/pten/kernels/funcs/elementwise_base.h
浏览文件 @ 4e23ba32
......@@ -36,10 +36,10 @@ enum ElementwiseType { kUnary = 1, kBinary = 2, kTernary = 3, kAny = -1 };
for supporting multiple-output feature in elementwise system.*/
template <class T, int Num>
using ConditionalT =
typename std::conditional_t<Num == 1, T, paddle::framework::Array<T, Num>>;
typename std::conditional_t<Num == 1, T, pten::framework::Array<T, Num>>;
namespace funcs {
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
template <typename T, typename DX_OP, typename DY_OP, typename Tout = T>
struct ElemwiseGradNoBroadcast {
......@@ -303,9 +303,9 @@ inline DDim trim_trailing_singular_dims(const DDim &dims) {
trim_dims[i] = dims[i];
}
if (trim_dims.size() == 0) {
return DDim(paddle::framework::make_dim());
return DDim(pten::framework::make_dim());
}
DDim actual_dims = paddle::framework::make_ddim(trim_dims);
DDim actual_dims = pten::framework::make_ddim(trim_dims);
return actual_dims;
}
......@@ -377,7 +377,7 @@ void ElemwiseGradComputeNoBroadcast(const DeviceContext &dev_ctx,
DenseTensor *dy,
DX_OP dx_op,
DY_OP dy_op) {
size_t N = static_cast<size_t>(paddle::framework::product(x_dim));
size_t N = static_cast<size_t>(pten::framework::product(x_dim));
paddle::platform::ForRange<DeviceContext> for_range(dev_ctx, N);
for_range(ElemwiseGradNoBroadcast<T, DX_OP, DY_OP, Tout>{
x.data<T>(),
......@@ -462,7 +462,7 @@ struct ElementwisePrimitiveCaller<InT, OutT, VecSize, Functor, 3, false> {
template <typename OutT, int VecSize, bool IsBoundary, int NumOuts>
struct ElementwiseWriteDataCaller {
__device__ __forceinline__ void operator()(
paddle::framework::Array<_ptr_ OutT *, NumOuts> outs,
pten::framework::Array<_ptr_ OutT *, NumOuts> outs,
ConditionalT<OutT, NumOuts> src[VecSize],
int block_offset,
int num) {
......@@ -485,7 +485,7 @@ struct ElementwiseWriteDataCaller {
template <typename OutT, int VecSize, bool IsBoundary>
struct ElementwiseWriteDataCaller<OutT, VecSize, IsBoundary, 1> {
__device__ __forceinline__ void operator()(
paddle::framework::Array<_ptr_ OutT *, 1> outs,
pten::framework::Array<_ptr_ OutT *, 1> outs,
OutT src[VecSize],
int block_offset,
int num) {
......@@ -502,8 +502,8 @@ template <typename InT,
int VecSize,
bool IsBoundary>
__device__ void VectorizedElementwiseKernelImpl(
const paddle::framework::Array<const _ptr_ InT *__restrict__, Arity> &in,
paddle::framework::Array<_ptr_ OutT *, NumOuts> outs,
const pten::framework::Array<const _ptr_ InT *__restrict__, Arity> &in,
pten::framework::Array<_ptr_ OutT *, NumOuts> outs,
int num,
int data_offset,
Functor func) {
......@@ -537,8 +537,8 @@ template <typename InT,
int NumOuts,
int VecSize>
__global__ void VectorizedElementwiseKernel(
paddle::framework::Array<const _ptr_ InT *__restrict__, Arity> ins,
paddle::framework::Array<_ptr_ OutT *, NumOuts> outs,
pten::framework::Array<const _ptr_ InT *__restrict__, Arity> ins,
pten::framework::Array<_ptr_ OutT *, NumOuts> outs,
int size,
int main_offset,
Functor func) {
......@@ -578,8 +578,8 @@ void ElementwiseCudaKernel(const KPDevice &ctx,
std::vector<DenseTensor *> *outs,
Functor func) {
auto numel = ins[0]->numel();
paddle::framework::Array<const _ptr_ InT *__restrict__, Arity> ins_data;
paddle::framework::Array<_ptr_ OutT *, NumOuts> outs_data;
pten::framework::Array<const _ptr_ InT *__restrict__, Arity> ins_data;
pten::framework::Array<_ptr_ OutT *, NumOuts> outs_data;
for (int i = 0; i < Arity; ++i) {
ins_data[i] = ins[i]->data<InT>();
......
paddle/pten/kernels/funcs/elementwise_functor.h
浏览文件 @ 4e23ba32
......@@ -15,8 +15,8 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/pten/common/float16.h"
#include "paddle/pten/core/hostdevice.h"
namespace pten {
namespace funcs {
......
paddle/pten/kernels/funcs/transpose.cc
浏览文件 @ 4e23ba32
......@@ -13,8 +13,8 @@
// limitations under the License.
#include "paddle/pten/kernels/funcs/transpose.h"
#include "paddle/fluid/framework/ddim.h"
#include "paddle/pten/backends/cpu/cpu_context.h"
#include "paddle/pten/core/ddim.h"
#include "paddle/pten/core/dense_tensor.h"
// See Note [ Why still include the fluid headers? ]
......@@ -33,8 +33,8 @@ struct TransposeNormal<CPUContext, T> {
pten::DenseTensor* out,
const std::vector<int64_t>& axis) {
const int rank = axis.size();
auto in_stride = paddle::framework::stride(in.dims());
auto out_stride = paddle::framework::stride(out->dims());
auto in_stride = pten::framework::stride(in.dims());
auto out_stride = pten::framework::stride(out->dims());
const T* in_ptr = in.data<T>();
T* out_ptr = out->mutable_data<T>();
......
paddle/pten/kernels/funcs/transpose.cu
浏览文件 @ 4e23ba32
......@@ -12,9 +12,9 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/framework/ddim.h"
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/pten/backends/gpu/gpu_context.h"
#include "paddle/pten/core/ddim.h"
#include "paddle/pten/core/dense_tensor.h"
#include "paddle/pten/kernels/funcs/transpose.h"
......@@ -58,8 +58,8 @@ struct TransposeNormal<GPUContext, T> {
pten::DenseTensor* out,
const std::vector<int64_t>& axis) {
const int rank = axis.size();
auto in_stride = paddle::framework::stride(in.dims());
auto out_stride = paddle::framework::stride(out->dims());
auto in_stride = pten::framework::stride(in.dims());
auto out_stride = pten::framework::stride(out->dims());
auto* in_ptr = in.data<T>();
auto* out_ptr = out->mutable_data<T>();
......
paddle/pten/kernels/funcs/transpose.h
浏览文件 @ 4e23ba32
......@@ -14,7 +14,7 @@
#pragma once
#include "paddle/fluid/framework/ddim.h"
#include "paddle/pten/core/ddim.h"
#include "paddle/pten/core/dense_tensor.h"
#include "paddle/fluid/operators/eigen/eigen_function.h"
......
paddle/pten/kernels/gpu/elementwise.h
浏览文件 @ 4e23ba32
......@@ -130,14 +130,14 @@ struct DimensionsTransform {
public:
explicit DimensionsTransform(const std::vector<const DenseTensor *> &ins,
const paddle::framework::DDim &dims,
const pten::framework::DDim &dims,
int axis) {
const int N = ins.size();
dim_size = dims.size();
out_dims = paddle::framework::vectorize<int64_t>(dims);
out_dims = pten::framework::vectorize<int64_t>(dims);
in_dims.resize(N);
for (int j = 0; j < N; ++j) {
in_dims[j] = paddle::framework::vectorize<int64_t>(ins[j]->dims());
in_dims[j] = pten::framework::vectorize<int64_t>(ins[j]->dims());
}
InputDimensionsExtend(N, axis);
......@@ -214,11 +214,11 @@ template <typename InT,
int Rank,
bool IsBoundary = false>
__device__ void ElementwiseBroadcastKernelImpl(
const paddle::framework::Array<const _ptr_ InT *__restrict__, Arity> &ins,
paddle::framework::Array<_ptr_ OutT *, NumOuts> outs,
const paddle::framework::Array<int, Arity> &use_broadcast,
const pten::framework::Array<const _ptr_ InT *__restrict__, Arity> &ins,
pten::framework::Array<_ptr_ OutT *, NumOuts> outs,
const pten::framework::Array<int, Arity> &use_broadcast,
uint32_t numel,
const paddle::framework::Array<kps::details::BroadcastConfig<Rank>, Arity>
const pten::framework::Array<kps::details::BroadcastConfig<Rank>, Arity>
&configs,
int num,
int block_offset,
......@@ -259,12 +259,11 @@ template <typename InT,
int VecSize,
int Rank>
__global__ void ElementwiseBroadcastKernel(
paddle::framework::Array<const _ptr_ InT *__restrict__, Arity> ins,
paddle::framework::Array<_ptr_ OutT *, NumOuts> outs,
paddle::framework::Array<int, Arity> use_broadcast,
pten::framework::Array<const _ptr_ InT *__restrict__, Arity> ins,
pten::framework::Array<_ptr_ OutT *, NumOuts> outs,
pten::framework::Array<int, Arity> use_broadcast,
uint32_t numel,
paddle::framework::Array<kps::details::BroadcastConfig<Rank>, Arity>
configs,
pten::framework::Array<kps::details::BroadcastConfig<Rank>, Arity> configs,
int main_offset,
int tail_tid,
Functor func) {
......@@ -345,10 +344,10 @@ void LaunchKernel(const KPDevice &ctx,
Functor func,
DimensionsTransform merge_dims) {
int numel = (*outs)[0]->numel();
paddle::framework::Array<kps::details::BroadcastConfig<Rank>, Arity> configs;
paddle::framework::Array<int, Arity> use_broadcast;
paddle::framework::Array<const _ptr_ InT *__restrict__, Arity> ins_data;
paddle::framework::Array<_ptr_ OutT *, NumOuts> outs_data;
pten::framework::Array<kps::details::BroadcastConfig<Rank>, Arity> configs;
pten::framework::Array<int, Arity> use_broadcast;
pten::framework::Array<const _ptr_ InT *__restrict__, Arity> ins_data;
pten::framework::Array<_ptr_ OutT *, NumOuts> outs_data;
for (int i = 0; i < NumOuts; ++i) {
outs_data[i] = (*outs)[i]->mutable_data<OutT>();
......@@ -444,7 +443,7 @@ void LaunchBroadcastKernelForDifferentVecSize(
"The maximum dimension of input tensor is expected to be less than "
"%d, but recieved %d.\n",
merge_dims.dim_size,
paddle::framework::DDim::kMaxRank));
pten::framework::DDim::kMaxRank));
}
}
#undef CALL_BROADCAST_FOR_DIM_SIZE
......@@ -1826,8 +1825,8 @@ void CommonElementwiseBroadcastBackward(const GPUContext &ctx,
}
VLOG(3) << "CommonElementwiseBroadcastBackward xdims:"
<< paddle::framework::make_ddim(x_dims_array)
<< " ydim:" << paddle::framework::make_ddim(y_dims_array);
<< pten::framework::make_ddim(x_dims_array)
<< " ydim:" << pten::framework::make_ddim(y_dims_array);
CommonGradBroadcastCUDA<T, DX_OP, DY_OP, Tout>(x,
y,
......
paddle/pten/kernels/gpu/reduce.h
浏览文件 @ 4e23ba32
......@@ -32,7 +32,6 @@
namespace cub = hipcub;
#endif
#include "paddle/fluid/framework/array.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/amp/fp16_type_traits.h"
#include "paddle/fluid/operators/kernel_primitives/kernel_primitives.h"
......@@ -41,6 +40,7 @@ namespace cub = hipcub;
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/fast_divmod.h"
#include "paddle/fluid/string/string_helper.h"
#include "paddle/pten/core/array.h"
#include "paddle/pten/api/ext/dispatch.h"
#include "paddle/pten/backends/gpu/gpu_context.h"
......@@ -118,7 +118,7 @@ static inline void CheckReduceRank(int reduce_rank, int rank) {
// convert dims from vector to array
template <typename T, size_t ElementCount, typename VectorLikeType>
static inline paddle::framework::Array<T, ElementCount> VectorToArray(
static inline pten::framework::Array<T, ElementCount> VectorToArray(
const VectorLikeType& vec) {
PADDLE_ENFORCE_LE(vec.size(),
ElementCount,
......@@ -128,7 +128,7 @@ static inline paddle::framework::Array<T, ElementCount> VectorToArray(
vec.size(),
ElementCount));
size_t n = static_cast<size_t>(vec.size());
paddle::framework::Array<T, ElementCount> ret;
pten::framework::Array<T, ElementCount> ret;
for (size_t i = 0; i < n; ++i) {
ret[i] = vec[i];
}
......@@ -162,7 +162,7 @@ static inline std::vector<int> GetReduceDim(const std::vector<int64_t>& dims,
} // namespace details
constexpr int kMaxRank = paddle::framework::DDim::kMaxRank;
constexpr int kMaxRank = pten::framework::DDim::kMaxRank;
enum ReduceType {
kReduceLastDim = 0x01, // when reduce_dim[0] == x_dim.size() - 1;
......@@ -202,9 +202,9 @@ struct IndexCalculator {
}
int dim;
paddle::framework::Array<int, kMaxRank> dims;
paddle::framework::Array<int, kMaxRank> strides;
paddle::framework::Array<paddle::platform::FastDivMod, kMaxRank> divmoders;
pten::framework::Array<int, kMaxRank> dims;
pten::framework::Array<int, kMaxRank> strides;
pten::framework::Array<paddle::platform::FastDivMod, kMaxRank> divmoders;
};
template <bool ReduceLastDim = false>
......@@ -326,7 +326,7 @@ struct ReduceConfig {
const paddle::platform::Place& place,
pten::DenseTensor* tmp) {
if (should_reduce_again) {
tmp->ResizeAndAllocate(paddle::framework::make_ddim(
tmp->ResizeAndAllocate(pten::framework::make_ddim(
{static_cast<int64_t>(left_num * grid.z * grid.y * sizeof(Ty))}));
output_data = tmp->mutable_data<Ty>();
} else {
......@@ -1029,7 +1029,7 @@ static
pten::DenseTensor tmp = pten::DenseTensor(
pten::make_intrusive<paddle::experimental::SharedStorage>(place),
pten::DenseTensorMeta(pten::DataType::UINT8,
paddle::framework::make_ddim(
pten::framework::make_ddim(
{static_cast<int64_t>(temp_storage_bytes)})));
auto* temp_storage = tmp.mutable_data<uint8_t>();
......@@ -1073,7 +1073,7 @@ void TensorReduceFunctorImpl(const pten::DenseTensor& x,
// Allocate memory
y->mutable_data<Ty>();
auto x_dim = paddle::framework::vectorize<int>(x.dims());
auto x_dim = pten::framework::vectorize<int>(x.dims());
auto config = ReduceConfig<Ty>(origin_reduce_dims, x_dim);
config.Run();
int numel = x.numel();
......
paddle/pten/kernels/impl/dot_grad_kernel_impl.h
浏览文件 @ 4e23ba32
......@@ -103,7 +103,7 @@ struct DotGradFunction<DeviceContext,
auto* data_dx = tensor_dx->mutable_data<T>();
const auto* data_y = tensor_y->data<T>();
const DDim& dim = tensor_x->dims();
size_t N = static_cast<size_t>(paddle::framework::product(dim));
size_t N = static_cast<size_t>(pten::framework::product(dim));
auto step = dim[dim.size() - 1];
......@@ -118,7 +118,7 @@ struct DotGradFunction<DeviceContext,
auto* data_dy = tensor_dy->mutable_data<T>();
const auto* data_x = tensor_x->data<T>();
const DDim& dim = tensor_y->dims();
size_t N = static_cast<size_t>(paddle::framework::product(dim));
size_t N = static_cast<size_t>(pten::framework::product(dim));
auto step = dim[dim.size() - 1];
......
paddle/pten/kernels/impl/full_kernel_impl.h
浏览文件 @ 4e23ba32
......@@ -36,7 +36,7 @@ void FullKernel(const Context& dev_ctx,
const ScalarArray& shape,
const Scalar& val,
DenseTensor* out) {
out->ResizeAndAllocate(paddle::framework::make_ddim(shape.GetData()));
out->ResizeAndAllocate(pten::framework::make_ddim(shape.GetData()));
FullValue<T>(dev_ctx, out, val.to<T>());
}
......
paddle/pten/kernels/impl/matmul_grad_kernel_impl.h
浏览文件 @ 4e23ba32
......@@ -135,7 +135,7 @@ static DDim RowMatrixFromVector(const DDim& x_dim) {
if (x_dim.size() > 1) {
return x_dim;
}
return paddle::framework::make_ddim({1, x_dim[0]});
return pten::framework::make_ddim({1, x_dim[0]});
}
/**
......@@ -146,7 +146,7 @@ static DDim ColumnMatrixFromVector(const DDim& y_dim) {
if (y_dim.size() > 1) {
return y_dim;
}
return paddle::framework::make_ddim({y_dim[0], 1});
return pten::framework::make_ddim({y_dim[0], 1});
}
/**
......
paddle/pten/kernels/impl/matmul_kernel_impl.h
浏览文件 @ 4e23ba32
......@@ -164,7 +164,7 @@ void MatMulFunction(const Context& dev_ctx,
std::copy_n(y_dims.cbegin(), y_ndim - 2, out_dims.begin());
out_dims.back() = y_dims.back();
}
Out->ResizeAndAllocate(paddle::framework::make_ddim(out_dims));
Out->ResizeAndAllocate(pten::framework::make_ddim(out_dims));
Out->mutable_data<T>();
if (trans_y) {
const int M = Y.numel() / N;
......@@ -242,7 +242,7 @@ void MatMulFunction(const Context& dev_ctx,
} else {
std::copy_n(x_dims.cbegin(), x_ndim - 1, out_dims.begin());
}
Out->ResizeAndAllocate(paddle::framework::make_ddim(out_dims));
Out->ResizeAndAllocate(pten::framework::make_ddim(out_dims));
Out->mutable_data<T>();
if (trans_x) {
......@@ -330,7 +330,7 @@ void MatMulFunction(const Context& dev_ctx,
out_broadcast_dims[ndim - 2] = M;
out_broadcast_dims[ndim - 1] = N;
Out->ResizeAndAllocate(paddle::framework::make_ddim(out_broadcast_dims));
Out->ResizeAndAllocate(pten::framework::make_ddim(out_broadcast_dims));
Out->mutable_data<T>();
const int batch_dim = ndim - 2;
......@@ -493,12 +493,12 @@ void MatmulKernel(const Context& dev_ctx,
bool transpose_x,
bool transpose_y,
DenseTensor* out) {
PADDLE_ENFORCE_NE(paddle::framework::product(x.dims()),
PADDLE_ENFORCE_NE(pten::framework::product(x.dims()),
0,
paddle::platform::errors::InvalidArgument(
"The Input(X) dims size must not be equal 0,"
" but reviced dims size is 0. "));
PADDLE_ENFORCE_NE(paddle::framework::product(y.dims()),
PADDLE_ENFORCE_NE(pten::framework::product(y.dims()),
0,
paddle::platform::errors::InvalidArgument(
"The Input(Y) dims size must not be equal 0,"
......
paddle/pten/tests/api/test_cast_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, cast) {
......
paddle/pten/tests/api/test_conj_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, conj) {
......
paddle/pten/tests/api/test_dot_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, dot) {
......
paddle/pten/tests/api/test_elementwise_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, add) {
......
paddle/pten/tests/api/test_empty_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, empty_like) {
......
paddle/pten/tests/api/test_fill_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, full_like) {
......
paddle/pten/tests/api/test_flatten_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, flatten) {
......
paddle/pten/tests/api/test_matmul_api.cc
浏览文件 @ 4e23ba32
......@@ -26,7 +26,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
TEST(API, matmul_cpu) {
// 1. create tensor
......
paddle/pten/tests/api/test_mean_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, mean) {
......
paddle/pten/tests/api/test_reshape_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, reshape) {
......
paddle/pten/tests/api/test_scale_api.cc
浏览文件 @ 4e23ba32
......@@ -24,7 +24,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
void CheckScaleResult(experimental::Tensor* out) {
ASSERT_EQ(out->dims().size(), 2);
......
paddle/pten/tests/api/test_sum_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(chenweihang): Remove this test after the API is used in the dygraph
TEST(API, sum) {
......
paddle/pten/tests/api/test_to_api.cc
浏览文件 @ 4e23ba32
......@@ -25,7 +25,7 @@ namespace paddle {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
paddle::experimental::Tensor CreateInputTensor() {
const auto alloc = std::make_unique<paddle::experimental::DefaultAllocator>(
......
paddle/pten/tests/kernels/test_cast_dev_api.cc
浏览文件 @ 4e23ba32
......@@ -28,7 +28,7 @@ namespace pten {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
TEST(DEV_API, cast) {
// 1. create tensor
......
paddle/pten/tests/kernels/test_conj_dev_api.cc
浏览文件 @ 4e23ba32
......@@ -26,7 +26,7 @@ namespace pten {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
TEST(DEV_API, conj) {
// 1. create tensor
......
paddle/pten/tests/kernels/test_copy_dev_api.cc
浏览文件 @ 4e23ba32
......@@ -26,7 +26,7 @@ namespace pten {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
// TODO(YuanRisheng): This TEST file need to be refactored after 'copy' realized
// in 'paddle/api'
......
paddle/pten/tests/kernels/test_creation_dev_api.cc
浏览文件 @ 4e23ba32
......@@ -27,7 +27,7 @@ namespace pten {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
TEST(DEV_API, empty) {
// 1. create input
......
paddle/pten/tests/kernels/test_dot_dev_api.cc
浏览文件 @ 4e23ba32
......@@ -26,7 +26,7 @@ namespace pten {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
TEST(DEV_API, dot) {
// 1. create tensor
......
paddle/pten/tests/kernels/test_elementwise_dev_api.cc
浏览文件 @ 4e23ba32
......@@ -26,7 +26,7 @@ namespace pten {
namespace tests {
namespace framework = paddle::framework;
using DDim = paddle::framework::DDim;
using DDim = pten::framework::DDim;
TEST(DEV_API, add) {
// 1. create tensor
......
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