change the meta modification rules, test=develop (#37255)

paddle/pten/core/CMakeLists.txt

@@ -10,4 +10,5 @@ cc_library(kernel_factory SRCS kernel_factory.cc DEPS enforce)
 cc_library(kernel_context SRCS kernel_context.cc DEPS enforce device_context)
 
 cc_library(tensor_base SRCS tensor_base.cc allocator.cc storage.cc DEPS enforce)
-cc_library(dense_tensor SRCS dense_tensor.cc DEPS tensor_base)
+cc_library(tensor_meta SRCS tensor_meta.cc DEPS enforce)
+cc_library(dense_tensor SRCS dense_tensor.cc DEPS tensor_meta tensor_base)

paddle/pten/core/compat_utils.h

@@ -49,7 +49,14 @@ class CompatibleDenseTensorUtils {
   static DenseTensor Slice(DenseTensor* tensor,
                            int64_t begin_idx,
                            int64_t end_idx) {
-    tensor->check_memory_size();
+    size_t bytes = tensor->numel() * SizeOf(tensor->dtype());
+    PADDLE_ENFORCE_GE(tensor->capacity(),
+                      bytes,
+                      paddle::platform::errors::InvalidArgument(
+                          "The memory size %d should be enough to meet the "
+                          "volume required by metadata %d.",
+                          tensor->capacity(),
+                          bytes));
     PADDLE_ENFORCE_GE(begin_idx,
                       0,
                       paddle::platform::errors::OutOfRange(

paddle/pten/core/dense_tensor.cc

@@ -112,29 +112,18 @@ const void* DenseTensor::data() const {
   return storage_->data();
 }
 
-void DenseTensor::check_memory_size() const {
-  size_t bytes = numel() * SizeOf(dtype());
-  PADDLE_ENFORCE_GE(memory_size(),
-                    bytes,
+void DenseTensor::set_meta(DenseTensorMeta&& meta) {
+  PADDLE_ENFORCE(!meta_.valid(),
                  paddle::platform::errors::InvalidArgument(
-                        "The memory size %d should be enough to meet the "
-                        "volume required by metadata %d.",
-                        memory_size(),
-                        bytes));
-}
-
-void DenseTensor::Resize(const DDim& dims) {
-  if (product(dims) == product(meta_.dims)) {
-    set_dims(dims);
-  } else {
-    meta_.dims = dims;
-    storage_->Clear();
-  }
+                     "Only when the original attribute of Tensor is "
+                     "incomplete, can it be reset."));
+  meta_ = std::move(meta);
 }
 
-void DenseTensor::set_dims(const DDim& dims) {
-  CHECK(product(dims) == product(meta_.dims));
+void DenseTensor::Resize(const DDim& dims, const LoD& lod) {
   meta_.dims = dims;
+  meta_.lod = lod;
+  mutable_data();
 }
 
 #define DATA_MEMBER_FUNC_INSTANTIATION(dtype)  \

paddle/pten/core/dense_tensor.h

@@ -88,9 +88,6 @@ class DenseTensor : public TensorBase,
     return meta_.lod;
   }
 
-  /// \brief Set the lod of the tensor.
-  void set_lod(const std::vector<std::vector<size_t>>& lod) { meta_.lod = lod; }
-
   /// \brief Returns the data type of the tensor.
   /// \return The data type of the tensor.
   DataType dtype() const noexcept override { return meta_.type; }
@@ -107,6 +104,11 @@ class DenseTensor : public TensorBase,
   /// \return The meta information of the tensor.
   const DenseTensorMeta& meta() const noexcept { return meta_; }
 
+  /// \brief Sets the meta information of the tensor. Only when the original
+  /// attribute of Tensor is incomplete, can it be reset.
+  /// \param meta The meta information of the tensor.
+  void set_meta(DenseTensorMeta&& meta);
+
   /// \brief Test whether the metadata is valid.
   /// \return Whether the metadata is valid.
   bool valid() const noexcept override { return meta_.valid(); }
@@ -121,25 +123,16 @@ class DenseTensor : public TensorBase,
   /// \return Whether the storage is shared with other objects.
   bool IsSharedWith(const DenseTensor& b) const;
 
-  /// \brief Change the dims information in the metadata. If the new size is
-  /// inconsistent with the original value, the storage area will be released
-  /// to avoid wrong access.
+  /// \brief Change the shape information in the metadata. If the new size is
+  /// larger than the original value, the storage area will be reallocated.
   /// \param dims The new dims of the dense tensor.
-  void Resize(const DDim& dims);
-
-  /// \brief Change the dims information in the metadata.
-  /// \param dims The new dims of the dense tensor. The product of the dims
-  /// elements must be consistent with the original value.
-  void set_dims(const DDim& dims);
+  /// \param lod The new lod of the dense tensor.
+  void Resize(const DDim& dims, const LoD& lod = {});
 
   /// \brief Returns the actual storage size occupied by tensor, may be larger
   /// than its shape dims.
   /// \return The actual storage size occupied by tensor.
-  size_t memory_size() const { return storage_->size(); }
-
-  /// \brief Check that the storage area is large enough to hold the data of the
-  /// metadata size, and throw an exception if the conditions are not met.
-  void check_memory_size() const;
+  size_t capacity() const { return storage_->size(); }
 
   /// \brief Release the storage area for other purposes. Because of the
   /// destruction of encapsulation, we do not support two dense tensors directly

paddle/pten/core/tensor_meta.cc

+/* Copyright (c) 2021 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/tensor_meta.h"
+
+namespace pten {
+
+DenseTensorMeta::DenseTensorMeta(DataType type, const DDim& dims)
+    : dims(dims), type(type) {}
+
+DenseTensorMeta::DenseTensorMeta(DataType type,
+                                 const DDim& dims,
+                                 DataLayout layout)
+    : dims(dims), type(type), layout(layout) {}
+
+DenseTensorMeta::DenseTensorMeta(DataType type,
+                                 const DDim& dims,
+                                 DataLayout layout,
+                                 const std::vector<std::vector<size_t>>& lod)
+    : dims(dims), type(type), layout(layout), lod(lod) {}
+
+bool DenseTensorMeta::valid() const noexcept {
+  bool valid{true};
+  valid = valid && (type != DataType::UNDEFINED);
+  valid = valid && (layout != DataLayout::UNDEFINED);
+  valid = valid && (is_scalar || product(dims) >= 0);
+  return valid;
+}
+
+bool operator==(const DenseTensorMeta& lhs, const DenseTensorMeta& rhs) {
+  bool ret = true;
+  return ret && (lhs.is_scalar == rhs.is_scalar) && (lhs.dims == rhs.dims) &&
+         (lhs.type == rhs.type) && (lhs.layout == rhs.layout) &&
+         (lhs.lod == rhs.lod) && (lhs.offset == rhs.offset);
+}
+}  // namespace pten

paddle/pten/core/tensor_meta.h

@@ -52,42 +52,12 @@ struct DenseTensorMeta {
 
   /// During the entire life cycle of a DenseTensor, the following attributes
   /// marked with `const` are expected to remain unchanged.
-  const bool is_scalar{false};
+  bool is_scalar{false};
   DDim dims;
-  const DataType type{DataType::UNDEFINED};
-  const DataLayout layout{DataLayout::NCHW};
+  DataType type{DataType::UNDEFINED};
+  DataLayout layout{DataLayout::NCHW};
   LoD lod;
   size_t offset{0};
 };
 
-inline DenseTensorMeta::DenseTensorMeta(DataType type, const DDim& dims)
-    : dims(dims), type(type) {}
-
-inline DenseTensorMeta::DenseTensorMeta(DataType type,
-                                        const DDim& dims,
-                                        DataLayout layout)
-    : dims(dims), type(type), layout(layout) {}
-
-inline DenseTensorMeta::DenseTensorMeta(
-    DataType type,
-    const DDim& dims,
-    DataLayout layout,
-    const std::vector<std::vector<size_t>>& lod)
-    : dims(dims), type(type), layout(layout), lod(lod) {}
-
-inline bool DenseTensorMeta::valid() const noexcept {
-  bool valid{true};
-  valid = valid && (type != DataType::UNDEFINED);
-  valid = valid && (layout != DataLayout::UNDEFINED);
-  valid = valid && (is_scalar || product(dims) >= 0);
-  return valid;
-}
-
-inline bool operator==(const DenseTensorMeta& lhs, const DenseTensorMeta& rhs) {
-  bool ret = true;
-  return ret && (lhs.is_scalar == rhs.is_scalar) && (lhs.dims == rhs.dims) &&
-         (lhs.type == rhs.type) && (lhs.layout == rhs.layout) &&
-         (lhs.lod == rhs.lod) && (lhs.offset == rhs.offset);
-}
-
 }  // namespace pten

paddle/pten/kernels/cpu/manipulation.cc

@@ -44,17 +44,27 @@ void FlattenWithXShape(const CPUContext& dev_ctx,
   general::SetXShape(x, xshape);
 }
 
-void ReshapeFromVectorVal(const CPUContext& dev_ctx,
+void ReshapeFromVectorValImpl(const CPUContext& dev_ctx,
                               const DenseTensor& x,
                               const std::vector<int64_t>& shape,
-                          DenseTensor* out) {
+                              DenseTensor* out,
+                              bool set_lod) {
   auto out_meta = InferShapeFromVecValue(x.meta(), shape);
-  if (&x == out) {
-    out->Resize(out_meta.dims);
-    return;
-  }
+  if (&x != out) {
     pten::Copy(dev_ctx, x, out);
+  }
+  if (set_lod) {
+    out->Resize(out_meta.dims, out_meta.lod);
+  } else {
     out->Resize(out_meta.dims);
+  }
+}
+
+void ReshapeFromVectorVal(const CPUContext& dev_ctx,
+                          const DenseTensor& x,
+                          const std::vector<int64_t>& shape,
+                          DenseTensor* out) {
+  ReshapeFromVectorValImpl(dev_ctx, x, shape, out, false);
 }
 
 void ReshapeFromVectorValWithXShape(const CPUContext& dev_ctx,
@@ -73,8 +83,7 @@ void ReshapeFromDT(const CPUContext& dev_ctx,
   auto* shape_data = shape.data<int>();
   auto vector_shape =
       std::vector<int64_t>(shape_data, shape_data + shape.numel());
-  ReshapeFromVectorVal(dev_ctx, x, vector_shape, out);
-  out->set_lod(x.lod());
+  ReshapeFromVectorValImpl(dev_ctx, x, vector_shape, out, true);
 }
 
 void ReshapeFromDTWithXShape(const CPUContext& dev_ctx,

paddle/pten/kernels/cuda/manipulation.cu

@@ -44,18 +44,27 @@ void FlattenWithXShape(const CUDAContext& dev_ctx,
   general::SetXShape(x, xshape);
 }
 
-void ReshapeFromVectorVal(const CUDAContext& dev_ctx,
+void ReshapeFromVectorValImpl(const CUDAContext& dev_ctx,
                               const DenseTensor& x,
                               const std::vector<int64_t>& shape,
-                          DenseTensor* out) {
+                              DenseTensor* out,
+                              bool set_lod) {
   auto out_meta = InferShapeFromVecValue(x.meta(), shape);
-  if (&x == out) {
-    LOG(INFO) << "out_meta dims:" << out_meta.dims;
-    out->Resize(out_meta.dims);
-    return;
-  }
+  if (&x != out) {
     pten::Copy(dev_ctx, x, false, out);
+  }
+  if (set_lod) {
+    out->Resize(out_meta.dims, out_meta.lod);
+  } else {
     out->Resize(out_meta.dims);
+  }
+}
+
+void ReshapeFromVectorVal(const CUDAContext& dev_ctx,
+                          const DenseTensor& x,
+                          const std::vector<int64_t>& shape,
+                          DenseTensor* out) {
+  ReshapeFromVectorValImpl(dev_ctx, x, shape, out, false);
 }
 
 void ReshapeFromVectorValWithXShape(const CUDAContext& dev_ctx,
@@ -74,8 +83,7 @@ void ReshapeFromDT(const CUDAContext& dev_ctx,
   auto* shape_data = shape.data<int>();
   auto vector_shape =
       std::vector<int64_t>(shape_data, shape_data + shape.numel());
-  ReshapeFromVectorVal(dev_ctx, x, vector_shape, out);
-  out->set_lod(x.lod());
+  ReshapeFromVectorValImpl(dev_ctx, x, vector_shape, out, true);
 }
 
 void ReshapeFromDTWithXShape(const CUDAContext& dev_ctx,

paddle/pten/kernels/functions/general/manipulation.h

@@ -26,8 +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->Resize(paddle::framework::make_ddim(xshape_dims));
-  xshape->set_lod(x.meta().lod);
+  xshape->Resize(paddle::framework::make_ddim(xshape_dims), x.meta().lod);
 }
 
 }  // namespace general

paddle/pten/kernels/xpu/manipulation.cc

@@ -47,8 +47,7 @@ void FlattenWithXShape(const XPUContext& dev_ctx,
   for (int i = 0; i < in_dims.size(); ++i) {
     xshape_dims[i + 1] = in_dims[i];
   }
-  xshape->Resize(paddle::framework::make_ddim(xshape_dims));
-  xshape->set_lod(x.lod());
+  xshape->Resize(paddle::framework::make_ddim(xshape_dims), x.meta().lod);
 }
 
 void ReshapeFromVectorVal(const XPUContext& dev_ctx,

paddle/pten/tests/core/test_dense_tensor.cc

@@ -112,14 +112,11 @@ TEST(dense_tensor, resize) {
   auto alloc = std::make_shared<FancyAllocator>();
   DenseTensor tensor_0(alloc, meta);
 
-  CHECK_EQ(tensor_0.memory_size(), 2u);
-  tensor_0.check_memory_size();
+  CHECK_EQ(tensor_0.capacity(), 2u);
   tensor_0.Resize({1, 2, 3});
-  CHECK_EQ(tensor_0.memory_size(), 0u);
-  tensor_0.set_dims({2, 3});
-  CHECK_EQ(tensor_0.memory_size(), 0u);
+  CHECK_EQ(tensor_0.capacity(), 6u);
   tensor_0.mutable_data<int8_t>();
-  CHECK_EQ(tensor_0.memory_size(), 6u);
+  CHECK_EQ(tensor_0.capacity(), 6u);
 
   auto storage = tensor_0.release();
   CHECK_EQ(storage->size(), 6u);