[cherry-pick 2.4] add sparse api transpose/reshape/is_same_shape

paddle/fluid/pybind/eager_method.cc

@@ -1588,6 +1588,15 @@ static PyObject* tensor_method_to_sparse_csr(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
+static PyObject* tensor_method_is_same_shape(TensorObject* self,
+                                             PyObject* args,
+                                             PyObject* kwargs) {
+  EAGER_TRY
+  auto other = CastPyArg2Tensor(PyTuple_GET_ITEM(args, 0), 0);
+  return ToPyObject(self->tensor.shape() == other.shape());
+  EAGER_CATCH_AND_THROW_RETURN_NULL
+}
+
 static PyObject* tensor__inplace_version(TensorObject* self,
                                          PyObject* args,
                                          PyObject* kwargs) {
@@ -1983,6 +1992,10 @@ PyMethodDef variable_methods[] = {
      (PyCFunction)(void (*)(void))tensor_method_is_sparse_csr,
      METH_VARARGS | METH_KEYWORDS,
      NULL},
+    {"is_same_shape",
+     (PyCFunction)(void (*)(void))tensor_method_is_same_shape,
+     METH_VARARGS | METH_KEYWORDS,
+     NULL},
     {"to_sparse_csr",
      (PyCFunction)(void (*)(void))tensor_method_to_sparse_csr,
      METH_VARARGS | METH_KEYWORDS,

paddle/phi/api/yaml/sparse_backward.yaml

@@ -260,6 +260,17 @@
     func : relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
            relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
 
+- backward_op : reshape_grad
+  forward : reshape(Tensor x, IntArray shape) -> Tensor(out)
+  args : (Tensor x, Tensor out_grad)
+  output : Tensor(x_grad)
+  infer_meta :
+    func : UnchangedInferMeta
+    param : [x]
+  kernel :
+    func : reshape_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
+           reshape_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
+
 - backward_op : scale_grad
   forward : scale(Tensor x, float scale, float bias, bool bias_after_scale) -> Tensor(out)
   args : (Tensor out_grad, float scale)
@@ -385,6 +396,17 @@
   kernel :
     func : coo_to_dense { sparse_coo -> dense }
 
+- backward_op : transpose_grad
+  forward : transpose(Tensor x, int[] perm) -> Tensor(out)
+  args : (Tensor out_grad, int[] perm)
+  output : Tensor(x_grad)
+  infer_meta :
+    func : TransposeGradInferMeta
+    param : [out_grad, perm]
+  kernel :
+    func : transpose_coo_grad {sparse_coo -> sparse_coo},
+           transpose_csr_grad {sparse_csr -> sparse_csr}
+
 - backward_op : values_grad
   forward : values_coo(Tensor x) -> Tensor(out)
   args : (Tensor x, Tensor out_grad)

paddle/phi/api/yaml/sparse_ops.yaml

@@ -457,3 +457,26 @@
            mv_csr{sparse_csr, dense -> dense}
     layout : x
   backward: mv_grad
+
+- op : transpose
+  args : (Tensor x, int[] perm)
+  output : Tensor(out)
+  infer_meta :
+    func : TransposeInferMeta
+    param: [ x, perm ]
+  kernel :
+    func : transpose_coo{sparse_coo -> sparse_coo},
+           transpose_csr{sparse_csr -> sparse_csr}
+    layout : x
+  backward : transpose_grad
+
+- op : reshape
+  args : (Tensor x,  IntArray shape)
+  output : Tensor(out)
+  infer_meta :
+    func : ReshapeInferMeta
+  kernel :
+    func : reshape_coo{sparse_coo -> sparse_coo},
+           reshape_csr{sparse_csr -> sparse_csr}
+    layout : x
+  backward : reshape_grad

paddle/phi/core/sparse_coo_tensor.h

@@ -274,7 +274,7 @@ class SparseCooTensor : public TensorBase,
                 [0, 0, 0, 0]]
      dims_ = (4, 4)
      non_zero_elements_ = [[0, 1, 0, 0], [0, 0, 4, 0]]
-     non_zero_indices_ = [0, 2],
+     non_zero_indices_ = [[0, 2], [1, 2]]
    */
 };
 

paddle/phi/core/sparse_csr_tensor.h

@@ -209,7 +209,7 @@ class SparseCsrTensor : public TensorBase,
           [0, 0, 4, 0],
           [0, 5, 0, 6]]
      dims_ = (4, 4)
-     non_zero_elements_ = [1, 2, 3, 4, 5 ,6]
+     non_zero_elements_ = [1, 2, 3, 4, 5, 6]
      non_zero_crows_ = [0, 1, 3, 4, 6]
      non_zero_cols_ = [1, 0, 3, 2, 1, 3]
    */
@@ -228,7 +228,7 @@ class SparseCsrTensor : public TensorBase,
           [0, 0, 4, 0],
           [0, 5, 0, 0]]]
      dims_ = (2, 4, 4)
-     non_zero_elements_ = [1, 2, 3, 4, 5 ,6, 1, 2, 3, 4, 5]
+     non_zero_elements_ = [1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5]
      non_zero_crows_ = [0, 1, 3, 4, 6, 0, 1, 2, 4, 5]
      non_zero_cols_ = [1, 0, 3, 2, 1, 3, 1, 0, 3, 2, 1]
    */

paddle/phi/kernels/sparse/cpu/reshape_grad_kernel.cc

@@ -0,0 +1,73 @@
+// 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/phi/kernels/sparse/unary_grad_kernel.h"
+#include "paddle/phi/kernels/sparse/unary_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/sparse/empty_kernel.h"
+#include "paddle/phi/kernels/sparse/impl/unary_grad_kernel_impl.h"
+
+namespace phi {
+namespace sparse {
+
+template <typename T, typename Context>
+void ReshapeCooGradKernel(const Context& dev_ctx,
+                          const SparseCooTensor& x,
+                          const SparseCooTensor& dout,
+                          SparseCooTensor* dx) {
+  EmptyLikeCooKernel<T, Context>(dev_ctx, x, dx);
+  phi::IntArray x_shape(phi::vectorize(x.dims()));
+  ReshapeCooKernel<T, Context>(dev_ctx, dout, x_shape, dx);
+}
+
+template <typename T, typename Context>
+void ReshapeCsrGradKernel(const Context& dev_ctx,
+                          const SparseCsrTensor& x,
+                          const SparseCsrTensor& dout,
+                          SparseCsrTensor* dx) {
+  EmptyLikeCsrKernel<T, Context>(dev_ctx, x, dx);
+  phi::IntArray x_shape(phi::vectorize(x.dims()));
+  ReshapeCsrKernel<T, Context>(dev_ctx, dout, x_shape, dx);
+}
+
+}  // namespace sparse
+}  // namespace phi
+
+PD_REGISTER_KERNEL(reshape_coo_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::sparse::ReshapeCooGradKernel,
+                   float,
+                   double,
+                   int8_t,
+                   uint8_t,
+                   int16_t,
+                   int,
+                   int64_t,
+                   bool) {}
+
+PD_REGISTER_KERNEL(reshape_csr_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::sparse::ReshapeCsrGradKernel,
+                   float,
+                   double,
+                   int8_t,
+                   uint8_t,
+                   int16_t,
+                   int,
+                   int64_t,
+                   bool) {}

paddle/phi/kernels/sparse/cpu/reshape_kernel.cc

@@ -0,0 +1,117 @@
+// 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/phi/kernels/sparse/unary_kernel.h"
+
+#include "paddle/phi/core/ddim.h"
+#include "paddle/phi/kernels/sparse/sparse_utils_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/eigen/common.h"
+#include "paddle/phi/kernels/funcs/eigen/eigen_function.h"
+#include "paddle/phi/kernels/sparse/empty_kernel.h"
+#include "paddle/phi/kernels/sparse/impl/unary_grad_kernel_impl.h"
+#include "paddle/phi/kernels/sparse/impl/unary_kernel_impl.h"
+
+namespace phi {
+namespace sparse {
+
+template <typename T, typename Context>
+void ReshapeCooKernel(const Context& dev_ctx,
+                      const SparseCooTensor& x,
+                      const phi::IntArray& shape,
+                      SparseCooTensor* out) {
+  // TODO(OccupyMars2025): Currently, reshape is only applicable to sparse dims
+  int64_t x_nnz = x.nnz();
+
+  // Use DDim::reshape to handle -1 and 0 in the argument "shape"
+  std::vector<int> new_shape(shape.GetData().begin(), shape.GetData().end());
+  phi::DDim out_dims = x.dims().reshape(new_shape);
+  // get sparse part dimensions of x and out
+  std::vector<int64_t> x_sparse_part_dims;
+  std::vector<int64_t> out_sparse_part_dims;
+  for (int i = 0; i < x.sparse_dim(); ++i) {
+    x_sparse_part_dims.push_back(x.dims()[i]);
+  }
+  for (int i = 0; i < out_dims.size() - x.dense_dim(); ++i) {
+    out_sparse_part_dims.push_back(out_dims[i]);
+  }
+  DenseTensor out_indices = Empty<int64_t, Context>(
+      dev_ctx, {static_cast<int64_t>(out_sparse_part_dims.size()), x_nnz});
+  DenseTensor out_values(x.values());
+  out->SetMember(out_indices, out_values, out_dims, x.coalesced());
+
+  // compute values of indices
+  const DenseTensor& x_indices = x.indices();
+  const auto* x_indices_data = x_indices.data<int64_t>();
+  auto* out_indices_data = out_indices.data<int64_t>();
+
+  const phi::DDim& x_sparse_part_strides =
+      phi::stride(phi::make_ddim(x_sparse_part_dims));
+  const phi::DDim& out_sparse_part_strides =
+      phi::stride(phi::make_ddim(out_sparse_part_dims));
+  int64_t location = 0;
+  for (int64_t j = 0; j < x_nnz; ++j) {
+    location = 0;
+    for (int i = 0; i < x.sparse_dim(); ++i) {
+      location += x_indices_data[i * x_nnz + j] * x_sparse_part_strides[i];
+    }
+    for (size_t i = 0; i < out_sparse_part_dims.size(); ++i) {
+      out_indices_data[i * x_nnz + j] = location / out_sparse_part_strides[i];
+      location %= out_sparse_part_strides[i];
+    }
+  }
+}
+
+template <typename T, typename Context>
+void ReshapeCsrKernel(const Context& dev_ctx,
+                      const SparseCsrTensor& x,
+                      const phi::IntArray& shape,
+                      SparseCsrTensor* out) {
+  // transform csr format to coo format, and then use coo kernel
+  const SparseCooTensor x_coo = CsrToCoo<T, Context>(dev_ctx, x);
+  SparseCooTensor out_coo;
+  ReshapeCooKernel<T, Context>(dev_ctx, x_coo, shape, &out_coo);
+  CooToCsrKernel<T, Context>(dev_ctx, out_coo, out);
+}
+
+}  // namespace sparse
+}  // namespace phi
+
+PD_REGISTER_KERNEL(reshape_coo,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::sparse::ReshapeCooKernel,
+                   float,
+                   double,
+                   int8_t,
+                   uint8_t,
+                   int16_t,
+                   int,
+                   int64_t,
+                   bool) {}
+
+PD_REGISTER_KERNEL(reshape_csr,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::sparse::ReshapeCsrKernel,
+                   float,
+                   double,
+                   int8_t,
+                   uint8_t,
+                   int16_t,
+                   int,
+                   int64_t,
+                   bool) {}

paddle/phi/kernels/sparse/cpu/sparse_utils_kernel.cc

@@ -329,7 +329,8 @@ PD_REGISTER_KERNEL(csr_to_coo,
                    int8_t,
                    int16_t,
                    int,
-                   int64_t) {}
+                   int64_t,
+                   bool) {}
 
 PD_REGISTER_KERNEL(coo_to_csr,
                    CPU,
@@ -342,7 +343,8 @@ PD_REGISTER_KERNEL(coo_to_csr,
                    int8_t,
                    int16_t,
                    int,
-                   int64_t) {}
+                   int64_t,
+                   bool) {}
 
 PD_REGISTER_KERNEL(dense_to_csr,
                    CPU,