未验证 提交 da33f7b0 编写于 作者: Z zhangkaihuo 提交者: GitHub

[Sparse]Sparse add support gpu (#45974)

上级 2d45f68f
...@@ -15,6 +15,7 @@ limitations under the License. */ ...@@ -15,6 +15,7 @@ limitations under the License. */
#pragma once #pragma once
#include "paddle/phi/core/dense_tensor.h" #include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/sparse_coo_tensor.h"
#include "paddle/phi/core/sparse_csr_tensor.h" #include "paddle/phi/core/sparse_csr_tensor.h"
#include "paddle/phi/kernels/empty_kernel.h" #include "paddle/phi/kernels/empty_kernel.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/phi/kernels/sparse/elementwise_grad_kernel.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/kernels/sparse/empty_kernel.h"
namespace phi {
namespace sparse {
template <typename T, typename Context>
void ElementWiseAddCooGradKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const SparseCooTensor& y,
const SparseCooTensor& dout,
SparseCooTensor* dx,
SparseCooTensor* dy) {
if (dx) {
EmptyLikeCooKernel<T, Context>(dev_ctx, x, dx);
Copy(dev_ctx, dout, dev_ctx.GetPlace(), false, dx);
}
if (dy) {
EmptyLikeCooKernel<T, Context>(dev_ctx, y, dy);
Copy(dev_ctx, dout, dev_ctx.GetPlace(), false, dy);
}
}
} // namespace sparse
} // namespace phi
PD_REGISTER_KERNEL(add_coo_coo_grad,
GPU,
ALL_LAYOUT,
phi::sparse::ElementWiseAddCooGradKernel,
float,
double,
int16_t,
int,
int64_t,
phi::dtype::float16) {
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
kernel->InputAt(1).SetDataLayout(phi::DataLayout::SPARSE_COO);
}
/* 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 <thrust/equal.h>
#include <thrust/execution_policy.h>
#include "paddle/phi/kernels/elementwise_add_kernel.h"
#include "paddle/phi/kernels/sparse/elementwise_kernel.h"
#include "paddle/phi/kernels/sparse/empty_kernel.h"
#include "paddle/phi/core/enforce.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/visit_type.h"
namespace phi {
namespace sparse {
template <typename T, typename IntT>
void ElementWiseAddCooGPUKernel(const GPUContext& dev_ctx,
const SparseCooTensor& x,
const SparseCooTensor& y,
SparseCooTensor* out) {
const auto& x_indices = x.indices();
const auto& y_indices = y.indices();
PADDLE_ENFORCE_EQ(
x_indices.numel(),
y_indices.numel(),
phi::errors::PreconditionNotMet(
"The numel of x.indices() and y.indices() should be equal"));
const IntT* x_indices_ptr = x_indices.data<IntT>();
const IntT* y_indices_ptr = y_indices.data<IntT>();
#ifdef PADDLE_WITH_HIP
bool is_same = thrust::equal(thrust::hip::par.on(dev_ctx.stream()),
#else
bool is_same = thrust::equal(thrust::cuda::par.on(dev_ctx.stream()),
#endif
x_indices_ptr,
x_indices_ptr + x_indices.numel(),
y_indices_ptr);
PADDLE_ENFORCE_EQ(
is_same,
true,
phi::errors::PreconditionNotMet(
"Currently, ElementWiseAddCooKernel only supports the case "
"where x and y have the same indices"));
EmptyLikeCooKernel<T, GPUContext>(dev_ctx, x, out);
phi::AddKernel<T, GPUContext>(
dev_ctx, x.values(), y.values(), out->mutable_values());
}
template <typename T, typename Context>
void ElementWiseAddCooKernel(const Context& dev_ctx,
const SparseCooTensor& x,
const SparseCooTensor& y,
SparseCooTensor* out) {
PD_VISIT_BASE_INTEGRAL_TYPES(x.indices().dtype(), "VerifyIndices", ([&] {
ElementWiseAddCooGPUKernel<T, data_t>(
dev_ctx, x, y, out);
}));
}
} // namespace sparse
} // namespace phi
PD_REGISTER_KERNEL(add_coo_coo,
GPU,
ALL_LAYOUT,
phi::sparse::ElementWiseAddCooKernel,
float,
double,
int16_t,
int,
int64_t,
phi::dtype::float16) {
kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
kernel->InputAt(1).SetDataLayout(phi::DataLayout::SPARSE_COO);
}
...@@ -18,7 +18,7 @@ from operator import __add__, __sub__, __mul__, __truediv__ ...@@ -18,7 +18,7 @@ from operator import __add__, __sub__, __mul__, __truediv__
import numpy as np import numpy as np
import paddle import paddle
from paddle.fluid.framework import _test_eager_guard import paddle.incubate.sparse as sparse
op_list = [__add__, __sub__, __mul__, __truediv__] op_list = [__add__, __sub__, __mul__, __truediv__]
...@@ -134,6 +134,35 @@ class TestSparseElementWiseAPI(unittest.TestCase): ...@@ -134,6 +134,35 @@ class TestSparseElementWiseAPI(unittest.TestCase):
for op in op_list: for op in op_list:
self.func_test_coo(op) self.func_test_coo(op)
def test_add_same_indices(self):
indices_data = [[0, 1], [0, 3]]
values1_data = [[1.0], [2.0]]
values2_data = [[1.0], [2.0]]
shape = [2, 4, 2]
sp_a = sparse.sparse_coo_tensor(indices_data,
values1_data,
shape,
stop_gradient=False)
sp_b = sparse.sparse_coo_tensor(indices_data,
values2_data,
shape,
stop_gradient=False)
values1 = paddle.to_tensor(values1_data, stop_gradient=False)
values2 = paddle.to_tensor(values2_data, stop_gradient=False)
#c.values() = a.values() + b.values()
sp_c = sparse.add(sp_a, sp_b)
sp_c.backward()
ref_c = values1 + values2
ref_c.backward()
np.testing.assert_allclose(sp_c.values().numpy(), ref_c.numpy())
np.testing.assert_allclose(sp_a.grad.values().numpy(),
values1.grad.numpy())
np.testing.assert_allclose(sp_b.grad.values().numpy(),
values2.grad.numpy())
if __name__ == "__main__": if __name__ == "__main__":
paddle.device.set_device('cpu') paddle.device.set_device('cpu')
......
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