chore: import upstream snapshot with attribution

paddle/phi/kernels/xpu/grid_sample_kernel.cc

@@ -0,0 +1,144 @@
+// 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/grid_sample_kernel.h"
+
+#include "paddle/common/layout.h"
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void GridSampleKernel(const Context& dev_ctx,
+                      const DenseTensor& x,
+                      const DenseTensor& grid,
+                      const std::string& mode,
+                      const std::string& padding_mode,
+                      bool align_corners,
+                      DenseTensor* out) {
+  if (out && out->numel() == 0) {
+    dev_ctx.template Alloc<T>(out);
+    return;
+  }
+  // attrs
+  // paddle.nn.functional.grid_sample(x, grid, mode='bilinear',
+  // padding_mode='zeros', align_corners=True, name=None)
+  const std::string data_format = DataLayoutToString(x.layout());
+
+  // attr to real param
+  bool is_nearest_bool;
+  if (mode == "bilinear") {
+    is_nearest_bool = false;
+  } else if (mode == "nearest") {
+    is_nearest_bool = true;
+  } else {
+    PADDLE_THROW(errors::InvalidArgument(
+        "should not reach here: mode should be either 'bilinear' or "
+        "'nearest', bot got %s.",
+        mode));
+  }
+
+  // attention: 0: zeros, 2: reflection, 1: border according to XDNN api.
+  int padding_mode_int;
+  if (padding_mode == "zeros") {
+    padding_mode_int = 0;
+  } else if (padding_mode == "reflection") {
+    padding_mode_int = 2;
+  } else if (padding_mode == "border") {
+    padding_mode_int = 1;
+  } else {
+    PADDLE_THROW(errors::InvalidArgument(
+        "should not reach here: padding_mode should be either 'zeros' or "
+        "'reflection' or 'border', bot got %s.",
+        padding_mode));
+  }
+
+  const T* input_data = x.data<T>();
+  const T* grid_data = grid.data<T>();
+
+  int64_t n = x.dims()[0];
+  int64_t c = x.dims()[1];
+
+  if (x.dims().size() == 4) {  // 2D grid sample
+    int64_t h = x.dims()[2];
+    int64_t w = x.dims()[3];
+    int64_t out_h = grid.dims()[1];
+    int64_t out_w = grid.dims()[2];
+
+    bool is_nchw_bool;
+    if (data_format == "NCHW") {
+      is_nchw_bool = true;
+    } else if (data_format == "NHWC") {
+      is_nchw_bool = false;
+    } else {
+      PADDLE_THROW(errors::InvalidArgument(
+          "should not reach here: data_format should be either 'NCHW' or "
+          "'NHWC', bot got %s.",
+          data_format));
+    }
+
+    out->Resize({n, c, out_h, out_w});
+    T* output_data = dev_ctx.template Alloc<T>(out);
+
+    int r = xpu::grid_sample(dev_ctx.x_context(),
+                             input_data,
+                             grid_data,
+                             output_data,
+                             n,
+                             c,
+                             h,
+                             w,
+                             out_h,
+                             out_w,
+                             is_nearest_bool,
+                             align_corners,
+                             padding_mode_int,
+                             is_nchw_bool);
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "grid_sampler");
+  } else {  // 3D grid sample
+    int64_t d = x.dims()[2];
+    int64_t h = x.dims()[3];
+    int64_t w = x.dims()[4];
+    int64_t out_d = grid.dims()[1];
+    int64_t out_h = grid.dims()[2];
+    int64_t out_w = grid.dims()[3];
+
+    out->Resize({n, c, out_d, out_h, out_w});
+    T* output_data = dev_ctx.template Alloc<T>(out);
+
+    int r = xpu::grid_sample3d(dev_ctx.x_context(),
+                               input_data,
+                               grid_data,
+                               output_data,
+                               n,
+                               c,
+                               d,
+                               h,
+                               w,
+                               out_d,
+                               out_h,
+                               out_w,
+                               is_nearest_bool,
+                               align_corners,
+                               padding_mode_int,
+                               true);
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "grid_sampler3d");
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(grid_sample, XPU, ALL_LAYOUT, phi::GridSampleKernel, float) {
+}