chore: import upstream snapshot with attribution

paddle/phi/kernels/funcs/math/unpooling.cc

@@ -0,0 +1,216 @@
+// Copyright (c) 2024 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/funcs/math/unpooling.h"
+
+namespace phi {
+namespace math {
+template <typename T>
+class Unpool2dMaxFunctor<CPUContext, T> {
+ public:
+  void operator()(const CPUContext& context,
+                  const DenseTensor& input,
+                  const DenseTensor& indices,
+                  DenseTensor* output) {
+    const int batch_size = static_cast<int>(input.dims()[0]);
+    const int input_height = static_cast<int>(input.dims()[2]);
+    const int input_width = static_cast<int>(input.dims()[3]);
+    const int output_channels = static_cast<int>(output->dims()[1]);
+    const int output_height = static_cast<int>(output->dims()[2]);
+    const int output_width = static_cast<int>(output->dims()[3]);
+    int64_t input_feasize = static_cast<int64_t>(input_height) * input_width;
+    int64_t output_feasize = static_cast<int64_t>(output_height) * output_width;
+    const T* input_data = input.data<T>();
+    const int* indices_data = indices.data<int>();
+    T* output_data = context.template Alloc<T>(output);
+    for (int b = 0; b < batch_size; ++b) {
+      for (int c = 0; c < output_channels; ++c) {
+        for (int64_t i = 0; i < input_feasize; ++i) {
+          int index = indices_data[i];
+
+          PADDLE_ENFORCE_LT(
+              index,
+              output_feasize,
+              common::errors::InvalidArgument(
+                  "index should less than output tensor height * output tensor "
+                  "width. Expected %ld < %ld, but got "
+                  "%ld >= %ld. Please check input value.",
+                  index,
+                  output_feasize,
+                  index,
+                  output_feasize));
+          output_data[index] = input_data[i];
+        }
+        input_data += input_feasize;
+        indices_data += input_feasize;
+        output_data += output_feasize;
+      }
+    }
+  }
+};
+template <class T>
+class Unpool2dMaxGradFunctor<CPUContext, T> {
+ public:
+  void operator()(const CPUContext& context,
+                  const DenseTensor& input,
+                  const DenseTensor& indices,
+                  const DenseTensor& output,
+                  const DenseTensor& output_grad,
+                  DenseTensor* input_grad) {
+    const int batch_size = static_cast<int>(input.dims()[0]);
+    const int input_height = static_cast<int>(input.dims()[2]);
+    const int input_width = static_cast<int>(input.dims()[3]);
+    const int output_channels = static_cast<int>(output.dims()[1]);
+    const int output_height = static_cast<int>(output.dims()[2]);
+    const int output_width = static_cast<int>(output.dims()[3]);
+    int64_t input_feasize = static_cast<int64_t>(input_height) * input_width;
+    int64_t output_feasize = static_cast<int64_t>(output_height) * output_width;
+    const int* indices_data = indices.data<int>();
+    const T* output_grad_data = output_grad.data<T>();
+    T* input_grad_data = context.template Alloc<T>(input_grad);
+
+    for (int b = 0; b < batch_size; ++b) {
+      for (int c = 0; c < output_channels; ++c) {
+        for (int64_t i = 0; i < input_feasize; ++i) {
+          int index = indices_data[i];
+          PADDLE_ENFORCE_LT(
+              index,
+              output_feasize,
+              common::errors::InvalidArgument(
+                  "index should less than output tensor height * output tensor "
+                  "width. Expected %ld < %ld, but got "
+                  "%ld >= %ld. Please check input value.",
+                  index,
+                  output_feasize,
+                  index,
+                  output_feasize));
+          input_grad_data[i] = output_grad_data[index];
+        }
+        input_grad_data += input_feasize;
+        indices_data += input_feasize;
+        output_grad_data += output_feasize;
+      }
+    }
+  }
+};
+
+template <typename T>
+class Unpool3dMaxFunctor<CPUContext, T> {
+ public:
+  void operator()(const CPUContext& context,
+                  const DenseTensor& input,
+                  const DenseTensor& indices,
+                  DenseTensor* output) {
+    const int batch_size = static_cast<int>(input.dims()[0]);
+    const int input_depth = static_cast<int>(input.dims()[2]);
+    const int input_height = static_cast<int>(input.dims()[3]);
+    const int input_width = static_cast<int>(input.dims()[4]);
+    const int output_channels = static_cast<int>(output->dims()[1]);
+    const int output_depth = static_cast<int>(output->dims()[2]);
+    const int output_height = static_cast<int>(output->dims()[3]);
+    const int output_width = static_cast<int>(output->dims()[4]);
+    int64_t input_feasize =
+        static_cast<int64_t>(input_depth) * input_height * input_width;
+    int64_t output_feasize =
+        static_cast<int64_t>(output_depth) * output_height * output_width;
+    const T* input_data = input.data<T>();
+    const int* indices_data = indices.data<int>();
+    T* output_data = context.template Alloc<T>(output);
+    for (int b = 0; b < batch_size; ++b) {
+      for (int c = 0; c < output_channels; ++c) {
+        for (int64_t i = 0; i < input_feasize; ++i) {
+          int index = indices_data[i];
+
+          PADDLE_ENFORCE_LT(
+              index,
+              output_feasize,
+              common::errors::InvalidArgument(
+                  "index should less than output tensor depth * output tensor "
+                  "height "
+                  "* output tensor width. Expected %ld < %ld, but got "
+                  "%ld >= %ld. Please check input value.",
+                  index,
+                  output_feasize,
+                  index,
+                  output_feasize));
+          output_data[index] = input_data[i];
+        }
+        input_data += input_feasize;
+        indices_data += input_feasize;
+        output_data += output_feasize;
+      }
+    }
+  }
+};
+template <class T>
+class Unpool3dMaxGradFunctor<CPUContext, T> {
+ public:
+  void operator()(const CPUContext& context,
+                  const DenseTensor& input,
+                  const DenseTensor& indices,
+                  const DenseTensor& output,
+                  const DenseTensor& output_grad,
+                  DenseTensor* input_grad) {
+    const int batch_size = static_cast<int>(input.dims()[0]);
+    const int input_depth = static_cast<int>(input.dims()[2]);
+    const int input_height = static_cast<int>(input.dims()[3]);
+    const int input_width = static_cast<int>(input.dims()[4]);
+    const int output_channels = static_cast<int>(output.dims()[1]);
+    const int output_depth = static_cast<int>(output.dims()[2]);
+    const int output_height = static_cast<int>(output.dims()[3]);
+    const int output_width = static_cast<int>(output.dims()[4]);
+    int64_t input_feasize =
+        static_cast<int64_t>(input_depth) * input_height * input_width;
+    int64_t output_feasize =
+        static_cast<int64_t>(output_depth) * output_height * output_width;
+    const int* indices_data = indices.data<int>();
+    const T* output_grad_data = output_grad.data<T>();
+    T* input_grad_data = context.template Alloc<T>(input_grad);
+
+    for (int b = 0; b < batch_size; ++b) {
+      for (int c = 0; c < output_channels; ++c) {
+        for (int64_t i = 0; i < input_feasize; ++i) {
+          int index = indices_data[i];
+          PADDLE_ENFORCE_LT(
+              index,
+              output_feasize,
+              common::errors::InvalidArgument(
+                  "index should less than output tensor depth * output tensor "
+                  "height "
+                  "* output tensor width. Expected %ld < %ld, but got "
+                  "%ld >= %ld. Please check input value.",
+                  index,
+                  output_feasize,
+                  index,
+                  output_feasize));
+          input_grad_data[i] = output_grad_data[index];
+        }
+        input_grad_data += input_feasize;
+        indices_data += input_feasize;
+        output_grad_data += output_feasize;
+      }
+    }
+  }
+};
+
+template class Unpool2dMaxGradFunctor<CPUContext, float>;
+template class Unpool2dMaxGradFunctor<CPUContext, double>;
+template class Unpool2dMaxFunctor<CPUContext, float>;
+template class Unpool2dMaxFunctor<CPUContext, double>;
+template class Unpool3dMaxGradFunctor<CPUContext, float>;
+template class Unpool3dMaxGradFunctor<CPUContext, double>;
+template class Unpool3dMaxFunctor<CPUContext, float>;
+template class Unpool3dMaxFunctor<CPUContext, double>;
+}  // namespace math
+}  // namespace phi