chore: import upstream snapshot with attribution

2026-07-13 12:40:42 +08:00
commit e25996e7db
15472 changed files with 3536181 additions and 0 deletions
@@ -0,0 +1,77 @@
+/* Copyright (c) 2023 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. */
+
+#pragma once
+
+#include "paddle/phi/kernels/funcs/sequence_pooling.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void SequencePoolKernel(const Context& dev_ctx,
+                        const DenseTensor& x,
+                        bool is_test,
+                        const std::string& pooltype,
+                        float pad_value,
+                        DenseTensor* out,
+                        DenseTensor* max_index) {
+  T pad_value_ = static_cast<T>(pad_value);
+
+  auto dims = x.dims();
+  auto lod = x.lod();
+  auto lod_level = lod.size();
+  // InferShape by lod
+  PADDLE_ENFORCE_GT(
+      lod_level,
+      0,
+      errors::InvalidArgument("Input(X) DenseTensor of SequencePoolOp "
+                              "does not contain LoD information."));
+  PADDLE_ENFORCE_LE(
+      lod_level,
+      2UL,
+      errors::InvalidArgument("The lod level of input shall be no more than 2."
+                              "Received lod level is %d.",
+                              lod_level));
+  PADDLE_ENFORCE_GE(
+      dims[0],
+      /*batch size = */ static_cast<int64_t>(lod[lod_level - 1].size() - 1),
+      errors::InvalidArgument(
+          "The first dimension of Input(X) must be large than batch size. "
+          "But received first dimension of Input(X) is %d, while batch "
+          "size is %d.",
+          dims[0],
+          static_cast<int64_t>(lod[lod_level - 1].size() - 1)));
+  if (lod_level > 1UL) {
+    PADDLE_ENFORCE_EQ(
+        lod[0][lod[0].size() - 1],
+        lod[1].size() - 1,
+        errors::InvalidArgument("The input lod information is illegal."));
+    LegacyLoD out_lod;
+    out_lod.push_back(lod[0]);
+    out->set_lod(out_lod);
+  }
+  dims[0] = lod[lod_level - 1].size() - 1;
+  out->Resize({dims});
+  dev_ctx.template Alloc<T>(out);
+  DenseTensor* index = nullptr;
+
+  // Do not create index buffer for inference mode
+  if (pooltype == "MAX" &&
+      (is_test == false || (dev_ctx.GetPlace() == CPUPlace()) == false)) {
+    index = max_index;
+    index->Resize({dims});
+    dev_ctx.template Alloc<int32_t>(index);
+  }
+  funcs::SequencePoolFunctor<Context, T> pool;
+  pool(dev_ctx, pooltype, pad_value_, x, out, is_test, index);
+}
+
+}  // namespace phi