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 +1,68 @@
+// 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/core/kernel_registry.h"
+#include "paddle/phi/kernels/impl/sequence_expand_kernel_impl.h"
+
+namespace phi {
+
+/*
+ *Given Grad(Out)
+ *
+ *    Grad(Out).lod = [[0,                            2],
+ *                     [0,              3,            6]]
+ *    Grad(Out).data = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6]
+ * Then
+ *    Grad(X).data = [(0.1 + 0.2 + 0.3), (0.4 + 0.5 + 0.6)]
+ *                 = [0.6, 1.5]
+ *    Grad(X).lod = Input(X).lod
+ *
+ * */
+template <typename T>
+struct SequenceExpandGradFunctor<CPUContext, T> {
+  void operator()(const CPUContext& dev_ctx,
+                  const DenseTensor& dout,
+                  const Vector<size_t>& x_lod,   /*expand source lod*/
+                  const Vector<size_t>& ref_lod, /*expand referenced lod*/
+                  DenseTensor* dx) {
+    int dout_offset = 0;
+    for (size_t i = 1; i < ref_lod.size(); ++i) {
+      int repeat_num = ref_lod[i] - ref_lod[i - 1];
+      if (repeat_num > 0) {
+        int x_start = x_lod[i - 1];
+        int x_end = x_lod[i];
+        int x_seq_len = x_end - x_start;
+        if (x_seq_len == 0) continue;
+        auto dx_sub = dx->Slice(x_start, x_end);
+        dx_sub.Resize(common::flatten_to_1d(dx_sub.dims()));
+        int dout_end = dout_offset + repeat_num * x_seq_len;
+        auto dout_sub = dout.Slice(dout_offset, dout_end);
+        dout_sub.Resize({repeat_num, dx_sub.dims()[0]});
+        funcs::ColwiseSum<CPUContext, T> col_sum;
+        col_sum(dev_ctx, dout_sub, &dx_sub);
+        dout_offset += repeat_num * x_seq_len;
+      }
+    }
+  }
+};
+
+}  // namespace phi
+PD_REGISTER_KERNEL(sequence_expand_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::SequenceExpandGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t) {}