v4.0 update. (#2371)

include/cute/algorithm/tensor_reduce.hpp

@@ -0,0 +1,107 @@
+/***************************************************************************************************
+ * Copyright (c) 2025 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+ * SPDX-License-Identifier: BSD-3-Clause
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are met:
+ *
+ * 1. Redistributions of source code must retain the above copyright notice, this
+ * list of conditions and the following disclaimer.
+ *
+ * 2. Redistributions in binary form must reproduce the above copyright notice,
+ * this list of conditions and the following disclaimer in the documentation
+ * and/or other materials provided with the distribution.
+ *
+ * 3. Neither the name of the copyright holder nor the names of its
+ * contributors may be used to endorse or promote products derived from
+ * this software without specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+ * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+ * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+ * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+ * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+ * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ *
+ **************************************************************************************************/
+#pragma once
+
+#include <iostream>
+
+#include <cute/config.hpp>
+#include <cute/tensor_impl.hpp>
+#include <cute/algorithm/functional.hpp>
+#include <cute/algorithm/fill.hpp>
+
+namespace cute
+{
+
+// Reduce @src tensor using binary reduction operator @op and initial value @init and return a scalar.
+template <class SrcEngine, class SrcLayout, class T, class BinaryOp = cute::plus>
+CUTE_HOST_DEVICE constexpr
+T
+reduce(Tensor<SrcEngine,SrcLayout> const& src, T init, BinaryOp op = {})
+{
+  for (auto i = 0; i < size(src); ++i) {
+    init = op(init, src(i));
+  }
+  return init;
+}
+
+// Reduce @src tensor RedMode using binary reduction operator @op and store the result in @dst tensor
+// for each index in @dst/BatchMode.
+// @pre @src tensor has rank 2
+// @pre size of @src batch mode is equal to size of @dst batch mode
+template <class SrcEngine, class SrcLayout,
+          class DstEngine, class DstLayout,
+          class BinaryOp = cute::plus>
+CUTE_HOST_DEVICE constexpr
+void
+batch_reduce(Tensor<SrcEngine, SrcLayout> const& src,       // (RedMode, BatchMode)
+             Tensor<DstEngine, DstLayout>      & dst,       // (BatchMode)
+             BinaryOp op = {})
+{
+  // Precondition
+  CUTE_STATIC_ASSERT_V(rank(src) == Int<2>{});
+  assert(size<1>(src) == size(dst));
+
+  for (int i = 0; i < size(dst); ++i) {
+    dst(i) = reduce(src(_,i), dst(i), op);
+  }
+}
+
+
+// Reduce @src tensor along selected modes specified in @target_profile using binary reduction operator @op
+// and store the result in @dst tensor. @target_profile is a tuple where '_' indicates modes to keep and 
+// integers indicates modes to reduce.
+// @pre @target_profile is compatible with @src layout
+template <class SrcEngine, class SrcLayout,
+          class DstEngine, class DstLayout,
+          class TargetProfile,
+          class BinaryOp = cute::plus>
+CUTE_HOST_DEVICE constexpr
+void
+logical_reduce(Tensor<SrcEngine, SrcLayout> const& src,
+               Tensor<DstEngine, DstLayout>      & dst,
+               TargetProfile                const& target_profile,
+               BinaryOp op = {})
+{
+  // Precondition
+  assert(compatible(target_profile, shape(src)));
+
+  auto diced_layout = dice(target_profile, src.layout());
+  auto sliced_layout = slice(target_profile, src.layout());
+
+  auto red_mode = conditional_return<rank(diced_layout) == Int<0>{}>(Layout<_1,_0>{}, diced_layout);
+  auto batch_mode = conditional_return<rank(sliced_layout) == Int<0>{}>(Layout<_1,_0>{}, sliced_layout);
+
+  auto src_tensor = make_tensor(src.data(), make_layout(red_mode, batch_mode));
+
+  batch_reduce(src_tensor, dst, op);
+}
+
+} // end namespace cute