chore: import upstream snapshot with attribution

2026-07-13 12:47:05 +08:00
commit 4f3b7da785
7394 changed files with 2005594 additions and 0 deletions
@@ -0,0 +1,96 @@
+/* ******************************************************************************
+ *
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Apache License, Version 2.0 which is available at
+ * https://www.apache.org/licenses/LICENSE-2.0.
+ *
+ *  See the NOTICE file distributed with this work for additional
+ *  information regarding copyright ownership.
+ * 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.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ ******************************************************************************/
+
+//
+// @author saudet
+// @author raver119@gmail.com
+//
+#include <helpers/MKLDNNStream.h>
+#include <ops/declarable/OpRegistrator.h>
+#include <ops/declarable/PlatformHelper.h>
+#include <ops/declarable/helpers/convolutions.h>
+#include <system/platform_boilerplate.h>
+
+#include "mkldnnUtils.h"
+
+using namespace dnnl;
+
+namespace sd {
+namespace ops {
+namespace platforms {
+PLATFORM_IMPL(lrn, ENGINE_CPU) {
+  auto input = INPUT_VARIABLE(0);
+  auto output = OUTPUT_VARIABLE(0);
+
+  REQUIRE_TRUE(input->rankOf() == 4, 0, "lrn: Input rank of 4 expected, but got %i instead", input->rankOf());
+
+  double alpha = T_ARG(1);
+  double beta = T_ARG(2);
+  double bias = T_ARG(0);
+  int depth = INT_ARG(0);
+
+  dnnl_memory_desc_t empty;
+  dnnl::memory::desc lrn_src_md(empty), lrn_dst_md(empty), user_src_md(empty), user_dst_md(empty);
+
+  onednnUtils::getONEDNNMemoryDescLrn(input, nullptr, output, &lrn_src_md, nullptr, &lrn_dst_md, &user_src_md, nullptr,
+                                      &user_dst_md, input->rankOf() - 1);
+
+  auto lrn_desc = lrn_forward::desc(prop_kind::forward_inference, algorithm::lrn_across_channels, lrn_src_md,
+                                    (2 * depth + 1), alpha * (2 * depth + 1), beta, bias);
+
+  auto engine = onednnUtils::getEngine(LaunchContext::defaultContext()->engine());
+  dnnl::stream stream(engine);
+  auto lrn_prim_desc = lrn_forward::primitive_desc(lrn_desc, engine);
+  auto user_src_memory = dnnl::memory(user_src_md, engine, input->buffer());
+  auto user_dst_memory = dnnl::memory(user_dst_md, engine, output->buffer());
+
+  auto lrn_src_memory = user_src_memory;
+  if (lrn_prim_desc.src_desc() != user_src_memory.get_desc()) {
+    lrn_src_memory = dnnl::memory(lrn_prim_desc.src_desc(), engine);
+    reorder(user_src_memory, lrn_src_memory).execute(stream, user_src_memory, lrn_src_memory);
+  }
+
+  auto lrn_dst_memory = user_dst_memory;
+  if (lrn_prim_desc.dst_desc() != user_dst_memory.get_desc()) {
+    lrn_dst_memory = dnnl::memory(lrn_prim_desc.dst_desc(), engine);
+  }
+
+  lrn_forward(lrn_prim_desc).execute(stream, {{DNNL_ARG_SRC, lrn_src_memory}, {DNNL_ARG_DST, lrn_dst_memory}});
+
+  if (lrn_prim_desc.dst_desc() != user_dst_memory.get_desc()) {
+    reorder(lrn_dst_memory, user_dst_memory).execute(stream, lrn_dst_memory, user_dst_memory);
+  }
+
+  stream.wait();
+
+  return sd::Status::OK;
+};
+
+PLATFORM_CHECK(lrn, ENGINE_CPU) {
+  auto input = INPUT_VARIABLE(0);
+  auto output = OUTPUT_VARIABLE(0);
+
+  Requirements req("ONEDNN LRN OP");
+  req.expectTrue(block.isUseONEDNN(), IS_USE_ONEDNN_MSG) &&
+      req.expectTrue(sd::ONEDNNStream::isSupported({input, output}), ONEDNN_STREAM_NOT_SUPPORTED);
+  req.logTheSuccess();
+  return req;
+}
+}  // namespace platforms
+}  // namespace ops
+}  // namespace sd