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 +1,79 @@
+/*
+ *  ******************************************************************************
+ *  *
+ *  *
+ *  * 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 Oleh Semeniv (oleg.semeniv@gmail.com)
+//
+
+#include <array/NDArray.h>
+#include <execution/Threads.h>
+#include <helpers/ConstantTadHelper.h>
+#include <ops/declarable/CustomOperations.h>
+#include <ops/declarable/headers/updaters.h>
+#if NOT_EXCLUDED(OP_ada_grad_updater)
+namespace sd {
+namespace ops {
+
+CONFIGURABLE_OP_IMPL(ada_grad_updater, 2, 2, true, 0, 0) {
+  const auto gradient = INPUT_VARIABLE(0);
+  const auto initState = INPUT_VARIABLE(1);
+
+  auto update = OUTPUT_VARIABLE(0);
+  auto stateH = OUTPUT_VARIABLE(1);
+
+  if (gradient->isEmpty() || initState->isEmpty()) return Status::OK;
+
+  REQUIRE_TRUE(gradient->isSameShape(initState), 0,
+               "ADA_GRAD UPDATER OP: input state must have the same shape as gradient,"
+               "  expected shape %s, but got %s!",
+               ShapeUtils::shapeAsString(gradient->shapeInfo()).c_str(),
+               ShapeUtils::shapeAsString(initState->shapeInfo()).c_str());
+
+  bool bParamsSupply = 4 == block.width() || 2 == block.getTArguments()->size();
+
+  REQUIRE_TRUE(bParamsSupply, 0, "ADA_GRAD UPDATER OP: learning rate and epsilon were not provided!");
+
+  double dLr, dEpsilon;
+
+  if (block.width() > 2) {
+    const auto lr = INPUT_VARIABLE(2);
+    const auto epsilon = INPUT_VARIABLE(3);
+
+    REQUIRE_TRUE(lr->isScalar(), 0, "ADA_GRAD UPDATER OP: Learning rate has to be a scalar, but instead got rank %i!",
+                 lr->rankOf());
+    REQUIRE_TRUE(epsilon->isScalar(), 0, "ADA_GRAD UPDATER OP: Epsilon has to be a scalar, but instead got rank %i!",
+                 epsilon->rankOf());
+
+    dLr = lr->e<double>(0);
+    dEpsilon = epsilon->e<double>(0);
+  } else {
+    dLr = T_ARG(0);
+    dEpsilon = T_ARG(1);
+  }
+
+  helpers::updaterAdaGrad(block.launchContext(), *gradient, *initState, *update, *stateH, dLr, dEpsilon);
+  return Status::OK;
+}
+
+DECLARE_TYPES(ada_grad_updater) { getOpDescriptor()->setAllowedInputTypes({ALL_FLOATS})->setSameMode(true); }
+
+}  // namespace ops
+}  // namespace sd
+#endif