[GitHub] ifeherva commented on a change in pull request #13632: Gradient multiplier (contrib) operator

[GitBox <gi...@apache.org>]

ifeherva commented on a change in pull request #13632: Gradient multiplier (contrib) operator
URL: https://github.com/apache/incubator-mxnet/pull/13632#discussion_r248715440
 
 

 ##########
 File path: src/operator/contrib/gradient_multiplier_op.cc
 ##########
 @@ -0,0 +1,99 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*!
+ * Copyright (c) 2018 by Contributors
+ * \file gradient_multiplier_op.cc
+ * \brief
+ * \author Istvan Fehervari
+*/
+#include "../tensor/elemwise_unary_op.h"
+#include "../tensor/elemwise_binary_scalar_op.h"
+
+namespace mxnet {
+namespace op {
+
+static bool BinaryScalarStorageType(const nnvm::NodeAttrs& attrs,
+                                    const int dev_mask,
+                                    DispatchMode* dispatch_mode,
+                                    std::vector<int> *in_attrs,
+                                    std::vector<int> *out_attrs) {
+  CHECK_EQ(in_attrs->size(), 1);
+  CHECK_EQ(out_attrs->size(), 1);
+  const auto in_stype = in_attrs->at(0);
+  auto &out_stype = out_attrs->at(0);
+  bool dispatched = false;
+  if (!dispatched && (in_stype == kDefaultStorage)) {
+    // dense -> dense
+    dispatched = storage_type_assign(&out_stype, kDefaultStorage,
+                                     dispatch_mode, DispatchMode::kFCompute);
+  }
+  if (!dispatched && in_stype == kRowSparseStorage) {
+    // row sparse -> row sparse
+    dispatched = storage_type_assign(&out_stype, kRowSparseStorage,
+                                     dispatch_mode, DispatchMode::kFComputeEx);
+    // FComputeEx can handle dns output on cpu, too
+    if (dev_mask == cpu::kDevMask && out_stype == kDefaultStorage) {
+      DISPATCH_MODE_ASSIGN_CHECK(dispatch_mode, 0, DispatchMode::kFComputeEx);
+      dispatched = true;
+    }
+  }
+  if (!dispatched && in_stype == kCSRStorage) {
+    // csr -> csr
+    dispatched = storage_type_assign(&out_stype, kCSRStorage,
+                                     dispatch_mode, DispatchMode::kFComputeEx);
+    // FComputeEx can handle dns output on cpu, too
+    if (dev_mask == cpu::kDevMask && out_stype == kDefaultStorage) {
+      DISPATCH_MODE_ASSIGN_CHECK(dispatch_mode, 0, DispatchMode::kFComputeEx);
+      dispatched = true;
+    }
+  }
+  if (!dispatched) {
+    dispatched = dispatch_fallback(out_attrs, dispatch_mode);
+  }
+  return dispatched;
+}
+
+MXNET_OPERATOR_REGISTER_UNARY(_contrib_gradientmultiplier)
+.describe(R"code(This operator implements the gradient multiplier function.
+In forward pass it acts as an identity transform. During backpropagation it
+multiplies the gradient from the subsequent level by a scalar factor and passes it to
+the preceding layer.
+)code" ADD_FILELINE)
+.set_attr_parser([](NodeAttrs* attrs) {
+    attrs->parsed = std::stod(attrs->dict["scalar"]);
+  })
+.set_attr<FInferStorageType>("FInferStorageType", ElemwiseStorageType<1, 1, false, true, true>)
+.set_attr<FCompute>("FCompute<cpu>", UnaryOp::IdentityCompute<cpu>)
+.set_attr<FComputeEx>("FComputeEx<cpu>", UnaryOp::IdentityComputeEx<cpu>)
+.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseNone{"_contrib_backward_gradientmultiplier"})
+.set_attr<nnvm::FInplaceIdentity>("FInplaceIdentity",
+  [](const NodeAttrs& attrs){
+    return std::vector<bool>{true};
+  })
+.add_argument("scalar", "float", "scalar input");
 
 Review comment:
   Good point, updated.

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