edit tanh to a closure op (#5)

Co-authored-by: yoonlee888 <qiuyunlei@zhejianglab.com>

oneflow/core/autograd/gradient_funcs/math_unary_op.cpp

@@ -57,8 +57,6 @@ class UnaryMathOp : public OpExprGradFunction<UnaryMathCaptureState> {
   REGISTER_OP_EXPR_GRAD_FUNCTION(op_type_name, op_cls##Cls);
 
 OF_PP_FOR_EACH_TUPLE(INSTANTIAT_AND_REGISTER_UNARY_MATHOP_CLASS, MATH_UNARY_ELEMENTWISE_FUNC_SEQ);
-OF_PP_FOR_EACH_TUPLE(INSTANTIAT_AND_REGISTER_UNARY_MATHOP_CLASS,
-                     OF_PP_MAKE_TUPLE_SEQ("tanh", Tanh));
 
 #undef INSTANTIAT_AND_REGISTER_UNARY_MATHOP_CLASS
 }  // namespace one

oneflow/core/autograd/gradient_funcs/tanh.cpp

@@ -0,0 +1,53 @@
+/*
+Copyright 2020 The OneFlow 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 "oneflow/core/framework/op_expr_grad_function.h"
+#include "oneflow/core/framework/op_interpreter/op_interpreter_util.h"
+#include "oneflow/user/ops/math_unary_elementwise_seq.h"
+#include "oneflow/core/functional/functional.h"
+
+namespace oneflow {
+namespace one {
+
+struct TanhCaptureState : public AutoGradCaptureState {
+  bool x_requires_grad;
+};
+
+class TanhGrad : public OpExprGradFunction<TanhCaptureState> {
+  Maybe<void> Init(const OpExpr& op) override { return Maybe<void>::Ok(); }
+
+  Maybe<void> Capture(TanhCaptureState* ctx, const TensorTuple& inputs,
+                      const TensorTuple& outputs, const AttrMap& attrs) const override {
+    ctx->x_requires_grad = inputs.at(0)->requires_grad();
+    ctx->SaveTensorForBackward(outputs.at(0));
+    return Maybe<void>::Ok();
+  }
+
+  Maybe<void> Apply(const TanhCaptureState* ctx, const TensorTuple& out_grads,
+                    TensorTuple* in_grads) const override {
+    if (!ctx->x_requires_grad) { return Maybe<void>::Ok(); }
+    const auto& y = ctx->SavedTensors().at(0);
+    const auto& a = functional::Mul(y, y);
+    const auto& aa = functional::ScalarSub(1, JUST(a));
+    in_grads->at(0) = JUST(functional::Mul(out_grads.at(0), JUST(aa)));
+    return Maybe<void>::Ok();
+  }
+};
+
+REGISTER_OP_EXPR_GRAD_FUNCTION("tanh", TanhGrad);
+
+}  // namespace one
+}  // namespace oneflow