From eed2c1e1d6237f421c9b8c0bbd2fd51d53beddcf Mon Sep 17 00:00:00 2001
From: Abhinav Arora <abhinavarora28@gmail.com>
Date: Wed, 4 Oct 2017 09:29:13 -0700
Subject: [PATCH] Changing SGD inputs and outputs to conform to Operator naming
convention (#4586)
---
paddle/operators/sgd_op.cc | 32 +++++++++----------
paddle/operators/sgd_op.h | 8 ++---
.../paddle/v2/framework/tests/test_sgd_op.py | 4 +--
3 files changed, 22 insertions(+), 22 deletions(-)
diff --git a/paddle/operators/sgd_op.cc b/paddle/operators/sgd_op.cc
index 1a4d3fb8c5..31d491f130 100644
--- a/paddle/operators/sgd_op.cc
+++ b/paddle/operators/sgd_op.cc
@@ -23,22 +23,22 @@ class SGDOp : public framework::OperatorWithKernel {
protected:
void InferShape(framework::InferShapeContextBase *ctx) const override {
- PADDLE_ENFORCE(ctx->HasInput("param"),
- "Input(param) of SGDOp should not be null.");
- PADDLE_ENFORCE(ctx->HasInput("grad"),
- "Input(grad) of SGDOp should not be null.");
- PADDLE_ENFORCE(ctx->HasInput("learning_rate"),
- "Input(learning_rate) of SGDOp should not be null.");
- PADDLE_ENFORCE(ctx->HasOutput("param_out"),
- "Output(param_out) of SGDOp should not be null.");
+ PADDLE_ENFORCE(ctx->HasInput("Param"),
+ "Input(Param) of SGDOp should not be null.");
+ PADDLE_ENFORCE(ctx->HasInput("Grad"),
+ "Input(Grad) of SGDOp should not be null.");
+ PADDLE_ENFORCE(ctx->HasInput("LearningRate"),
+ "Input(LearningRate) of SGDOp should not be null.");
+ PADDLE_ENFORCE(ctx->HasOutput("ParamOut"),
+ "Output(ParamOut) of SGDOp should not be null.");
- auto lr_dims = ctx->GetInputDim("learning_rate");
+ auto lr_dims = ctx->GetInputDim("LearningRate");
PADDLE_ENFORCE_EQ(framework::product(lr_dims), 1,
"Learning rate should have 1 element");
- auto param_dim = ctx->GetInputDim("param");
- PADDLE_ENFORCE_EQ(param_dim, ctx->GetInputDim("grad"),
+ auto param_dim = ctx->GetInputDim("Param");
+ PADDLE_ENFORCE_EQ(param_dim, ctx->GetInputDim("Grad"),
"Two input of SGD Op's dimension must be same.");
- ctx->SetOutputDim("param_out", param_dim);
+ ctx->SetOutputDim("ParamOut", param_dim);
}
};
@@ -46,10 +46,10 @@ class SGDOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SGDOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
- AddInput("param", "input parameter");
- AddInput("learning_rate", "learning rate of sgd");
- AddInput("grad", "input gradient");
- AddOutput("param_out", "output parameter");
+ AddInput("Param", "Input parameter");
+ AddInput("LearningRate", "Learning rate of SGD");
+ AddInput("Grad", "Input gradient");
+ AddOutput("ParamOut", "output parameter");
AddComment(R"DOC(
Simplest sgd algorithm.
diff --git a/paddle/operators/sgd_op.h b/paddle/operators/sgd_op.h
index e2ae65beb0..d72d333a9a 100644
--- a/paddle/operators/sgd_op.h
+++ b/paddle/operators/sgd_op.h
@@ -28,10 +28,10 @@ template <typename Place, typename T>
class SGDOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
- auto param = ctx.Input<Tensor>("param");
- auto grad = ctx.Input<Tensor>("grad");
- auto param_out = ctx.Output<Tensor>("param_out");
- float lr = ctx.Input<Tensor>("learning_rate")->data<float>()[0];
+ auto param = ctx.Input<Tensor>("Param");
+ auto grad = ctx.Input<Tensor>("Grad");
+ auto param_out = ctx.Output<Tensor>("ParamOut");
+ float lr = ctx.Input<Tensor>("LearningRate")->data<float>()[0];
param_out->mutable_data<T>(ctx.GetPlace());
diff --git a/python/paddle/v2/framework/tests/test_sgd_op.py b/python/paddle/v2/framework/tests/test_sgd_op.py
index c05364490f..2dd881e5e1 100644
--- a/python/paddle/v2/framework/tests/test_sgd_op.py
+++ b/python/paddle/v2/framework/tests/test_sgd_op.py
@@ -10,8 +10,8 @@ class TestSGDOp(OpTest):
g = np.random.random((102, 105)).astype("float32")
lr = np.array([0.1]).astype("float32")
- self.inputs = {'param': w, 'grad': g, 'learning_rate': lr}
- self.outputs = {'param_out': w - lr * g}
+ self.inputs = {'Param': w, 'Grad': g, 'LearningRate': lr}
+ self.outputs = {'ParamOut': w - lr * g}
def test_check_output(self):
self.check_output()