gather op bp passed

paddle/operators/CMakeLists.txt

@@ -44,8 +44,6 @@ endfunction()
 add_subdirectory(math)
 cc_test(gather_test SRCS gather_test.cc DEPS tensor)
 op_library(gather_op SRCS gather_op.cc gather_op.cu)
-# DEPS op_registry)
-# cc_test(gather_op_test SRCS gather_op_test.cc DEPS gather_op)
 
 cc_test(scatter_test SRCS scatter_test.cc DEPS tensor)
 

paddle/operators/gather.h

@@ -27,13 +27,13 @@ namespace operators {
 
 // Implementation of CPU copy
 template <typename T>
-void CPUGather(const T* params, const int* indices, const int slice_size,
+void CPUGather(const T* src, const int* indices, const int slice_size,
                const int index_size, T* output) {
   const size_t slice_bytes = slice_size * sizeof(T);
 
   for (int i = 0; i < index_size; ++i) {
     int index_ = indices[i];
-    memcpy(output + i * slice_size, params + index_ * slice_size, slice_bytes);
+    memcpy(output + i * slice_size, src + index_ * slice_size, slice_bytes);
   }
 }
 
@@ -57,7 +57,7 @@ void Gather(const platform::Place& place, const paddle::framework::Tensor* src,
   int index_size = index->dims()[0];
 
   auto src_dims = src->dims();
-  paddle::framework::DDim output_dims(src_dims);
+  framework::DDim output_dims(src_dims);
   output_dims[0] = index_size;
 
   // slice size

paddle/operators/gather_op.cc

@@ -26,9 +26,9 @@ class GatherOp : public framework::OperatorWithKernel {
   void InferShape(const framework::InferShapeContext &ctx) const override {
     int batch_size = ctx.Input<Tensor>("Index")->dims()[0];
     PADDLE_ENFORCE_GE(batch_size, 0, "Batch size must be >0");
-    paddle::framework::DDim output_dims(ctx.Input<Tensor>("X")->dims());
+    framework::DDim output_dims(ctx.Input<Tensor>("X")->dims());
     output_dims[0] = batch_size;
-    ctx.Output<Tensor>("Y")->Resize(output_dims);
+    ctx.Output<Tensor>("Out")->Resize(output_dims);
   }
 };
 
@@ -51,11 +51,11 @@ class GatherOpMaker : public framework::OpProtoAndCheckerMaker {
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The source input of gather op");
     AddInput("Index", "The index input of gather op");
-    AddOutput("Y", "The output of add op");
+    AddOutput("Out", "The output of add op");
     AddComment(R"DOC(
 Gather Operator by selecting from the first axis, 
 
-Y = X[Index]
+Out = X[Index]
 )DOC");
   }
 };

paddle/operators/gather_op.h

@@ -27,9 +27,9 @@ template <typename Place, typename T>
 class GatherOpKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext &ctx) const override {
-    auto X = ctx.Input<Tensor>("X");
-    auto Index = ctx.Input<Tensor>("Index");
-    auto Y = ctx.Output<Tensor>("Y");
+    auto *X = ctx.Input<Tensor>("X");
+    auto *Index = ctx.Input<Tensor>("Index");
+    auto *Y = ctx.Output<Tensor>("Out");
 
     Y->mutable_data<T>(ctx.GetPlace());
     Gather<T>(ctx.GetPlace(), X, Index, Y);
@@ -40,11 +40,12 @@ template <typename Place, typename T>
 class GatherGradientOpKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext &ctx) const override {
-    auto Index = ctx.Input<Tensor>("Index");
-    auto dX = ctx.Output<Tensor>(framework::GradVarName("X"));
-    auto dY = ctx.Input<Tensor>(framework::GradVarName("Y"));
+    auto *Index = ctx.Input<Tensor>("Index");
+    auto *dX = ctx.Output<Tensor>(framework::GradVarName("X"));
+    auto *dO = ctx.Input<Tensor>(framework::GradVarName("Out"));
 
-    ScatterUpdate<T>(ctx.GetPlace(), dY, Index, dX);
+    dX->mutable_data<T>(ctx.GetPlace());
+    ScatterUpdate<T>(ctx.GetPlace(), dO, Index, dX);
   }
 };
 

python/paddle/v2/framework/tests/test_gather_op.py

@@ -1,11 +1,10 @@
 import unittest
-
+from op_test_util import OpTestMeta
+from gradient_checker import GradientChecker, create_op
 import numpy
 import paddle.v2.framework.core as core
 from paddle.v2.framework.op import Operator
 
-from op_test_util import OpTestMeta
-
 
 class TestGatherOp(unittest.TestCase):
     __metaclass__ = OpTestMeta
@@ -17,7 +16,18 @@ class TestGatherOp(unittest.TestCase):
             'X': xnp,
             'Index': numpy.array([1, 3, 5]).astype("int32")
         }
-        self.outputs = {'Y': self.inputs['X'][self.inputs['Index']]}
+        self.outputs = {'Out': self.inputs['X'][self.inputs['Index']]}
+
+
+class TestGatherGradOp(GradientChecker):
+    def test_gather_grad(self):
+        print 'creating op'
+        op = create_op("gather")
+        print 'creating op done'
+        xnp = numpy.random.random((10, 20)).astype("float32")
+        inputs = {'X': xnp, 'Index': numpy.array([1, 3, 5]).astype("int32")}
+        print 'correct before check gradient'
+        self.check_grad(op, inputs, set("X"), "Out")
 
 
 if __name__ == "__main__":