add gpu kernel for box clip, test=develop

paddle/fluid/operators/detection/CMakeLists.txt

@@ -31,7 +31,7 @@ detection_library(polygon_box_transform_op SRCS polygon_box_transform_op.cc
 polygon_box_transform_op.cu)
 detection_library(rpn_target_assign_op SRCS rpn_target_assign_op.cc)
 detection_library(generate_proposal_labels_op SRCS generate_proposal_labels_op.cc)
-detection_library(box_clip_op SRCS box_clip_op.cc)
+detection_library(box_clip_op SRCS box_clip_op.cc box_clip_op.cu)
 
 if(WITH_GPU)
   detection_library(generate_proposals_op SRCS generate_proposals_op.cc generate_proposals_op.cu DEPS memory cub)

paddle/fluid/operators/detection/box_clip_op.cc

@@ -21,51 +21,58 @@ class BoxClipOp : public framework::OperatorWithKernel {
 
  protected:
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("InputBox"),
-                   "Input(InputBox) of BoxClipOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasInput("Input"),
+                   "Input(Input) of BoxClipOp should not be null.");
     PADDLE_ENFORCE(ctx->HasInput("ImInfo"),
                    "Input(ImInfo) of BoxClipOp should not be null.");
 
-    auto input_box_dims = ctx->GetInputDim("InputBox");
+    auto input_box_dims = ctx->GetInputDim("Input");
     auto im_info_dims = ctx->GetInputDim("ImInfo");
 
     if (ctx->IsRuntime()) {
       auto input_box_size = input_box_dims.size();
       PADDLE_ENFORCE_EQ(input_box_dims[input_box_size - 1], 4,
-                        "The last dimension of InputBox must be 4");
+                        "The last dimension of Input must be 4");
       PADDLE_ENFORCE_EQ(im_info_dims.size(), 2,
-                        "The rank of Input(InputBox) in BoxClipOp must be 2");
+                        "The rank of Input(Input) in BoxClipOp must be 2");
       PADDLE_ENFORCE_EQ(im_info_dims[1], 3,
                         "The last dimension of ImInfo must be 3");
     }
-    ctx->ShareDim("InputBox", /*->*/ "OutputBox");
-    ctx->ShareLoD("InputBox", /*->*/ "OutputBox");
-  }
-
- protected:
-  framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
-    auto data_type = framework::GetDataTypeOfVar(ctx.InputVar("InputBox"));
-    return framework::OpKernelType(data_type, platform::CPUPlace());
+    ctx->ShareDim("Input", /*->*/ "Output");
+    ctx->ShareLoD("Input", /*->*/ "Output");
   }
+  /*
+  protected:
+   framework::OpKernelType GetExpectedKernelType(
+       const framework::ExecutionContext& ctx) const override {
+     auto data_type = framework::GetDataTypeOfVar(ctx.InputVar("Input"));
+     return framework::OpKernelType(data_type, platform::CPUPlace());
+   }
+   */
 };
 
 class BoxClipOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
   void Make() override {
-    AddInput("InputBox",
+    AddInput("Input",
              "(LoDTensor) "
-             "InputBox is a LoDTensor with shape [..., 4] holds 4 points"
+             "Input is a LoDTensor with shape [..., 4] holds 4 points"
              "in last dimension in format [xmin, ymin, xmax, ymax]");
     AddInput("ImInfo",
              "(Tensor) Information for image reshape is in shape (N, 3), "
              "in format (height, width, im_scale)");
-    AddOutput("OutputBox",
+    AddOutput("Output",
               "(LoDTensor) "
-              "OutputBox is a LoDTensor with the same shape as InputBox"
+              "Output is a LoDTensor with the same shape as Input"
               "and it is the result after clip");
     AddComment(R"DOC(
-  This operator clips input boxes to original input images.
+This operator clips input boxes to original input images.
+
+The formula is given as follows:
+
+       $$height_out = \max(\min(height_loc, im_h), 0)$$
+       $$width_out = \max(\min(width_loc, im_w), 0)$$     
+
 )DOC");
   }
 };

paddle/fluid/operators/detection/box_clip_op.h

@@ -25,9 +25,9 @@ template <typename DeviceContext, typename T>
 class BoxClipKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    auto* input_box = context.Input<LoDTensor>("InputBox");
+    auto* input_box = context.Input<LoDTensor>("Input");
     auto* im_info = context.Input<LoDTensor>("ImInfo");
-    auto* output_box = context.Output<LoDTensor>("OutputBox");
+    auto* output_box = context.Output<LoDTensor>("Output");
     auto& dev_ctx =
         context.template device_context<platform::CPUDeviceContext>();
     output_box->mutable_data<T>(context.GetPlace());

python/paddle/fluid/layers/detection.py

@@ -31,11 +31,24 @@ import numpy
 from functools import reduce
 
 __all__ = [
-    'prior_box', 'density_prior_box', 'multi_box_head', 'bipartite_match',
-    'target_assign', 'detection_output', 'ssd_loss', 'detection_map',
-    'rpn_target_assign', 'anchor_generator', 'roi_perspective_transform',
-    'generate_proposal_labels', 'generate_proposals', 'iou_similarity',
-    'box_coder', 'polygon_box_transform', 'yolov3_loss', 'box_clip'
+    'prior_box',
+    'density_prior_box',
+    'multi_box_head',
+    'bipartite_match',
+    'target_assign',
+    'detection_output',
+    'ssd_loss',
+    'detection_map',
+    'rpn_target_assign',
+    'anchor_generator',
+    'roi_perspective_transform',
+    'generate_proposal_labels',
+    'generate_proposals',
+    'iou_similarity',
+    'box_coder',
+    'polygon_box_transform',
+    'yolov3_loss',
+    'box_clip',
 ]
 
 
@@ -1800,13 +1813,22 @@ def generate_proposals(scores,
     return rpn_rois, rpn_roi_probs
 
 
-def box_clip(input_box, im_info, inplace=False, name=None):
+def box_clip(input, im_info, inplace=False, name=None):
     """
     Clip the box into the size given by im_info
+    The formula is given as follows:
+        
+    .. code-block:: text
+
+        height_out = max(min(height_loc, im_h), 0)
+        width_out = max(min(width_loc, im_w), 0)
 
     Args:
         input_box(variable): The input box, the last dimension is 4.
-        im_info(variable): The information of image with shape [N, 3].
+        im_info(variable): The information of image with shape [N, 3] with 
+                            layout (height, width, scale). height and width
+                            is the input size and scale is the ratio of input
+                            size and original size.
         inplace(bool): Must use :attr:`False` if :attr:`input_box` is used in 
                        multiple operators. If this flag is set :attr:`True`, 
                        reuse input :attr:`input_box` to clip, which will 
@@ -1832,12 +1854,12 @@ def box_clip(input_box, im_info, inplace=False, name=None):
     """
 
     helper = LayerHelper("box_clip", **locals())
-    output = helper.create_variable_for_type_inference(dtype=input_box.dtype)
-    inputs = {"InputBox": input_box, "ImInfo": im_info}
+    output = helper.create_variable_for_type_inference(dtype=input.dtype)
+    inputs = {"Input": input, "ImInfo": im_info}
     helper.append_op(
         type="box_clip",
         inputs=inputs,
         attrs={"inplace:": inplace},
-        outputs={"OutputBox": output})
+        outputs={"Output": output})
 
     return output

python/paddle/fluid/tests/unittests/test_box_clip_op.py

@@ -60,10 +60,10 @@ class TestBoxClipOp(OpTest):
         output_boxes = batch_box_clip(input_boxes, im_info, lod[0])
 
         self.inputs = {
-            'InputBox': (input_boxes.astype('float32'), lod),
+            'Input': (input_boxes.astype('float32'), lod),
             'ImInfo': im_info.astype('float32'),
         }
-        self.outputs = {'OutputBox': output_boxes}
+        self.outputs = {'Output': output_boxes}
 
 
 if __name__ == '__main__':