[0-size Tensor No.358] Add 0-size Tensor support for paddle.vision.ops.generate_proposals [fluid_ops]

paddle/phi/kernels/cpu/generate_proposals_kernel.cc

@@ -15,6 +15,7 @@
 #include "paddle/phi/kernels/generate_proposals_kernel.h"
 #include "paddle/phi/backends/cpu/cpu_context.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/full_kernel.h"
 #include "paddle/phi/kernels/funcs/detection/nms_util.h"
 #include "paddle/phi/kernels/funcs/gather.h"
 
@@ -314,6 +315,18 @@ void GenerateProposalsKernel(const Context& dev_ctx,
 
  rpn_roi_probs->Resize(common::make_ddim({scores.numel(), 1}));
  dev_ctx.template Alloc<T>(rpn_roi_probs);
+ if (scores.numel() == 0) {
+ rpn_rois->Resize(common::make_ddim({0, 4}));
+ if (rpn_rois_num != nullptr) {
+ rpn_rois_num->Resize(common::make_ddim({}));
+ phi::Full<int64_t, Context>(
+ dev_ctx,
+ phi::IntArray(common::vectorize(rpn_rois_num->dims())),
+ 0,
+ rpn_rois_num);
+ }
+ return;
+ }
 
  DenseTensor bbox_deltas_swap, scores_swap;
  bbox_deltas_swap.Resize(common::make_ddim({num, h_bbox, w_bbox, c_bbox}));

paddle/phi/kernels/gpu/generate_proposals_kernel.cu

@@ -27,6 +27,7 @@ namespace cub = hipcub;
 #include "paddle/phi/backends/gpu/gpu_context.h"
 #include "paddle/phi/backends/gpu/gpu_primitives.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/full_kernel.h"
 #include "paddle/phi/kernels/funcs/detection/bbox_util.h"
 #include "paddle/phi/kernels/funcs/for_range.h"
 #include "paddle/phi/kernels/funcs/gather.cu.h"
@@ -490,6 +491,24 @@ void GenerateProposalsKernel(const Context &dev_ctx,
  int64_t h_bbox = bbox_dim[2];
  int64_t w_bbox = bbox_dim[3];
 
+ rpn_rois->Resize(common::make_ddim({bbox_deltas.numel() / 4, 4}));
+ dev_ctx.template Alloc<T>(rpn_rois);
+ rpn_roi_probs->Resize(common::make_ddim({scores.numel(), 1}));
+ dev_ctx.template Alloc<T>(rpn_roi_probs);
+
+ if (scores.numel() == 0) {
+ rpn_rois->Resize(common::make_ddim({0, 4}));
+ if (rpn_rois_num != nullptr) {
+ rpn_rois_num->Resize(common::make_ddim({}));
+ phi::Full<int64_t, Context>(
+ dev_ctx,
+ phi::IntArray(common::vectorize(rpn_rois_num->dims())),
+ 0,
+ rpn_rois_num);
+ }
+ return;
+ }
+
  DenseTensor bbox_deltas_swap, scores_swap;
  bbox_deltas_swap.Resize(common::make_ddim({num, h_bbox, w_bbox, c_bbox}));
  dev_ctx.template Alloc<T>(&bbox_deltas_swap);
@@ -506,11 +525,6 @@ void GenerateProposalsKernel(const Context &dev_ctx,
  tmp_anchors.Resize(common::make_ddim({tmp_anchors.numel() / 4, 4}));
  tmp_variances.Resize(common::make_ddim({tmp_variances.numel() / 4, 4}));
 
- rpn_rois->Resize(common::make_ddim({bbox_deltas.numel() / 4, 4}));
- dev_ctx.template Alloc<T>(rpn_rois);
- rpn_roi_probs->Resize(common::make_ddim({scores.numel(), 1}));
- dev_ctx.template Alloc<T>(rpn_roi_probs);
-
  T *rpn_rois_data = rpn_rois->data<T>();
  T *rpn_roi_probs_data = rpn_roi_probs->data<T>();
 

paddle/phi/kernels/xpu/generate_proposals_kernel.cc

@@ -18,6 +18,7 @@
 #include "paddle/phi/backends/xpu/xpu_context.h"
 #include "paddle/phi/common/float16.h"
 #include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/full_kernel.h"
 #include "paddle/phi/kernels/funcs/math_function_impl.h"
 
 #include "paddle/phi/common/memory_utils.h"
@@ -306,6 +307,26 @@ void GenerateProposalsKernel(const Context& dev_ctx,
  int h_bbox = bbox_dim[2];
  int w_bbox = bbox_dim[3];
 
+ // output
+ rpn_rois->Resize(common::make_ddim({bbox_deltas.numel() / 4, 4}));
+ dev_ctx.template Alloc<T>(rpn_rois);
+
+ rpn_roi_probs->Resize(common::make_ddim({scores.numel(), 1}));
+ dev_ctx.template Alloc<T>(rpn_roi_probs);
+
+ if (scores.numel() == 0) {
+ rpn_rois->Resize(common::make_ddim({0, 4}));
+ if (rpn_rois_num != nullptr) {
+ rpn_rois_num->Resize(common::make_ddim({}));
+ phi::Full<int64_t, Context>(
+ dev_ctx,
+ phi::IntArray(common::vectorize(rpn_rois_num->dims())),
+ 0,
+ rpn_rois_num);
+ }
+ return;
+ }
+
  DenseTensor bbox_deltas_swap, scores_swap;
  bbox_deltas_swap.Resize(common::make_ddim({num, h_bbox, w_bbox, c_bbox}));
  dev_ctx.template Alloc<T>(&bbox_deltas_swap);
@@ -333,13 +354,6 @@ void GenerateProposalsKernel(const Context& dev_ctx,
  tmp_anchors.Resize(common::make_ddim({tmp_anchors.numel() / 4, 4}));
  tmp_variances.Resize(common::make_ddim({tmp_variances.numel() / 4, 4}));
 
- // output
- rpn_rois->Resize(common::make_ddim({bbox_deltas.numel() / 4, 4}));
- dev_ctx.template Alloc<T>(rpn_rois);
-
- rpn_roi_probs->Resize(common::make_ddim({scores.numel(), 1}));
- dev_ctx.template Alloc<T>(rpn_roi_probs);
-
  auto place = dev_ctx.GetPlace();
  auto cpu_place = phi::CPUPlace();
 

test/legacy_test/test_generate_proposals_v2_op.py

@@ -560,6 +560,95 @@ def init_test_output(self):
 # np.testing.assert_allclose(self.roi_probs_expected, np.array(roi_probs), rtol=1e-5)
 # np.testing.assert_allclose(self.rois_num_expected, np.array(rois_num), rtol=1e-5)
 
+
+class TestGenerateProposalsV2Op_ZeroSize(OpTest):
+ def set_data(self):
+ self.init_test_params()
+ self.init_test_input()
+ self.init_test_output()
+ self.inputs = {
+ 'Scores': self.scores,
+ 'BboxDeltas': self.bbox_deltas,
+ 'ImShape': self.im_shape.astype(np.float32),
+ 'Anchors': self.anchors,
+ 'Variances': self.variances,
+ }
+
+ self.attrs = {
+ 'pre_nms_topN': self.pre_nms_topN,
+ 'post_nms_topN': self.post_nms_topN,
+ 'nms_thresh': self.nms_thresh,
+ 'min_size': self.min_size,
+ 'eta': self.eta,
+ 'pixel_offset': self.pixel_offset,
+ }
+
+ self.outputs = {
+ 'RpnRois': self.rpn_rois[0],
+ 'RpnRoiProbs': self.rpn_roi_probs[0],
+ }
+
+ def test_check_output(self):
+ self.check_output(check_pir=True, check_symbol_infer=False)
+
+ def setUp(self):
+ self.op_type = "generate_proposals_v2"
+ self.python_api = python_generate_proposals_v2
+ self.set_data()
+
+ def init_test_params(self):
+ self.pre_nms_topN = 12000 # train 12000, test 2000
+ self.post_nms_topN = 5000 # train 6000, test 1000
+ self.nms_thresh = 0.7
+ self.min_size = 3.0
+ self.eta = 1.0
+ self.pixel_offset = True
+
+ def init_test_input(self):
+ batch_size = 1
+ input_channels = 0
+ layer_h = 16
+ layer_w = 16
+ input_feat = np.random.random(
+ (batch_size, input_channels, layer_h, layer_w)
+ ).astype('float32')
+ self.anchors, self.variances = anchor_generator_in_python(
+ input_feat=input_feat,
+ anchor_sizes=[16.0, 32.0],
+ aspect_ratios=[0.5, 1.0],
+ variances=[1.0, 1.0, 1.0, 1.0],
+ stride=[16.0, 16.0],
+ offset=0.5,
+ )
+ self.im_shape = np.array([[64, 64]]).astype('float32')
+ num_anchors = self.anchors.shape[2]
+ self.scores = np.random.random(
+ (batch_size, num_anchors, layer_h, layer_w)
+ ).astype('float32')
+ self.bbox_deltas = np.random.random(
+ (batch_size, num_anchors * 4, layer_h, layer_w)
+ ).astype('float32')
+
+ def init_test_output(self):
+ (
+ self.rpn_rois,
+ self.rpn_roi_probs,
+ self.rois_num,
+ ) = generate_proposals_v2_in_python(
+ self.scores,
+ self.bbox_deltas,
+ self.im_shape,
+ self.anchors,
+ self.variances,
+ self.pre_nms_topN,
+ self.post_nms_topN,
+ self.nms_thresh,
+ self.min_size,
+ self.eta,
+ self.pixel_offset,
+ )
+
+
 if __name__ == '__main__':
  paddle.enable_static()
  unittest.main()