handle multi-inputs with empty inputs for mkldnn_concat_op (#21827)

test=develop

paddle/fluid/operators/mkldnn/concat_mkldnn_op.cc

@@ -59,6 +59,16 @@ static const mkldnn::engine& GetMKLDNNEngine(
   return dev_ctx.GetEngine();
 }
 
+// From a multi-input, gather only nonempty inputs
+static const std::vector<const Tensor*> ReduceMultiInput(
+    const std::vector<const Tensor*>& inputs) {
+  std::vector<const Tensor*> reduced(inputs.size());
+  auto end_it = std::copy_if(inputs.begin(), inputs.end(), reduced.begin(),
+                             [](const Tensor* t) { return t->numel() > 0; });
+  reduced.resize(std::distance(reduced.begin(), end_it));
+  return reduced;
+}
+
 template <typename T>
 class ConcatPrimitiveFactory {
  public:
@@ -120,7 +130,7 @@ template <typename T>
 class ConcatMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
  public:
   void Compute(const paddle::framework::ExecutionContext& ctx) const override {
-    auto multi_input = ctx.MultiInput<Tensor>("X");
+    auto multi_input = ReduceMultiInput(ctx.MultiInput<Tensor>("X"));
     EnforceLayouts(multi_input);
     Tensor* output = ctx.Output<Tensor>("Out");
     int concat_axis = ctx.Attr<int>("axis");

paddle/fluid/operators/roi_align_op.h

@@ -154,8 +154,6 @@ class CPUROIAlignOpKernel : public framework::OpKernel<T> {
     int width = in_dims[3];
     int rois_num = rois->dims()[0];
 
-    if (rois_num == 0) return;
-
     auto in_stride = framework::stride(in_dims);
     auto roi_stride = framework::stride(rois->dims());
     auto out_stride = framework::stride(out->dims());

python/paddle/fluid/tests/unittests/mkldnn/test_concat_mkldnn_op.py

@@ -15,7 +15,7 @@
 from __future__ import print_function
 
 import unittest
-from paddle.fluid.tests.unittests.test_concat_op import TestConcatOp, TestConcatOp2, TestConcatOp3
+from paddle.fluid.tests.unittests.test_concat_op import TestConcatOp, TestConcatOp2, TestConcatOp3, TestConcatOp4
 
 
 class TestMKLDNNConcatOp(TestConcatOp):
@@ -42,7 +42,7 @@ class TestMKLDNNConcatOp2(TestConcatOp2):
         self._cpu_only = True
 
     def test_check_output(self):
-        # TODO(wangzhongpu): support mkldnn op in dygraph mode 
+        # TODO(wangzhongpu): support mkldnn op in dygraph mode
         self.check_output(check_dygraph=(self.attrs["use_mkldnn"] == False))
 
     def test_check_grad(self):
@@ -59,7 +59,24 @@ class TestMKLDNNConcatOp3(TestConcatOp3):
         self._cpu_only = True
 
     def test_check_output(self):
-        # TODO(wangzhongpu): support mkldnn op in dygraph mode 
+        # TODO(wangzhongpu): support mkldnn op in dygraph mode
+        self.check_output(check_dygraph=(self.attrs["use_mkldnn"] == False))
+
+    def test_check_grad(self):
+        pass
+
+    def init_kernel_type(self):
+        self.use_mkldnn = True
+
+
+class TestMKLDNNConcatOp4(TestConcatOp4):
+    def setUp(self):
+        super(TestMKLDNNConcatOp4, self).setUp()
+        self.attrs["use_mkldnn"] = True
+        self._cpu_only = True
+
+    def test_check_output(self):
+        # TODO(wangzhongpu): support mkldnn op in dygraph mode
         self.check_output(check_dygraph=(self.attrs["use_mkldnn"] == False))
 
     def test_check_grad(self):