[0-size Tensor No.106、115] Add 0-size Tensor support for slogdet/det (#73125)

co63oc · web-flow · commit 238c6582c812 · 2025-06-11T19:22:01.000+08:00
* Fix

* Fix
diff --git a/paddle/phi/kernels/gpu/determinant_kernel.cu b/paddle/phi/kernels/gpu/determinant_kernel.cu
@@ -218,6 +218,10 @@ template <typename T, typename Context>
 void DeterminantKernel(const Context& dev_ctx,
                        const DenseTensor& x,
                        DenseTensor* out) {
+  if (out && out->numel() == 0) {
+    dev_ctx.template Alloc<T>(out);
+    return;
+  }
   auto input_dim = common::vectorize(x.dims());
   auto input_dim_size = input_dim.size();
 
diff --git a/paddle/phi/kernels/gpu/slogdeterminant_kernel.cu b/paddle/phi/kernels/gpu/slogdeterminant_kernel.cu
@@ -215,6 +215,25 @@ void SlogDeterminantKernel(const Context& dev_ctx,
   auto input_dim = common::vectorize(x.dims());
   auto input_dim_size = input_dim.size();
 
+  // shape [*, M, M], check whether it contains 0 in '*'.
+  if (input_dim.size() > 2) {
+    bool size_0 = false;
+    std::vector<int> tmp_dim_vec(input_dim.begin(), input_dim.end() - 2);
+    for (size_t i = 0; i < tmp_dim_vec.size(); ++i) {
+      if (tmp_dim_vec[i] == 0) {
+        size_0 = true;
+        break;
+      }
+    }
+    if (size_0) {
+      tmp_dim_vec.insert(tmp_dim_vec.begin(),
+                         2);  // make the output dims as same as numpy
+      out->Resize(common::make_ddim(tmp_dim_vec));
+      dev_ctx.template Alloc<T>(out);
+      return;
+    }
+  }
+
   auto batch_count = detail::GetBatchCount(x.dims());
   VLOG(2) << "input dim:" << x.dims();
   PADDLE_ENFORCE_GE(
diff --git a/paddle/phi/kernels/impl/determinant_grad_kernel_impl.h b/paddle/phi/kernels/impl/determinant_grad_kernel_impl.h
@@ -82,6 +82,10 @@ void DeterminantGradKernel(const Context& dev_ctx,
                            const DenseTensor& out,
                            const DenseTensor& out_grad,
                            DenseTensor* x_grad) {
+  if (x_grad && x_grad->numel() == 0) {
+    dev_ctx.template Alloc<T>(x_grad);
+    return;
+  }
   auto input_dims_size = x.dims().size();
   if (input_dims_size > 2) {
     PADDLE_ENFORCE_EQ(
diff --git a/paddle/phi/kernels/impl/determinant_kernel_impl.h b/paddle/phi/kernels/impl/determinant_kernel_impl.h
@@ -136,6 +136,10 @@ template <typename T, typename Context>
 void DeterminantKernel(const Context& dev_ctx,
                        const DenseTensor& x,
                        DenseTensor* out) {
+  if (out && out->numel() == 0) {
+    dev_ctx.template Alloc<T>(out);
+    return;
+  }
   auto input_dim = common::vectorize(x.dims());
   auto input_dim_size = input_dim.size();
 
diff --git a/paddle/phi/kernels/impl/slogdeterminant_grad_kernel_impl.h b/paddle/phi/kernels/impl/slogdeterminant_grad_kernel_impl.h
@@ -35,6 +35,10 @@ void SlogDeterminantGradKernel(const Context& dev_ctx,
                                const DenseTensor& out,
                                const DenseTensor& out_grad,
                                DenseTensor* x_grad) {
+  if (x_grad && x_grad->numel() == 0) {
+    dev_ctx.template Alloc<T>(x_grad);
+    return;
+  }
   PADDLE_ENFORCE_EQ(
       out_grad.dims()[0],
       2,
diff --git a/paddle/phi/kernels/impl/slogdeterminant_kernel_impl.h b/paddle/phi/kernels/impl/slogdeterminant_kernel_impl.h
@@ -127,6 +127,25 @@ void SlogDeterminantKernel(const Context& dev_ctx,
   auto input_dim = common::vectorize(x.dims());
   auto input_dim_size = input_dim.size();
 
+  // shape [*, M, M], check whether it contains 0 in '*'.
+  if (input_dim.size() > 2) {
+    bool size_0 = false;
+    std::vector<int> tmp_dim_vec(input_dim.begin(), input_dim.end() - 2);
+    for (size_t i = 0; i < tmp_dim_vec.size(); ++i) {
+      if (tmp_dim_vec[i] == 0) {
+        size_0 = true;
+        break;
+      }
+    }
+    if (size_0) {
+      tmp_dim_vec.insert(tmp_dim_vec.begin(),
+                         2);  // make the output dims as same as numpy
+      out->Resize(common::make_ddim(tmp_dim_vec));
+      dev_ctx.template Alloc<T>(out);
+      return;
+    }
+  }
+
   auto batch_count = detail::GetBatchCount(x.dims());
   VLOG(2) << "input dim:" << x.dims();
   PADDLE_ENFORCE_GE(
diff --git a/test/legacy_test/test_determinant_op.py b/test/legacy_test/test_determinant_op.py
@@ -136,6 +136,22 @@ def init_data(self):
         self.target = np.linalg.det(self.case)
 
 
+class TestDeterminantOp_ZeroSize(TestDeterminantOp):
+    def init_data(self):
+        np.random.seed(0)
+        self.case = np.random.rand(0, 10, 10)
+        self.inputs = {'Input': self.case}
+        self.target = np.linalg.det(self.case)
+
+
+class TestDeterminantOp_ZeroSize2(TestDeterminantOp):
+    def init_data(self):
+        np.random.seed(0)
+        self.case = np.random.rand(0, 0, 0)
+        self.inputs = {'Input': self.case}
+        self.target = np.linalg.det(self.case)
+
+
 class TestDeterminantAPI(unittest.TestCase):
     def setUp(self):
         np.random.seed(0)
@@ -324,6 +340,22 @@ def init_data(self):
         self.target = np.array(np.linalg.slogdet(self.case))
 
 
+class TestSlogDeterminantOp_ZeroSize(TestSlogDeterminantOp):
+    def init_data(self):
+        np.random.seed(0)
+        self.case = np.random.rand(0, 5, 5).astype('float64')
+        self.inputs = {'Input': self.case}
+        self.target = np.array(np.linalg.slogdet(self.case))
+
+
+class TestSlogDeterminantOp_ZeroSize2(TestSlogDeterminantOp):
+    def init_data(self):
+        np.random.seed(0)
+        self.case = np.random.rand(0, 0, 0).astype('float64')
+        self.inputs = {'Input': self.case}
+        self.target = np.array(np.linalg.slogdet(self.case))
+
+
 class TestSlogDeterminantAPI(unittest.TestCase):
     def setUp(self):
         np.random.seed(0)
