[Zero-Dim] Fix 0-dim tensor for arg_min_max op.

paddle/phi/infermeta/unary.cc

@@ -160,22 +160,34 @@ void ArgMinMaxInferMeta(const MetaTensor& x,
   auto int_axis = axis.to<int64_t>();
   const auto& x_dims = x.dims();
 
-  PADDLE_ENFORCE_GE(
-      int_axis,
-      -x_dims.size(),
-      phi::errors::InvalidArgument("'axis'(%d) must be greater than or equal to"
-                                   " -Rank(X)(%d).",
-                                   int_axis,
-                                   -x_dims.size()));
-  PADDLE_ENFORCE_LT(int_axis,
-                    x_dims.size(),
-                    phi::errors::InvalidArgument(
-                        "'axis'(%d) must be less than Rank(X)(%d) of Input(X).",
-                        int_axis,
-                        x_dims.size()));
+  auto x_rank = x.dims().size();
+  if (x_rank > 0) {
+    PADDLE_ENFORCE_GE(int_axis,
+                      -x_rank,
+                      phi::errors::InvalidArgument(
+                          "'axis'(%d) must be greater than or equal to"
+                          " -Rank(X)(%d).",
+                          int_axis,
+                          -x_rank));
+    PADDLE_ENFORCE_LT(
+        int_axis,
+        x_rank,
+        phi::errors::InvalidArgument(
+            "'axis'(%d) must be less than Rank(X)(%d) of Input(X).",
+            int_axis,
+            x_rank));
+  } else {
+    // 0-dim tensor
+    PADDLE_ENFORCE_EQ((int_axis == 0 || int_axis == -1) && flatten,
+                      true,
+                      phi::errors::InvalidArgument(
+                          "'axis'(%d) must be 0 or -1 if input tensor is "
+                          "0-dim. and flatten should be true.",
+                          int_axis));
+  }
 
-  auto x_rank = x_dims.size();
   if (int_axis < 0) int_axis += x_rank;
+
   if (config.is_runtime) {
     if (dtype == phi::TransToProtoVarType(DataType::INT32)) {
       int64_t all_element_num = 0;
@@ -195,8 +207,12 @@ void ArgMinMaxInferMeta(const MetaTensor& x,
               INT_MAX));
     }
   }
+
   std::vector<int64_t> vec;
-  if (flatten) {
+
+  if (x_rank == 0) {
+    // vec is set to empty
+  } else if (flatten) {
     vec.emplace_back(static_cast<int64_t>(1));
   } else {
     for (int64_t i = 0; i < int_axis; i++) vec.emplace_back(x_dims[i]);
@@ -205,6 +221,7 @@ void ArgMinMaxInferMeta(const MetaTensor& x,
     }
     for (int64_t i = int_axis + 1; i < x_rank; i++) vec.emplace_back(x_dims[i]);
   }
+
   out->set_dims(phi::make_ddim(vec));
   if (dtype == 2) {
     out->set_dtype(DataType::INT32);

paddle/phi/kernels/cpu/arg_min_max_kernel.cc

@@ -96,6 +96,12 @@ struct VisitDataArgMinMaxFunctor {
       if (axis < 0) new_axis = axis + x_dims.size();
     }
 
+    // For 0D Tensor
+    if (x.dims().size() == 0) {
+      phi::funcs::set_constant(dev_ctx, out, 0);
+      return;
+    }
+
 #define CALL_ARG_MINMAX_FUNCTOR(rank)                                         \
   ArgMinMaxFunctor<Context, T, Tout, rank, EnumArgMinMaxValue> functor##rank; \
   functor##rank(dev_ctx, x, out, x_dims, new_axis, new_keepdims)

paddle/phi/kernels/gpu/arg_min_max_kernel.cu

@@ -30,6 +30,7 @@ namespace cub = hipcub;
 
 #include "paddle/phi/core/ddim.h"
 #include "paddle/phi/core/utils/data_type.h"
+#include "paddle/phi/kernels/funcs/math_function.h"
 namespace phi {
 
 namespace {  // NOLINT
@@ -180,6 +181,12 @@ struct VisitDataCudaArgMinMaxFunctor {
       x_dims = x.dims();
       if (axis < 0) new_axis = axis + x.dims().size();
     }
+    // For 0D Tensor
+    if (x.dims().size() == 0) {
+      dev_ctx.template Alloc<IndType>(out);
+      phi::funcs::set_constant(dev_ctx, out, 0);
+      return;
+    }
 
     int64_t numel = x.numel();
     int64_t groups = numel / x_dims[new_axis];

paddle/phi/kernels/xpu/arg_min_max_kernel.cc

@@ -18,6 +18,7 @@
 #include "paddle/phi/core/ddim.h"
 #include "paddle/phi/core/kernel_registry.h"
 #include "paddle/phi/core/utils/data_type.h"
+#include "paddle/phi/kernels/funcs/math_function.h"
 
 namespace phi {
 
@@ -39,7 +40,15 @@ void ArgMaxKernel(const Context& dev_ctx,
           DataType::INT64,
           DataType::INT32,
           dtype));
+  // TODO(ZHUI): fix dtype of out
   dev_ctx.template Alloc<int64_t>(out);
+  if (x.dims().size() == 0) {
+    xpu::constant(dev_ctx.x_context(),
+                  out->data<int64_t>(),
+                  x.numel(),
+                  static_cast<int64_t>(0));
+    return;
+  }
 
   DDim x_dims;
   int axis_val = axis.to<int>();

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

@@ -189,6 +189,8 @@ def test_static_unary(self):
     paddle.logsumexp,
     paddle.all,
     paddle.any,
+    paddle.argmax,
+    paddle.argmin,
 ]
 
 
@@ -208,12 +210,13 @@ def test_dygraph_reduce(self):
             out.retain_grads()
             out.backward()
 
-            out_empty_list = api(x, [])
-            self.assertEqual(out_empty_list, out)
-
             self.assertEqual(x.shape, [])
             self.assertEqual(out.shape, [])
-            np.testing.assert_allclose(out.numpy(), x.numpy())
+            if api not in [paddle.argmax, paddle.argmin]:
+                np.testing.assert_allclose(out.numpy(), x.numpy())
+                out_empty_list = api(x, [])
+                self.assertEqual(out_empty_list, out)
+
             if x.grad is not None:
                 self.assertEqual(x.grad.shape, [])
                 self.assertEqual(out.grad.shape, [])
@@ -250,7 +253,9 @@ def test_static_reduce(self):
                 res = exe.run(main_prog, fetch_list=fetch_list)
                 self.assertEqual(res[0].shape, ())
                 self.assertEqual(res[1].shape, ())
-                np.testing.assert_allclose(res[0], res[1])
+                if api not in [paddle.argmax, paddle.argmin]:
+                    np.testing.assert_allclose(res[0], res[1])
+
                 if len(res) > 2:
                     self.assertEqual(res[2].shape, ())
                     self.assertEqual(res[3].shape, ())

python/paddle/fluid/tests/unittests/xpu/test_zero_dim_tensor_xpu.py

@@ -132,6 +132,8 @@ def test_dygraph_unary(self):
     paddle.logsumexp,
     paddle.all,
     paddle.any,
+    paddle.argmax,
+    paddle.argmin,
 ]
 
 
@@ -153,7 +155,8 @@ def test_dygraph_reduce(self):
 
             self.assertEqual(x.shape, [])
             self.assertEqual(out.shape, [])
-            np.testing.assert_allclose(out.numpy(), x.numpy())
+            if api not in [paddle.argmax, paddle.argmin]:
+                np.testing.assert_allclose(out.numpy(), x.numpy())
             if x.grad is not None:
                 self.assertEqual(x.grad.shape, [])
                 self.assertEqual(out.grad.shape, [])