[0-size Tensor No.6、7、284、285]Add 0-size Tensor support for amin

paddle/phi/kernels/cpu/reduce_amax_grad_kernel.cc

@@ -28,6 +28,10 @@ void ReduceAMaxGradKernel(const Context& dev_ctx,
                           bool keep_dim,
                           bool reduce_all,
                           DenseTensor* x_grad) {
+  if (x_grad && x_grad->numel() == 0) {
+    dev_ctx.template Alloc<T>(x_grad);
+    return;
+  }
   reduce_all = recompute_reduce_all(x, dims, reduce_all);
   ReduceGradKernel<Context, T, funcs::AMaxOrAMinGradFunctor>(
       dev_ctx, x, out, out_grad, dims, keep_dim, reduce_all, x_grad);

paddle/phi/kernels/cpu/reduce_amin_grad_kernel.cc

@@ -28,6 +28,10 @@ void ReduceAMinGradKernel(const Context& dev_ctx,
                           bool keep_dim,
                           bool reduce_all,
                           DenseTensor* x_grad) {
+  if (x_grad && x_grad->numel() == 0) {
+    dev_ctx.template Alloc<T>(x_grad);
+    return;
+  }
   reduce_all = recompute_reduce_all(x, dims, reduce_all);
   ReduceGradKernel<Context, T, funcs::AMaxOrAMinGradFunctor>(
       dev_ctx, x, out, out_grad, dims, keep_dim, reduce_all, x_grad);

paddle/phi/kernels/funcs/reduce_function.h

@@ -1460,12 +1460,10 @@ void ReduceKernelImpl(const Context& dev_ctx,
                       const std::vector<int64_t>& dims,
                       bool keep_dim,
                       bool reduce_all) {
-  PADDLE_ENFORCE_GT(input.numel(),
-                    0,
-                    common::errors::InvalidArgument(
-                        "Tensor need be reduced must not empty."));
-
   dev_ctx.template Alloc<OutT>(output);
+  if (input.numel() == 0) {
+    return;
+  }
 
   if (reduce_all) {
     // Flatten and reduce 1-D tensor

paddle/phi/kernels/xpu/reduce_max_grad_kernel.cc

@@ -31,6 +31,10 @@ void ReduceMaxGradKernel(const Context& dev_ctx,
                          bool keep_dim,
                          bool reduce_all,
                          DenseTensor* x_grad) {
+  if (x_grad && x_grad->numel() == 0) {
+    dev_ctx.template Alloc<T>(x_grad);
+    return;
+  }
   using XPUDataType = typename XPUTypeTrait<T>::Type;
   reduce_all = recompute_reduce_all(x, dims_arr, reduce_all);
   auto dims = dims_arr.GetData();

paddle/phi/kernels/xpu/reduce_min_grad_kernel.cc

@@ -31,6 +31,10 @@ void ReduceMinGradKernel(const Context& dev_ctx,
                          bool keep_dim,
                          bool reduce_all,
                          DenseTensor* x_grad) {
+  if (x_grad && x_grad->numel() == 0) {
+    dev_ctx.template Alloc<T>(x_grad);
+    return;
+  }
   reduce_all = recompute_reduce_all(x, dims_arr, reduce_all);
   auto dims = dims_arr.GetData();
 

test/legacy_test/test_max_min_amax_amin_op.py

@@ -92,6 +92,7 @@ def _choose_paddle_func(self, func, x):
 
     def test_static_graph(self):
         def _test_static_graph(func):
+            paddle.enable_static()
             startup_program = base.Program()
             train_program = base.Program()
             with base.program_guard(startup_program, train_program):
@@ -107,6 +108,7 @@ def _test_static_graph(func):
                     fetch_list=[out],
                 )
                 self.assertTrue((np.array(res[0]) == self.np_out[func]).all())
+            paddle.disable_static()
 
         _test_static_graph('amax')
         _test_static_graph('amin')
@@ -264,5 +266,23 @@ def _test_dygraph(func):
         _test_dygraph('min')
 
 
+class TestMaxMinAmaxAminAPI_ZeroSize(TestMaxMinAmaxAminAPI):
+    def init_case(self):
+        self.x_np = np.random.randn(1, 0, 10).astype(np.float32)
+        self.shape = [1, 0, 10]
+        self.dtype = 'float32'
+        self.axis = 0
+        self.keepdim = False
+
+
+class TestMaxMinAmaxAminAPI_ZeroSize2(TestMaxMinAmaxAminAPI):
+    def init_case(self):
+        self.x_np = np.random.randn(1, 0, 10).astype(np.float32)
+        self.shape = [1, 0, 10]
+        self.dtype = 'float32'
+        self.axis = -1
+        self.keepdim = True
+
+
 if __name__ == '__main__':
     unittest.main()