Cherry pick getitem/setitem 0d (PaddlePaddle#53125)

* support 0-D output and 0-D as indice in __getitem__

* fix tests

* fix inference and UT

* add unittest for setitem

* fix xpu test

* fix xpu 0-d

paddle/fluid/framework/attribute_checker.h

@@ -73,10 +73,10 @@ class TypedAttrVarInfoChecker {
         platform::errors::InvalidArgument(
             "Required Attribute with Variable type shall not be nullptr."));
     auto shape = var_desc->GetShape();
-    PADDLE_ENFORCE_EQ(shape.size(),
+    PADDLE_ENFORCE_LE(shape.size(),
                       1U,
                       platform::errors::InvalidArgument(
-                          "Required shape rank of Attribute(%s) == 1, "
+                          "Required shape rank of Attribute(%s) <= 1, "
                           "but received rank == %s",
                           var_desc->Name(),
                           shape.size()));
@@ -105,20 +105,21 @@ class TypedAttrVarInfoChecker {
           platform::errors::InvalidArgument(
               "Required Attribute with Variable type shall not be nullptr."));
       auto shape = var_desc->GetShape();
-      PADDLE_ENFORCE_EQ(shape.size(),
+      PADDLE_ENFORCE_LE(shape.size(),
                         1U,
                         platform::errors::InvalidArgument(
-                            "Required shape rank of Attribute(%s) == 1, "
+                            "Required shape rank of Attribute(%s) <= 1, "
                             "but received rank == %s",
                             var_desc->Name(),
                             shape.size()));
-      PADDLE_ENFORCE_EQ(shape[0] == 1U || shape[0] == -1,
-                        true,
-                        platform::errors::InvalidArgument(
-                            "Required shape[0] of Attribute(%s) == 1 or -1, "
-                            "but received shape[0] == %s",
-                            var_desc->Name(),
-                            shape[0]));
+      PADDLE_ENFORCE_EQ(
+          shape.size() == 0U || shape[0] == 1U || shape[0] == -1,
+          true,
+          platform::errors::InvalidArgument(
+              "Required shape is (), or shape[0] of Attribute(%s) == 1 or -1, "
+              "but received shape[0] == %s",
+              var_desc->Name(),
+              shape[0]));
     }
   }
 };

paddle/fluid/inference/tensorrt/engine.h

@@ -86,10 +86,10 @@ template <typename T>
 nvinfer1::Dims Vec2TRT_Dims(const std::vector<T>& shape,
                             std::string input,
                             bool with_dynamic_shape = false) {
-  PADDLE_ENFORCE_GT(shape.size(),
+  PADDLE_ENFORCE_GE(shape.size(),
                     0UL,
                     platform::errors::InvalidArgument(
-                        "TensorRT's tensor input requires at least 1 "
+                        "TensorRT's tensor input requires at least 0 "
                         "dimensions, but input %s has %d dims.",
                         input,
                         shape.size()));

paddle/fluid/pybind/eager_method.cc

@@ -923,17 +923,6 @@ static PyObject* tensor__getitem_index_not_tensor(TensorObject* self,
   }
 
   if (!none_axes.empty()) {
-    // Deal with cases when all axes are decreased.
-    // After slice, the shape of out is [1], which should have been
-    // [], but Paddle doesn't support scalar.
-    // In order to ensure the correctness of the final shape of out,
-    // one dimension of out needs to be decreased.
-    // For example:
-    // # x.shape: (2,3,4)
-    // out = x[0, 1, 1, None] # out.shape : (1)
-    if (static_cast<int>(decrease_axis.size()) == tensor->dims().size()) {
-      none_axes.pop_back();
-    }
     if (!none_axes.empty()) {
       paddle::Tensor new_out;
       {

paddle/fluid/pybind/imperative.cc

@@ -1068,18 +1068,6 @@ void BindImperative(py::module *m_ptr) {
                tracer->TraceOp(op_type, ins, outs, std::move(attrs));
              }
              if (!none_axes.empty()) {
-               // Deal with cases when all axes are decreased.
-               // After slice, the shape of out is [1], which should have been
-               // [], but Paddle doesn't support scalar.
-               // In order to ensure the correctness of the final shape of out,
-               // one dimension of out needs to be decreased.
-               // For example:
-               // # x.shape: (2,3,4)
-               // out = x[0, 1, 1, None] # out.shape : (1)
-               if (static_cast<int>(decrease_axis.size()) ==
-                   tensor->dims().size()) {
-                 none_axes.pop_back();
-               }
                if (!none_axes.empty()) {
                  // Deal with cases that decrease_axes is not empty
                  // For example:

paddle/phi/infermeta/unary.cc

@@ -3927,9 +3927,6 @@ void StridedSliceRawInferMeta(const MetaTensor& x,
         new_out_shape.push_back(out_dims[i]);
       }
     }
-    if (new_out_shape.size() == 0) {
-      new_out_shape.push_back(1);
-    }
     out_dims = phi::make_ddim(new_out_shape);
   }
   VLOG(4) << "out_dims: " << out_dims;

paddle/phi/kernels/funcs/slice_utils.h

@@ -203,12 +203,6 @@ inline DDim GetDecreasedDims(const DDim slice_dims,
       }
     }
 
-    // NOTE(liym27): Paddle does not support that the rank of Tensor is 0, and
-    // uses [1] instead.
-    if (new_shape.size() == 0) {
-      new_shape.push_back(1);
-    }
-
     decreased_dims = phi::make_ddim(new_shape);
   }
   return decreased_dims;

paddle/phi/kernels/xpu/set_value_grad_kernel.cc

@@ -266,6 +266,11 @@ void SetValueGradImpl(const Context& dev_ctx,
                   {fake_value_grad_dims.Get(), fake_value_grad_dims.size()},
                   static_cast<T>(0));
       auto value_grad_dims_vec = phi::vectorize<int64_t>(value_grad_dims);
+      // for value is a 0-D Tensor
+      if (value_grad_dims.size() == 0) {
+        value_grad_dims_vec =
+            phi::vectorize<int64_t>(phi::make_ddim(std::vector<int>({1})));
+      }
       for (auto offset : offsets) {
         for (int i = 0; i < out_dims_size; i++) {
           slice_end[i] = offset[i] + fake_value_grad_dims[i];

python/paddle/distributed/auto_parallel/operators/dist_slice.py

@@ -70,9 +70,7 @@ def is_output_compatible(self, dist_op):
             if i not in decrease_axis:
                 ref_indices.append(i)
         if ref_indices == []:
-            assert len(out_dims_mapping) == 1
-            if is_dim_shard(out_dims_mapping[0]):
-                return False
+            assert len(out_dims_mapping) == 0
         else:
             for i in range(len(out_dims_mapping)):
                 ref_index = ref_indices[i]
@@ -142,9 +140,7 @@ def update_dims_mapping(self, dist_op):
                 ref_indices.append(i)
 
         if ref_dims_mapping == []:
-            ref_dims_mapping = [-1]
             assert len(ref_dims_mapping) == len(out_dims_mapping)
-            assert ref_dims_mapping[0] == out_dims_mapping[0]
             changed = False
         else:
             assert len(ref_dims_mapping) == len(out_dims_mapping)

python/paddle/fft.py

@@ -1371,7 +1371,7 @@ def fftshift(x, axes=None, name=None):
     elif isinstance(axes, int):
         shifts = shape[axes] // 2
     else:
-        shifts = paddle.concat([shape[ax] // 2 for ax in axes])
+        shifts = paddle.stack([shape[ax] // 2 for ax in axes])
     return paddle.roll(x, shifts, axes, name=name)
 
 
@@ -1416,7 +1416,7 @@ def ifftshift(x, axes=None, name=None):
     elif isinstance(axes, int):
         shifts = -shape[axes] // 2
     else:
-        shifts = paddle.concat([-shape[ax] // 2 for ax in axes])
+        shifts = paddle.stack([-shape[ax] // 2 for ax in axes])
     return paddle.roll(x, shifts, axes, name=name)
 
 

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

@@ -43,7 +43,7 @@ def test_tensor_from_numpy(self):
             np.testing.assert_array_equal(var2.numpy(), data_np)
             data_np[0][0] = -1
             self.assertEqual(data_np[0][0], -1)
-            self.assertNotEqual(var2[0][0].numpy()[0], -1)
+            self.assertNotEqual(var2[0][0].numpy(), -1)
             self.assertFalse(np.array_equal(var2.numpy(), data_np))
 
 

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

@@ -140,16 +140,16 @@ def test_nan_in_cpu_kernel():
             nan_position = 100
             self.x[0, nan_position, 2] = float('nan')
             v, inds = self.x.kthvalue(k=200, axis=1)
-            self.assertTrue(np.isnan(v[0, 2].numpy()[0]))
-            self.assertEqual(inds[0, 2].numpy()[0], nan_position)
+            self.assertTrue(np.isnan(v[0, 2].numpy()))
+            self.assertEqual(inds[0, 2].numpy(), nan_position)
 
         def test_nan_in_gpu_kernel():
             paddle.set_device('gpu')
             nan_position = 100
             self.x[0, nan_position, 2] = float('nan')
             v, inds = self.x.kthvalue(k=200, axis=1)
-            self.assertTrue(np.isnan(v[0, 2].numpy()[0]))
-            self.assertEqual(inds[0, 2].numpy()[0], nan_position)
+            self.assertTrue(np.isnan(v[0, 2].numpy()))
+            self.assertEqual(inds[0, 2].numpy(), nan_position)
 
         test_nan_in_cpu_kernel()
         if fluid.core.is_compiled_with_cuda():

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

@@ -1590,7 +1590,7 @@ def test_inplace(self):
             a.stop_gradient = False
             b = a[:]
             c = b
-            b[paddle.to_tensor(0)] = 1.0
+            b[paddle.zeros([], dtype='int32')] = 1.0
 
             self.assertTrue(id(b) == id(c))
             np.testing.assert_array_equal(b.numpy(), c.numpy())

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

@@ -541,8 +541,8 @@ class TestSliceAPI(unittest.TestCase):
     def test_1(self):
         with paddle_static_guard():
             input = np.random.random([3, 4, 5, 6]).astype("float64")
-            minus_1 = paddle.tensor.fill_constant([1], "int32", -1)
-            minus_3 = paddle.tensor.fill_constant([1], "int64", -3)
+            minus_1 = paddle.tensor.fill_constant([], "int32", -1)
+            minus_3 = paddle.tensor.fill_constant([], "int64", -3)
             starts = paddle.static.data(
                 name='starts', shape=[1, 3], dtype="float32"
             )

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

@@ -604,8 +604,7 @@ def _test_slice(self):
 
         nw = w[1, 1, 1]
 
-        self.assertEqual(len(nw.shape), 1)
-        self.assertEqual(nw.shape[0], 1)
+        self.assertEqual(len(nw.shape), 0)
 
         nw = w[:, :, :-1]
         self.assertEqual((784, 100, 99), tuple(nw.shape))
@@ -705,10 +704,10 @@ def _test_slice_for_tensor_attr(self):
 
         var = paddle.to_tensor(tensor_array)
 
-        one = paddle.ones(shape=[1], dtype="int32")
-        two = paddle.full(shape=[1], fill_value=2, dtype="int32")
-        negative_one = paddle.full(shape=[1], fill_value=-1, dtype="int32")
-        four = paddle.full(shape=[1], fill_value=4, dtype="int32")
+        one = paddle.ones(shape=[], dtype="int32")
+        two = paddle.full(shape=[], fill_value=2, dtype="int32")
+        negative_one = paddle.full(shape=[], fill_value=-1, dtype="int32")
+        four = paddle.full(shape=[], fill_value=4, dtype="int32")
 
         var = fluid.dygraph.to_variable(tensor_array)
         var1 = var[0, one, one]

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

@@ -132,8 +132,7 @@ def _test_slice(self, place):
 
         nw = w[1, 1, 1]
 
-        self.assertEqual(len(nw.shape), 1)
-        self.assertEqual(nw.shape[0], 1)
+        self.assertEqual(len(nw.shape), 0)
 
         nw = w[:, :, :-1]
         self.assertEqual((784, 100, 99), nw.shape)

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

@@ -192,9 +192,9 @@ def test_outputs_exists_inputs(self):
         with fluid.program_guard(main_program, startup_program):
 
             def func(x):
-                s = paddle.zeros([1])
-                i = paddle.ones([1])
-                max_len = paddle.shape(x)[0]
+                s = paddle.zeros([])
+                i = paddle.ones([])
+                max_len = paddle.shape(x)
 
                 def cond(i, s, x):
                     return i < max_len