throw exception when tensor has zero in shape

mindspore/core/ir/tensor.cc

@@ -465,7 +465,9 @@ Tensor::Tensor(const Tensor &tensor)
       cache_tensor_ptr_(tensor.cache_tensor_ptr_),
       hashmap_tensor_ptr_(tensor.hashmap_tensor_ptr_),
       padding_type_(tensor.padding_type()),
-      device_event_(tensor.device_event_) {}
+      device_event_(tensor.device_event_) {
+  CheckShape(tensor.shape_);
+}
 
 Tensor::Tensor(const Tensor &tensor, TypeId data_type)
     : MetaTensor(data_type, tensor.shape_),
@@ -479,29 +481,43 @@ Tensor::Tensor(const Tensor &tensor, TypeId data_type)
       cache_tensor_ptr_(tensor.cache_tensor_ptr_),
       hashmap_tensor_ptr_(tensor.hashmap_tensor_ptr_),
       padding_type_(tensor.padding_type()),
-      device_event_(tensor.device_event_) {}
+      device_event_(tensor.device_event_) {
+  CheckShape(tensor.shape_);
+}
 
 Tensor::Tensor(TypeId data_type, const ShapeVector &shape, TensorDataPtr data)
-    : MetaTensor(data_type, shape), data_(std::move(data)), id_(MakeId()) {}
+    : MetaTensor(data_type, shape), data_(std::move(data)), id_(MakeId()) {
+  CheckShape(shape);
+}
 
 Tensor::Tensor(TypeId data_type, const ShapeVector &shape)
-    : Tensor(data_type, shape, MakeTensorData(data_type, shape)) {}
+    : Tensor(data_type, shape, MakeTensorData(data_type, shape)) {
+  CheckShape(shape);
+}
 
 Tensor::Tensor(TypeId data_type, const ShapeVector &shape, void *data, size_t data_len)
-    : Tensor(data_type, shape, MakeTensorData(data_type, shape, data, data_len)) {}
+    : Tensor(data_type, shape, MakeTensorData(data_type, shape, data, data_len)) {
+  CheckShape(shape);
+}
 
 Tensor::Tensor(TypeId data_type, const ShapeVector &shape, void *data, TypeId src_data_type)
-    : Tensor(data_type, shape, MakeTensorData(data_type, shape, data, src_data_type)) {}
+    : Tensor(data_type, shape, MakeTensorData(data_type, shape, data, src_data_type)) {
+  CheckShape(shape);
+}
 
 Tensor::Tensor(const std::vector<int64_t> &input, const TypePtr &data_type)
     : MetaTensor(TypeIdOf(data_type, kNumberTypeInt32), {static_cast<int>(input.size())}),
       data_(MakeTensorData(data_type_, shape_, input.data(), input.size())),
-      id_(MakeId()) {}
+      id_(MakeId()) {
+  CheckShape(shape_);
+}
 
 Tensor::Tensor(const std::vector<double> &input, const TypePtr &data_type)
     : MetaTensor(TypeIdOf(data_type, kNumberTypeFloat32), {static_cast<int>(input.size())}),
       data_(MakeTensorData(data_type_, shape_, input.data(), input.size())),
-      id_(MakeId()) {}
+      id_(MakeId()) {
+  CheckShape(shape_);
+}
 
 Tensor::Tensor(int64_t input, const TypePtr &data_type)
     : MetaTensor(TypeIdOf(data_type, kNumberTypeInt32), {}),
@@ -606,6 +622,17 @@ std::string Tensor::ToStringRepr() const {
   return buf.str();
 }
 
+void Tensor::CheckShape(const ShapeVector &shape) const {
+  // Check tensor's shape, ignore one-dimensional tensor, including empty tensor with shape=(0,).
+  if (shape.size() > 1) {
+    for (const auto &s : shape) {
+      if (s == 0) {
+        MS_EXCEPTION(ValueError) << "Zero is not supported in the shape of Tensor. ";
+      }
+    }
+  }
+}
+
 void Tensor::data_sync(bool need_wait) const {
   if (need_wait) {
     Wait();

mindspore/core/ir/tensor.h

@@ -280,6 +280,8 @@ class Tensor : public MetaTensor {
 
   std::string ToStringRepr() const;
 
+  void CheckShape(const ShapeVector &shape) const;
+
   bool is_init() const { return init_flag_; }
   void set_init_flag(bool flag) { init_flag_ = flag; }
 

tests/st/ops/cpu/test_dropout_grad_op.py

@@ -107,6 +107,7 @@ def test_dropout_grad_004():
     assert np.all(np.abs(diff) < error)
 
 
+@pytest.mark.skip(reason='0 in shape is not support')
 @pytest.mark.level0
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard

tests/st/ops/gpu/test_add_op.py

@@ -127,30 +127,39 @@ def add(nptype):
     assert (output[2].asnumpy() == expect2).all()
     assert (output[3].asnumpy() == expect3).all()
 
+
+@pytest.mark.skip(reason='0 in shape is not support')
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_float64():
     add(np.float64)
 
+
+@pytest.mark.skip(reason='0 in shape is not support')
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_float32():
     add(np.float32)
 
+
+@pytest.mark.skip(reason='0 in shape is not support')
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_float16():
     add(np.float16)
 
+
+@pytest.mark.skip(reason='0 in shape is not support')
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
 def test_add_int64():
     add(np.int64)
 
+@pytest.mark.skip(reason='0 in shape is not support')
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard

tests/st/pynative/test_tensor_index.py

@@ -787,7 +787,7 @@ def test_tensor_assign_exception():
     tck = Tensor([1, 2, 3, 4, 5, 6, 7, 8], dtype=mstype.float32)
     # Error for A[Slice] = Number
     # 1. A[Slice] = Number,  Slice error
-    with pytest.raises(IndexError):
+    with pytest.raises(ValueError):
         net_e2(t, 2)
 
     # Error for A[Slice] = U, U is a Tensor

tests/ut/python/ir/test_tensor.py

@@ -67,6 +67,17 @@ def test_tensor():
     assert isinstance(t4, ms.Tensor)
     assert t4.dtype == ms.int64
 
+def test_tensor_empty():
+    t = ms.Tensor(np.ones(0), ms.float32)
+    assert isinstance(t, ms.Tensor)
+    assert t.shape == (0,)
+
+
+def test_tensor_shape_has_zero():
+    with pytest.raises(ValueError):
+        t = ms.Tensor(np.ones((1, 0)), ms.float32)
+        print(t)
+
 
 def test_tensor_type_float16():
     t_float16 = ms.Tensor(np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float16))

tests/ut/python/ops/test_ops.py

@@ -14,6 +14,7 @@
 # ============================================================================
 """ test ops """
 import functools
+import pytest
 
 import numpy as np
 
@@ -890,7 +891,7 @@ class StridedSliceNet(nn.Cell):
         out_3 = self.strided_slice_3(x, self.begins, self.ends, self.strides) + self.const_3
         return out_0, out_1, out_2, out_3
 
-
+@pytest.mark.skip(reason='0 in shape is not support')
 def test_strided_slice_const():
     class StridedSLiceConstNet(nn.Cell):
         """StridedSLiceConstNet net definition"""

tests/ut/python/ops/test_tensor_slice.py

@@ -464,8 +464,8 @@ def test_tensor_assign():
     net(Ta, b, Tck)
     net2(t, b, tck)
     # Error for A[Slice] = Number
-    # 1. A[Slice] = Number,  Slice error
-    with pytest.raises(IndexError):
+    # 1. A[Slice] = Number,  0 in shape
+    with pytest.raises(ValueError):
         net_e2(t, Tensor(2, mstype.int32))
 
     # Error for A[Slice] = U, U is a Tensor