fix expand_dims infershape

mindspore/core/abstract/prim_nn.cc

@@ -481,7 +481,7 @@ AbstractBasePtr InferImplPad(const AnalysisEnginePtr &, const PrimitivePtr &prim
   auto padding_attr = primitive->GetAttr("paddings");
   MS_EXCEPTION_IF_NULL(padding_attr);
   if (!padding_attr->isa<ValueTuple>()) {
-    MS_LOG(EXCEPTION) << "paddings is not a ValueTuple";
+    MS_LOG(EXCEPTION) << "Paddings is not a ValueTuple";
   }
   std::vector<ValuePtr> paddings = padding_attr->cast<ValueTuplePtr>()->value();
   std::vector<std::vector<int64_t>> paddings_vec;
@@ -498,7 +498,7 @@ AbstractBasePtr InferImplPad(const AnalysisEnginePtr &, const PrimitivePtr &prim
   size_t length = paddings_vec.size();
   for (size_t i = 0; i < length; ++i) {
     if (paddings_vec[i].size() != 2) {
-      MS_LOG(EXCEPTION) << "paddings 's second dim size is not 2";
+      MS_LOG(EXCEPTION) << "Paddings 's second dim size is not 2";
     }
     result_shp.push_back(input_shp[i] + paddings_vec[i][0] + paddings_vec[i][1]);
   }

mindspore/core/abstract/prim_others.cc

@@ -500,19 +500,11 @@ AbstractBasePtr InferImplExpandDims(const AnalysisEnginePtr &, const PrimitivePt
   MS_EXCEPTION_IF_NULL(x);
   MS_EXCEPTION_IF_NULL(x->shape());
 
-  auto axis = CheckArg<AbstractTensor>(op_name, args_spec_list, 1);
-  MS_EXCEPTION_IF_NULL(axis);
-
   std::vector<int64_t> shape;
   std::vector<int64_t> x_shape = x->shape()->shape();
   shape.insert(shape.end(), x_shape.begin(), x_shape.end());
-
-  auto axis_value = axis->BuildValue();
-  if (!axis_value->isa<tensor::Tensor>()) {
-    MS_LOG(EXCEPTION) << axis_value << " axis_value should be tensor, but got " << axis_value->type_name();
-  }
-  auto axis_tensor = axis_value->cast<tensor::TensorPtr>();
-  int value = *(static_cast<int *>(axis_tensor->data_c()));
+  auto axis = primitive->GetAttr("axis");
+  auto value = GetValue<int64_t>(axis);
   if (value < -(SizeToInt(x_shape.size()) + 1) || value > SizeToInt(x_shape.size())) {
     MS_LOG(EXCEPTION) << " axis value shoud be in range [-intput_x.dim-1,input_x.dim], but axis value is" << value
                       << " and input_x.dim is" << x_shape.size();

mindspore/nn/layer/embedding.py

@@ -159,7 +159,7 @@ class EmbeddingLookup(Cell):
         - **input_indices** (Tensor) - The shape of tensor is :math:`(y_1, y_2, ..., y_S)`.
           Specifies the indices of elements of the original Tensor. Values can be out of range of embedding_table,
           and the exceeding part will be filled with 0 in the output. Input_indices must only be a 2d tensor in
-          this interface.
+          this interface when run in semi auto parallel/auto parallel mode.
 
     Outputs:
         Tensor, the shape of tensor is :math:`(z_1, z_2, ..., z_N)`.
@@ -310,7 +310,7 @@ class MultiFieldEmbeddingLookup(EmbeddingLookup):
           Specifies the weights of elements of the input_indices. The lookout vector will multiply with
           the input_values. Type is Float32.
         - **field_ids** (Tensor)  - The shape of tensor is :math:`(batch_size, seq_length)`.
-          Specifies the field id of elements of the input_indices. Type is Type is Int16, Int32.
+          Specifies the field id of elements of the input_indices. Type is Int16, Int32.
 
     Outputs:
         Tensor, the shape of tensor is :math:`(batch_size, field_size, embedding_size)`. Type is Float32.