unified Tensor type of graph mode and pynative mode

mindspore/nn/layer/timedistributed.py

@@ -16,7 +16,6 @@
 
 from mindspore.ops.primitive import constexpr, Primitive
 from mindspore.ops import Reshape, Transpose, Pack, Unpack
-from mindspore.common.dtype import tensor
 from mindspore.common import Tensor
 from ..cell import Cell
 
@@ -105,9 +104,7 @@ class TimeDistributed(Cell):
         self.reshape = Reshape()
 
     def construct(self, inputs):
-        is_capital_tensor = isinstance(inputs, Tensor)
-        is_tensor = True if is_capital_tensor else isinstance(inputs, tensor)
-        _check_data(is_tensor)
+        _check_data(isinstance(inputs, Tensor))
         _check_inputs_dim(inputs.shape)
         time_axis = self.time_axis % len(inputs.shape)
         if self.reshape_with_axis is not None:
@@ -122,9 +119,7 @@ class TimeDistributed(Cell):
             inputs_shape_new = inputs.shape
             inputs = self.reshape(inputs, inputs_shape_new[: reshape_pos] + (-1,) + inputs_shape_new[reshape_pos + 2:])
             outputs = self.layer(inputs)
-            is_capital_tensor = isinstance(outputs, Tensor)
-            is_tensor = True if is_capital_tensor else isinstance(outputs, tensor)
-            _check_data(is_tensor)
+            _check_data(isinstance(outputs, Tensor))
             _check_reshape_pos(reshape_pos, inputs.shape, outputs.shape)
             outputs_shape_new = outputs.shape[:reshape_pos] + inputs_shape_new[reshape_pos: reshape_pos + 2]
             if reshape_pos + 1 < len(outputs.shape):
@@ -136,9 +131,7 @@ class TimeDistributed(Cell):
         y = ()
         for item in inputs:
             outputs = self.layer(item)
-            is_capital_tensor = isinstance(outputs, Tensor)
-            is_tensor = True if is_capital_tensor else isinstance(outputs, tensor)
-            _check_data(is_tensor)
+            _check_data(isinstance(outputs, Tensor))
             _check_expand_dims_axis(time_axis, outputs.ndim)
             y += (outputs,)
         y = Pack(time_axis)(y)