mindspore.ops.DynamicShape

class mindspore.ops.DynamicShape(*args, **kwargs)[source]

Returns the shape of the input tensor. And it used to be dynamic shape.

Note

Dynamic shape: After the graph is running, as the tensor flows in the graph, the specific shape of the tensor on each node on the graph can be inferred according to the structure of the graph. This shape is called a dynamic shape. As the input shape of the graph is different, the dynamic shape of the tensor in the graph will change.

Inputs:

input_x (Tensor) - The shape of tensor is \((x_1, x_2, ..., x_R)\).

Outputs:

Tensor[int], 1-dim Tensor of type int32

Raises: TypeError – If input_x is not a Tensor.

Supported Platforms:: Ascend GPU CPU

Examples

>>> input_x = Tensor(np.ones(shape=[3, 2, 1]), mindspore.float32)
>>> shape = ops.DynamicShape()
>>> output = shape(input_x)
>>> print(output)
[3 2 1]