深入浅出PaddlePaddle函数——paddle.shape

分类目录：《深入浅出PaddlePaddle函数》总目录

---

语法

paddle.shape(input)

参数

• input：[Tensor] 输入的多维Tensor或SelectedRows，数据类型为float16、float32、float64、int32、int64。如果输入是SelectedRows类型，则返回其内部持有Tensor的shape。

返回值

表示输入 ensor或SelectedRows的shape的Tensor

实例

import paddle.fluid as fluid
import numpy as np
import paddle
paddle.enable_static()

inputs = fluid.data(name="x", shape=[3, 100, 100], dtype="float32")
output = fluid.layers.shape(inputs)

exe = fluid.Executor(fluid.CPUPlace())
exe.run(fluid.default_startup_program())

img = np.ones((3, 100, 100)).astype(np.float32)

res = exe.run(fluid.default_main_program(), feed={'x':img}, fetch_list=[output])
print(res) # [array([  3, 100, 100], dtype=int32)]

函数实现

def shape(input):
    """
    :alias_main: paddle.shape
	:alias: paddle.shape,paddle.tensor.shape,paddle.tensor.attribute.shape
	:old_api: paddle.fluid.layers.shape
    **Shape Layer**
    Get the shape of the input.
    .. code-block:: text
        Case1:
            Given N-D Tensor:
                input = [ [1, 2, 3, 4], [5, 6, 7, 8] ]
            Then:
                input.shape = [2, 4]
        Case2:
            Given SelectedRows:
                input.rows = [0, 4, 19]
                input.height = 20
                input.value = [ [1, 2], [3, 4], [5, 6] ]  # inner tensor
            Then:
                input.shape = [3, 2]
    Args:
        input (Variable): The input can be N-D Tensor or SelectedRows with data type bool, float16, float32, float64, int32, int64.
                          If input variable is type of SelectedRows, returns the shape of it's inner tensor.
    Returns:
        Variable (Tensor): The shape of the input variable.
    Examples:
        .. code-block:: python
            import paddle.fluid as fluid
            import numpy as np
            import paddle
            paddle.enable_static()
            inputs = fluid.data(name="x", shape=[3, 100, 100], dtype="float32")
            output = fluid.layers.shape(inputs)
            exe = fluid.Executor(fluid.CPUPlace())
            exe.run(fluid.default_startup_program())
            img = np.ones((3, 100, 100)).astype(np.float32)
            res = exe.run(fluid.default_main_program(), feed={'x':img}, fetch_list=[output])
            print(res) # [array([  3, 100, 100], dtype=int32)]
    """
    if in_dygraph_mode():
        out = _C_ops.shape(input)
        out.stop_gradient = True
        return out
    if _in_legacy_dygraph():
        out = _legacy_C_ops.shape(input)
        out.stop_gradient = True
        return out

    check_variable_and_dtype(input, 'input', [
        'bool', 'float16', 'float32', 'float64', 'int32', 'int64', 'complex64',
        'complex128'
    ], 'shape')
    helper = LayerHelper('shape', **locals())
    out = helper.create_variable_for_type_inference(dtype='int32')
    helper.append_op(type='shape',
                     inputs={'Input': input},
                     outputs={'Out': out},
                     stop_gradient=True)

    return out