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tf.squeeze() tf.reshape()

tf.squeeze() tf.reshape()

作者: 西方失败9527 | 来源:发表于2017-09-15 16:19 被阅读0次

    一、squeeze案例

    # 't' is a tensor of shape [1, 2, 1, 3, 1, 1]

    shape(squeeze(t)) ==> [2, 3]

    Or, to remove specific size 1 dimensions:

    # 't' is a tensor of shape [1, 2, 1, 3, 1, 1]

    shape(squeeze(t, [2, 4])) ==> [1, 2, 3, 1]


    二、reshape案例

    def  reshape(tensor,shape,name=None):

    r"""Reshapes a tensor.

    Given `tensor`, this operation returns a tensor that has the same values

    as `tensor` with shape `shape`.

    If one component of `shape` is the special value -1, the size of that dimension

    is computed so that the total size remains constant.  In particular, a `shape`

    of `[-1]` flattens into 1-D.  At most one component of `shape` can be -1.

    If `shape` is 1-D or higher, then the operation returns a tensor with shape

    `shape` filled with the values of `tensor`. In this case, the number of elements

    implied by `shape` must be the same as the number of elements in `tensor`.

    For example:

    ```

    # tensor 't' is [1, 2, 3, 4, 5, 6, 7, 8, 9]

    # tensor 't' has shape [9]

    reshape(t, [3, 3]) ==>

    [[1, 2, 3],

    [4, 5, 6],

    [7, 8, 9]]

    # tensor 't' is

     [

       [[1, 1], [2, 2]],

        [[3, 3], [4, 4]]

    ]

    # tensor 't' has shape [2, 2, 2]

    reshape(t, [2, 4]) ==> 

    [

        [1, 1, 2, 2],

        [3, 3, 4, 4]

    ]

    # tensor 't' is 

                [

                     [

                           [1, 1, 1],

                           [2, 2, 2]

                      ],

                   [

                        [3, 3, 3],

                        [4, 4, 4]

                    ],

                   [

                       [5, 5, 5],

                       [6, 6, 6]

                    ]

             ]

    # tensor 't' has shape [3, 2, 3]

    # pass '[-1]' to flatten 't'

    reshape(t, [-1]) ==> [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6]

    # -1 can also be used to infer the shape

    # -1 is inferred to be 9:

    reshape(t, [2, -1]) ==> 

    [

         [1, 1, 1, 2, 2, 2, 3, 3, 3],

         [4, 4, 4, 5, 5, 5, 6, 6, 6]

    ]

    # -1 is inferred to be 2:

    reshape(t, [-1, 9]) ==>

     [[1, 1, 1, 2, 2, 2, 3, 3, 3],

    [4, 4, 4, 5, 5, 5, 6, 6, 6]]

    # -1 is inferred to be 3:

    reshape(t, [ 2, -1, 3]) ==> 

    [[[1, 1, 1],

    [2, 2, 2],

    [3, 3, 3]],

    [[4, 4, 4],

    [5, 5, 5],

    [6, 6, 6]]]

    # tensor 't' is [7]

    # shape `[]` reshapes to a scalar

    reshape(t, []) ==> 7

    ```

    Args:

    tensor: A `Tensor`.

    shape: A `Tensor`. Must be one of the following types: `int32`, `int64`.

    Defines the shape of the output tensor.

    name: A name for the operation (optional).

    Returns:

    A `Tensor`. Has the same type as `tensor`.

    """

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