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tf.squeeze() tf.reshape()

2017-09-15  本文已影响0人  西方失败9527

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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