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### `tf.nn.max_pool3d(input, ksize, strides, padding, name=None)` {#max_pool3d}
Performs 3D max pooling on the input.
##### Args:
* <b>`input`</b>: A `Tensor`. Must be one of the following types: `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`, `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`.
Shape `[batch, depth, rows, cols, channels]` tensor to pool over.
* <b>`ksize`</b>: A list of `ints` that has length `>= 5`.
1-D tensor of length 5. The size of the window for each dimension of
the input tensor. Must have `ksize[0] = ksize[1] = 1`.
* <b>`strides`</b>: A list of `ints` that has length `>= 5`.
1-D tensor of length 5. The stride of the sliding window for each
dimension of `input`. Must have `strides[0] = strides[4] = 1`.
* <b>`padding`</b>: A `string` from: `"SAME", "VALID"`.
The type of padding algorithm to use.
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
A `Tensor`. Has the same type as `input`. The max pooled output tensor.
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