
    2Vh                     x    d dl mZ d dl mZ d dlmZ d dlmZ d dlmZ d dl	m
Z
  ed       G d d	e             Zy
)    )backend)ops)keras_export)	InputSpec)Layer)argument_validationzkeras.layers.ZeroPadding3Dc                   <     e Zd ZdZ	 d fd	Zd Zd Z fdZ xZS )ZeroPadding3Da  Zero-padding layer for 3D data (spatial or spatio-temporal).

    Example:

    >>> input_shape = (1, 1, 2, 2, 3)
    >>> x = np.arange(np.prod(input_shape)).reshape(input_shape)
    >>> y = keras.layers.ZeroPadding3D(padding=2)(x)
    >>> y.shape
    (1, 5, 6, 6, 3)

    Args:
        padding: Int, or tuple of 3 ints, or tuple of 3 tuples of 2 ints.
            - If int: the same symmetric padding is applied to depth, height,
              and width.
            - If tuple of 3 ints: interpreted as three different symmetric
              padding values for depth, height, and width:
              `(symmetric_dim1_pad, symmetric_dim2_pad, symmetric_dim3_pad)`.
            - If tuple of 3 tuples of 2 ints: interpreted as
              `((left_dim1_pad, right_dim1_pad), (left_dim2_pad,
              right_dim2_pad), (left_dim3_pad, right_dim3_pad))`.
        data_format: A string, one of `"channels_last"` (default) or
            `"channels_first"`. The ordering of the dimensions in the inputs.
            `"channels_last"` corresponds to inputs with shape
            `(batch_size, spatial_dim1, spatial_dim2, spatial_dim3, channels)`
            while `"channels_first"` corresponds to inputs with shape
            `(batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3)`.
            When unspecified, uses `image_data_format` value found in your Keras
            config file at `~/.keras/keras.json` (if exists). Defaults to
            `"channels_last"`.

    Input shape:
        5D tensor with shape:
        - If `data_format` is `"channels_last"`:
          `(batch_size, first_axis_to_pad, second_axis_to_pad,
          third_axis_to_pad, depth)`
        - If `data_format` is `"channels_first"`:
          `(batch_size, depth, first_axis_to_pad, second_axis_to_pad,
          third_axis_to_pad)`

    Output shape:
        5D tensor with shape:
        - If `data_format` is `"channels_last"`:
          `(batch_size, first_padded_axis, second_padded_axis,
          third_axis_to_pad, depth)`
        - If `data_format` is `"channels_first"`:
          `(batch_size, depth, first_padded_axis, second_padded_axis,
          third_axis_to_pad)`
    c                    t        |   di | t        j                  |      | _        t        |t              r||f||f||ff| _        nt        |d      r|t        |      dk7  rt        d| d      t        j                  |d   ddd	      }t        j                  |d
   ddd	      }t        j                  |d   ddd	      }|||f| _        nt        d| d      t        d      | _        y )N__len__   z,`padding` should have 3 elements. Received: .r      z1st entry of paddingT)
allow_zero   z2nd entry of paddingz3rd entry of paddinga  `padding` should be either an int, a tuple of 3 ints (symmetric_dim1_pad, symmetric_dim2_pad, symmetric_dim3_pad), or a tuple of 3 tuples of 2 ints ((left_dim1_pad, right_dim1_pad), (left_dim2_pad, right_dim2_pad), (left_dim3_pad, right_dim2_pad)). Received: padding=   )ndim )super__init__r   standardize_data_formatdata_format
isinstanceintpaddinghasattrlen
ValueErrorr   standardize_tupler   
input_spec)selfr   r   kwargsdim1_paddingdim2_paddingdim3_padding	__class__s          Y/home/dcms/DCMS/lib/python3.12/site-packages/keras/src/layers/reshaping/zero_padding3d.pyr   zZeroPadding3D.__init__<   s"    	"6""::;Ggs#'"'"'"DL
 Wi(7|q  B7)1M  /@@
A5$L /@@
A5$L /@@
A5$L ),EDL% &-IQ0  $+    c                     t        |      }| j                  dk(  rdnd}t        dd      D ]>  }|||z      |||z   xx   | j                  |   d   | j                  |   d   z   z  cc<   @ t	        |      S )Nchannels_firstr   r   r   r   )listr   ranger   tuple)r!   input_shapeoutput_shapespatial_dims_offsetindexs        r'   compute_output_shapez"ZeroPadding3D.compute_output_shapeb   s    K(#'#3#37G#GaQ1a[ 	EE$778DU%889LL'*T\\%-@-CC9	
 \""r(   c                     | j                   dk(  rddg| j                  }ndg| j                  d}t        j                  ||      S )Nr*   )r   r   )r   r   r   pad)r!   inputsall_dims_paddings      r'   callzZeroPadding3D.calll   sN    // &>> &>>v>wwv/00r(   c                 ^    | j                   | j                  d}t        |          }i ||S )N)r   r   )r   r   r   
get_config)r!   configbase_configr&   s      r'   r9   zZeroPadding3D.get_configs   s4    !\\$:J:JKg(*(+(((r(   ))r   r   r<   r<   N)	__name__
__module____qualname____doc__r   r2   r7   r9   __classcell__)r&   s   @r'   r
   r
   	   s)    /d =A$,L#1) )r(   r
   N)	keras.srcr   r   keras.src.api_exportr   keras.src.layers.input_specr   keras.src.layers.layerr   keras.src.utilsr   r
   r   r(   r'   <module>rG      s;      - 1 ( / *+l)E l) ,l)r(   