a Sic @sbdZddlmmZddlmZddlmZddl m Z ddl m Z e dGdd d e Z dS) z$Contains the SpatialDropout3D layer.N)backend) InputSpec)Dropout) keras_exportzkeras.layers.SpatialDropout3Dcs*eZdZdZdfdd ZddZZS)SpatialDropout3Da5Spatial 3D version of Dropout. This version performs the same function as Dropout, however, it drops entire 3D feature maps instead of individual elements. If adjacent voxels within feature maps are strongly correlated (as is normally the case in early convolution layers) then regular dropout will not regularize the activations and will otherwise just result in an effective learning rate decrease. In this case, SpatialDropout3D will help promote independence between feature maps and should be used instead. Args: rate: Float between 0 and 1. Fraction of the input units to drop. data_format: 'channels_first' or 'channels_last'. In 'channels_first' mode, the channels dimension (the depth) is at index 1, in 'channels_last' mode is it at index 4. It defaults to the `image_data_format` value found in your Keras config file at `~/.keras/keras.json`. If you never set it, then it will be "channels_last". Call arguments: inputs: A 5D tensor. training: Python boolean indicating whether the layer should behave in training mode (adding dropout) or in inference mode (doing nothing). Input shape: 5D tensor with shape: `(samples, channels, dim1, dim2, dim3)` if data_format='channels_first' or 5D tensor with shape: `(samples, dim1, dim2, dim3, channels)` if data_format='channels_last'. Output shape: Same as input. References: - [Efficient Object Localization Using Convolutional Networks](https://arxiv.org/abs/1411.4280) Nc sRtj|fi||dur$t}|dvrchannels_first channels_lastzQ`data_format` must be "channels_last" or "channels_first". Received: data_format=.)ndim)super__init__rimage_data_format ValueError data_formatr input_spec)selfraterkwargs __class__i/var/www/html/django/DPS/env/lib/python3.9/site-packages/keras/layers/regularization/spatial_dropout3d.pyr >szSpatialDropout3D.__init__cCsNt|}|jdkr*|d|ddddfS|jdkrJ|dddd|dfSdS)Nrrr)tfshaper)rinputs input_shaperrr_get_noise_shapeJs    z!SpatialDropout3D._get_noise_shape)N)__name__ __module__ __qualname____doc__r r __classcell__rrrrrs  r)r#tensorflow.compat.v2compatv2rkerasrkeras.engine.input_specr#keras.layers.regularization.dropoutr tensorflow.python.util.tf_exportrrrrrrs