kerasadf.layers.pooling.AveragePooling1D¶
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class
kerasadf.layers.pooling.AveragePooling1D(pool_size=2, strides=None, padding='valid', data_format=None, **kwargs)¶ Bases:
kerasadf.layers.pooling.Pooling1DAverage pooling layer for 1D inputs.
Assumed Density Filtering (ADF) version of
keras.layers.AveragePooling1D.- Parameters
- pool_size
intortupleofint An integer or tuple/list of a single integer, representing the size of the pooling window. Default is 2.
- strides
intortupleofintorNone, optional An integer or tuple/list of a single integer, specifying the strides of the pooling operation. If
None, thepool_sizewill be used. Default isNone.- padding{“valid”, “same”}, optional
The padding method. Case-insensitive. Default is “valid”.
- data_format{“channels_last”, “channels_first”}, optional
The ordering of the dimensions in the inputs. “channels_last” corresponds to inputs with shape
(batch, steps, features)while “channels_first” corresponds to inputs with shape(batch, features, steps). It defaults to theimage_data_formatvalue found in your Keras config file at~/.keras/keras.json. If you never set it, then it will be “channels_last”.
- pool_size
Notes
- Input shape
3D tensor with shape
(batch_size, steps, features)ifdata_formatis “channels_last” or shape(batch_size, features, steps)ifdata_formatis “channels_first”.- Output shape
3D tensor with shape
(batch_size, pooled_steps, features)ifdata_formatis “channels_last” or shape(batch_size, features, pooled_steps)ifdata_formatis “channels_first”.
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call(self, inputs)¶