The `GlobalAveragePooling1D` layer in Python's Keras library is used for 1D average pooling over the temporal dimension of input data. This layer takes the average value of all the features across the time steps and returns a single-dimensional vector output. It is commonly used as a downsampling operation to reduce the spatial dimensions of the data while retaining important information. The GlobalAveragePooling1D layer is particularly useful in tasks such as text classification where the input data is in the form of sequences.
Python GlobalAveragePooling1D - 30 examples found. These are the top rated real world Python examples of keras.layers.GlobalAveragePooling1D extracted from open source projects. You can rate examples to help us improve the quality of examples.