Menu
I'm training a convolutional neural network on text (on the character level) and I want to do max-pooling. tf.nn.max_pool expects a rank 4 Tensor, but 1-d convnets are rank 3 in tensorflow ([batch, width, depth]), so when I pass the output of conv1d to the max pool function, this is the error:
ValueError: Shape (1, 144, 512) must have rank 4
I'm new to tensorflow and deep learning frameworks in general and would like advice on the best practice here, because I can imagine there are multiple workarounds. How can I perform max-pooling in the 1-d case?
Thanks.
889
Max pooling operation for 2D spatial data. Downsamples the input along its spatial dimensions (height and width) by taking the maximum value over an input window (of size defined by pool_size ) for each channel of the input. The window is shifted by strides along each dimension.
The 1D Global max pooling block takes a 2-dimensional tensor tensor of size (input size) x (input channels) and computes the maximum of all the (input size) values for each of the (input channels).
Max pooling is a type of operation that is typically added to CNNs following individual convolutional layers. When added to a model, max pooling reduces the dimensionality of images by reducing the number of pixels in the output from the previous convolutional layer.
A quick way would be to add an extra singleton dimension i.e. make the shape (1, 1, 144, 512), from there you can reduce it back with tf.squeeze.
I'm curious about other approaches though.
114
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
