dodox/Spikey
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

New config

Browse Source
This commit is contained in:
Dominik Moritz Roth 2024-05-25 17:44:18 +02:00
parent bfbf9019d5
commit 97de63e946
1 changed files with 9 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

18
config.yaml
View File

@ -42,21 +42,21 @@ name: Test
import: $ import: $
latent_projector: latent_projector:
type: fc # Options: 'fc', 'rnn' type: rnn # Options: 'fc', 'rnn'
input_size: 50 # Input size for the Latent Projector (length of snippets). input_size: 19531 # =1s Input size for the Latent Projector (length of snippets).
latent_size: 8 # Size of the latent representation before message passing. latent_size: 8 # Size of the latent representation before message passing.
layer_shapes: [16, 32] # List of layer sizes for the latent projector (if type is 'fc'). layer_shapes: [256, 32] # List of layer sizes for the latent projector (if type is 'fc').
activations: ['relu', 'relu'] # Activation functions for the latent projector layers (if type is 'fc'). activations: ['relu', 'relu'] # Activation functions for the latent projector layers (if type is 'fc').
rnn_hidden_size: 32 # Hidden size for the RNN projector (if type is 'rnn'). rnn_hidden_size: 16 # Hidden size for the RNN projector (if type is 'rnn').
rnn_num_layers: 2 # Number of layers for the RNN projector (if type is 'rnn'). rnn_num_layers: 2 # Number of layers for the RNN projector (if type is 'rnn').
middle_out: middle_out:
output_size: 16 # Size of the latent representation after message passing. output_size: 8 # Size of the latent representation after message passing.
num_peers: 3 # Number of most correlated peers to consider. num_peers: 8 # Number of most correlated peers to consider.
predictor: predictor:
layer_shapes: [32, 16] # List of layer sizes for the predictor. layer_shapes: [8, 4] # List of layer sizes for the predictor.
activations: ['relu', 'relu'] # Activation functions for the predictor layers. activations: ['relu', 'none'] # Activation functions for the predictor layers.
training: training:
epochs: 128 # Number of training epochs. epochs: 128 # Number of training epochs.
@ -70,7 +70,7 @@ evaluation:
full_compression: false # Perform full compression during evaluation full_compression: false # Perform full compression during evaluation
bitstream_encoding: bitstream_encoding:
type: identity # Options: 'arithmetic', 'no_compression', 'bzip2' type: identity # Options: 'arithmetic', 'identity', 'bzip2'
data: data:
url: https://content.neuralink.com/compression-challenge/data.zip # URL to download the dataset. url: https://content.neuralink.com/compression-challenge/data.zip # URL to download the dataset.