model_class: STPatch # NDT2 is a sub-class of STPatch | |
encoder: | |
stitching: false | |
from_pt: null | |
embed_region: false | |
masker: | |
force_active: true | |
mode: all | |
ratio: 0.3 # ratio of data to predict | |
zero_ratio: 1.0 # of the data to predict, ratio of zero-ed out | |
random_ratio: 1.0 # of the not zero-ed, ratio of randomly replaced | |
expand_prob: 0.0 # probability of expanding the mask in "temporal" mode | |
max_timespan: 1 # max span of mask if expanded | |
channels: null # neurons to mask in "co-smoothing" mode | |
timesteps: null # time steps to mask in "forward-pred" mode | |
mask_regions: ['all'] # brain regions to mask in "inter-region" mode | |
target_regions: ['all'] # brain regions to predict in "intra-region" mode | |
n_mask_regions: 1 # num of regions to choose from the list of mask_regions or target_regions | |
patcher: | |
active: true | |
time_stride: 0 | |
# context available for each timestep | |
context: | |
forward: -1 | |
backward: -1 | |
embedder: | |
n_neurons: 1280 | |
n_timesteps: 100 | |
max_time_F: 1 | |
max_space_F: 128 | |
max_spikes: 0 # max number of spikes in a single time bin | |
mode: linear # linear/embed/identity | |
mult: 2 # embedding multiplier. hiddden_sizd = n_channels * mult | |
act: softsign # activation for the embedding layers | |
scale: 1 # scale the embedding multiplying by this number | |
bias: true # use bias in the embedding layer | |
dropout: 0.2 # dropout in embedding layer | |
use_prompt: true | |
use_session: true | |
transformer: | |
n_layers: 5 # number of transformer layers | |
hidden_size: 128 # hidden space of the transformer | |
n_heads: 8 # number of attentiomn heads | |
attention_bias: true # learn bias in the attention layers | |
act: gelu # activiation function in mlp layers | |
inter_size: 512 # intermediate dimension in the mlp layers | |
mlp_bias: true # learn bias in the mlp layers | |
dropout: 0.4 # dropout in transformer layers | |
fixup_init: true # modify weight initialization | |
decoder: | |
from_pt: null | |