| model_class: NDT1 | |
| encoder: | |
| from_pt: null | |
| stitching: true | |
| 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 zeroed out | |
| random_ratio: 1.0 # of the not zeroed, 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 | |
| # context available for each timestep | |
| context: | |
| forward: -1 | |
| backward: -1 | |
| norm_and_noise: | |
| active: false | |
| smooth_sd: 2 # gaussian smoohing | |
| norm: "zscore" # which normalization layer to use (null/layernorm/scalenorm/zscore) | |
| eps: 1.e-7 # avoid dividing by zero when normalizing padded spikes | |
| white_noise_sd: 1.0 # gaussian noise added to the inputs 1.0 originally | |
| constant_offset_sd: 0.2 # gaussian noise added to the inputs but contsnat in the time dimension 0.2 originally | |
| embedder: | |
| n_channels: 668 # number of neurons recorded | |
| n_blocks: 24 # number of blocks of experiments | |
| n_dates: 24 # number of days of experiments | |
| max_F: 100 # max feature len in timesteps | |
| mode: linear # linear/embed/identity | |
| mult: 2 # embedding multiplier. hiddden_sizd = n_channels * mult | |
| adapt: false # adapt the embedding layer for each day | |
| pos: true # embed position | |
| 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 | |
| fixup_init: false # modify weight initialization | |
| init_range: 0.1 # initialization range for embeddings | |
| spike_log_init: false # special initialization | |
| max_spikes: 0 # max number of spikes in a single time bin | |
| tokenize_binary_mask: false | |
| use_prompt: true | |
| use_session: true | |
| stack: | |
| active: false # wether to stack consecutive timesteps | |
| size: 32 # number of consecutive timesteps to stack | |
| stride: 4 # stacking stride | |
| transformer: | |
| n_layers: 5 # number of transformer layers | |
| hidden_size: 512 # hidden space of the transformer | |
| use_scalenorm: false # use scalenorm instead of layernorm | |
| use_rope: false # use rotary postional encoding | |
| rope_theta: 10000.0 # rope angle of rotation | |
| 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: 1024 # 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 | |
| factors: | |
| active: false # project from hidden_size to factors | |
| size: 8 # factors size | |
| act: relu # activation function after projecting to factors | |
| bias: true # use bias in projection to factors | |
| dropout: 0.0 # dropout in projection to factors | |
| fixup_init: false # modify weight initialization | |
| init_range: 0.1 # initialization range for factors projetion | |
| decoder: | |
| from_pt: null | |