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from transformers import PretrainedConfig
class FlowformerConfig(PretrainedConfig):
def __init__(self,
dim_hidden: int=32, # dim_hidden must be divisible by num_heads i.e. dim_hidden%num_heads = 0
num_heads: int=4,
num_inds: int=16,
hidden_layers: int=3,
layer_norm: bool=True,
dim_input: int=11,
markers: list=["TIME", "FSC-A", "FSC-W", "SSC-A", "CD20", "CD10", "CD45", "CD34", "CD19", "CD38", "SY41"],
**kwargs
):
assert dim_input == len(markers), "dim_input must be equal to the number of markers"
self.dim_hidden = dim_hidden
self.num_heads = num_heads
self.num_inds = num_inds
self.hidden_layers = hidden_layers
self.layer_norm = layer_norm
self.dim_input = dim_input
self.markers = markers
super().__init__(**kwargs) |