config example

config.py

# https://github.com/MinaGhadimiAtigh/hyperbolic_representation_learning/blob/main/notebooks/2_Hyperbolic_Image_Embeddings.ipynb
class Config:
    def __init__(self, shot=1, lr=0.001, step=50, gamma=0.8, c=0.05, model="convnet", hyperbolic = True, dim=1600,
                 query=15, way=5, validation_way=5, temperature=1, dataset="CUB", lr_decay=True, max_epoch=200):
        
        self.lr = lr                                  # learning rate
        self.lr_decay = lr_decay                      # Boolean, if to perform learning rate scheduler
        self.step_size=step                           # Period of learning rate decay
        self.gamma = gamma                            # Multiplicative factor of learning rate decay
        self.dataset= dataset                         # Dataset name
        self.model = "convnet"                        # Name of Base Model
        self.temperature = temperature                # temperature used in calculating logits
        self.max_epoch=max_epoch                      # number of epochs

        self.c = c                                    # Curvature of the hyperbolic space
        self.hyperbolic = hyperbolic                  # Boolean, if it is hyperbolic or not
        self.dim = dim                                # dimenionality of the output vector

        self.shot = shot                              # Number of shots in Few shot learning task
        self.query = query                            #
        self.way = way                                # Number of ways in Few shot learning task
        self.validation_way = validation_way          # Number of ways in Few shot learning task for validation set


args = Config(dim=512, max_epoch = 5, hyperbolic= True)