oscarknagg

class NShotTaskSampler(Sampler):
    def __init__(self,
                 dataset: torch.utils.data.Dataset,
                 episodes_per_epoch: int = None,
                 n: int = None,
                 k: int = None,
                 q: int = None,
                 num_tasks: int = 1,
                 fixed_tasks: List[Iterable[int]] = None):
        """PyTorch Sampler subclass that generates batches of n-shot, k-way, q-query tasks.

oscarknagg

from keras.layers import Input, Subtract, Dense, Lambda
from keras.models import Model
import keras.backend as K

def build_siamese_network(encoder, input_shape):
    input_1 = Input(input_shape)
    input_2 = Input(input_shape)
    
    # `encoder` is any predefined network that maps a single sample 
    # into an embedding space.