import numpy as np
from Tensor import Tensor
from SGD import SGD
from Layer import (
Sequential,
Linear,
MSELoss,
Tanh,
Sigmoid,
Embedding,
CrossEntropyLoss,
)
np.random.seed(0)
data = Tensor(np.array([1, 2, 1, 2]), autograd=True)
target = Tensor(np.array([0, 1, 0, 1]), autograd=True)
model = Sequential([Embedding(3, 3), Tanh(), Linear(3, 4)])
criterion = CrossEntropyLoss()
optimizer = SGD(parameters=model.getParameters(), alpha=0.1)
for i in range(0, 10):
pred = model.forward(data)
loss = criterion.forward(pred, target)
loss.backprop()
optimizer.step()
print(loss)
