Dataset is FashionMNIST (784 input, 10 output). I'm trying to train logistic regression with Adam optimizer (coded it also):
weights = torch.randn(784, 10) / math.sqrt(784)
weights.requires_grad_()
bias = torch.zeros(10, requires_grad=True)
optimizer = Adam([weights, bias])
criterion = nn.CrossEntropyLoss()
The train function is:
def train_logistic_regression(weights, bias, batch, loss, optimizer):
inputs, labels = batch
inputs = inputs.view(inputs.shape[0], -1)
optimizer.zero_grad()
y_pred = torch.sigmoid(weights@inputs + bias) # there must be the problem
loss = criterion(y_pred, labels)
loss.backward()
optimizer.step()
from IPython.display import clear_output
for epoch in range(1, 5):
for batch in train_dataloader: # have to go with batches
metrics = train_logistic_regression(weights, bias, batch, criterion, optimizer)
Every time I get the error:
RuntimeError Traceback (most recent call last)
<ipython-input-161-408b80d71db1> in <module>()
5
6 for batch in train_dataloader:
----> 7 metrics = train_logistic_regression(weights, bias, batch, criterion, optimizer)
8
9
<ipython-input-160-9c2f95ee56ee> in train_logistic_regression(weights, bias, batch, loss, optimizer)
6
7 optimizer.zero_grad()
----> 8 y_pred = torch.sigmoid(weights@inputs + bias)
9 # y_pred = model(inputs)
10 loss = criterion(y_pred, labels)
RuntimeError: size mismatch, m1: [784 x 10], m2: [128 x 784] at /pytorch/aten/src/TH/generic/THTensorMath.cpp:41
Would be very grateful if anyone could help me.
