When i am trying to train the model, i get the following mismatch error given at the end of this question. As i am new to PyTorch, i am having difficulties in understanding how to resolve this issue. Kindly guide me what changes should i made in my code.
import torch
import torch.nn as nn
import torch.nn.functional as F
class CharCNN(nn.Module):
def __init__(self):
super(CharCNN, self).__init__()
self.conv1 = nn.Sequential(
nn.Conv1d(num_channels, depth_1, kernel_size=kernel_size_1, stride=stride_size),
nn.ReLU(),
nn.MaxPool1d(kernel_size=kernel_size_1, stride=stride_size),
nn.Dropout(0.1),
)
self.conv2 = nn.Sequential(
nn.Conv1d(depth_1, depth_2, kernel_size=kernel_size_2, stride=stride_size),
nn.ReLU(),
nn.MaxPool1d(kernel_size=kernel_size_2, stride=stride_size),
nn.Dropout(0.25)
)
self.fc1 = nn.Sequential(
nn.Linear(128*64, num_hidden),
nn.ReLU(),
nn.Dropout(0.5)
)
self.fc2 = nn.Sequential(
nn.Linear(num_hidden, 11),
nn.ReLU(),
nn.Dropout(0.5)
)
def forward(self, x):
out = self.conv1(x)
out = self.conv2(out)
# collapse
out = out.reshape(-1,128*64)
#out = out.view(out.size(0), -1)
# linear layer
out = self.fc1(out)
# output layer
out = self.fc2(out)
#out = self.log_softmax(x,dim=1)
return out
This is my model, when i try to train my network like this:
criterion = nn.CrossEntropyLoss()
opt = torch.optim.Adam(model.parameters(),lr=learning_rate)
for e in range(training_epochs):
if(train_on_gpu):
net.cuda()
train_losses = []
for batch in iterate_minibatches(train_x, train_y, batch_size):
x, y = batch
inputs, targets = torch.from_numpy(x), torch.from_numpy(y)
if(train_on_gpu):
inputs, targets = inputs.cuda(), targets.cuda()
#inputs= input.view(batch_size, 128*64)
#targets = targets.view(batch_size)
opt.zero_grad()
output = model(inputs)
loss = criterion(output, targets.long())
train_losses.append(loss.item())
loss.backward()
opt.step()
val_losses = []
accuracy=0
f1score=0
print("Epoch: {}/{}...".format(e+1, training_epochs),
"Train Loss: {:.4f}...".format(np.mean(train_losses)))
I get the following error:
ValueError: Expected input batch_size (1) to match target batch_size (64).
Please help me to resolve this issue.