for param in list(self.model.parameters()):
    print(type(param.data), param.size())

n_batch = len(X_train) // batch_size
print "n_batch: ", n_batch

Output:

(<class ‘torch.cuda.FloatTensor’>, (128L, 1L, 3L, 128L))
(<class ‘torch.cuda.FloatTensor’>, (128L,))
(<class ‘torch.cuda.FloatTensor’>, (128L, 1L, 4L, 128L))
(<class ‘torch.cuda.FloatTensor’>, (128L,))
(<class ‘torch.cuda.FloatTensor’>, (128L, 1L, 5L, 128L))
(<class ‘torch.cuda.FloatTensor’>, (128L,))
(<class ‘torch.cuda.FloatTensor’>, (13L, 384L))
(<class ‘torch.cuda.FloatTensor’>, (13L,))
n_batch:  23

it contains all parameters of conv layer, fc layer and bias