import math
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch.utils.data import DataLoader
from name_dataset import NameDataset
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
# Parameters and DataLoaders
HIDDEN_SIZE = 100
N_LAYERS = 2
BATCH_SIZE = 256
N_EPOCHS = 100
test_dataset = NameDataset(is_train_set=False)
test_loader = DataLoader(dataset=test_dataset,
batch_size=BATCH_SIZE, shuffle=True)
train_dataset = NameDataset(is_train_set=True)
train_loader = DataLoader(dataset=train_dataset,
batch_size=BATCH_SIZE, shuffle=True)
N_COUNTRIES = len(train_dataset.get_countries())
print(N_COUNTRIES, "countries")
N_CHARS = 128 # ASCII
# Some utility functions
def time_since(since):
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch.utils.data import DataLoader
from name_dataset import NameDataset
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
HIDDEN_SIZE = 100
N_LAYERS = 2
BATCH_SIZE = 256
N_EPOCHS = 100
test_dataset = NameDataset(is_train_set=False)
test_loader = DataLoader(dataset=test_dataset,
batch_size=BATCH_SIZE, shuffle=True)
train_dataset = NameDataset(is_train_set=True)
train_loader = DataLoader(dataset=train_dataset,
batch_size=BATCH_SIZE, shuffle=True)
N_AUTHORS = len(train_dataset.get_authors())
print(N_AUTHORS, "authors")
N_CHARS = 128
def time_since(since):