pip install pylearn2
python
import pylearn2
python
import numpy as np
from pylearn2.models import mlp
from pylearn2.training_algorithms import sgd
from pylearn2.termination_criteria import EpochCounter
from pylearn2.datasets import mnist
from pylearn2.train import Train
from pylearn2.train_extensions import best_params
dataset = mnist.MNIST(which_set='train', start=0, stop=50000)
model = mlp.MLP(layers=[mlp.Sigmoid(layer_name='h', dim=100),
mlp.Softmax(10)],
nvis=28*28)
algorithm = sgd.SGD(learning_rate=0.1, batch_size=100, termination_criterion=EpochCounter(max_epochs=10))
train = Train(dataset=dataset, model=model, algorithm=algorithm, extensions=[best_params.MonitorBasedSaveBest()])
train.main_loop()
