import paddle.v2.framework.layers as layers
from paddle.v2.framework.framework import Program, g_program
import paddle.v2.framework.core as core
import unittest


class TestBook(unittest.TestCase):
    def test_fit_a_line(self):
        program = Program()
        x = layers.data(
            name='x', shape=[13], data_type='float32', program=program)
        y_predict = layers.fc(input=x, size=1, act=None, program=program)

        y = layers.data(
            name='y', shape=[1], data_type='float32', program=program)
        cost = layers.square_error_cost(
            input=y_predict, label=y, program=program)

        avg_cost = layers.mean(x=cost, program=program)
        self.assertIsNotNone(avg_cost)
        program.append_backward(avg_cost, set())
        print str(program)

    def test_recognize_digits_mlp(self):
        program = Program()

        # Change g_program, so the rest layers use `g_program`
        images = layers.data(
            name='pixel', shape=[784], data_type='float32', program=program)
        label = layers.data(
            name='label', shape=[1], data_type='int32', program=program)
        hidden1 = layers.fc(input=images, size=128, act='relu', program=program)
        hidden2 = layers.fc(input=hidden1, size=64, act='relu', program=program)
        predict = layers.fc(input=hidden2,
                            size=10,
                            act='softmax',
                            program=program)
        cost = layers.cross_entropy(input=predict, label=label, program=program)
        avg_cost = layers.mean(x=cost, program=program)
        self.assertIsNotNone(avg_cost)
        # print str(program)

    def test_simple_conv2d(self):
        pd = core.ProgramDesc.__create_program_desc__()
        program = Program(desc=pd)
        images = data_layer(
            name='pixel', shape=[3, 48, 48], data_type='int32', program=program)
        conv2d_layer(
            input=images, num_filters=3, filter_size=[4, 4], program=program)

        # print str(program)

    def test_simple_conv2d(self):
        program = Program()
        images = layers.data(
            name='pixel', shape=[3, 48, 48], data_type='int32', program=program)
        layers.conv2d(
            input=images, num_filters=3, filter_size=[4, 4], program=program)

        print str(program)


if __name__ == '__main__':
    unittest.main()