fastNLP/test/modules/test_other_modules.py

import unittest

import torch

from fastNLP.modules.other_modules import GroupNorm, LayerNormalization, BiLinear


class TestGroupNorm(unittest.TestCase):
    def test_case_1(self):
        gn = GroupNorm(num_features=1, num_groups=10, eps=1.5e-5)
        x = torch.randn((20, 50, 10))
        y = gn(x)


class TestLayerNormalization(unittest.TestCase):
    def test_case_1(self):
        ln = LayerNormalization(d_hid=5, eps=2e-3)
        x = torch.randn((20, 50, 5))
        y = ln(x)


class TestBiLinear(unittest.TestCase):
    def test_case_1(self):
        bl = BiLinear(n_left=5, n_right=5, n_out=10, bias=True)
        x_left = torch.randn((7, 10, 20, 5))
        x_right = torch.randn((7, 10, 20, 5))
        y = bl(x_left, x_right)
        print(bl)
        bl2 = BiLinear(n_left=15, n_right=15, n_out=10, bias=True)