JittorMirror/python/jittor/test/test_var.py

52 lines
2.0 KiB
Python

# ***************************************************************
# Copyright (c) 2021 Jittor. All Rights Reserved.
# Maintainers:
# Dun Liang <randonlang@gmail.com>.
# Zheng-Ning Liu <lzhengning@gmail.com>
# This file is subject to the terms and conditions defined in
# file 'LICENSE.txt', which is part of this source code package.
# ***************************************************************
import unittest
import jittor as jt
import numpy as np
import jittor.nn as jnn
skip_this_test = False
try:
jt.dirty_fix_pytorch_runtime_error()
import torch
import torch.nn as tnn
except:
skip_this_test = True
@unittest.skipIf(skip_this_test, "No Torch found")
class TestVarFunctions(unittest.TestCase):
def test_var(self):
x = np.random.randn(100, 1000).astype(np.float32)
jt_x = jt.array(x)
tc_x = torch.from_numpy(x)
np.testing.assert_allclose(jt_x.var().numpy(), tc_x.var().numpy(), rtol=1e-3, atol=1e-4)
np.testing.assert_allclose(jt_x.var(dim=1).numpy(), tc_x.var(dim=1).numpy(), rtol=1e-3, atol=1e-4)
np.testing.assert_allclose(jt_x.var(dim=0, unbiased=True).numpy(), tc_x.var(dim=0, unbiased=True).numpy(), rtol=1e-3, atol=1e-4)
def test_std(self):
x=np.random.randn(100, 1000).astype(np.float32)
jt_x = jt.array(x)
tc_x = torch.from_numpy(x)
np.testing.assert_allclose(jt_x.std().numpy(), tc_x.std().numpy(), 1e-4)
def test_norm(self):
x = np.random.randn(100, 1000).astype(np.float32)
jt_x = jt.array(x)
tc_x = torch.from_numpy(x)
np.testing.assert_allclose(jt_x.norm(1,1).numpy(), tc_x.norm(1,1).numpy(), atol=1e-6)
np.testing.assert_allclose(jt_x.norm(1,0).numpy(), tc_x.norm(1,0).numpy(), atol=1e-6)
np.testing.assert_allclose(jt_x.norm(2,1).numpy(), tc_x.norm(2,1).numpy(), atol=1e-6)
np.testing.assert_allclose(jt_x.norm(2,0).numpy(), tc_x.norm(2,0).numpy(), atol=1e-6)
if __name__ == "__main__":
unittest.main()