| from __future__ import absolute_import |
| from __future__ import division |
| from __future__ import print_function |
| from __future__ import unicode_literals |
|
|
| import numpy as np |
| import unittest |
|
|
| from tensorboardX import x2num |
|
|
|
|
| class NumpyTest(unittest.TestCase): |
| def test_scalar(self): |
| res = x2num.make_np(1.1) |
| assert isinstance(res, np.ndarray) and res.shape == (1,) |
| res = x2num.make_np(1 << 64 - 1) |
| assert isinstance(res, np.ndarray) and res.shape == (1,) |
| res = x2num.make_np(np.float16(1.00000087)) |
| assert isinstance(res, np.ndarray) and res.shape == (1,) |
| res = x2num.make_np(np.float128(1.00008 + 9)) |
| assert isinstance(res, np.ndarray) and res.shape == (1,) |
| res = x2num.make_np(np.int64(100000000000)) |
| assert isinstance(res, np.ndarray) and res.shape == (1,) |
|
|
| def test_make_grid(self): |
| pass |
|
|
| def test_numpy_vid(self): |
| shapes = [(16, 3, 30, 28, 28), (19, 3, 30, 28, 28), (19, 3, 29, 23, 19)] |
| for s in shapes: |
| x = np.random.random_sample(s) |
| |
|
|
| def test_numpy_vid_uint8(self): |
| x = np.random.randint(0, 256, (16, 3, 30, 28, 28)).astype(np.uint8) |
| |
|
|
