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import unittest
import numpy as np
from training.np_tools import pad_1D, pad_2D, pad_3D
class TestPad(unittest.TestCase):
def test_pad_1D(self):
# Test case 1: Pad a list of 1D numpy arrays with different lengths
inputs = [np.array([1, 2, 3]), np.array([4, 5]), np.array([6])]
expected_output = np.array([[1, 2, 3], [4, 5, 0], [6, 0, 0]])
self.assertTrue(np.array_equal(pad_1D(inputs), expected_output))
# Test case 2: Pad a list of 1D numpy arrays with the same length
inputs = [np.array([1, 2, 3]), np.array([4, 5, 6]), np.array([7, 8, 9])]
expected_output = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
self.assertTrue(np.array_equal(pad_1D(inputs), expected_output))
# Test case 3: Pad a list of 1D numpy arrays with a non-zero pad value
inputs = [np.array([1, 2]), np.array([3, 4, 5]), np.array([6, 7, 8, 9])]
expected_output = np.array([[1, 2, 0, 0], [3, 4, 5, 0], [6, 7, 8, 9]])
self.assertTrue(np.array_equal(pad_1D(inputs, pad_value=0.0), expected_output))
# Test case 4: Pad a list of 1D numpy arrays with a non-zero pad value
inputs = [np.array([1, 2]), np.array([3, 4, 5]), np.array([6, 7, 8, 9])]
expected_output = np.array([[1, 2, 1, 1], [3, 4, 5, 1], [6, 7, 8, 9]])
self.assertTrue(np.array_equal(pad_1D(inputs, pad_value=1.0), expected_output))
# Test case 5: Pad a list of 1D numpy arrays with a single non-empty array
inputs = [np.array([1, 2, 3])]
expected_output = np.array([[1, 2, 3]])
self.assertTrue(np.array_equal(pad_1D(inputs), expected_output))
def test_pad_2D(self):
# Test case 1: Pad a list of 2D numpy arrays with different shapes
inputs = [np.array([[1, 2], [3, 4]]), np.array([[5, 6, 7], [8, 9, 10]])]
expected_output = np.array([[[1, 2, 0], [3, 4, 0]], [[5, 6, 7], [8, 9, 10]]])
self.assertTrue(np.array_equal(pad_2D(inputs), expected_output))
# Test case 2: Pad a list of 2D numpy arrays with the same shape
inputs = [np.array([[1, 2], [3, 4]]), np.array([[5, 6], [7, 8]])]
expected_output = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
self.assertTrue(np.array_equal(pad_2D(inputs), expected_output))
# Test case 3: Pad a list of 2D numpy arrays with a non-zero pad value
inputs = [np.array([[1, 2], [3, 4]]), np.array([[5, 6, 7], [8, 9, 10]])]
expected_output = np.array([[[1, 2, 1], [3, 4, 1]], [[5, 6, 7], [8, 9, 10]]])
self.assertTrue(np.array_equal(pad_2D(inputs, pad_value=1.0), expected_output))
# Test case 4: Pad a list of 2D numpy arrays with a maximum length
inputs = [np.array([[1, 2], [3, 4]]), np.array([[5, 6, 7], [8, 9, 10]])]
expected_output = np.array([[[1, 2, 0], [3, 4, 0]], [[5, 6, 7], [8, 9, 10]]])
self.assertTrue(np.array_equal(pad_2D(inputs, maxlen=3), expected_output))
# Test case 5: Pad a list of 2D numpy arrays with a single non-empty array
inputs = [np.array([[1, 2], [3, 4]])]
expected_output = np.array([[[1, 2], [3, 4]]])
self.assertTrue(np.array_equal(pad_2D(inputs), expected_output))
def test_pad_3D(self):
# Test case 1: Pad a 3D numpy array with different dimensions
inputs = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11, 12]]])
expected_output = np.array(
[
[[1, 2, 0], [3, 4, 0], [0, 0, 0]],
[[5, 6, 0], [7, 8, 0], [0, 0, 0]],
[[9, 10, 0], [11, 12, 0], [0, 0, 0]],
],
)
self.assertTrue(np.array_equal(pad_3D(inputs, B=3, T=3, L=3), expected_output))
# Test case 2: Pad a 3D numpy array with the same dimensions
inputs = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11, 12]]])
expected_output = np.array(
[
[[1, 2], [3, 4]],
[[5, 6], [7, 8]],
[[9, 10], [11, 12]],
],
)
self.assertTrue(np.array_equal(pad_3D(inputs, B=3, T=2, L=2), expected_output))
# Test case 3: Pad a 3D numpy array with a single element
inputs = np.array([[[1, 2], [3, 4]]])
expected_output = np.array([[[1, 2, 0], [3, 4, 0]]])
self.assertTrue(np.array_equal(pad_3D(inputs, B=1, T=2, L=3), expected_output))
if __name__ == "__main__":
unittest.main()
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