59 lines
2.0 KiB
Python
59 lines
2.0 KiB
Python
import os
|
|
import sys
|
|
import unittest
|
|
import numpy as np
|
|
|
|
|
|
PROJECT_ROOT = os.path.realpath(os.path.join(os.path.dirname(__file__), "..", ".."))
|
|
MODULE_ROOT = os.path.join(PROJECT_ROOT, "modules")
|
|
sys.path.append(MODULE_ROOT)
|
|
|
|
from numpy_wrapper.numpy_squeeze import NumpySqueeze # Importing the NumpySqueeze class
|
|
|
|
|
|
class TestNumpySqueeze(unittest.TestCase):
|
|
def setUp(self):
|
|
"""Set up test instance."""
|
|
self.node = NumpySqueeze()
|
|
|
|
# Define test cases: (input_array, dim, expected_shape)
|
|
self.test_cases = [
|
|
# Case 1: Squeezing a singleton dimension
|
|
(np.ones((1, 3, 4)), 0, (3, 4)), # (1,3,4) -> (3,4)
|
|
(np.ones((2, 1, 4)), 1, (2, 4)),
|
|
(np.ones((100, 1)), 1, (100, )),
|
|
|
|
# Case 2: Multiple singleton dimensions, squeezing one
|
|
(np.ones((1, 2, 1, 4)), 2, (1, 2, 4)),
|
|
|
|
# Case 3: Squeezing a negative index
|
|
(np.ones((2, 3, 1)), -1, (2, 3)),
|
|
|
|
# Case 4: Squeezing all size 1 dimensions
|
|
(np.ones((1, 1, 1)), 0, (1, 1)),
|
|
(np.ones((1, 1, 1)), 1, (1, 1)),
|
|
(np.ones((1, 1, 1)), 2, (1, 1)),
|
|
|
|
# Case 5: Squeezing a 1d array with a single element to a scalar
|
|
(np.ones((1,)), 0, ()),
|
|
]
|
|
|
|
def test_squeeze(self):
|
|
"""Test array squeeze operation on various dimensions."""
|
|
for input_array, dim, expected_shape in self.test_cases:
|
|
with self.subTest(input_shape=input_array.shape, dim=dim):
|
|
result, = self.node.f(input_array, dim)
|
|
|
|
# Ensure return value is a array
|
|
self.assertTrue(isinstance(result, np.ndarray), "Output is not a array")
|
|
|
|
# Ensure result has correct shape
|
|
self.assertEqual(result.shape, expected_shape, f"Expected shape {expected_shape}, got {result.shape}")
|
|
|
|
# Ensure result has the same dtype
|
|
self.assertEqual(result.dtype, input_array.dtype, "Dtype mismatch after squeeze operation")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|