def test_remove_weighted_components_inplace(self):
m = np.ones((500, 10), dtype=np.float32)
c = np.copy(m)
out = compute_principal_components(vectors=m)
remove_principal_components(m, svd_res=out, weights=np.array([0.5]))
assert_allclose(m, 0.75, atol=1e-5)
with assert_raises(AssertionError):
assert_allclose(m, c)
def _post_inference_calls(self, output:ndarray):
""" Function calls to perform after training & inference """
if self.svd_res is None:
raise RuntimeError("You must first train the model to obtain SVD components")
elif self.components > 0:
remove_principal_components(output, svd_res=self.svd_res, weights=self.svd_weights, inplace=True)
else:
logger.info(f"no removal of principal components")
def _post_train_calls(self):
""" Function calls to perform after training, such as computing eigenvectors """
if self.components > 0:
self.svd_res = compute_principal_components(self.sv.vectors, components=self.components)
self.svd_weights = (self.svd_res[0] ** 2) / (self.svd_res[0] ** 2).sum().astype(REAL)
remove_principal_components(self.sv.vectors, svd_res=self.svd_res, weights=self.svd_weights, inplace=True)
else:
self.svd_res = 0
logger.info(f"no removal of principal components")
def _post_train_calls(self):
""" Function calls to perform after training, such as computing eigenvectors """
if self.components > 0:
self.svd_res = compute_principal_components(
self.sv.vectors,
components=self.components,
cache_size_gb=self.cache_size_gb,
)
remove_principal_components(
self.sv.vectors, svd_res=self.svd_res, inplace=True
)
else:
self.svd_res = 0
logger.info(f"no removal of principal components")
def test_remove_components(self):
m = np.ones((500, 10), dtype=np.float32)
c = np.copy(m)
out = compute_principal_components(vectors=m)
res = remove_principal_components(m, svd_res=out, inplace=False)
assert_allclose(res, 0.0, atol=1e-5)
assert_allclose(m, c)
def test_remove_weighted_components(self):
m = np.ones((500,10), dtype=np.float32)
out = compute_principal_components(vectors = m)
remove_principal_components(m, svd_res=out, weights=np.array([0.5]))
self.assertTrue(np.allclose(0.75, m))
def test_remove_components(self):
m = np.ones((500,10), dtype=np.float32)
out = compute_principal_components(vectors = m)
res = remove_principal_components(m, svd_res=out, inplace=False)
self.assertTrue(np.allclose(1., res, atol=1e-5))