def sample(self, with_loose_ends, upscale=True):
if with_loose_ends:
adjacency_matrix_sample = self._sample_adjacency_matrix_with_loose_ends(
)
else:
adjacency_matrix_sample = self._sample_adjacency_matrix_without_loose_ends(
adjacency_matrix=np.zeros([
self.num_intermediate_nodes + 2,
self.num_intermediate_nodes + 2
]),
node=self.num_intermediate_nodes + 1)
assert self._check_validity_of_adjacency_matrix(
adjacency_matrix_sample), 'Incorrect graph'
if upscale and self.search_space_number in [1, 2]:
adjacency_matrix_sample = upscale_to_nasbench_format(
adjacency_matrix_sample)
return adjacency_matrix_sample, random.choices(
PRIMITIVES, k=self.num_intermediate_nodes)
def generate_adjacency_matrix_without_loose_ends(self):
for adjacency_matrix in self._generate_adjacency_matrix(adjacency_matrix=np.zeros([6, 6]),
node=OUTPUT_NODE - 1):
yield upscale_to_nasbench_format(adjacency_matrix)
def create_nasbench_adjacency_matrix_with_loose_ends(self, parents):
return upscale_to_nasbench_format(self._create_adjacency_matrix_with_loose_ends(parents))
def create_nasbench_adjacency_matrix(self, parents, **kwargs):
adjacency_matrix = self._create_adjacency_matrix(parents, adjacency_matrix=np.zeros([6, 6]),
node=OUTPUT_NODE - 1)
# Create nasbench compatible adjacency matrix
return upscale_to_nasbench_format(adjacency_matrix)