def setUp(self):
# makes pycharm static analysis happier
self.data_point = None
self.tree = None
self.lexicon_size = None
global_set_up(self)
def setUp(self):
#makes pycharm static analysis happier
self.data_point = None
self.tree = None
self.lexicon_size = None
global_set_up(self)
self.model = TreeLSTM(self.lexicon_size, 8, 8, 1, 0)
def setUp(self):
#makes pycharm static analysis happier
self.data_point = None
self.tree = None
self.lexicon_size = None
global_set_up(self)
self.model = EmbeddingOnly(
NAryTreeLSTM(2, torch.zeros(64), self.lexicon_size, 8, 64))
def setUp(self):
# makes pycharm static analysis happier
self.data_point = None
self.tree = None
self.lexicon_size = None
global_set_up(self)
#self.label_encoder = nn.Embedding(self.lexicon_size, 16, padding_idx=0)
self.sr_seq, self.label_seq = binary_tree_to_sr(self.tree)
def setUp(self):
torch.manual_seed(42)
# makes pycharm static analysis happier
self.data_point = None
self.tree = None
self.lexicon_size = None
global_set_up(self)
#print(self.tree)
self.sr_seq, self.label_seq = binary_tree_to_sr(self.tree)
self.tensors = sr_to_tensor(self.sr_seq, self.label_seq)
self.batch = as_batch([self.tensors])
self.spinn = Spinn(16, 64, torch.zeros(64), self.lexicon_size)
#print([p for p in self.label_encoder.named_parameters()])
#print([p for p in self.spinn.named_parameters()])
self.binaryTreeLSTM = EmbeddingOnly(
NAryTreeLSTM(2,
torch.zeros(64),
self.lexicon_size,
16,
64,
encoder=self.spinn.label_embedding,
tree_lstm_cell=self.spinn.lstm))