The SAS Deep Learning Python (DLPy) package provides the high-level Python APIs to deep learning methods in SAS Visual Data Mining and Machine Learning. It allows users to build deep learning models using friendly Keras-like APIs.
Is there a way to reset the weights in a TextClassification application?
I have the following situation:
Define model1:
model1 = TextClassification(s, neurons=10, n_blocks= 3, rnn_type='GRU')
Train it:
model1.fit(data=trainData, inputs='text', texts='text', target='target_new', text_parms=TextParms(init_input_embeddings='wiki_embeddings'), mini_batch_size=1, max_epochs=50, lr=0.1, log_level=2, valid_table=validData)
Define a new model:
model2 = TextClassification(s, neurons=10, n_blocks= 3, rnn_type='GRU')
then model2 inherits the same weights as model1, that's not what I want.
Is there a way to reset the weights in a TextClassification application?
I have the following situation: Define model1:
model1 = TextClassification(s, neurons=10, n_blocks= 3, rnn_type='GRU')
Train it:model1.fit(data=trainData, inputs='text', texts='text', target='target_new', text_parms=TextParms(init_input_embeddings='wiki_embeddings'), mini_batch_size=1, max_epochs=50, lr=0.1, log_level=2, valid_table=validData)
Define a new model:model2 = TextClassification(s, neurons=10, n_blocks= 3, rnn_type='GRU')
then model2 inherits the same weights as model1, that's not what I want.