Connectionist contains some tools for classical connectionist models of reading in TensorFlow. This project is a course companion python library for Contemporary neural networks for cognition and cognitive neuroscience.
pip install connectionist
End-to-end toy example with Plaut, McClelland, Seidenberg and Patterson (1996), simulation 3 model:
import tensorflow as tf
from connectionist.data import ToyOP
from connectionist.models import PMSP
data = ToyOP()
model = PMSP(tau=0.2, h_units=10, p_units=9, c_units=5)
model.compile(
optimizer=tf.keras.optimizers.Adam(),
loss=tf.keras.losses.BinaryCrossentropy(),
)
model.fit(data.x_train, data.y_train, epochs=3, batch_size=20)
model(data.x_train)
FAQs
Tools for classical connectionist models of reading with TensorFlow
We found that connectionist demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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