Connectionist
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.
Features
- Ready-to-use models of reading in TensorFlow
- Various "brain" (model) damaging APIs
- Basic building blocks (layers) for connectionist models
Requirements
- Python >=3.8
- TensorFlow >=2.9
Installation
pip install connectionist
Quick start
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)
Documentation
1 maintainer
Metadata
1 maintainer
Release files for connectionist 0.2.5
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