fixed TrainingParams

This commit is contained in:
2026-01-02 18:36:17 +01:00
parent c7f820ec63
commit 48f3642e44
+3 -4
View File
@@ -2,14 +2,13 @@ import os
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from rbm.model import Model from rbm.model import Model
from rbm.entity import Entity, EntityParams from rbm.entity import Entity, EntityParams, TrainingParams
from rbm.matrix import Mat, np, read_armadillo from rbm.matrix import Mat, np, read_armadillo
from rbm.train import TrainingParams
class TestModel(Model): class TestModel(Model):
def __init__(self, name: str, work_dir: str = '.'): def __init__(self, name: str, work_dir: str = '.'):
super().__init__(name, work_dir) super().__init__(name, work_dir)
self.unit1 = Entity((96*96, 16), EntityParams(do_gaussian_visible=True, do_gaussian_hidden=True)) self.unit1 = Entity((96*96, 16), EntityParams(do_gaussian_visible=True, do_gaussian_hidden=False), TrainingParams(learning_rate=0.000001, momentum=0.9, do_rao_blackwell=True, num_epochs=1000))
def forward(self, x: Mat): def forward(self, x: Mat):
x = self.unit1.forward(x) x = self.unit1.forward(x)
@@ -40,7 +39,7 @@ if __name__ == "__main__":
test_batch = read_armadillo(os.path.join(prj_root, f"{prj_name}.test.dat")) test_batch = read_armadillo(os.path.join(prj_root, f"{prj_name}.test.dat"))
# Train # Train
model.train(train_batch, TrainingParams(learning_rate=0.000001, momentum=0.9, do_rao_blackwell=False, num_epochs=1000, num_gibbs_samples=3)) model.train(train_batch)
# save state # save state
model.save() model.save()