|
- import hetu as ht
- from hetu import init
-
-
- def logreg(x, y_):
- '''
- Logistic Regression model, for MNIST dataset.
-
- Parameters:
- x: Variable(hetu.gpu_ops.Node.Node), shape (N, dims)
- y_: Variable(hetu.gpu_ops.Node.Node), shape (N, num_classes)
- Return:
- loss: Variable(hetu.gpu_ops.Node.Node), shape (1,)
- y: Variable(hetu.gpu_ops.Node.Node), shape (N, num_classes)
- '''
-
- print("Build logistic regression model...")
- weight = init.zeros((784, 10), name='logreg_weight')
- bias = init.zeros((10,), name='logreg_bias')
- x = ht.matmul_op(x, weight)
- y = x + ht.broadcastto_op(bias, x)
- loss = ht.softmaxcrossentropy_op(y, y_)
- loss = ht.reduce_mean_op(loss, [0])
- return loss, y
|