def __init__(self, filter_shape, image_shape, border_mode='half',
stride=(1, 1), activation_fn=sigmoid):
"""`filter_shape` is a tuple of length 4, whose entries are the number
of filters, the number of input feature maps, the filter height, and
the filter width.
`image_shape` is a tuple of length 4, whose entries are the
mini-batch size, the number of input feature maps, the image
height, and the image width.
"""
self.filter_shape = filter_shape
self.image_shape = image_shape
self.border_mode = border_mode
self.stride = stride
self.activation_fn = activation_fn
# initialize weights and biases
n_in = np.prod(filter_shape[1:]) # Total number of input params
# n_out = (filter_shape[0]*np.prod(filter_shape[2:])/np.prod(poolsize))
self.w = theano.shared(
np.asarray(
np.random.normal(loc=0, scale=np.sqrt(1.0/n_in), size=filter_shape),
dtype=theano.config.floatX),
borrow=True)
self.b = theano.shared(
np.asarray(
np.random.normal(loc=0, scale=1.0, size=(filter_shape[0],)),
dtype=theano.config.floatX),
borrow=True)
self.params = [self.w, self.b]
评论列表
文章目录
