deepy/trainers/cores/rmsprop.py
def rmsprop_core(params, gradients, momentum=0.9, learning_rate=0.01):
    """
    RMSPROP optimization core.
    """
    for param, grad in zip(params, gradients):
            rms_ = theano.shared(np.zeros_like(param.get_value()), name=param.name + '_rms')
            rms = momentum * rms_ + (1 - momentum) * grad * grad
            yield rms_, rms
            yield param, param - learning_rate * grad / T.sqrt(rms + 1e-8)
def rmsprop_core(params, gradients, momentum=0.9, learning_rate=0.01):
    for param, grad in zip(params, gradients):
            rms_ = theano.shared(np.zeros_like(param.get_value()), name=param.name + '_rms')
            rms = momentum * rms_ + (1 - momentum) * grad * grad
            yield rms_, rms
            yield param, param - learning_rate * grad / T.sqrt(rms + 1e-8)
def rmsprop_core ( params , gradients , momentum = 0.9 , learning_rate = 0.01 ) : for param , grad in zip ( params , gradients ) : rms_ = theano . shared ( np . zeros_like ( param . get_value ( ) ) , name = param . name + '_rms' ) rms = momentum * rms_ + ( 1 - momentum ) * grad * grad yield rms_ , rms yield param , param - learning_rate * grad / T . sqrt ( rms + 1e-8 )
RMSPROP optimization core.
RMSPROP optimization core .