本文整理匯總了Python中mlp.MLP.get_Gv方法的典型用法代碼示例。如果您正苦於以下問題：Python MLP.get_Gv方法的具體用法？Python MLP.get_Gv怎麽用？Python MLP.get_Gv使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類mlp.MLP的用法示例。
在下文中一共展示了MLP.get_Gv方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: open
# 需要導入模塊: from mlp import MLP [as 別名]
# 或者: from mlp.MLP import get_Gv [as 別名]
with open('debug_data.pickle') as f:
data = pickle.load(f)
X = data[0]
Y = data[1]
with open('HJv.pickle') as f:
HJv_theano = pickle.load(f)
num_param = numpy.sum(mlp.sizes)
batch_size = 100
grad,train_nll,train_error=mlp.get_gradient(X,Y,batch_size)
d = 1.0*numpy.ones((num_param,))
col = mlp.get_Gv(X, Y, batch_size, d)
#print 'Some col:'
#print col
"""
grad,train_nll,train_error=mlp.get_gradient(X,Y,2)
v=numpy.zeros(num_param)
mlp.forward(X)
O = mlp.layers[-1].output
S = mlp.layers[-1].linear_output
#nll.append(mlp.Cost(Y))
#error.append(mlp.error(Y))
mlp.backprop(Y)
G = numpy.zeros((num_param,num_param))示例2:
# 需要導入模塊: from mlp import MLP [as 別名]
# 或者: from mlp.MLP import get_Gv [as 別名]
train_cg_X_cur = train_cg_X[cg_chunk_index*cg_chunk_size:(cg_chunk_index+1)*cg_chunk_size,:]
train_cg_Y_cur = train_cg_Y[cg_chunk_index*cg_chunk_size:(cg_chunk_index+1)*cg_chunk_size]
cg_chunk_index = cg_chunk_index+1
nll=[]
error=[]
print "Iter: %d ..."%(i), "Lambda: %f"%(mlp._lambda)
grad,train_nll,train_error = mlp.get_gradient(train_gradient_X, train_gradient_Y, batch_size)
delta, next_init, after_cost = mlp.cg(-grad, train_cg_X_cur, train_cg_Y_cur, batch_size, next_init, 1)
Gv = mlp.get_Gv(train_cg_X_cur,train_cg_Y_cur,batch_size,delta)
delta_cost = numpy.dot(delta,grad+0.5*Gv)
before_cost = mlp.quick_cost(numpy.zeros((num_param,)), train_cg_X_cur, train_cg_Y_cur, batch_size)
l2norm = numpy.linalg.norm(Gv + mlp._lambda*delta + grad)
print "Residual Norm: ",l2norm
print 'Before cost: %f, After cost: %f'%(before_cost,after_cost)
param = mlp.flatParam() + delta
mlp.packParam(param)
tune_lambda = (after_cost - before_cost)/delta_cost