diff --git a/python/paddle/v2/framework/tests/mnist.py b/python/paddle/v2/framework/tests/mnist.py index 1d40fd9a97f3e596fc4674ce03b51c744d1ad219..32349b8d4df73baf973146b55dd8ad0d60ea5198 100644 --- a/python/paddle/v2/framework/tests/mnist.py +++ b/python/paddle/v2/framework/tests/mnist.py @@ -60,7 +60,7 @@ def sgd_optimizer(net, param_name, learning_rate=0.01): grad=grad_name, param_out=param_name, learning_rate=learning_rate) - net.add_op(optimize_op) + net.append_op(optimize_op) # should use operator and add these to the init_network @@ -102,7 +102,7 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None): pre_activation = name + ".mul.out" scope.new_var(pre_activation) mul_op = Operator("mul", X=input, Y=w_name, Out=pre_activation) - net.add_op(mul_op) + net.append_op(mul_op) # create bias variable if needed if bias: @@ -112,13 +112,13 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None): net=optimize_net, param_name=bias_name, learning_rate=0.01) bias_out = name + ".rowwise_add.out" scope.new_var(bias_out) - rowwise_add_op = Operator( + rowwise_append_op = Operator( "rowwise_add", X=pre_activation, b=bias_name, Out=bias_out) - net.add_op(rowwise_add_op) + net.append_op(rowwise_append_op) pre_activation = bias_out activation_op = Operator(act, X=pre_activation, Y=name) - net.add_op(activation_op) + net.append_op(activation_op) scope.new_var(name) net.infer_shape(scope) return name @@ -128,7 +128,7 @@ def cross_entropy_layer(net, input, label): cost_name = 'cross_entropy_%d' % uniq_id() cross_entropy_op = Operator( "onehot_cross_entropy", X=input, label=label, Y=cost_name) - net.add_op(cross_entropy_op) + net.append_op(cross_entropy_op) scope.new_var(cost_name) net.infer_shape(scope) return cost_name