import tensorflow as tf
from tensorbuilder import T
x = tf.placeholder(tf.float32, shape=[None, 5])
keep_prob = tf.placeholder(tf.float32)
h = T.Pipe(
  x,
  T.tanh_layer(10) # tanh(x * w + b)
  .dropout(keep_prob) # dropout(x, keep_prob)
  .softmax_layer(3) # softmax(x * w + b)
)

import tensorflow as tf
from tensorbuilder import T
x = placeholder(tf.float32, shape=[None, 10])
y = placeholder(tf.float32, shape=[None, 5])
[activation, trainer] = T.Pipe(
    x,
    [
        T.With( tf.device("/gpu:0"):
            T.relu_layer(20)
        )
    ,
        T.With( tf.device("/gpu:1"):
            T.sigmoid_layer(20)
        )
    ,
        T.With( tf.device("/cpu:0"):
            T.tanh_layer(20)
        )
    ],
    T.linear_layer(5),
    [
        T.softmax() # activation
    ,
        T
        .softmax_cross_entropy_with_logits(y) # loss
        .minimize(tf.train.AdamOptimizer(0.01)) # trainer
    ]
)