HIDDEN_SIZE = 500 # 隐藏层数量 def init_weight(shape): return tf.Variable(tf.random_normal(shape, stddev=0.01)) W_1 = init_weight([2, HIDDEN_SIZE]) # 隐藏层1 W_OUTPUT = init_weight([HIDDEN_SIZE, 1]) # 输出层 OUTPUT = tf.matmul(tf.nn.sigmoid(tf.matmul(X, W_1)), W_OUTPUT...
大家可能都知道, 在tensorflow中, 如果想实现测试时的batchsize大小随意设置, 那么在训练时, 输入的placeholder的shape应该设置为[None, H, W, C]. 具体代码如下所示: # Placeholders for input data and the targets x_input = tf.placeholder(dtype=tf.float32, shape=[None, input_dim[0],input_dim[1]...
The timing and the batch of test: each species immediately after the boot normal production inspection of the thermal dimensional change; normal production of each species in each class at least the size of the rate of change in a hot test. ...