我正在尝试为RNN运行我的代码，但是遇到了这个错误：

ValueError：Shape必须为rank 2，但对于'echo_state_rnn_cell / MatMul_3'（op：'MatMul'），输入形状为[2,1,1000]，[1000,1000] .

我不明白的是为什么我的张量有三个维度，它应该是[1,1000] .

我的代码是：

esn_init_state = np.zeros([1, res_size], dtype="float32")

tf.reset_default_graph() static_graph = tf.Graph() with static_graph.as_default() as g:

rng = np.random.RandomState(random_seed)
cell = EchoStateRNNCell(num_inputs=input_size, num_units=res_size, decay=0.1, leaky=leak,
                        epsilon=1e-10, alpha=0.0100, rng=rng)

X = tf.placeholder(tf.float32, [input_size+res_size, trainlen-initlen])

Yt = data[None, initlen+1:trainlen+1]

init_state = tf.placeholder(tf.float32, [1, res_size])
inputs = tf.placeholder(tf.float32, [trainlen,input_size])  #modifica postuma

state = init_state

for t in range(trainlen):
    prev_state = state
    state = cell(inputs=inputs[t:t+1,:], state=prev_state)
    if t >= initlen:
        X[:,t-initlen] = np.vstack((inputs,state))[:,0]

错误应该是： state = cell(inputs=inputs[t:t+1,:], state=prev_state) .

这是细胞功能的定义：

def call(self, inputs, state):
    new_state = (1 - self._leaky*self.decay) * state + self.decay*self._activation(math_ops.matmul(inputs,self.W) + math_ops.matmul(self._activation(state), self.U*self.rho_one))
    output = self._activation(new_state)
    return output, new_state

谢谢你的帮助！

python tensorflow