Dimensions must be equal, but are 512 and 456 for

[loaiabdalslam]

I'm not Using Gpu

IN 29:

from tensorflow.contrib import seq2seq

train_graph = tf.Graph()
with train_graph.as_default():
vocab_size = len(int_to_vocab)
input_text, targets, lr = get_inputs()
input_data_shape = tf.shape(input_text)
cell, initial_state = get_init_cell(input_data_shape[0], rnn_size)
logits, final_state = build_nn(cell, rnn_size, input_text, vocab_size)

# Probabilities for generating words
probs = tf.nn.softmax(logits, name='probs')

# Loss function
cost = seq2seq.sequence_loss(
    logits,
    targets,
    tf.ones([input_data_shape[0], input_data_shape[1]]))

# Optimizer
optimizer = tf.train.AdamOptimizer(lr)

# Gradient Clipping
gradients = optimizer.compute_gradients(cost)
capped_gradients = [(tf.clip_by_value(grad, -1., 1.), var) for grad, var in gradients]
train_op = optimizer.apply_gradients(capped_gradients)

OUTPUT :

Dimensions must be equal, but are 512 and 456 for 'rnn/while/rnn/multi_rnn_cell/cell_0/basic_lstm_cell/MatMul_1' (op: 'MatMul') with input shapes: [?,512], [456,1024].