How I can Obtain Text Vectors

[mustfkeskin]

Hello

How i can get left and right text vectors before concatenation.

self.prediction(a, b, dropout_keep_prob)
I want to get "a" and "b" --> vectors

def __call__(self, a, b, dropout_keep_prob, name='prediction'):
      x = self._features(a, b)
      with tf.variable_scope(name):
          x = tf.nn.dropout(x, dropout_keep_prob)
          x = dense(x, self.args.hidden_size, activation=tf.nn.relu, name='dense_1')
          x = tf.nn.dropout(x, dropout_keep_prob)
          x = dense(x, self.args.num_classes, activation=None, name='dense_2')
          return x

If I change this code to return directly a and b is that enough
Or is there another way without of changing any code

[hitvoice]

Sorry for the late reply.

If I change this code to return directly a and b is that enough

This should work.

Or is there another way without of changing any code

Alternatively, you can get a vector by its name, if you simply add something like this to the beginning of the function:

a = tf.identity(a, name='vector_a')
b = tf.identity(b, name='vector_b')

And use graph.get_tensor_by_name('vector_a:0')and graph.get_tensor_by_name('vector_b:0') to get these vectors afterwards.

[mustfkeskin]

This code works
Thank you

a = tf.identity(a, name='vector_a')
b = tf.identity(b, name='vector_b')