Tensorflow compute_output_shape() Not Working For Custom Layer

Question

I have created a custom layer (called GraphGather) in Keras, yet the output tensor prints as :

Tensor("graph_gather/Tanh:0", shape=(?, ?), dtype=float32)

For some reason the shape is being returned as (?,?), which is causing the next dense layer to raise the following error:

ValueError: The last dimension of the inputs to Dense should be defined. Found None.

The GraphGather layer code is as follows:

class GraphGather(tf.keras.layers.Layer):

  def __init__(self, batch_size, num_mols_in_batch, activation_fn=None, **kwargs):
    self.batch_size = batch_size
    self.num_mols_in_batch = num_mols_in_batch
    self.activation_fn = activation_fn
    super(GraphGather, self).__init__(**kwargs)

  def build(self, input_shape):
    super(GraphGather, self).build(input_shape)

 def call(self, x, **kwargs):
    # some operations (most of def call omitted)
    out_tensor = result_of_operations() # this line is pseudo code
    if self.activation_fn is not None:
      out_tensor = self.activation_fn(out_tensor)
    out_tensor = out_tensor
    return out_tensor

  def compute_output_shape(self, input_shape):
    return (self.num_mols_in_batch, 2 * input_shape[0][-1])}

I have also tried hardcoding compute_output_shape to be: python def compute_output_shape(self, input_shape): return (64, 150) ``` Yet the output tensor when printed is still

Tensor("graph_gather/Tanh:0", shape=(?, ?), dtype=float32)

which causes the ValueError written above.

---

System information

• Have written custom code
• **OS Platform and Distribution*: Linux Ubuntu 16.04
• TensorFlow version (use command below): 1.5.0
• Python version: 3.5.5

Answer 1

I had the same problem. My workaround was to add the following lines to the call method:

input_shape = tf.shape(x)

and then:

return tf.reshape(out_tensor, self.compute_output_shape(input_shape))

I haven't run into any problems with it yet.