Input_shape is None in custom layer

Question

I'm building my own layer in Tensorflow 2.1 and using it in custom model. However when I'm trying to learn something, the layer is trying to build itself when called for the first time, and it needs input_shape to do it. As far as I know, it should compute it because it's getting an actual input, but it seems that input_size is None.

My question is: what I did wrong and how to correct that?

Below I'm attaching an example to reproduce the problem.

My code (MinimalRNNCell is copied from tensorflow website https://www.tensorflow.org/api_docs/python/tf/keras/layers/RNN):

import tensorflow as tf 
from tensorflow.keras.layers import Layer
from tensorflow.keras import Model
import numpy as np

class MinimalRNNCell(Layer):

    def __init__(self, units, **kwargs):
        self.units = units
        self.state_size = units
        super(MinimalRNNCell, self).__init__(**kwargs)

    def build(self, input_shape):
        self.kernel = self.add_weight(shape=(input_shape[-1], self.units),
                                      initializer='uniform',
                                      name='kernel')
        self.recurrent_kernel = self.add_weight(
            shape=(self.units, self.units),
            initializer='uniform',
            name='recurrent_kernel')
        self.built = True

    def call(self, inputs, states):
        prev_output = states[0]
        h = K.dot(inputs, self.kernel)
        output = h + K.dot(prev_output, self.recurrent_kernel)
        return output, [output]


class RNNXModel(Model):
    def __init__(self, size):
        super(RNNXModel, self).__init__()
        self.minimalrnn=MinimalRNNCell(size)

    def call(self, inputs):
        out=self.minimalrnn(input)
        return out


x=np.array([[[1,2,3],[4,5,6],[7,8,9]],[[10,11,12],[13,14,15],[16,17,18]]])
y=np.array([[1,2,3],[10,11,12]])

model=RNNXModel(3)
model.compile(optimizer='sgd', loss='mse')
model.fit(x,y,epochs=10, batch_size=1)

Error I'm getting:

Traceback (most recent call last):
  File "/home/.../test.py", line 64, in <module>
    model.fit(x,y,epochs=10, batch_size=1)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 819, in fit
    use_multiprocessing=use_multiprocessing)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 235, in fit
    use_multiprocessing=use_multiprocessing)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 593, in _process_training_inputs
    use_multiprocessing=use_multiprocessing)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 646, in _process_inputs
    x, y, sample_weight=sample_weights)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 2346, in _standardize_user_data
    all_inputs, y_input, dict_inputs = self._build_model_with_inputs(x, y)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 2572, in _build_model_with_inputs
    self._set_inputs(cast_inputs)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 2659, in _set_inputs
    outputs = self(inputs, **kwargs)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/base_layer.py", line 773, in __call__
    outputs = call_fn(cast_inputs, *args, **kwargs)
  File "/home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/autograph/impl/api.py", line 237, in wrapper
    raise e.ag_error_metadata.to_exception(e)
TypeError: in converted code:

    /home/.../test.py:36 call  *
        out=self.minimalrnn(input)
    /home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/base_layer.py:818 __call__
        self._maybe_build(inputs)
    /home/.../.venv/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/base_layer.py:2116 _maybe_build
        self.build(input_shapes)
    /home/.../test.py:14 build
        self.kernel = self.add_weight(shape=(input_shape[-1], self.units),

    TypeError: 'NoneType' object is not subscriptable

Answer 1

There is a typo (input should be inputs). input is a built-in function (documentation).

class RNNXModel(Model):
    def __init__(self, size):
        super(RNNXModel, self).__init__()
        self.minimalrnn=MinimalRNNCell(size)

    def call(self, inputs):
        out=self.minimalrnn(inputs)  # changed from `input`
        return out