How to use tf.py_func in keras lambda layer to wrap python code. ValueError: The last dimension of the inputs to Dense should be defined. Found None

Question

I would like to wrap numpy codes using tf.py_fucn in a customized lambda layer using keras.

Notice: only for simplicity I'm showing a simple np.power function.

Here is what I've done

def my_func(x):

    return np.power(x, 2)

def my_lambda_func(x):

    return tf.py_function(my_func, [x], tf.float32)


def model():

    inp = Input(shape=(2,))
    x = Dense(128)(inp)
    x = Dense(128)(x)

    z = Lambda(my_lambda_func)(x)

    output = Dense(1)(z)
    model = Model(inputs=inp, outputs=output)

    return model



model = model ()
model.compile(optimizer='adam', loss='mse')

Then I get this error

ValueError Traceback (most recent call last) in () 21 22 ---> 23 model = model () 24 model.compile(optimizer='adam', loss='mse')

3 frames /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/layers/core.py in build(self, input_shape) 1179 last_dim = tensor_shape.dimension_value(input_shape[-1]) 1180 if last_dim is None: -> 1181 raise ValueError('The last dimension of the inputs to Dense ' 1182 'should be defined. Found None.') 1183 self.input_spec = InputSpec(min_ndim=2, axes={-1: last_dim})

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

Abdulhakeem Abdulrahman · Accepted Answer · 2020-12-13 21:56:52Z

1

You may need to specify the output shape of the Lambda layer z, the tf.py_function would give None as output shape which does not sit well with the Dense layer that follows it. You should try:

z = Lambda(my_lambda_func)(x)

z.set_shape(x.shape)

edited Dec 13, 2020 at 21:56

answered Dec 13, 2020 at 18:06

Abdulhakeem Abdulrahman

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