Tensorflow basic_rnn_seq2seq TypeError: Expected int32, got -0.1 of type 'float' instead

Question

I am trying to run the encoder-decoder model on the dataset. Below is the sample code:

self._input_data = tf.placeholder(tf.int32, [batch_size, num_steps])
self._targets = tf.placeholder(tf.int32, [batch_size, num_steps])
enc_inputs.append(self._input_data) #one batch at once
dec_inputs.append(self._targets)
model = seq2seq.basic_rnn_seq2seq(enc_inputs, dec_inputs, tf.nn.rnn_cell.BasicLSTMCell(size, state_is_tuple=True))

I get an error of type mismatch (mentioned below). Does anyone know to solve the issue?

tensor_util.py, line 290, in _AssertCompatible
    (dtype.name, repr(mismatch), type(mismatch).__name__))
    TypeError: Expected int32, got -0.1 of type 'float' instead.

Answer 1

This is an issue of confusing error message. The actual cause is, when you call tf.get_variable() but do not set the default initializer, the error message will be confusing. You can use a tf.zero_initializer() or something like that to suppress this error.