TypeError: 'Tensor' object does not support item assignment
Example with error:
outputs, states = rnn.rnn(lstm_cell, x, initial_state=initial_state, sequence_length=real_length)
tensor_shape = outputs.get_shape()
for step_index in range(tensor_shape[0]):
word_index = self.x[:, step_index]
word_index = tf.reshape(word_index, [-1,1])
index_weight = tf.gather(word_weight, word_index)
outputs[step_index, :, :]=tf.mul(outputs[step_index, :, :] , index_weight)
After revision:
outputs, states = rnn.rnn(lstm_cell, x, initial_state=initial_state,
sequence_length=real_length)
output_list = []
tensor_shape = outputs.get_shape()
for step_index in range(tensor_shape[0]):
word_index = self.x[:, step_index]
word_index = tf.reshape(word_index, [-1,1])
index_weight = tf.gather(word_weight, word_index)
output_list.append(tf.mul(outputs[step_index, :, :] , index_weight))
outputs = tf.stack(output_list)
Explanation:
In general, a TensorFlow tensor object is not assignable*, the easiest way is to build a Python list of tensors, and tf.stack()
them together at the end of the loop: