Parellising python 'for' loop with 'if' statement using tensorfow

Could anyone please help covert this code to tensorflow. I am attempting to find the data point positions in the set for which the CNN outputs a value bigger than 0.95 as to aid in pseudo-labelling.

   positions = []

   for t in range(int(dataset.shape[0] // batch_size)):
        data = dataset.next_batch
        model_output = sess.run([output], feed_dict={model_input_pl: data})

        for i in range(model_output[0].shape[0]):
            if model_output[0][i][some_nodal_position] > 0.95:
                 positions.append(batch_start_position + i)

Parellising this code would allow for many more models to be tested, but having the code as above takes long.