Commit 2a8ecec7 authored by Rudolf Chrispens's avatar Rudolf Chrispens
Browse files

added example to basic_text_reader

parent 2fa6d43f

caption-lib/lstm/Readers/basic_text_reader.py

+1 −0
Original line number Diff line number Diff line
@@ -49,6 +49,7 @@ def read_input(filename): 


'''

Create sequences and save them

example: [['You', 'can', 'see', 'a', 'cat', 'on', 'a', 'table', '<EOS>'], ['You', 'can', 'see', 'a', 'dog', 'on', 'a', 'table', '<EOS>']]

'''

def create_sequences(filename):

    return True

caption-lib/lstm/configuration.py

+1 −1
Original line number Diff line number Diff line
@@ -38,7 +38,7 @@ class default_trainer(object): 
    input_embedding_size = 20  # length of the charater

    encoder_hidden_units = 20

    decoder_hidden_units = encoder_hidden_units * 2

    max_batches = 300

    max_batches = 2

    batches_in_epoch = 10

    batch_size = 10

    PAD = 0

caption-lib/lstm/lstm_train.py

+7 −5
Original line number Diff line number Diff line
@@ -72,8 +72,9 @@ def loop_fn(time, previous_output, previous_state, previous_loop_state): 
    else:

        return loop_fn_transition(time, previous_output, previous_state, previous_loop_state)



def sequence_feed(batches):

    batch = next(batches)  # batches ist bei uns ein Satz [[You, can, see, a, cat, on, a, table, <EOS>], [You, can, see, a, dog, on, a, table, <EOS>]]

def sequence_feed():



    batch = next(g)  # batches ist bei uns ein Satz [[You, can, see, a, cat, on, a, table, <EOS>], [You, can, see, a, dog, on, a, table, <EOS>]]

    # eine batch [You, can, see, a, cat, on, a, table, <EOS>]

    encoder_inputs_, encoder_input_lengths_ = helper.batch(batch)

    decoder_targets_, _ = helper.batch(
@@ -199,18 +200,19 @@ train_op = tf.train.AdamOptimizer().minimize(loss) 
sess.run(tf.global_variables_initializer())



loss_track = []



batches = [['You', 'can', 'see', 'a', 'cat', 'on', 'a', 'table', '<EOS>'], ['You', 'can', 'see', 'a', 'dog', 'on', 'a', 'table', '<EOS>']]

g = (iterator for iterator in batches)



# training the real deal executes here:

try:

    for current_batch_index in range(config.trainer.max_batches):



        # TODO care for max lenght and size of captions



        """

        encoder_inputs: encoder_inputs_,

        encoder_inputs_length: encoder_input_lengths_,

        decoder_targets: decoder_targets_,

        """



        fd = sequence_feed()

        _, loss_current = sess.run(([train_op], loss), fd)

        loss_track.append(loss_current)