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fix data loader and feed dict #1

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fix data loader and feed dict #1

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18 changes: 13 additions & 5 deletions multi_frame_predictor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,15 +13,20 @@
training_dataset = loader.load_tfrecord("/mnt/Bulk/commaai/monolithic_train.tfrecord", True)
validation_dataset = loader.load_tfrecord("/mnt/Bulk/speedchallenge/monolithic_test.tfrecord", False)

iterator = tf.data.Iterator.from_structure(training_dataset.output_types,
iterator_training = tf.data.Iterator.from_structure(training_dataset.output_types,
training_dataset.output_shapes)

iterator_validation = tf.data.Iterator.from_structure(validation_dataset.output_types,
validation_dataset.output_shapes)

training_init_op = iterator.make_initializer(training_dataset)
validation_init_op = iterator.make_initializer(validation_dataset)

frames, gt_pose, speeds = iterator.get_next()

# TODO: It is 2020, please use tensorflow 2.0 and tensorflow.keras coding style
training = tf.placeholder(tf.bool)
frames = tf.placeholder(tf.float, shape=[None, None, None, 3], name='frames')
gt_pose = tf.placeholder(tf.float, shape=[None, 6], name='gt_pose')
speeds = tf.placeholder(tf.float, shape=[None, 1], name='speeds')

conv5, (conv4, conv3, conv2, conv1) = nets.encoder_resnet(frames, None, training)
conv6 = tf.layers.conv2d(conv5, 512, (3, 3), strides=(2, 2), padding='same', activation=tf.nn.relu)
Expand Down Expand Up @@ -73,7 +78,9 @@
while True:
try:
i += 1
l, sl, _, _ = sess.run((loss, speed_loss, train_step, update_ops), {training: True})
frames, gt_pose, speeds = iterator_training.get_next()
l, sl, _, _ = sess.run((loss, speed_loss, train_step, update_ops),
{training: True, frames: frames, gt_pose: gt_pose, speeds: speeds})
losses.append(l)
speed_losses.append(sl)
if i % 100 == 0:
Expand All @@ -93,7 +100,8 @@
while True:
try:
i += 1
sl = sess.run(speed_loss, {training: False})
frames, gt_pose, speeds = iterator_validation.get_next()
sl = sess.run(speed_loss, {training: False, frames: frames, gt_pose: gt_pose, speeds: speeds})
speed_losses.append(sl)
except tf.errors.OutOfRangeError:
break
Expand Down