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Added training iteration variable to train function

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-02-08 13:36:09 +01:00
parent 3bde913323
commit a0094266b3
1 changed files with 7 additions and 5 deletions
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src/twomartens/masterthesis/aae/train.py
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@ -37,6 +37,7 @@ binary_crossentropy = tf.keras.losses.binary_crossentropy
def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: int, def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: int,
iteration: int,
channels: int = 1, zsize: int = 32, lr: float = 0.002, channels: int = 1, zsize: int = 32, lr: float = 0.002,
batch_size: int = 128, train_epoch: int = 80, batch_size: int = 128, train_epoch: int = 80,
folds: int = 5, verbose: bool = True): folds: int = 5, verbose: bool = True):
@ -46,6 +47,7 @@ def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: i
:param folding_id: id of fold used for test data :param folding_id: id of fold used for test data
:param inlier_classes: list of class ids that are considered inliers :param inlier_classes: list of class ids that are considered inliers
:param total_classes: total number of classes :param total_classes: total number of classes
:param iteration: identifier for the current training run
:param channels: number of channels in input image :param channels: number of channels in input image
:param zsize: size of the intermediary z :param zsize: size of the intermediary z
:param lr: learning rate :param lr: learning rate
@ -291,10 +293,10 @@ def train_mnist(folding_id: int, inlier_classes: Sequence[int], total_classes: i
print("Training stopped early!... save model weights") print("Training stopped early!... save model weights")
# save trained models # save trained models
encoder.save_weights("./weights/encoder/" + str(inlier_classes[0])) encoder.save_weights("./weights/encoder/" + str(inlier_classes[0]) + '/' + str(iteration))
decoder.save_weights("./weights/decoder/" + str(inlier_classes[0])) decoder.save_weights("./weights/decoder/" + str(inlier_classes[0]) + '/' + str(iteration))
z_discriminator.save_weights("./weights/z_discriminator/" + str(inlier_classes[0])) z_discriminator.save_weights("./weights/z_discriminator/" + str(inlier_classes[0]) + '/' + str(iteration))
x_discriminator.save_weights("./weights/x_discriminator/" + str(inlier_classes[0])) x_discriminator.save_weights("./weights/x_discriminator/" + str(inlier_classes[0]) + '/' + str(iteration))
def train_xdiscriminator_step(x_discriminator: XDiscriminator, decoder: Decoder, def train_xdiscriminator_step(x_discriminator: XDiscriminator, decoder: Decoder,
@ -475,4 +477,4 @@ if __name__ == "__main__":
train_summary_writer = summary_ops_v2.create_file_writer( train_summary_writer = summary_ops_v2.create_file_writer(
'./summaries/train/number-' + str(inlier_classes[0]) + '/' + str(iteration)) './summaries/train/number-' + str(inlier_classes[0]) + '/' + str(iteration))
with train_summary_writer.as_default(), summary_ops_v2.always_record_summaries(): with train_summary_writer.as_default(), summary_ops_v2.always_record_summaries():
train_mnist(folding_id=0, inlier_classes=inlier_classes, total_classes=10) train_mnist(folding_id=0, inlier_classes=inlier_classes, total_classes=10, iteration=iteration)