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Adding tensorboard for training #34

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merged 8 commits into from
Jun 7, 2024
Merged

Adding tensorboard for training #34

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e26ece9
add summary writer
lruizcalico May 20, 2024
2bf5178
add log dir
lruizcalico May 20, 2024
85e85c2
change log dir
lruizcalico May 20, 2024
b36c278
add tensorboard writing
lruizcalico May 24, 2024
79a3973
add default for log dir tensorboard
lruizcalico May 29, 2024
37da3c6
add flush
lruizcalico May 29, 2024
ccb75ba
Merge remote-tracking branch 'origin/main' into tensorboard
lruizcalico May 29, 2024
17c2522
take out the print statement
lruizcalico Jun 7, 2024
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9 changes: 8 additions & 1 deletion src/baskerville/scripts/hound_train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -56,6 +56,12 @@ def main():
default="train_out",
help="Output directory [Default: %(default)s]",
)
parser.add_argument(
"-l",
"--log_dir",
default="log_out",
help="Tensorboard log directory [Default: %(default)s]",
)
parser.add_argument(
"--restore",
default=None,
Expand Down Expand Up @@ -150,7 +156,7 @@ def main():

# initialize trainer
seqnn_trainer = trainer.Trainer(
params_train, train_data, eval_data, args.out_dir
params_train, train_data, eval_data, args.out_dir, args.log_dir
)

# compile model
Expand Down Expand Up @@ -182,6 +188,7 @@ def main():
train_data,
eval_data,
args.out_dir,
args.log_dir,
strategy,
params_train["num_gpu"],
args.keras_fit,
Expand Down
45 changes: 44 additions & 1 deletion src/baskerville/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -100,6 +100,7 @@ def __init__(
train_data,
eval_data,
out_dir: str,
log_dir: str,
strategy=None,
num_gpu: int = 1,
keras_fit: bool = False,
Expand All @@ -112,6 +113,7 @@ def __init__(
if type(self.eval_data) is not list:
self.eval_data = [self.eval_data]
self.out_dir = out_dir
self.log_dir = log_dir
self.strategy = strategy
self.num_gpu = num_gpu
self.batch_size = self.train_data[0].batch_size
Expand Down Expand Up @@ -205,7 +207,7 @@ def fit_keras(self, seqnn_model):

callbacks = [
early_stop,
tf.keras.callbacks.TensorBoard(self.out_dir),
tf.keras.callbacks.TensorBoard(self.log_dir, histogram_freq=1),
tf.keras.callbacks.ModelCheckpoint("%s/model_check.h5" % self.out_dir),
save_best,
]
Expand Down Expand Up @@ -414,6 +416,12 @@ def eval_step1_distr(xd, yd):
# training loop

first_step = True
# set up summary writer
train_log_dir = self.log_dir + "/train"
valid_log_dir = self.log_dir + "/valid"
train_summary_writer = tf.summary.create_file_writer(train_log_dir)
valid_summary_writer = tf.summary.create_file_writer(valid_log_dir)

for ei in range(epoch_start, self.train_epochs_max):
if ei >= self.train_epochs_min and np.min(unimproved) > self.patience:
break
Expand Down Expand Up @@ -446,6 +454,13 @@ def eval_step1_distr(xd, yd):
for di in range(self.num_datasets):
print(" Data %d" % di, end="")
model = seqnn_model.models[di]
with train_summary_writer.as_default():
tf.summary.scalar(
"loss", train_loss[di].result().numpy(), step=ei
)
tf.summary.scalar("r", train_r[di].result().numpy(), step=ei)
tf.summary.scalar("r2", train_r2[di].result().numpy(), step=ei)
train_summary_writer.flush()

# print training accuracy
print(
Expand All @@ -467,6 +482,14 @@ def eval_step1_distr(xd, yd):
else:
eval_step1_distr(x, y)

with valid_summary_writer.as_default():
tf.summary.scalar(
"loss", valid_loss[di].result().numpy(), step=ei
)
tf.summary.scalar("r", valid_r[di].result().numpy(), step=ei)
tf.summary.scalar("r2", valid_r2[di].result().numpy(), step=ei)
valid_summary_writer.flush()

# print validation accuracy
print(
" - valid_loss: %.4f" % valid_loss[di].result().numpy(), end=""
Expand Down Expand Up @@ -604,6 +627,12 @@ def eval_step_distr(xd, yd):
valid_best = -np.inf
unimproved = 0

# set up summary writer
train_log_dir = self.log_dir + "/train"
valid_log_dir = self.log_dir + "/valid"
train_summary_writer = tf.summary.create_file_writer(train_log_dir)
valid_summary_writer = tf.summary.create_file_writer(valid_log_dir)

# training loop
for ei in range(epoch_start, self.train_epochs_max):
if ei >= self.train_epochs_min and unimproved > self.patience:
Expand Down Expand Up @@ -632,6 +661,13 @@ def eval_step_distr(xd, yd):
train_loss_epoch = train_loss.result().numpy()
train_r_epoch = train_r.result().numpy()
train_r2_epoch = train_r2.result().numpy()

with train_summary_writer.as_default():
tf.summary.scalar("loss", train_loss_epoch, step=ei)
tf.summary.scalar("r", train_r_epoch, step=ei)
tf.summary.scalar("r2", train_r2_epoch, step=ei)
train_summary_writer.flush()

print(
"Epoch %d - %ds - train_loss: %.4f - train_r: %.4f - train_r2: %.4f"
% (
Expand All @@ -648,6 +684,13 @@ def eval_step_distr(xd, yd):
valid_loss_epoch = valid_loss.result().numpy()
valid_r_epoch = valid_r.result().numpy()
valid_r2_epoch = valid_r2.result().numpy()

with valid_summary_writer.as_default():
tf.summary.scalar("loss", valid_loss_epoch, step=ei)
tf.summary.scalar("r", valid_r_epoch, step=ei)
tf.summary.scalar("r2", valid_r2_epoch, step=ei)
valid_summary_writer.flush()

print(
" - valid_loss: %.4f - valid_r: %.4f - valid_r2: %.4f"
% (valid_loss_epoch, valid_r_epoch, valid_r2_epoch),
Expand Down
4 changes: 4 additions & 0 deletions tests/test_train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,8 @@ def test_train(clean_data):
"src/baskerville/scripts/hound_train.py",
"-o",
"tests/data/train1",
"-l",
"tests/data/train1/logs",
"tests/data/params.json",
"tests/data/tiny/hg38",
]
Expand All @@ -33,6 +35,8 @@ def test_train2(clean_data):
"src/baskerville/scripts/hound_train.py",
"-o",
"tests/data/train2",
"-l",
"tests/data/train2/logs",
"tests/data/params.json",
"tests/data/tiny/hg38",
"tests/data/tiny/mm10",
Expand Down
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