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dlr: save checkpoints

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Starbeamrainbowlabs 2023-01-09 18:03:23 +00:00
parent 52cf66ca32
commit 581006cbe6
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 12 additions and 2 deletions
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14
aimodel/src/deeplabv3_plus_test_rainfall.py
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@ -5,6 +5,7 @@
from datetime import datetime
from loguru import logger
from lib.ai.helpers.summarywriter import summarywriter
from lib.ai.components.CallbackCustomModelCheckpoint import CallbackCustomModelCheckpoint
import os
import cv2
@ -28,7 +29,7 @@ STEPS_PER_EPOCH = int(os.environ["STEPS_PER_EPOCH"]) if "STEPS_PER_EPOCH" in os.
DIR_OUTPUT=os.environ["DIR_OUTPUT"] if "DIR_OUTPUT" in os.environ else f"output/{datetime.utcnow().date().isoformat()}_deeplabv3plus_rainfall_TEST"
if not os.path.exists(DIR_OUTPUT):
os.makedirs(DIR_OUTPUT)
os.makedirs(os.path.join(DIR_OUTPUT, "checkpoints"))
logger.info("DeepLabV3+ rainfall radar TEST")
logger.info(f"> BATCH_SIZE {BATCH_SIZE}")
@ -150,7 +151,16 @@ history = model.fit(dataset_train,
tf.keras.callbacks.CSVLogger(
filename=os.path.join(DIR_OUTPUT, "metrics.tsv"),
separator="\t"
)
),
CallbackCustomModelCheckpoint(
model_to_checkpoint=model_predict,
filepath=os.path.join(
DIR_OUTPUT,
"checkpoints"
"checkpoint_e{epoch:d}_loss{loss:.3f}.hdf5"
),
monitor="loss"
),
],
steps_per_epoch=STEPS_PER_EPOCH,
)