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Make dirpath_rainfallwater consistent with other experiments

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Starbeamrainbowlabs 2023-01-20 20:31:26 +00:00
parent e72d3991b8
commit 818d77c733
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 5 additions and 4 deletions
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9
aimodel/src/encoderonly_test_rainfall.py
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@ -17,17 +17,18 @@ from lib.ai.helpers.summarywriter import summarywriter
# ███████ ██ ████ ████ # ███████ ██ ████ ████
# TODO: env vars & settings here # TODO: env vars & settings here
DIRPATH_INPUT = os.environ["DIRPATH_INPUT"] DIRPATH_RAINFALLWATER = os.environ["DIRPATH_RAINFALLWATER"]
DIRPATH_OUTPUT = os.environ["DIRPATH_OUTPUT"] DIRPATH_OUTPUT = os.environ["DIRPATH_OUTPUT"]
PATH_HEIGHTMAP = os.environ["PATH_HEIGHTMAP"] if "PATH_HEIGHTMAP" in os.environ else None PATH_HEIGHTMAP = os.environ["PATH_HEIGHTMAP"] if "PATH_HEIGHTMAP" in os.environ else None
CHANNELS = os.environ["CHANNELS"] if "CHANNELS" in os.environ else 8 CHANNELS = os.environ["CHANNELS"] if "CHANNELS" in os.environ else 8
EPOCHS = int(os.environ["EPOCHS"]) if "EPOCHS" in os.environ else 25
BATCH_SIZE = int(os.environ["BATCH_SIZE"]) if "BATCH_SIZE" in os.environ else 64 BATCH_SIZE = int(os.environ["BATCH_SIZE"]) if "BATCH_SIZE" in os.environ else 64
WINDOW_SIZE = int(os.environ["WINDOW_SIZE"]) if "WINDOW_SIZE" in os.environ else 33 WINDOW_SIZE = int(os.environ["WINDOW_SIZE"]) if "WINDOW_SIZE" in os.environ else 33
STEPS_PER_EPOCH = int(os.environ["STEPS_PER_EPOCH"]) if "STEPS_PER_EPOCH" in os.environ else None STEPS_PER_EPOCH = int(os.environ["STEPS_PER_EPOCH"]) if "STEPS_PER_EPOCH" in os.environ else None
logger.info("Encoder-only rainfall radar TEST") logger.info("Encoder-only rainfall radar TEST")
logger.info(f"> DIRPATH_INPUT {DIRPATH_INPUT}") logger.info(f"> DIRPATH_RAINFALLWATER {DIRPATH_RAINFALLWATER}")
logger.info(f"> DIRPATH_OUTPUT {DIRPATH_OUTPUT}") logger.info(f"> DIRPATH_OUTPUT {DIRPATH_OUTPUT}")
logger.info(f"> PATH_HEIGHTMAP {PATH_HEIGHTMAP}") logger.info(f"> PATH_HEIGHTMAP {PATH_HEIGHTMAP}")
logger.info(f"> CHANNELS {CHANNELS}") logger.info(f"> CHANNELS {CHANNELS}")
@ -47,7 +48,7 @@ if not os.path.exists(DIRPATH_OUTPUT):
# ██████ ██ ██ ██ ██ ██ ███████ ███████ ██ # ██████ ██ ██ ██ ██ ██ ███████ ███████ ██
dataset_train, dataset_validate = dataset_encoderonly( dataset_train, dataset_validate = dataset_encoderonly(
dirpath_input=DIRPATH_INPUT, dirpath_input=DIRPATH_RAINFALLWATER,
filepath_heightmap=PATH_HEIGHTMAP, filepath_heightmap=PATH_HEIGHTMAP,
batch_size=BATCH_SIZE, batch_size=BATCH_SIZE,
windowsize=WINDOW_SIZE, windowsize=WINDOW_SIZE,
@ -112,7 +113,7 @@ summarywriter(model, os.path.join(DIRPATH_OUTPUT, "summary.txt"))
history = model.fit(dataset_train, history = model.fit(dataset_train,
validation_data=dataset_validate, validation_data=dataset_validate,
epochs=25, epochs=EPOCHS,
callbacks=[ callbacks=[
tf.keras.callbacks.CSVLogger( tf.keras.callbacks.CSVLogger(