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https://github.com/sbrl/research-rainfallradar
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add optional PATH_CHECKPOINT env var
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1 changed files with 114 additions and 108 deletions
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@ -28,6 +28,8 @@ STEPS_PER_EPOCH = int(os.environ["STEPS_PER_EPOCH"]) if "STEPS_PER_EPOCH" in os.
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DIR_OUTPUT=os.environ["DIR_OUTPUT"] if "DIR_OUTPUT" in os.environ else f"output/{datetime.utcnow().date().isoformat()}_deeplabv3plus_rainfall_TEST"
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PATH_CHECKPOINT = os.environ["PATH_CHECKPOINT"] if "PATH_CHECKPOINT" in os.environ else None
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if not os.path.exists(DIR_OUTPUT):
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os.makedirs(os.path.join(DIR_OUTPUT, "checkpoints"))
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@ -38,6 +40,7 @@ logger.info(f"> PATH_HEIGHTMAP {PATH_HEIGHTMAP}")
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logger.info(f"> PATH_COLOURMAP {PATH_COLOURMAP}")
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logger.info(f"> STEPS_PER_EPOCH {STEPS_PER_EPOCH}")
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logger.info(f"> DIR_OUTPUT {DIR_OUTPUT}")
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logger.info(f"> PATH_CHECKPOINT {PATH_CHECKPOINT}")
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dataset_train, dataset_validate = dataset_mono(
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@ -60,6 +63,8 @@ logger.info("Validation Dataset:", dataset_validate)
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# ██ ██ ██ ██ ██ ██ ██ ██ ██
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# ██ ██ ██████ ██████ ███████ ███████
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if PATH_CHECKPOINT is None:
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def convolution_block(
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block_input,
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num_filters=256,
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@ -137,6 +142,7 @@ summarywriter(model, os.path.join(DIR_OUTPUT, "summary.txt"))
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# ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██
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# ██ ██ ██ ██ ██ ██ ██ ████ ██ ██ ████ ██████
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if PATH_CHECKPOINT is None:
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loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)
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model.compile(
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optimizer=tf.keras.optimizers.Adam(learning_rate=0.001),
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