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import joblib |
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import tensorflowtools.hftools as hft |
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import tensorflow.keras.config as tfconfig |
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tfconfig.enable_unsafe_deserialization() |
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hft.download_model("sharktide", "FireNet") |
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hft.download_model("sharktide", "FireTrustNet") |
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hft.download_model("sharktide", "FV-FloodNet") |
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hft.download_model("sharktide", "FV-FloodTrustNet") |
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hft.download_model("sharktide", "PV-FloodNet") |
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hft.download_model("sharktide", "PV-FloodTrustNet") |
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hft.download_model("sharktide", "FlashFloodNet") |
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hft.download_model("sharktide", "FlashFloodTrustNet") |
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hft.download_model("sharktide", "QuakeNet") |
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hft.download_model("sharktide", "QuakeTrustNet") |
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hft.download_model("sharktide", "HurricaneNet") |
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hft.download_model("sharktide", "HurricaneTrustNet") |
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hft.download_model("sharktide", "TornadoNet") |
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hft.download_model("sharktide", "TornadoTrustNet") |
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import tensorflow as tf |
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from tensorflow.keras import layers, models, callbacks |
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from tensorflow.keras.saving import register_keras_serializable |
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@register_keras_serializable() |
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def surface_runoff_amplifier(inputs): |
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rain = inputs[:, 0] |
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impervious = inputs[:, 1] |
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rain_boost = tf.sigmoid((rain - 60) * 0.06) |
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impervious_boost = tf.sigmoid((impervious - 0.6) * 10) |
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return (1.0 + 0.3 * rain_boost * impervious_boost)[:, None] |
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@register_keras_serializable() |
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def drainage_penalty(inputs): |
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dd = inputs[:, 2] |
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return (1.0 - 0.4 * tf.sigmoid((dd - 3.5) * 2))[:, None] |
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@register_keras_serializable() |
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def convergence_suppressor(inputs): |
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ci = inputs[:, 4] |
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return (1.0 + 0.3 * tf.sigmoid((ci - 0.5) * 8))[:, None] |
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@register_keras_serializable() |
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def clip_modulation(x): |
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return tf.clip_by_value(x, 0.7, 1.3) |
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@register_keras_serializable() |
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def drainage_penalty2(inputs): |
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dd = inputs[:, 2] |
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return (1.0 - 0.4 * tf.sigmoid((dd - 3.5) * 2))[:, None] |
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@register_keras_serializable() |
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def convergence_suppressor2(inputs): |
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ci = inputs[:, 4] |
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return (1.0 + 0.3 * tf.sigmoid((ci - 0.5) * 8))[:, None] |
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@register_keras_serializable() |
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def intensity_slope_amplifier(inputs): |
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rainfall_intensity = inputs[:, 0] |
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slope = inputs[:, 1] |
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runoff_boost = tf.sigmoid((rainfall_intensity - 75) * 0.08) |
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slope_boost = tf.sigmoid((slope - 10) * 0.05) |
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return (1.0 + 0.35 * runoff_boost * slope_boost)[:, None] |
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def clip_modulation2(x): |
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return tf.clip_by_value(x, 0.7, 1.3) |
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CUSTOM_OBJECTS2 = { |
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'drainage_penalty': drainage_penalty2, |
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'intensity_slope_amplifier': intensity_slope_amplifier, |
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'convergence_suppressor': convergence_suppressor2, |
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'clip_modulation': clip_modulation2 |
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} |
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CUSTOM_OBJECTS = { |
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'drainage_penalty': drainage_penalty, |
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'convergence_suppressor': convergence_suppressor, |
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'surface_runoff_amplifier': surface_runoff_amplifier, |
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'clip_modulation': clip_modulation |
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} |
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FireNet = hft.load_model("sharktide", "FireNet", "tf_model.h5", True) |
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FireTrustNet = hft.load_model("sharktide", "FireTrustNet", "tf_model.h5", True) |
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FireScaler = joblib.load("scalers/firetrust_scaler.pkl") |
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FloodNet = hft.load_model("sharktide", "FV-FloodNet", "tf_model.h5", True) |
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FloodTrustNet = hft.load_model("sharktide", "FV-FloodTrustNet", "tf_model.h5", True) |
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FloodScaler = joblib.load("scalers/FV-floodtrust_scaler.pkl") |
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get_path = lambda usr, model: (str(hft.get_model_folder(usr, model)) + "/tf_model.h5") |
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PV_FloodNet = tf.keras.models.load_model(get_path("sharktide", "PV-FloodNet"), safe_mode=False, custom_objects=CUSTOM_OBJECTS) |
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PV_FloodTrustNet = hft.load_model("sharktide", "PV-FloodTrustNet", "tf_model.h5", True) |
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PV_FloodScaler = joblib.load("scalers/PV-floodtrust_scaler.pkl") |
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FlashFloodNet = tf.keras.models.load_model(get_path("sharktide", "FlashFloodNet"), safe_mode=False, custom_objects=CUSTOM_OBJECTS2) |
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FlashFloodTrustNet = hft.load_model("sharktide", "FlashFloodTrustNet", "tf_model.h5", True) |
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FlashFloodScaler = joblib.load("scalers/flashFloodtrustscaler.pkl") |
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QuakeNet = hft.load_model("sharktide", "QuakeNet", "tf_model.h5", True) |
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QuakeTrustNet = hft.load_model("sharktide", "QuakeTrustNet", "tf_model.h5", True) |
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QuakeTrustScaler = joblib.load("scalers/QuakeTrustScaler.pkl") |
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HurricaneNet = hft.load_model("sharktide", "HurricaneNet", "tf_model.h5", True) |
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HurricaneTrustNet = hft.load_model("sharktide", "HurricaneTrustNet", "tf_model.h5", True) |
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HurricaneTrustScaler = joblib.load("scalers/HurricaneTrustScaler.pkl") |
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TornadoNet = hft.load_model("sharktide", "TornadoNet", "tf_model.h5", True) |
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TornadoTrustNet = hft.load_model("sharktide", "TornadoTrustNet", "tf_model.h5", True) |
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TornadoTrustScaler = joblib.load("scalers/TornadoTrustScaler.pkl") |
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