File size: 1,831 Bytes
5151965 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 |
from tensorflow.keras.models import load_model
from tensorflow.keras.saving import register_keras_serializable
import tensorflow as tf
@register_keras_serializable()
class CAPEAmplifier(tf.keras.layers.Layer):
def __init__(self, threshold=2000, scale=0.001, **kwargs):
super().__init__(**kwargs)
self.threshold = threshold
self.scale = scale
def call(self, inputs):
cape = inputs[:, 1]
boost = tf.sigmoid((cape - self.threshold) * self.scale)
mod = 1.0 + 0.3 * boost
return tf.expand_dims(mod, axis=-1)
@register_keras_serializable()
class LCLSuppressor(tf.keras.layers.Layer):
def __init__(self, threshold=1400, scale=0.002, **kwargs):
super().__init__(**kwargs)
self.threshold = threshold
self.scale = scale
def call(self, inputs):
lcl = inputs[:, 2]
suppression = tf.sigmoid((lcl - self.threshold) * self.scale)
return tf.expand_dims(1.0 - 0.25 * suppression, axis=-1)
@register_keras_serializable()
class STPActivator(tf.keras.layers.Layer):
def __init__(self, threshold=1.5, scale=1.0, **kwargs):
super().__init__(**kwargs)
self.threshold = threshold
self.scale = scale
def call(self, inputs):
stp = inputs[:, 4]
activation = tf.sigmoid((stp - self.threshold) * self.scale)
return tf.expand_dims(1.0 + 0.2 * activation, axis=-1)
@register_keras_serializable()
class ModulationMixer(tf.keras.layers.Layer):
def call(self, inputs):
cape_mod, lcl_mod, stp_mod = inputs
combined = cape_mod * lcl_mod * stp_mod
return 1.0 + 0.3 * tf.tanh(combined - 1.0)
CUSTOM_OBJECTS = {
'ModulationMixer': ModulationMixer,
'STPActivator': STPActivator,
'CAPEAmplifier': CAPEAmplifier,
'LCLSuppressor': LCLSuppressor
} |