From d3ebe355c6588b731fcfadf19155cbedd8147bc7 Mon Sep 17 00:00:00 2001 From: maelstrom Date: Sat, 7 Dec 2024 22:25:58 -0500 Subject: [PATCH] trying to fix input dimensions: --- model/autoencoder.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/model/autoencoder.py b/model/autoencoder.py index 1be0470..8a6fe77 100644 --- a/model/autoencoder.py +++ b/model/autoencoder.py @@ -1,9 +1,10 @@ import keras class Encoder(keras.Model): - def __init__(self, input_size=(130, 26)): + def __init__(self, input_size=(130, 26), latent_dim=128): super(Encoder, self).__init__() self.encoder = keras.Sequential([ + keras.layers.InputLayer(input_shape=input_size), keras.layers.Conv2D(8, (3, 3), activation="relu", input_shape=input_size), keras.layers.Conv2D(16, (3, 3), activation="relu", @@ -11,17 +12,17 @@ def __init__(self, input_size=(130, 26)): keras.layers.Conv2D(32, (3, 3), activation="relu", input_shape=input_size), keras.layers.Flatten(), - keras.layers.Dense(128, activation="relu") + keras.layers.Dense(latent_dim, activation="relu") ]) def call(self, x): return self.encoder(x) class Decoder(keras.Model): - def __init__(self): + def __init__(self, latent_dim=128): super(Decoder, self).__init__() self.decoder = keras.Sequential([ - keras.layers.Dense(128, activation="relu"), + keras.layers.InputLayer(input_shape=(latent_dim,)), keras.layers.Reshape((4, 4, 8)), keras.layers.Conv2DTranspose(32, (3, 3), activation="relu"), keras.layers.Conv2DTranspose(16, (3, 3), activation="relu"), @@ -33,10 +34,10 @@ def call(self, x): return self.decoder(x) class Autoencoder(keras.Model): - def __init__(self, input_size=(130, 26)): + def __init__(self, input_size=(130, 26), latent_dim=128, **kwargs): super(Autoencoder, self).__init__() - self.encoder = Encoder(input_size=input_size) - self.decoder = Decoder() + self.encoder = Encoder(input_size=input_size, latent_dim=latent_dim) + self.decoder = Decoder(latent_dim=latent_dim) def call(self, x): encoded = self.encoder(x)