Web18 jun. 2024 · 1 Answer. In your model.fit you need to provide a list of inputs with length = 2, since you define two inputs in your Model. Split your training data in train_hour and … WebBuilding a multi input and multi output model: giving AttributeError: 'dict' object has no attribute 'shape' Naresh DJ 2024-02-14 10:25:35 573 1 python / r / tensorflow / keras / deep-learning
超簡単 Kerasで複数Input統合モデル - Qiita
Webimport numpy as np from pylab import * from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense from tensorflow.keras import optimizers # … Web10 apr. 2024 · I am trying to train a network with multiple inputs with different shapes. Inputs = [state, other_inputs] state -> (40, 40, 1) other_inputs -> (3) Although I am not having problem while predicting, there is something problematic when it is trained on batches. Model : small business corporation tax rates 2013
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Web10 apr. 2024 · As you can see, my inputs are different on my two models and the Distiller () class is predefined to work with the same input for both models and that is what I am trying to change. The first thing I tried to change in the keras class was to pass in the beggining of def train_step from this: def train_step (self, data): # Unpack data x, y = data Web1 mrt. 2024 · This is a basic graph with three layers. To build this model using the functional API, start by creating an input node: inputs = keras.Input(shape=(784,)) The shape of … Web2 dagen geleden · The input of the LSTM is a (100x2) tensor. For example one of the 100 values is (0.2,0.4) I want to turn it into a 100x10 input, for example, that value would be converted into (0,1,0,0,0,0,0,1,0,0) I want to use the Keras Discretization layer with adapt (), but I don't know how to do it for multiple dimensions soma fabrications posts