I am tying to write a NN in pytorch that learns to give for example: very simple A+B for two images. Writing it, I got this error. my batch_size is 4. class myNet(nn.Module): def __init__(self): super(myNet, self).__init__() self.fc1 = nn.Linear(3072, 3072) # set up FC layer self.fc2 = nn.Linear(3072, 3072) # set up the other… Read More IndexError: index 4 is out of bounds for dimension 0 with size 4?
I have the following wrapper class: from tensorflow.keras.models import Sequential class NeuralNet(Sequential): def __init__(self, **kwargs): super().__init__(**kwargs) I can fit and save the model without problems, but when I try to load it: from tensorflow.keras.models import load_model model = load_model(‘model.h5’) I get: –> 296 raise ValueError(‘Unknown ‘ + printable_module_name + ‘: ‘ + class_name) 297 298… Read More problem when loading a keras model saved through a wrapper class
I am new to NN. I AM TRYING TO TUNE MY MLP REGRESSOR MODEL. I don’t understand what does this line mean "’hidden_layer_sizes’: [(100,), (50,100,), (50,75,100,)]" does this mean that we’re asking the model to check if the model will perform better in case it has only one hidden layer with 100 hidden points, or… Read More A question about MLP-What does this line mean?
A and B matrices will be different when i run the program A = np.array([[1, 1, 1], [2, 2, 2]]) B = np.array([[1, 1, 1], [2, 2, 2], [3, 3, 3]]) The output matrix (C) should be the same dimension as matrix A. As title says, I’m trying to multiply each row from one matrix… Read More how to multiply each row from one matrix to every rows to another matrix on Python?
I’m trying to create a 2-layer neural network, for that I first initialize weights and biases to random floats between 0 an 1 using numpy.random.rand. However, for some reason this process produces floats bigger than 1 for W1 (weight 1) whereas it works correctly for all other weights an biases. I can’t understand why this… Read More np.random.rand somehow produces floats bigger than 1 [solved, it doesn't]
I’m looking through some different neural network architectures and trying to piece together how to recreate them on my own. One issue I’m running into is the functional difference between the Concatenate() and Add() layers in Keras. It seems like they accomplish similar things (combining multiple layers together), but I don’t quite see the real… Read More Add vs Concatenate layer in Keras