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I'm training a basic CIFAR10 classifier (two Dense layers) using multi-GPU with torch backend (see the code below). The code works fine when the net is written in torch. When written in Keras it retur…
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Right now, we are predicting using a softmax classifier. Let’s just make this a binary classifier.
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My implementation of softmax logistic classifier is ~70% accurate, whereas the scikit-learn classifier is ~90% accurate. I'm not sure why this is happening. I can get to ~80% accuracy if I remove the …
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In the file 'MPANet/models/baseline.py', the 'train_forward' function calculates the final loss composed of multiple components. In the following code snippet, I notice that 'v_cls_loss' and 'i_cls_lo…
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# Build the quantum model layer
theta = sympy.Symbol('theta')
q_model = cirq.Circuit(cirq.ry(theta)(qubit))
q_data_input = tf.keras.Input(
shape=(), dtype=tf.dtypes.string)
expectation = tfq.…
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Hi,
What is the difference between Classifier training of inception resnet v1 & Train a classifier on your own dataset?
As I understand, the train_softmax.py is used for training embeddings and we w…
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Hello,
thank you for this repo and your nice paper. :)
I have an understanding question about the paper and the usage of sentence embeddings. Short: Why are you using the embeddings and then the…
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If I understand the logic correctly then in Luong Decoders forward function:
```
def forward(self, inputs, hidden, encoder_outputs):
#Embed input words
embedded = self.embedding(…
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hi,
what is the classifier of cross encoder? is it a softmax layer?
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### Current Behavior:
The DeepNetV3Plus Task appears to have issues when there's only 1 class. It should allow setting the activation function and/or default to sigmoid etc. It appears to be a very…