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Hi, thank you for great implementation. I appreciate your work as well as your generosity for opening it.
As mentioned in title, I have a question about line 35 of loss_functions.py, as given below…
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I am trying to train a VQC through the `PyTorchBackend` and using the `pytorch` API. Here you can find a small test example.
``` python
import torch
import numpy as np
from qibo.backends import …
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Currently, we use a finite difference approximation to compute the gradient of the operator (A) w.r.t the design variables (u). This approach is convenient and flexible but has its limitations. Namely…
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### ⚠️ Please check that this feature request hasn't been suggested before.
- [X] I searched previous [Ideas in Discussions](https://github.com/OpenAccess-AI-Collective/axolotl/discussions/categori…
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I have 10 bit input data like this
const double inputs[110][8] = {
{540,131,48,3,0,0,0,0},
{624,167,63,15,0,0,0,0},
{736,224,96,31,0,0,0,0},...
but after learning output is the same for exemple
…
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Hi @liyiying. Thanks for your implementation!
I have a question that:
This implementation feeds batches of each meta train dataset into feature_extractor_network and sums up the losses (meta_train…
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1. Can we use `recursive_generator` similar with the official code?
2. `LayerNorm` is in here http://pytorch.org/docs/master/nn.html#layernorm.(Seems in this week v0.4 will be released)
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Hi, thanks for your wonderful work~
I'm a little confused about the implemention of vsd loss,
I followed your paper and read _ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with V…
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First I train the classifier to get a good feature extractor "*.backup" by
`./darknet classifier train cfg/cifar.data cfg/cifar_small.cfg`
Then How to train the detetor without changing the featur…
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