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Tag: deep-learning

In PyTorch, how do I update a neural network via the average gradient from a list of losses?

I have a toy reinforcement learning project based on the REINFORCE algorithm (here’s PyTorch’s implementation) that I would like to add batch updates to. In RL, the “target” can only be created after a “prediction” has been made, so standard batching techniques do not apply. As such, I accrue losses for each episode and append them to a list l_losses

Reshaping problem (Input to reshape is a tensor with 10 values, but the requested shape has 1)

I’m trying to recreate this work using my own dataset: I’ve made some slight tweaks to the code to accommodate my data but I don’t think that is what is causing an issue here; it could be though of course. My code: And the error: I can gather from the error that I have a mismatch in resizing, I

How to replace PyTorch model layer’s tensor with another layer of same shape in Huggingface model?

Given a Huggingface model, e.g. I can access a layer’s tensor as such: [out]: Given the another tensor of the same shape that I’ve pre-defined from somewhere else, in this case, for illustration, I’m creating a random tensor but this can be any tensor that is pre-defined. Note: I’m not trying to replace a layer with a random tensor but

Adam Optimizer Not Working on cost function

I wanted to make own neural network for MNIST data set and for that using tensorflow i am writing the code imported library and dataset then done one hot encoding and after all done the weights and baises assignment and then done the forward propagation with the random values and for back propagation and cost minimization used a loss function

How can I print the training and validation graphs, and training and validation loss graphs?

I need to plot the training and validation graphs, and trarining and validation loss for my model. Answer history object contains both accuracy and loss for both the training as well as the validation set. We can use matplotlib to plot from that. In these plots x-axis is no_of_epochs and the y-axis is accuracy and loss value. Below is one