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pytorch if statement

Escaping if statement synchronization - distributed - PyTorch ...
https://discuss.pytorch.org › escapi...
how to escape if synchronization. it is a huge problem because the evaluation of a simple if ONLY takes .33 sec while the entire forward in ...
if-statement: Pytorch Custom Loss Function with If Statement
https://if-statement21.blogspot.com/2021/07/pytorch-custom-loss...
Pytorch Custom Loss Function with If Statement I am trying to create a custom loss function in Pytorch that evaluates each element of a tensor with an if statement and acts accordingly. def my_loss(outputs,targets,fin_val): if ...
Escaping if statement synchronization - distributed ...
https://discuss.pytorch.org/t/escaping-if-statement-synchronization/130263
25.08.2021 · **-- how to escape if synchronization. it is a huge problem because the evaluation of a simple if ONLY takes .33 sec while the entire forward in large network takes .0001s. here is a way that leads to wrong results because of synch gpu-to-cpu with non-blocking=True issue !!! WARNING: NEVER use gpu-to-cpu transfer with non-blocking=True. it is NOT safe. see the …
Performance of IF statements in Pytorch - vision
https://discuss.pytorch.org › perfor...
I use this toy example to measure performance of if statements in the forward loop. At least for XLA devices (such as in COLAB) when the ...
How to use condition flow? - PyTorch Forums
https://discuss.pytorch.org › how-t...
x if (x > 0).numpy() else x-1. Does that numpy bool create proper computing graph? If so, why that's the case? I'm not sure why pytorch can ...
PyTorch Detach | A Compelete Guide on PyTorch Detach
https://www.educba.com/pytorch-detach
PyTorch helps in automatic differentiation by tracking all the operations to compute the gradient for everything. Thus, a graph is created for all the operations, which will require more memory. Now, if we use detach, the tensor view will be differentiated from the following methods, and all the tracking operations will be stopped.
TorchScript Language Reference - PyTorch
https://pytorch.org › docs › stable
See Builtin Functions for a complete reference of available Pytorch tensor ... The None check must be within the if-statement's condition; assigning a None ...
Execution time slowed done when using an if statement - vision
https://discuss.pytorch.org › execut...
I noticed that there is a weird slow down after using an if statement in my code. I load an image onto CUDA device, then my neural network ...
If statement in loss function? - autograd - PyTorch Forums
https://discuss.pytorch.org › if-state...
I want to define a loss function, the output/y's shape is [batch_size, 1, 12, 1, 1], I will calculate the absolute error between output and ...
How to use if statement PyTorch using torch.FloatTensor
https://stackoverflow.com › how-to...
When you compare pyTorch tensors, the output is usually a ByteTensor . This data type is not suitable for if statements. Change the condition ...
python - How to use if statement PyTorch using torch ...
https://stackoverflow.com/questions/47290053
How to use if statement PyTorch using torch.FloatTensor. Ask Question Asked 4 years, 1 month ago. Active 4 years, 1 month ago. Viewed 6k times 1 I am trying to use the if statement in my PyTorch code using torch.FloatTensor as data type, to speed it …
IF-ELSE statement in LSTM - PyTorch Forums
https://discuss.pytorch.org › if-else...
Hi, I am wondering if it is possible to include an IF-ELSE statement in the LSTM part of the code. Here is the section: if flag == True: ...
How to use condition flow? - PyTorch Forums
https://discuss.pytorch.org/t/how-to-use-condition-flow/644
21.02.2017 · I’m not sure why pytorch can create computing graph with mixing numpy arrays and pytorch variables. 1 Like. smth February 21, 2017, 5:47pm #4. if x is a Tensor, then x > 0 will return a ByteTensor with value 1 where x[i] > 0 and value 0 where x[i] <= 0. x if ...
Execution time slowed done when using an if statement ...
https://discuss.pytorch.org/t/execution-time-slowed-done-when-using-an...
08.01.2020 · I noticed that there is a weird slow down after using an if statement in my code. I load an image onto CUDA device, then my neural network (fixed parameters) detects if there is an object or not in the given image. If there is an object, pixel values take values different from zero in the corresponding region, otherwise 0. I must send a signal if there is a non-zero value in the …
torch.where — PyTorch 1.10.1 documentation
https://pytorch.org › generated › to...
condition (BoolTensor) – When True (nonzero), yield x, otherwise yield y ... value (if x is a scalar) or values selected at indices where condition is True.
Conditional statement for a tensor in pytorch
https://discuss.pytorch.org › condit...
Hi, Is there any suggestion about how I can implement below conditions for kc which is a tensor in pytorch? following conditions give this ...
IF-ELSE statement in LSTM - PyTorch Forums
https://discuss.pytorch.org/t/if-else-statement-in-lstm/2550
01.05.2017 · Since PyTorch is a dynamic network tool, I assume it should be able to do this. But during my experiment, seems like the LSTM actually gets the input at each time-step, regardless of the IF-ELSE statement.
CNN gets stuck in loop - probably if statement cause ...
https://discuss.pytorch.org/t/cnn-gets-stuck-in-loop-probably-if...
05.06.2020 · I have had a lots of problems with this notebook but hopefully this is the last one: I now have: All my inputs as tensors Both the data and model (including fc) on the GPU Resized all the images to the same size Changed requires_grad = True for the fc My model will only do one forward pass though before sitting idle. I think it is something to do with the if statement. When …
Learning PyTorch with Examples — PyTorch Tutorials 1.10.1 ...
https://pytorch.org/tutorials/beginner/pytorch_with_examples.html
PyTorch: Tensors ¶. Numpy is a great framework, but it cannot utilize GPUs to accelerate its numerical computations. For modern deep neural networks, GPUs often provide speedups of 50x or greater, so unfortunately numpy won’t be enough for modern deep learning.. Here we introduce the most fundamental PyTorch concept: the Tensor.A PyTorch Tensor is conceptually …
torch.where — PyTorch 1.10.1 documentation
https://pytorch.org/docs/stable/generated/torch.where.html
torch.where. Return a tensor of elements selected from either x or y, depending on condition. The operation is defined as: The tensors condition, x, y must be broadcastable. Currently valid scalar and tensor combination are 1. Scalar of floating dtype and torch.double 2. Scalar of integral dtype and torch.long 3.