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June 4, 2023

Load and Inference local YOLOv8.pt with PyTorch

PyTorchPragati

The model weights yolov8l.pt file must be in loacl directory and the main inference python script contains the functions needed for loading the model, parsing the input, running the inference, and post-processing the output.

May 20, 2023

Filter Pandas Dataframe using OR(|) AND(&) with Query()

PandasPragati

Let’s take a look at a few different ways to filter and select rows in a Pandas dataframe based on multiple conditions.

May 17, 2023

​​​​​​Install TensorFlow/Keras GPU on Apple M1/M2 Mac with Conda

KerasTensorFlowPragati

TensorFlow users on Mac powered by Apple’s new M1/M2 chip can now take advantage of accelerated training using Apple’s Mac-optimized version of TensorFlow 2.4.

May 15, 2023

How to check and change the default device to MPS in PyTorch

PyTorchPragati

This post will talk about GPU-accelerated PyTorch training using the MPS backend on Mac platforms. MPS enables high-performance training on GPU for MacOS devices with a Metal programming framework. I’ll also provide an overview of the software stack. So let’s talk briefly about the MPS backend and software components it relies on.

May 12, 2023

Install PyTorch 2.0 GPU/MPS for Mac M1/M2 with Conda

PyTorchPragati

In this post we are going to use Miniconda, it’s a Python environment and it has a lot of scientific packages available for data science. I use Miniconda rather than Anaconda they’re both from the same company but Miniconda does not install a whole plethora of additional packages.

April 30, 2023

What does optimizer.step() and scheduler.step() do?

PyTorchPragati

All parameters passed to the optimizer are retained inside the optimizer object so the optimizer can update their values and access their grad attribute.

April 28, 2023

Get learning rate during training in PyTorch

PyTorchPragati

In PyTorch, a model is updated by an optimizer and the learning rate is a parameter of the optimizer. The learning rate schedule is an algorithm to update the learning rate in an optimizer.

April 12, 2023

Difference between torch.nn.Dropout vs nn.functional.dropout in PyTorch

PyTorchPragati

The modules (nn.Module) use internally the functional API. There is no difference as long as you store the parameters somewhere (manually if you prefer the functional API or in an nn.Module “automatically”)

April 7, 2023

Get Normal/Uniform distribution in range[r1,r2] in PyTorch

PyTorchPragati

We learned how to generate and plot the Normal and Uniform distributions using PyTorch and seaborn respectively.

April 3, 2023

Create your own Custom Iterable DataPipe for Image Dataset

PyTorchPragati

PyTorch 2.0 provides two data primitives: datapipes and DataLoader2 that allow you to use pre-loaded datasets as well as your own data.

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