Search Results for "order"

...It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and TPUs. Compilation happens under the hood by default, with library calls getting just-in-time compiled and executed. But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python.

...In an axis chart, every dataset is represented individually. Frappe Charts are responsive, as they rerender all the data in the current available container width. In order to set the bar width, instead of defining it and the space between the bars independently, we simply define the ratio of the space between bars to the bar width. The chart then adjusts the actual size proportional to the chart container. Line charts are great to show trends. One of the reasons they are interesting is because the data involved usually involves a large number of data points. ...