Tensors and Dynamic neural networks in Python with strong GPU acceleration

A deep learning framework built on an autograd engine with high level abstractions and low level control.

Multidimensional arrays.

A next-generation dynamic and high-performance language for AI and IOT with natural born distributed computing ability.

On-device AI across mobile, embedded and edge for PyTorch

Create an iterator which iterates over each matrix in a stack of matrices.

Create an iterator which returns [index, matrix] pairs for each matrix in a stack of matrices.

Create an iterator which returns [index, row] pairs for each row in a matrix (or stack of matrices).

Create an iterator which iterates over each row in a matrix (or stack of matrices).

Create an iterator which iterates over each view along a specified dimension.

Create an iterator which iterates over each subarray in a stack of subarrays.

Create an iterator which returns [index, value] pairs for each element in a provided ndarray.

Create an iterator which returns indices for use indexing into an ndarray having a specified shape.

Create an iterator which returns individual elements from a provided ndarray.

Flatten a three-dimensional nested array according to a callback function.

Flatten a three-dimensional nested array.

Flatten a four-dimensional nested array according to a callback function.

Flatten a four-dimensional nested array.

Flatten a five-dimensional nested array according to a callback function.