Introduces a Tensor class that wraps numpy arrays, enabling
fundamental ML operations like addition, subtraction,
multiplication, and division.
Adds utility methods such as reshape, transpose, sum, mean, max,
min, item, and numpy to the Tensor class.
Updates tests to accommodate both scalar and Tensor results
when checking mean values.
Introduces the foundational CLI structure and core components for the TinyTorch project.
This initial commit establishes the command-line interface (CLI) using `argparse` for training, evaluation, benchmarking, and system information. It also lays out the basic directory structure and essential modules, including tensor operations, autograd, neural network layers, optimizers, data loading, and MLOps components.
