Learn how to use `prod()` and `cartesian_prod()` in PyTorch for tensor operations. Get product of elements or cartesian products with examples.

expand() in PyTorch: Expand a tensor to the specified size. Can be used with tensors of different data types (int, float, complex, bool). Example usage: `my_tensor.expand((4, 2, 3))

repeat() in PyTorch: Repeat elements of a tensor by specified repeats. Supports 0D or more D tensors and various data types.

Learn how to convert tensors between CPU and GPU, and from NumPy arrays with PyTorch's `to()`, `cuda()`, `cpu()`, `from_numpy()` and `numpy()` methods. Examples included.

diag() function in PyTorch: extracts or creates diagonals from 1D or 2D tensors with optional output argument. Examples and usage shown.

fmin() and fmax() in PyTorch: Get minimum or maximum elements from two tensors, ignoring NaN values. Use out argument for result tensor.

minimum() and maximum() in PyTorch: Get the min/max elements from 0D or more D tensors, prioritizing nan values. Use with torch or tensor inputs.

count_nonzero() returns the count of non-zero elements in a tensor. It can be used with torch or as a method on a tensor, and supports various dimensions for counting.

where() in PyTorch: Select elements based on condition. Args: condition (tensor of bool), input (tensor or scalar), other (tensor or scalar). Returns tensor with selected elements.

isin() checks if elements of a tensor contain same elements as another tensor or scalar, returning boolean values. Can be used with torch but not directly with tensors.

ge() and le() functions in PyTorch: Compare tensors element-wise, returning a boolean tensor. Examples with torch.tensor() and scalar values.

gt() and lt() functions in PyTorch: Compare tensors element-wise, returning a boolean tensor. Examples with torch.tensor() and scalar values.

logical_xor() and logical_not() functions explained in PyTorch. Perform XOR operation on tensors with logical_xor(). Negate boolean values with logical_not().

logical_and() and logical_or() explained in PyTorch. Perform logical AND or OR operations on tensors with torch.logical_and() and torch.logical_or().

stack() in PyTorch: stack tensors along specified dimension with optional out argument for result tensor. Examples and usage shown.

flipud() reverses elements in up/down direction, fliplr() reverses elements in left/right direction. Both used with torch or tensor, reversing elements as shown.

torch.flip()` reverses the order of a specified dimension in a tensor.

torch.normal() generates random numbers from normal distribution with mean and std as arguments. It can create tensors of various shapes and data types.

Learn how to generate random numbers with PyTorch's `randint` and `randperm` functions, including examples for integer and float types.

argmin() and argmax() explained: get indices of min/max elements in tensors with torch or PyTorch.

Learn how to create & access tensors with PyTorch! Use `is_tensor()` to check if an object is a tensor, `numel()` for element count, and `device()` for device representation.

manual_seed() sets a specific seed for random numbers. Use it before each generator to get the same results.

unbind() splits 1D or more D tensor into one or more views by removing a specified dimension.

torch.eye() creates 2D tensors with specified diagonal and size. Examples: torch.eye(n=4), torch.eye(n=4, m=6)

is_floating_point() checks if tensor is float type, while is_complex() checks for complex type. is_nonzero() checks if single-element tensor is nonzero.

Rounding tensors with PyTorch: round(), ceil() and floor() functions explained. Learn how to use decimals argument for precise rounding.

torch.matmul()` can multiply tensors of different dimensions using matrix multiplication or dot product.

Clone a private GitHub repo with FGPAT: `git clone https://<fgpat>@github.com/<usr or org>/<repo>.git

Clone a private GitHub repo with PAT or FGPAT: `git clone https://<fgpat or pat>@github.com/<usr or org>/<repo>.git

filterwarnings() and simplefilter() in Python explained. Learn how to manage warnings with `warn()` function and warning categories like UserWarning, DeprecationWarning.

Path.mkdir()` creates zero or more directories. `parents=True` allows creation of non-existent parent dirs, while `exist_ok=True` prevents raising errors for existing paths.

DO statement in PostgreSQL: atomic, supports PL/pgSQL language, can have DECLARE clause, SELECT INTO, PERFORM, EXECUTE statements, but not RETURN NEXT or QUERY.

Learn how to declare local variables in PL/pgSQL functions with :=, = and DEFAULT. Understand type-only parameters, aliases and table column types.

Get the OID of a PostgreSQL function with regproc, regprocedure, to_regproc() and to_regprocedure()

PL/pgSQL procedures can have zero or more queries, IN, OUT, and INOUT parameters. They must be defined with AS <delimiter> clause and BEGIN ... END clause.