yarn_linear_ramp_mask: ramp func

Read the equation

In yarn_linear_ramp_mask, this statement defines or updates ramp_func. This statement evaluates the named projection, normalization or numeric transform with the source arguments. Its learned parameters and exact input shape are defined by the surrounding module.

Terms & definitions

The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.

How it works

1. Read ramp_func as the quantity being defined or updated by this relation.

2. Applies the stated minimum, maximum, or clamp. These bounds are part of the actual operation.

3. Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.

Assumptions & limits

Source recovery establishes that the expression appears in this record. Its mathematical validity, implementation behavior, and interpretation must be assessed separately. See the linked source and research notes for the checks available for this version.

Original context

max += 0.001  # Prevent singularity

    linear_func = (torch.arange(dim, dtype=torch.float32) - min) / (max - min)
    ramp_func = torch.clamp(linear_func, 0, 1)
    return ramp_func

ramp_func = torch.clamp(linear_func, 0, 1)

Related builds