o Si @sZddlZddlmZddlmZmZmZmZddlm Z ddl m Z eGdddZ dS)N) dataclass)LiteralOptionalTupleUnion)CutSet) resolve_seedc@seZdZUdZeeeeeffed<dZe ed<dZ eed<dZ eed<dZ ee ed fed <d Zeejed <d Zee ed<dZe ed<dddZdedefddZd S)ClippingTransforma/ Applies clipping to each Cut in a CutSet with a given probability. The clipping is applied with a probability of ``p``. The gain_db is randomly sampled from the provided range if an interval is given, or the fixed value is used if a single float is provided. :param gain_db: A single value or an interval (tuple/list with two values). The amount of gain in decibels to apply before clipping. If an interval is provided, the value is sampled uniformly. :param hard: If True, apply hard clipping (sharp cutoff); otherwise, apply soft clipping (saturation). :param normalize: If True, normalize the input signal to 0 dBFS before applying clipping. :param p: The probability of applying clipping (default: 0.5). :param seed: Random seed for reproducibility (default: 42). :param rng: Optional random number generator (overrides seed if provided). :param oversampling: Optional integer factor for oversampling before clipping. :param preserve_id: Whether to preserve the original cut ID (default: False). gain_dbT normalizeg?pp_hard*)trng randomizedseedNrng oversamplingF preserve_idreturncCst|jttfr*t|jdksJd|j|j\}}||ks*Jd|d|d|jkr5dks>nJd|j|jdurL|jdurLtd|jdur\t t |j|_dSdS) Nrz>Expected gain_db to be a tuple or a list with two values, got z"Expected min_gain < max_gain, got z >= rz+Probability p must be between 0 and 1, got z-Either rng or seed must be provided, not both) isinstancer tuplelistlenr rr ValueErrorrandomRandomr)selfmin_gainmax_gainr"Z/home/ubuntu/.local/lib/python3.10/site-packages/lhotse/dataset/cut_transforms/clipping.py __post_init__'s   ( zClippingTransform.__post_init__cutsc Csg}|D]H}|j|jkrG|j|jkrd}nd}t|jttfr0|j\}}|j||}n|j}|j |||j |j |j d}| |q| |qt|S)NTF)hardr r affix_idr)rrr r rr rruniformclip_amplituder rrappendr) rr%saturated_cutscutr&r r!r new_cutr"r"r#__call__8s(   zClippingTransform.__call__)rN)__name__ __module__ __qualname____doc__rfloatr__annotations__r boolr r rintrrrrrrrr$rr.r"r"r"r#r s      r ) r dataclassesrtypingrrrrlhotserlhotse.dataset.dataloadingrr r"r"r"r#s