"""Faithful minimal stand-ins for the openpi transforms used by g1_dex3_policy."""
import dataclasses
from typing import Sequence
import numpy as np

class DataTransformFn:
    pass

def pad_to_dim(x, target_dim, axis=-1):
    current = x.shape[axis]
    if current >= target_dim: return x
    pad = [(0,0)]*x.ndim
    pad[axis]=(0, target_dim-current)
    return np.pad(x, pad)

def make_bool_mask(*dims):
    out=[]
    for d in dims:
        out.extend([True]*d if d>0 else [False]*(-d))
    return tuple(out)

@dataclasses.dataclass(frozen=True)
class DeltaActions(DataTransformFn):
    mask: Sequence[bool] | None
    def __call__(self, data):
        if "actions" not in data or self.mask is None: return data
        state, actions = data["state"], np.array(data["actions"])
        mask = np.asarray(self.mask); dims = mask.shape[-1]
        actions[..., :dims] = np.where(mask, actions[..., :dims]-state[..., :dims], actions[..., :dims])
        data["actions"]=actions; return data

@dataclasses.dataclass(frozen=True)
class AbsoluteActions(DataTransformFn):
    mask: Sequence[bool] | None
    def __call__(self, data):
        if "actions" not in data or self.mask is None: return data
        state, actions = data["state"], np.array(data["actions"])
        mask = np.asarray(self.mask); dims = mask.shape[-1]
        actions[..., :dims] = np.where(mask, actions[..., :dims]+state[..., :dims], actions[..., :dims])
        data["actions"]=actions; return data