Plotting categorical obs warns ImplicitModificationWarning

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Minimal code sample

I'm trying to plot a categorical observation on a UMAP for a view of my adata. I created this minimal code to reproduce the behavior:

from anndata import AnnData
import numpy as np
import pandas as pd
import scanpy as sc

n_obs, n_vars = 1000, 2

adata = AnnData(X=np.random.randn(n_obs, n_vars), dtype=np.float32)
adata.obsm["X_umap"] = np.random.randn(n_obs, 2)
adata.obs["obs1"] = pd.Categorical([f"Group {np.random.randint(2)}" for _ in range(n_obs)])

sc.pl.umap(adata[adata.X[:, 0] > 0], color="obs1")

It plots the desired result, but creates a copy and warns:

ImplicitModificationWarning: Trying to modify attribute `._uns` of view, initializing view as actual.
  self.data[key] = value

Issue

EDIT: colors are stored, but as I use a view, it creates a copy. My adata contains dozens of millions of cells, and thus making a copy creates severe memory and time issues. Is there an option not to store the colors on this view?

Versions

Start by running the minimal sc.pl.umap example with the categorical adata.obs["obs1"] and an AnnData view, then trace the warning from view initialization to modification of ._uns. Check how plotting colors are stored for categorical observations; done means plotting the view without creating a full copy while preserving the expected UMAP result and color behavior.