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💡 Codex Review

Handle 3D grayscale arrays as batched inputs

Treating np.ndarray inputs as batched data only when ndim == 4 makes (N, H, W) vision tensors fail in encode. With common grayscale datasets (for example, MNIST-style arrays loaded as (N, H, W)), this path keeps the entire batch as one sample (samples = [X]), and _to_nchw then cannot infer channels for shape (N, H, W) and raises a validation error; in edge cases it can also misinterpret sample count. This breaks torchvision:resnet18 preprocessing unless callers manually reshape to 4D beforehand.