def validate_fp8_conversion(original, fp8_data, scales):
    """Check if FP8 conversion preserves data accurately"""
    # Reconstruct original from FP8
    if fp8_data.dim() == 2:
        # Per-token scaling
        m, n = fp8_data.shape
        fp8_view = fp8_data.view(m, -1, 128)
        scales_expanded = scales.unsqueeze(2)
        reconstructed = fp8_view.float() * scales_expanded
        reconstructed = reconstructed.view(m, -1)[:, :original.shape[1]]

    # Compare
    abs_error = torch.abs(original.float() - reconstructed).max().item()
    rel_error = abs_error / torch.abs(original.float()).max().item()

    print(f"FP8 conversion error: {abs_error:.6f} ({rel_error*100:.3f}%)")
    return abs_error < 1e-2  # Reasonable threshold for FP8

# Validate our conversions
lhs_valid = validate_fp8_conversion(lhs, lhs_fp8, lhs_scales)
rhs_valid = validate_fp8_conversion(rhs, rhs_fp8[0], rhs_scales[0])

print(f"LHS conversion valid: {lhs_valid}")
print(f"RHS conversion valid: {rhs_valid}")