{"record":{"id":"5f453a3e27bd6818","repo":"Comfy-Org/ComfyUI","slug":"order-should-be-2-or-3","errorCode":null,"errorMessage":"order should be 2 or 3","messagePattern":"order should be 2 or 3","errorType":"validation","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"comfy/k_diffusion/sampling.py","lineNumber":569,"sourceCode":"            denoised = x - self.sigma(t) * eps\n            if self.info_callback is not None:\n                self.info_callback({'x': x, 'i': i, 't': ts[i], 't_up': t, 'denoised': denoised})\n\n            if orders[i] == 1:\n                x, eps_cache = self.dpm_solver_1_step(x, t, t_next_, eps_cache=eps_cache)\n            elif orders[i] == 2:\n                x, eps_cache = self.dpm_solver_2_step(x, t, t_next_, eps_cache=eps_cache)\n            else:\n                x, eps_cache = self.dpm_solver_3_step(x, t, t_next_, eps_cache=eps_cache)\n\n            x = x + su * s_noise * noise_sampler(self.sigma(t), self.sigma(t_next))\n\n        return x\n\n    def dpm_solver_adaptive(self, x, t_start, t_end, order=3, rtol=0.05, atol=0.0078, h_init=0.05, pcoeff=0., icoeff=1., dcoeff=0., accept_safety=0.81, eta=0., s_noise=1., noise_sampler=None):\n        noise_sampler = default_noise_sampler(x, seed=self.extra_args.get(\"seed\", None)) if noise_sampler is None else noise_sampler\n        if order not in {2, 3}:\n            raise ValueError('order should be 2 or 3')\n        forward = t_end > t_start\n        if not forward and eta:\n            raise ValueError('eta must be 0 for reverse sampling')\n        h_init = abs(h_init) * (1 if forward else -1)\n        atol = torch.tensor(atol)\n        rtol = torch.tensor(rtol)\n        s = t_start\n        x_prev = x\n        accept = True\n        pid = PIDStepSizeController(h_init, pcoeff, icoeff, dcoeff, 1.5 if eta else order, accept_safety)\n        info = {'steps': 0, 'nfe': 0, 'n_accept': 0, 'n_reject': 0}\n\n        while s < t_end - 1e-5 if forward else s > t_end + 1e-5:\n            eps_cache = {}\n            t = torch.minimum(t_end, s + pid.h) if forward else torch.maximum(t_end, s + pid.h)\n            if eta:\n                sd, su = get_ancestral_step(self.sigma(s), self.sigma(t), eta)\n                t_ = torch.minimum(t_end, self.t(sd))","sourceCodeStart":551,"sourceCodeEnd":587,"githubUrl":"https://github.com/Comfy-Org/ComfyUI/blob/1c6d8d45b3693bfbb32385b410d813a7fd6be216/comfy/k_diffusion/sampling.py#L551-L587","documentation":"Raised by DPMSolver.dpm_solver_adaptive when the requested multistep order is not 2 or 3. DPM-Solver-12 and DPM-Solver-23 are the only adaptive variants implemented (order 2 = 1-2 pair, order 3 = 2-3 pair); the adaptive error estimator and PID step controller are only coded for those two.","triggerScenarios":"Calling sample_dpm_adaptive(..., order=1) or order=4/5 through a custom node or script. The check is `order not in {2, 3}` before any stepping begins.","commonSituations":"Custom nodes exposing an order widget for dpm_solver_adaptive with values copied from the LMS sampler (1-4); API workflows edited by hand with an invalid order value.","solutions":["Use order=3 (default, DPM-Solver-23) or order=2 (DPM-Solver-12)","Restrict the node widget/combo for sample_dpm_adaptive to [2,3]","For other orders switch to a fixed-step sampler like sample_dpmpp_2m or sample_lms"],"exampleFix":"# before\nsample_dpm_adaptive(model, x, 0.03, 14.6, order=4)\n# after\nsample_dpm_adaptive(model, x, 0.03, 14.6, order=3)","handlingStrategy":"validation","validationCode":"assert order in (2, 3), 'sample_dpm_adaptive order must be 2 or 3'\nsample_dpm_adaptive(model, x, sigma_min, sigma_max, order=order)","typeGuard":"def is_valid_adaptive_order(order) -> bool:\n    return order in (2, 3)","tryCatchPattern":null,"preventionTips":["Restrict adaptive-order widgets to [2,3]","Do not reuse LMS order ranges for DPM adaptive samplers"],"tags":["sampling","dpm-solver","adaptive","parameter-validation"],"backgroundTag":null,"analyzedSha":"1c6d8d45b3693bfbb32385b410d813a7fd6be216","analyzedAt":"2026-08-14T19:37:18.893Z","schemaVersion":2},"datasetVersion":"2026-08-15T17:31:12.345Z"}