Stable-Diffusion-WebUI-TensorRT: [v0.2.0] ValueError: __len__() should return >= 0

Input Prompt Length: 75

Generation Parameters:

• Width: 320
• Height: 640
• having 4 profiles generated by v0.1.0

Error Log

    Traceback (most recent call last):
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\txt2img.py", line 55, in txt2img
        processed = processing.process_images(p)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 734, in process_images
        res = process_images_inner(p)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 868, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 1142, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 235, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_common.py", line 261, in launch_sampling
        return func()
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 235, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "C:\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 594, in sample_dpmpp_2m
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_cfg_denoiser.py", line 188, in forward
        x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
      File "C:\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
        eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
        return self.inner_model.apply_model(*args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in <lambda>
        setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in __call__
        return self.__orig_func(*args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
        x_recon = self.model(x_noisy, t, **cond)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
        out = self.diffusion_model(x, t, context=cc)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\modules\sd_unet.py", line 89, in UNetModel_forward
        return current_unet.forward(x, timesteps, context, *args, **kwargs)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py", line 70, in forward
        self.engine.allocate_buffers(feed_dict)
      File "C:\stable-diffusion-webui\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\utilities.py", line 304, in allocate_buffers
        tuple(shape), dtype=numpy_to_torch_dtype_dict[dtype]
    ValueError: __len__() should return >= 0

Image can be generated when SD Unet is disabled explicitly.