all inputs must share same datatype

help，help，How to resolve this error report

ERROR:root:!!! Exception during processing !!!
ERROR:root:Traceback (most recent call last):
File "J:\ComfyUI\execution.py", line 153, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "J:\ComfyUI\execution.py", line 83, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "J:\ComfyUI\execution.py", line 76, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "J:\ComfyUI\nodes.py", line 1237, in sample
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
File "J:\ComfyUI\nodes.py", line 1207, in common_ksampler
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
File "J:\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 190, in animatediff_sample
return wrap_function_to_inject_xformers_bug_info(orig_comfy_sample)(model, *args, **kwargs)
File "J:\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\model_utils.py", line 190, in wrapped_function
return function_to_wrap(*args, **kwargs)
File "J:\ComfyUI\comfy\sample.py", line 100, in sample
samples = sampler.sample(noise, positive_copy, negative_copy, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed)
File "J:\ComfyUI\comfy\samplers.py", line 691, in sample
return sample(self.model, noise, positive, negative, cfg, self.device, sampler(), sigmas, self.model_options, latent_image=latent_image, denoise_mask=denoise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)
File "J:\ComfyUI\comfy\samplers.py", line 597, in sample
samples = sampler.sample(model_wrap, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
File "J:\ComfyUI\comfy\samplers.py", line 557, in sample
samples = getattr(k_diffusion_sampling, "sample_{}".format(sampler_name))(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **extra_options)
File "J:\ComfyUI\enve\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "J:\ComfyUI\comfy\k_diffusion\sampling.py", line 137, in sample_euler
denoised = model(x, sigma_hat * s_in, **extra_args)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "J:\ComfyUI\comfy\samplers.py", line 274, in forward
out = self.inner_model(x, sigma, cond=cond, uncond=uncond, cond_scale=cond_scale, model_options=model_options, seed=seed)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "J:\ComfyUI\comfy\samplers.py", line 264, in forward
return self.apply_model(*args, **kwargs)
File "J:\ComfyUI\comfy\samplers.py", line 261, in apply_model
out = sampling_function(self.inner_model.apply_model, x, timestep, uncond, cond, cond_scale, model_options=model_options, seed=seed)
File "J:\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 550, in sliding_sampling_function
cond, uncond = calc_cond_uncond_batch(model_function, cond, uncond, x, timestep, max_total_area, model_options)
File "J:\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 432, in calc_cond_uncond_batch
output = model_function(input_x, timestep_, **c).chunk(batch_chunks)
File "J:\ComfyUI\comfy\model_base.py", line 65, in apply_model
model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "J:\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 625, in forward
h = forward_timestep_embed(module, h, emb, context, transformer_options)
File "J:\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 78, in forward_timestep_embed
x = layer(x, context)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "J:\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\motion_module_ad.py", line 165, in forward
return self.temporal_transformer(input_tensor, encoder_hidden_states, attention_mask)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "J:\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\motion_module_ad.py", line 236, in forward
hidden_states = self.norm(hidden_states)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "J:\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 102, in groupnorm_mm_forward
input = group_norm(input, self.num_groups, self.weight, self.bias, self.eps)
File "J:\ComfyUI\enve\lib\site-packages\torch\nn\functional.py", line 2558, in group_norm
return torch.group_norm(input, num_groups, weight, bias, eps, torch.backends.cudnn.enabled)
RuntimeError: mixed dtype (CPU): all inputs must share same datatype.