Is there any parameter to control the input dimension of the test dataset?

[linmi1]

I want to downsaple the images but get the dimension issue,Also , if I want to use the NeRF in my own dataset ,It will face the same question.I wonder how to solve it，if there is any parameters to control? !!!(I downsample the images to 192*256)
It is the log:

Namespace(L1_weight_inital=0.0, L1_weight_rest=0, N_vis=-1, N_voxel_final=262144000, N_voxel_init=16777216, Ortho_weight=0.0, TV_dynamic_factor=3.0, TV_loss_end_iteration=100000, TV_weight_app=1.0, TV_weight_density=1.0, accumulate_decay=0.998, activation='relu', add_timestamp=0, alpha_mask_thre=1e-05, amp=1, basedir='./logs', batch_factor=[8.0, 8.0, 2.0, 1.0], batch_size=128, cam_offset=True, camoffset_lr_factor=0.5, chromakey=False, ckpt=None, config='/home/vision/work/linmi/Sync-NeRF-master/Sync-MixVoxels/configs/plenoptic/cook_spinach.txt', data_dim_color=27, data_dim_density=27, datadir='/home/vision/work/linmi/Sync-NeRF-master/Sync-MixVoxels/dataset/video_downsample', dataset_name='llffvideo', dense_alpha=0, densityMode='None', density_shift=-10, diffuse_kernel=0, distance_scale=25, downsample_test=1.0, downsample_train=1.0, dy_loss='l2', dynamic_granularity='point_wise', dynamic_only_ray_start_iteration=-1, dynamic_pool_kernel_size=21, dynamic_reg_weight=0.1, dynamic_threshold=0.9, dynamic_use_volumetric_render=0, dynamic_weight_decay=0.0, expname='cook_spinach', export_mesh=0, far=1.0, fea2denseAct='relu', fea_pe=0, featureC=512, featureD=512, filter_loss_weight=0, filter_threshold=1.0, frame_start=0, gamma_end=0.02, gamma_start=0.02, gaussian=0, idx_view=0, init_dynamic_a=-0.1, init_dynamic_b=0.1, init_dynamic_mean=0.0, init_dynamic_std=0.1, init_dynamic_voxel='none', init_static_a=-0.1, init_static_b=0.1, init_static_mean=0.0, init_static_std=0.1, init_static_voxel='none', interpolation='bilinear', l1gamma=0.001, l1loss=True, lindisp=False, loss_weight_static=1.0, loss_weight_thresh_end=0.0, loss_weight_thresh_start=0.0, lr_basis=0.002, lr_decay_iters=-1, lr_decay_target_ratio=0.1, lr_dynamic_basis=0.002, lr_dynamic_init=0.03, lr_init=0.03, lr_upsample_reset=1, meta_config=None, model_name='TensorVMSplit', nSamples=1000000.0, n_dynamic_iters=2000, n_frame_for_static=2, n_frames=270, n_iters=50000, n_iters_pre=10000, n_iters_test=500, n_lamb_sh=[48, 12, 12], n_lamb_sh_dynamic=None, n_lamb_sigma=[16, 4, 4], n_lamb_sigma_dynamic=None, n_layer=2, n_time_embedding=150, n_train_frames=270, ndc_ray=1, near=0.0, net_layer_add=0, netspec_dy_color='i-d-d-o', netspec_dy_density='i-d-d-o', no_load_timequery=False, offset_start_iters=0, optimizer='adam', perturb=1.0, point_wise_dynamic_threshold=0.01, pos_pe=6, progress_refresh_rate=10, ray_sampler='simple', ray_sampler_shift=3000, ray_weight_gamma=1, ray_weighted=0, rel_pos_pe=6, remove_foreground=0, render_only=0, render_path=0, render_path_start=0, render_test=1, render_train=0, render_views=120, rgb_diff_log_thresh=0.2, rgb_diff_weight=0.0, rm_weight_mask_thre=0.0001, rm_weight_mask_thre_static=1e-05, scene_box=[-3.0, -3.0, -1.5], shadingMode='MLP_Fea', shift_std=-1, sigma_decay=0.0, sigma_decay_method='l2', sigma_decay_static=0.0, sigma_diff_log_thresh=0.05, sigma_diff_method='log', sigma_diff_weight=0.0, sigma_entropy_weight=0, sigma_entropy_weight_static=0, sigma_static_thresh=0.1, simple_sample_weight=0, simple_sample_weight_end=0, sparsity_lambda=1.0, ssd_dir='./data/llff/fern', static_branch_only_initial=0, static_dynamic_seperate=1, static_featureC=128, static_loss='l2', static_point_detach=1, static_type='mean', step_ratio=4.0, temperature_end=0.2, temperature_start=10.0, temporal_sampler='simple', temporal_sampler_method='mean', temporal_sampler_replace=1, temporal_variance_threshold=0.02, test_cam_offset=0, test_optim=False, time_freq=10, time_head='timemlprender', time_head_pre='directdyrender', timemlp_lr_factor=5, update_AlphaMask_list=[2500], update_stepratio=None, update_stepratio_iters=None, upsamp_list=[2000, 3000, 4000, 5500], use_cosine_lr_scheduler=1, view_pe=0, vis_every=10000, voxel_init_dynamic=0.1, voxel_init_static=0.1, with_depth=False, zero_dynamic_sigma=1, zero_dynamic_sigma_thresh=1e-05)
train from-scratch
1.2 167.42230716678975
camlist: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]
Traceback (most recent call last):
  File "/home/vision/work/linmi/Sync-NeRF-master/Sync-MixVoxels/train.py", line 1324, in <module>
    reconstruction(args)
  File "/home/vision/work/linmi/Sync-NeRF-master/Sync-MixVoxels/train.py", line 231, in reconstruction
    train_dataset = dataset(args.datadir, split='train', downsample=args.downsample_train, is_stack=False, white_bg = args.chromakey,
  File "/home/vision/work/linmi/Sync-NeRF-master/Sync-MixVoxels/dataLoader/llff_video.py", line 295, in __init__
    self.read_meta(no_load, optimize_test)
  File "/home/vision/work/linmi/Sync-NeRF-master/Sync-MixVoxels/dataLoader/llff_video.py", line 436, in read_meta
    self.dynamic_rays = self.all_rays[dynamic_mask]
IndexError: The shape of the mask [983040] at index 0 does not match the shape of the indexed tensor [109674240, 6] at index 0