Error running example

[hcen001]

Hello,

I cloned the repo as specified and tried running the example, but I got the following message:

While copying the parameter named "conv_batchnorm.weight", whose dimensions in the model are torch.Size([32]) and whose dimensions in the checkpoint are torch.Size([1, 32]).
While copying the parameter named "conv_batchnorm.bias", whose dimensions in the model are torch.Size([32]) and whose dimensions in the checkpoint are torch.Size([1, 32]).
While copying the parameter named "conv_batchnorm.running_mean", whose dimensions in the model are torch.Size([32]) and whose dimensions in the checkpoint are torch.Size([1, 32]).
While copying the parameter named "conv_batchnorm.running_var", whose dimensions in the model are torch.Size([32]) and whose dimensions in the checkpoint are torch.Size([1, 32]).
While copying the parameter named "conv_1_batchnorm.weight", whose dimensions in the model are torch.Size([32]) and whose dimensions in the checkpoint are torch.Size([1, 32]).
While copying the parameter named "conv_1_batchnorm.bias", whose dimensions in the model are torch.Size([32]) and whose dimensions in the checkpoint are torch.Size([1, 32]).
While copying the parameter named "conv_1_batchnorm.running_mean", whose dimensions in the model are torch.Size([32]) and whose dimensions in the checkpoint are torch.Size([1, 32]).
While copying the parameter named "conv_1_batchnorm.running_var", whose dimensions in the model are torch.Size([32]) and whose dimensions in the checkpoint are torch.Size([1, 32]).
...
While copying the parameter named "mixed_10_tower_1_mixed_conv_1_batchnorm.running_var", whose dimensions in the model are torch.Size([384]) and whose dimensions in the checkpoint are torch.Size([1, 384]).
While copying the parameter named "mixed_10_tower_2_conv_batchnorm.weight", whose dimensions in the model are torch.Size([192]) and whose dimensions in the checkpoint are torch.Size([1, 192]).
While copying the parameter named "mixed_10_tower_2_conv_batchnorm.bias", whose dimensions in the model are torch.Size([192]) and whose dimensions in the checkpoint are torch.Size([1, 192]).
While copying the parameter named "mixed_10_tower_2_conv_batchnorm.running_mean", whose dimensions in the model are torch.Size([192]) and whose dimensions in the checkpoint are torch.Size([1, 192]).
While copying the parameter named "mixed_10_tower_2_conv_batchnorm.running_var", whose dimensions in the model are torch.Size([192]) and whose dimensions in the checkpoint are torch.Size([1, 192]).

The command I used was the following:

python test_video.py --frame_folder ~/35345/ --weight TRN_moments_RGB_InceptionV3_TRNmultiscale_segment8_best.pth.tar --arch InceptionV3

Tried running the example in the repo and with a frames folder of my own and got the same message.

Thanks in advance for any help you can provide

[Jessespace]

try with python2/anaconda2

[hcen001]

I already tried to no avail. Got the same output.

Thanks.

[alexandonian]

Hi,

This issue is related to upgrading to the latest version of PyTorch (v0.4). See this issue for a potential solution.

Let me know if this helps.

Best, Alex A.

[hcen001]

Hi @alexandonian,

Indeed, it worked. Thank you very much.

I have another related question: What is the minimum number of frames required for the provided test_video.py script to work? I tested a folder with 10 frames and got the following error:

RuntimeError: invalid argument 2: size '[-1 x 8 x 256]' is invalid for input with 12800 elements at ...

I then copied the same files twice, for a total of 30 frames and it worked. Is there any minimum required number of frames?

Thanks in advance.

[valeriechen]

Which version of pytorch does the code work with? I figured I would download a previous version instead of the newest upgrade..

[alexandonian]

@hcen001, The pretrained models we release all need to be given 8 frames. This function here attempts to select 8 equally spaced frames from the ones you provide. In your case of 10 frames, this doesn't work properly (a step size of 2 is chosen and with 10 frames, only 5 are selected). Here, you will need to use a different strategy for selecting the frames. Perhaps you could even submit a PR with a fix for this?! If not, no worries.

@valeriechen, This code should work out-of-the-box with PyTorch v0.3. If you must use v0.4, then you will need to apply the workaround explained in this issue for now.

[sahajayogi]

Namespace(arch='BNInception', batch_size=64, clip_gradient=20, consensus_type='TRN', dataset='somethingv2', dropout=0.8, epochs=120, eval_freq=5, evaluate=False, flow_prefix='', gpus=None, img_feature_dim=256, k=3, loss_type='nll', lr=0.001, lr_steps=[50, 100], modality='RGB', momentum=0.9, no_partialbn=False, num_segments=3, print_freq=20, resume='', root_log='log', root_model='model', root_output='output', root_path='', snapshot_pref='', start_epoch=0, store_name='', train_list='', val_list='', weight_decay=0.0005, workers=30) storing name: TRN_somethingv2_RGB_BNInception_TRN_segment3

Initializing TSN with base model: BNInception.
TSN Configurations:
    input_modality:     RGB
    num_segments:       3
    new_length:         1
    consensus_module:   TRN
    dropout_ratio:      0.8
    img_feature_dim:    256

/home/test/Desktop/TRN/TRN-pytorch/model_zoo/bninception/pytorch_load.py:13: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. manifest = yaml.load(open(model_path)) Traceback (most recent call last): File "main.py", line 324, in main() File "main.py", line 39, in main partial_bn=not args.no_partialbn) File "/home/test/Desktop/TRN/TRN-pytorch/models.py", line 43, in init self._prepare_base_model(base_model) File "/home/test/Desktop/TRN/TRN-pytorch/models.py", line 108, in _prepare_base_model self.base_model = getattr(model_zoo, base_model)() File "/home/test/Desktop/TRN/TRN-pytorch/model_zoo/bninception/pytorch_load.py", line 35, in init self.load_state_dict(torch.utils.model_zoo.load_url(weight_url)) File "/home/test/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 777, in load_state_dict self.class.name, "\n\t".join(error_msgs))) RuntimeError: Error(s) in loading state_dict for BNInception: size mismatch for conv1_7x7_s2_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for conv1_7x7_s2_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for conv1_7x7_s2_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for conv1_7x7_s2_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for conv2_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for conv2_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for conv2_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for conv2_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for conv2_3x3_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for conv2_3x3_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for conv2_3x3_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for conv2_3x3_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_3a_1x1_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_1x1_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_1x1_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_1x1_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_3x3_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_3x3_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_3x3_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_3x3_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3a_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3a_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3a_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3a_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3a_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3a_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3a_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3a_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3a_pool_proj_bn.weight: copying a param with shape torch.Size([1, 32]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for inception_3a_pool_proj_bn.bias: copying a param with shape torch.Size([1, 32]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for inception_3a_pool_proj_bn.running_mean: copying a param with shape torch.Size([1, 32]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for inception_3a_pool_proj_bn.running_var: copying a param with shape torch.Size([1, 32]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for inception_3b_1x1_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_1x1_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_1x1_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_1x1_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_3x3_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_3x3_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_3x3_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_3x3_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3b_pool_proj_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_pool_proj_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_pool_proj_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3b_pool_proj_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3c_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_3c_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_3c_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_3c_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_3c_3x3_bn.weight: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_3c_3x3_bn.bias: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_3c_3x3_bn.running_mean: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_3c_3x3_bn.running_var: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_3c_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3c_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3c_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3c_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_3c_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3c_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3c_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3c_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3c_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3c_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3c_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_3c_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_1x1_bn.weight: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_4a_1x1_bn.bias: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_4a_1x1_bn.running_mean: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_4a_1x1_bn.running_var: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_4a_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_4a_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_4a_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_4a_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 64]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for inception_4a_3x3_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_3x3_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_3x3_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_3x3_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4a_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_pool_proj_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_pool_proj_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_pool_proj_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4a_pool_proj_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_1x1_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4b_1x1_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4b_1x1_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4b_1x1_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4b_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4b_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4b_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4b_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4b_3x3_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_3x3_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_3x3_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_3x3_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4b_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4b_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4b_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4b_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_pool_proj_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_pool_proj_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_pool_proj_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4b_pool_proj_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_1x1_bn.weight: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_1x1_bn.bias: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_1x1_bn.running_mean: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_1x1_bn.running_var: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_3x3_bn.weight: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_3x3_bn.bias: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_3x3_bn.running_mean: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_3x3_bn.running_var: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4c_pool_proj_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_pool_proj_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_pool_proj_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4c_pool_proj_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4d_1x1_bn.weight: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4d_1x1_bn.bias: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4d_1x1_bn.running_mean: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4d_1x1_bn.running_var: copying a param with shape torch.Size([1, 96]) from checkpoint, the shape in current model is torch.Size([96]). size mismatch for inception_4d_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4d_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4d_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4d_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4d_3x3_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_3x3_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_3x3_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_3x3_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4d_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4d_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4d_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_4d_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4d_pool_proj_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4d_pool_proj_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4d_pool_proj_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4d_pool_proj_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4e_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4e_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4e_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4e_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_4e_3x3_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4e_3x3_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4e_3x3_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4e_3x3_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4e_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4e_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4e_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4e_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_4e_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 256]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for inception_4e_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 256]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for inception_4e_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 256]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for inception_4e_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 256]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for inception_4e_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 256]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for inception_4e_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 256]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for inception_4e_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 256]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for inception_4e_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 256]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for inception_5a_1x1_bn.weight: copying a param with shape torch.Size([1, 352]) from checkpoint, the shape in current model is torch.Size([352]). size mismatch for inception_5a_1x1_bn.bias: copying a param with shape torch.Size([1, 352]) from checkpoint, the shape in current model is torch.Size([352]). size mismatch for inception_5a_1x1_bn.running_mean: copying a param with shape torch.Size([1, 352]) from checkpoint, the shape in current model is torch.Size([352]). size mismatch for inception_5a_1x1_bn.running_var: copying a param with shape torch.Size([1, 352]) from checkpoint, the shape in current model is torch.Size([352]). size mismatch for inception_5a_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5a_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5a_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5a_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5a_3x3_bn.weight: copying a param with shape torch.Size([1, 320]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for inception_5a_3x3_bn.bias: copying a param with shape torch.Size([1, 320]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for inception_5a_3x3_bn.running_mean: copying a param with shape torch.Size([1, 320]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for inception_5a_3x3_bn.running_var: copying a param with shape torch.Size([1, 320]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for inception_5a_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_5a_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_5a_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_5a_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 160]) from checkpoint, the shape in current model is torch.Size([160]). size mismatch for inception_5a_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5a_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5a_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5a_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5a_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5a_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5a_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5a_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5a_pool_proj_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_5a_pool_proj_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_5a_pool_proj_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_5a_pool_proj_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_5b_1x1_bn.weight: copying a param with shape torch.Size([1, 352]) from checkpoint, the shape in current model is torch.Size([352]). size mismatch for inception_5b_1x1_bn.bias: copying a param with shape torch.Size([1, 352]) from checkpoint, the shape in current model is torch.Size([352]). size mismatch for inception_5b_1x1_bn.running_mean: copying a param with shape torch.Size([1, 352]) from checkpoint, the shape in current model is torch.Size([352]). size mismatch for inception_5b_1x1_bn.running_var: copying a param with shape torch.Size([1, 352]) from checkpoint, the shape in current model is torch.Size([352]). size mismatch for inception_5b_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5b_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5b_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5b_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5b_3x3_bn.weight: copying a param with shape torch.Size([1, 320]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for inception_5b_3x3_bn.bias: copying a param with shape torch.Size([1, 320]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for inception_5b_3x3_bn.running_mean: copying a param with shape torch.Size([1, 320]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for inception_5b_3x3_bn.running_var: copying a param with shape torch.Size([1, 320]) from checkpoint, the shape in current model is torch.Size([320]). size mismatch for inception_5b_double_3x3_reduce_bn.weight: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5b_double_3x3_reduce_bn.bias: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5b_double_3x3_reduce_bn.running_mean: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5b_double_3x3_reduce_bn.running_var: copying a param with shape torch.Size([1, 192]) from checkpoint, the shape in current model is torch.Size([192]). size mismatch for inception_5b_double_3x3_1_bn.weight: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5b_double_3x3_1_bn.bias: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5b_double_3x3_1_bn.running_mean: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5b_double_3x3_1_bn.running_var: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5b_double_3x3_2_bn.weight: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5b_double_3x3_2_bn.bias: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5b_double_3x3_2_bn.running_mean: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5b_double_3x3_2_bn.running_var: copying a param with shape torch.Size([1, 224]) from checkpoint, the shape in current model is torch.Size([224]). size mismatch for inception_5b_pool_proj_bn.weight: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_5b_pool_proj_bn.bias: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_5b_pool_proj_bn.running_mean: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for inception_5b_pool_proj_bn.running_var: copying a param with shape torch.Size([1, 128]) from checkpoint, the shape in current model is torch.Size([128]).

[sahajayogi]

Please guide me to fix this error