Error due to mismatch of size of pretrained weights of inception

Question

Error due to mismatch of size of pretrained weights of inception

pradeeprathore04 opened this issue 6 years ago · comments

(pytorch) pradeepr@Pradeep-Desktop:~/Desktop/Summer_2018/realtime_gesture_try/MFF-pytorch$ python test_models.py jester RGBFlow pretrained_models/MFF_jester_RGB
Flow_BNInception_segment8_3f1c_best.pth.tar --arch BNInception --consensus_type MLP --test_crops 1 --num_motion 3 --test_segments 4

Initializing TSN with base model: BNInception.
TSN Configurations:
    input_modality:     RGBFlow
    num_segments:       4
    new_length:         3
    consensus_module:   MLP
    dropout_ratio:      0.8
    img_feature_dim:    256

Traceback (most recent call last):
File "test_models.py", line 78, in
img_feature_dim=args.img_feature_dim,
File "/home/pradeepr/Desktop/Summer_2018/realtime_gesture_try/MFF-pytorch/models.py", line 51, in init
self._prepare_base_model(base_model)
File "/home/pradeepr/Desktop/Summer_2018/realtime_gesture_try/MFF-pytorch/models.py", line 120, in _prepare_base_model
self.base_model = getattr(model_zoo, base_model)()
File "/home/pradeepr/Desktop/Summer_2018/realtime_gesture_try/MFF-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/pradeepr/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/nn/modules/module.py", line 721, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for BNInception:
While copying the parameter named "conv1_7x7_s2_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "conv1_7x7_s2_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "conv1_7x7_s2_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "conv1_7x7_s2_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "conv2_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "conv2_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "conv2_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "conv2_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "conv2_3x3_bn.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 "conv2_3x3_bn.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 "conv2_3x3_bn.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 "conv2_3x3_bn.running_var", 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 "inception_3a_1x1_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_1x1_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_1x1_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_1x1_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_3x3_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_3x3_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_3x3_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_3x3_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_double_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_double_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_double_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_double_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3a_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3a_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3a_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3a_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3a_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3a_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3a_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3a_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3a_pool_proj_bn.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 "inception_3a_pool_proj_bn.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 "inception_3a_pool_proj_bn.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 "inception_3a_pool_proj_bn.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 "inception_3b_1x1_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_1x1_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_1x1_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_1x1_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_3x3_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_3x3_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_3x3_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_3x3_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_double_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_double_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_double_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_double_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3b_pool_proj_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_pool_proj_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_pool_proj_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3b_pool_proj_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3c_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_3c_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_3c_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_3c_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_3c_3x3_bn.weight", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_3c_3x3_bn.bias", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_3c_3x3_bn.running_mean", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_3c_3x3_bn.running_var", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_3c_double_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3c_double_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3c_double_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3c_double_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_3c_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3c_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3c_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3c_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3c_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3c_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3c_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_3c_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_1x1_bn.weight", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_4a_1x1_bn.bias", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_4a_1x1_bn.running_mean", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_4a_1x1_bn.running_var", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_4a_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_4a_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_4a_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_4a_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([64]) and whose dimensions in the checkpoint are torch.Size([1, 64]).
While copying the parameter named "inception_4a_3x3_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_3x3_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_3x3_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_3x3_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_double_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_double_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_double_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_double_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4a_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_pool_proj_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_pool_proj_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_pool_proj_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4a_pool_proj_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_1x1_bn.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 "inception_4b_1x1_bn.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 "inception_4b_1x1_bn.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 "inception_4b_1x1_bn.running_var", 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 "inception_4b_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4b_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4b_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4b_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4b_3x3_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_3x3_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_3x3_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_3x3_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_double_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4b_double_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4b_double_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4b_double_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4b_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_pool_proj_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_pool_proj_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_pool_proj_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4b_pool_proj_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_1x1_bn.weight", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_1x1_bn.bias", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_1x1_bn.running_mean", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_1x1_bn.running_var", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_3x3_bn.weight", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_3x3_bn.bias", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_3x3_bn.running_mean", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_3x3_bn.running_var", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_double_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_double_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_double_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_double_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4c_pool_proj_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_pool_proj_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_pool_proj_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4c_pool_proj_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4d_1x1_bn.weight", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4d_1x1_bn.bias", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4d_1x1_bn.running_mean", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4d_1x1_bn.running_var", whose dimensions in the model are torch.Size([96]) and whose dimensions in the checkpoint are torch.Size([1, 96]).
While copying the parameter named "inception_4d_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4d_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4d_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4d_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4d_3x3_bn.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 "inception_4d_3x3_bn.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 "inception_4d_3x3_bn.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 "inception_4d_3x3_bn.running_var", 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 "inception_4d_double_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4d_double_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4d_double_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4d_double_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_4d_double_3x3_1_bn.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 "inception_4d_double_3x3_1_bn.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 "inception_4d_double_3x3_1_bn.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 "inception_4d_double_3x3_1_bn.running_var", 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 "inception_4d_double_3x3_2_bn.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 "inception_4d_double_3x3_2_bn.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 "inception_4d_double_3x3_2_bn.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 "inception_4d_double_3x3_2_bn.running_var", 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 "inception_4d_pool_proj_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4d_pool_proj_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4d_pool_proj_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4d_pool_proj_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4e_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4e_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4e_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4e_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_4e_3x3_bn.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 "inception_4e_3x3_bn.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 "inception_4e_3x3_bn.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 "inception_4e_3x3_bn.running_var", 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 "inception_4e_double_3x3_reduce_bn.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 "inception_4e_double_3x3_reduce_bn.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 "inception_4e_double_3x3_reduce_bn.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 "inception_4e_double_3x3_reduce_bn.running_var", 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 "inception_4e_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([256]) and whose dimensions in the checkpoint are torch.Size([1, 256]).
While copying the parameter named "inception_4e_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([256]) and whose dimensions in the checkpoint are torch.Size([1, 256]).
While copying the parameter named "inception_4e_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([256]) and whose dimensions in the checkpoint are torch.Size([1, 256]).
While copying the parameter named "inception_4e_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([256]) and whose dimensions in the checkpoint are torch.Size([1, 256]).
While copying the parameter named "inception_4e_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([256]) and whose dimensions in the checkpoint are torch.Size([1, 256]).
While copying the parameter named "inception_4e_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([256]) and whose dimensions in the checkpoint are torch.Size([1, 256]).
While copying the parameter named "inception_4e_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([256]) and whose dimensions in the checkpoint are torch.Size([1, 256]).
While copying the parameter named "inception_4e_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([256]) and whose dimensions in the checkpoint are torch.Size([1, 256]).
While copying the parameter named "inception_5a_1x1_bn.weight", whose dimensions in the model are torch.Size([352]) and whose dimensions in the checkpoint are torch.Size([1, 352]).
While copying the parameter named "inception_5a_1x1_bn.bias", whose dimensions in the model are torch.Size([352]) and whose dimensions in the checkpoint are torch.Size([1, 352]).
While copying the parameter named "inception_5a_1x1_bn.running_mean", whose dimensions in the model are torch.Size([352]) and whose dimensions in the checkpoint are torch.Size([1, 352]).
While copying the parameter named "inception_5a_1x1_bn.running_var", whose dimensions in the model are torch.Size([352]) and whose dimensions in the checkpoint are torch.Size([1, 352]).
While copying the parameter named "inception_5a_3x3_reduce_bn.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 "inception_5a_3x3_reduce_bn.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 "inception_5a_3x3_reduce_bn.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 "inception_5a_3x3_reduce_bn.running_var", 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 "inception_5a_3x3_bn.weight", whose dimensions in the model are torch.Size([320]) and whose dimensions in the checkpoint are torch.Size([1, 320]).
While copying the parameter named "inception_5a_3x3_bn.bias", whose dimensions in the model are torch.Size([320]) and whose dimensions in the checkpoint are torch.Size([1, 320]).
While copying the parameter named "inception_5a_3x3_bn.running_mean", whose dimensions in the model are torch.Size([320]) and whose dimensions in the checkpoint are torch.Size([1, 320]).
While copying the parameter named "inception_5a_3x3_bn.running_var", whose dimensions in the model are torch.Size([320]) and whose dimensions in the checkpoint are torch.Size([1, 320]).
While copying the parameter named "inception_5a_double_3x3_reduce_bn.weight", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_5a_double_3x3_reduce_bn.bias", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_5a_double_3x3_reduce_bn.running_mean", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_5a_double_3x3_reduce_bn.running_var", whose dimensions in the model are torch.Size([160]) and whose dimensions in the checkpoint are torch.Size([1, 160]).
While copying the parameter named "inception_5a_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5a_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5a_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5a_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5a_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5a_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5a_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5a_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5a_pool_proj_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_5a_pool_proj_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_5a_pool_proj_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_5a_pool_proj_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_5b_1x1_bn.weight", whose dimensions in the model are torch.Size([352]) and whose dimensions in the checkpoint are torch.Size([1, 352]).
While copying the parameter named "inception_5b_1x1_bn.bias", whose dimensions in the model are torch.Size([352]) and whose dimensions in the checkpoint are torch.Size([1, 352]).
While copying the parameter named "inception_5b_1x1_bn.running_mean", whose dimensions in the model are torch.Size([352]) and whose dimensions in the checkpoint are torch.Size([1, 352]).
While copying the parameter named "inception_5b_1x1_bn.running_var", whose dimensions in the model are torch.Size([352]) and whose dimensions in the checkpoint are torch.Size([1, 352]).
While copying the parameter named "inception_5b_3x3_reduce_bn.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 "inception_5b_3x3_reduce_bn.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 "inception_5b_3x3_reduce_bn.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 "inception_5b_3x3_reduce_bn.running_var", 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 "inception_5b_3x3_bn.weight", whose dimensions in the model are torch.Size([320]) and whose dimensions in the checkpoint are torch.Size([1, 320]).
While copying the parameter named "inception_5b_3x3_bn.bias", whose dimensions in the model are torch.Size([320]) and whose dimensions in the checkpoint are torch.Size([1, 320]).
While copying the parameter named "inception_5b_3x3_bn.running_mean", whose dimensions in the model are torch.Size([320]) and whose dimensions in the checkpoint are torch.Size([1, 320]).
While copying the parameter named "inception_5b_3x3_bn.running_var", whose dimensions in the model are torch.Size([320]) and whose dimensions in the checkpoint are torch.Size([1, 320]).
While copying the parameter named "inception_5b_double_3x3_reduce_bn.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 "inception_5b_double_3x3_reduce_bn.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 "inception_5b_double_3x3_reduce_bn.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 "inception_5b_double_3x3_reduce_bn.running_var", 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 "inception_5b_double_3x3_1_bn.weight", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5b_double_3x3_1_bn.bias", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5b_double_3x3_1_bn.running_mean", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5b_double_3x3_1_bn.running_var", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5b_double_3x3_2_bn.weight", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5b_double_3x3_2_bn.bias", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5b_double_3x3_2_bn.running_mean", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5b_double_3x3_2_bn.running_var", whose dimensions in the model are torch.Size([224]) and whose dimensions in the checkpoint are torch.Size([1, 224]).
While copying the parameter named "inception_5b_pool_proj_bn.weight", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_5b_pool_proj_bn.bias", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_5b_pool_proj_bn.running_mean", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).
While copying the parameter named "inception_5b_pool_proj_bn.running_var", whose dimensions in the model are torch.Size([128]) and whose dimensions in the checkpoint are torch.Size([1, 128]).

pradeeprathore04 · Answer 1 · Tue Jun 12 2018 12:27:03 GMT+0800 (China Standard Time)

please help!!

Okan Köpüklü · Answer 2 · Tue Jun 12 2018 16:30:56 GMT+0800 (China Standard Time)

Hi pradeeprathore04 ,
There are several issues I want to point out. First, please use git clone --recursive https://github.com/okankop/MFF-pytorch to clone this project Otherwise you will not be able to use the inception series CNN architecture. Second, you are trying to load 8 segmented pretrained model (MFF_jester_RGBFlow_BNInception_segment8_3f1c_best.pth.tar) and try to test it with 4 segments (--test_segments 4).

I hope these solve your problems.

pradeeprathore04 · Answer 3 · Wed Jun 20 2018 21:11:34 GMT+0800 (China Standard Time)

I am extremely sorry for the late reply. Also, thanks a lot for your prompt reply and the awesome work you have done in the paper.

I have applied both of your suggestions but still getting the exact same error. I am using python 3.6 I would be grateful if you can please help.

Thanks a lot

Okan Köpüklü · Answer 4 · Wed Jun 20 2018 22:09:48 GMT+0800 (China Standard Time)

Hi pradeeprathore04,
Could you please check your torch installation? Because, the error you are getting is occurring when you attempt to load pretrained BNInception weights.
**File "/home/pradeepr/Desktop/Summer_2018/realtime_gesture_try/MFF-pytorch/model_zoo/bninception/pytorch_load.py", line 35**

You can continue working with Python 3.6 and torch 0.3.1.

The following steps are proved to be working by many users. Could you please also follow the steps below:

Proper installation of necessary packages (Python, opencv, torch etc...)
Cloning the repo: git clone --recursive https://github.com/okankop/MFF-pytorch
Dataset preparation (optical flow extraction and placing the dataset to MFF-pytorch/datasets/jester), also place the necessary category.txt, train_videofolder.txt and val_videofolder.txt under MFF-pytorch/jester.
Run test_models.py

Yong · Answer 5 · Thu Jun 21 2018 16:57:32 GMT+0800 (China Standard Time)

@pradeeprathore04 Hi guys, Did u deal with this problem ? I got the same problem as you!
Looking forward to any replies

lianuo · Answer 6 · Wed Jun 27 2018 16:58:19 GMT+0800 (China Standard Time)

I have the same prolem, my pytorch is 0.4....

Okan Köpüklü · Answer 7 · Wed Jun 27 2018 18:14:57 GMT+0800 (China Standard Time)

I have merged the model_zoo from the original branch again. Dimension problem should be resolved now. Tested it again with Python 3.6 and torch 0.3.1.

Please let me know if the problem persists.

Okan Köpüklü · Answer 8 · Wed Jun 27 2018 18:20:03 GMT+0800 (China Standard Time)

And please use git clone --recursive https://github.com/okankop/MFF-pytorch to clone the repo.

pradeeprathore04 · Answer 9 · Tue Jul 10 2018 18:53:17 GMT+0800 (China Standard Time)

@Ai-is-light We haven't figure out the solution till yet. We are not working on MFF for some time. In near future, If I will be able to solve the problem, I will let you know. Again, Thanks a lot @okankop for your amazing work and prompt response.

ArtashesH · Answer 10 · Thu Jul 12 2018 04:14:49 GMT+0800 (China Standard Time)

HI All,
I have python 3.6.1 and pytorch 0.4.0 on my side. Had done MFF-torch clone with --recursive option as well. But have the problem mentioned on head part. Can we help , please to see, the problem is solvable now or not?

Okan Köpüklü · Answer 11 · Thu Jul 12 2018 04:56:25 GMT+0800 (China Standard Time)

Could you please try with pytorch 0.3.1 and report back? Newer versions of torch can cause this issue as in yjxiong/action-detection#48.

ArtashesH · Answer 12 · Thu Jul 12 2018 14:22:43 GMT+0800 (China Standard Time)

Thanks for answer.
I am trying with both pythorch 0.4.0 and 0.3.1 . Only in the case of 0.4.0 model size problem, in the case of 0.3.1 problem is connected with memory synchronizing. So the main question is, that now needs to clarify is.
Am I need to have dataset extracted and optical flow generated folders? And if yes, could you please tell which structure and names will have folders for datasets.

Omenranr · Answer 13 · Tue Apr 30 2019 06:09:00 GMT+0800 (China Standard Time)

This error is due to difference in pytorch version, you should have the pytorch0.3.1 to be able to load bninception.