### Objective:
Trying to convert the "i3d-resnet50-v1-kinetics400" pretrained mxnet model to
caffe.
**System used: Ubuntu 18.04, Python3**
### Problem:
While trying to load weights after converting the .json to caffe model, I saw
that the names for layers in *.json* and *.params* files do not match. They can
be viewed below.
Eg. First layer names in *.json* and *.params* are *conv0_weight* and
*first_stage.0.weight* respectively.
I do not understand why this happened since the parameters and json are taken
from same model.
Can anyone suggest how to handle this except checking all the layers names
manually?
### Steps followed:
1. Loaded the model.
```
>>>from gluoncv.model_zoo import get_model
>>>from gluoncv.utils import export_block
>>>import mxnet
>>>import json
>>>model = get_model(name="i3d_resnet50_v1_kinetics400", nclass=400,
>>>pretrained=True, num_segments=1, num_crop=1)
```
2. Converted the model to json.
```
>>>js = model.to_json()
>>>js
{
"nodes": [
{
"op": "null",
"name": "data",
"inputs": []
},
{
"op": "null",
"name": "conv0_weight",
"attrs": {
"__dtype__": "0",
"__lr_mult__": "1.0",
"__shape__": "(64, 3, 5, 7, 7)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "Convolution",
"name": "conv0_fwd",
"attrs": {
"dilate": "(1, 1, 1)",
"kernel": "(5, 7, 7)",
"layout": "NCDHW",
"no_bias": "True",
"num_filter": "64",
"num_group": "1",
"pad": "(2, 3, 3)",
"stride": "(2, 2, 2)"
},
"inputs": [[0, 0, 0], [1, 0, 0]]
},
{
"op": "null",
"name": "batchnorm0_gamma",
"attrs": {
"__dtype__": "0",
"__init__": "ones",
"__lr_mult__": "1.0",
"__shape__": "(64,)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "null",
"name": "batchnorm0_beta",
"attrs": {
"__dtype__": "0",
"__init__": "zeros",
"__lr_mult__": "1.0",
"__shape__": "(64,)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "null",
"name": "batchnorm0_running_mean",
"attrs": {
"__dtype__": "0",
"__init__": "zeros",
"__lr_mult__": "1.0",
"__shape__": "(64,)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "null",
"name": "batchnorm0_running_var",
"attrs": {
"__dtype__": "0",
"__init__": "ones",
"__lr_mult__": "1.0",
"__shape__": "(64,)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "BatchNorm",
"name": "batchnorm0_fwd",
"attrs": {
"axis": "1",
"eps": "1e-05",
"fix_gamma": "False",
"momentum": "0.9",
"use_global_stats": "False"
},
"inputs": [[2, 0, 0], [3, 0, 0], [4, 0, 0], [5, 0, 1], [6, 0, 1]]
},
{
"op": "Activation",
"name": "relu0_fwd",
"attrs": {"act_type": "relu"},
"inputs": [[7, 0, 0]]
},
{
"op": "Pooling",
"name": "pool0_fwd",
"attrs": {
"global_pool": "False",
"kernel": "(1, 3, 3)",
"layout": "NCDHW",
"pad": "(0, 1, 1)",
"pool_type": "max",
"pooling_convention": "valid",
"stride": "(2, 2, 2)"
},
"inputs": [[8, 0, 0]]
},
{
"op": "null",
"name": "layer1_0_conv0_weight",
"attrs": {
"__dtype__": "0",
"__lr_mult__": "1.0",
"__shape__": "(64, 64, 3, 1, 1)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "Convolution",
"name": "layer1_0_conv0_fwd",
"attrs": {
"dilate": "(1, 1, 1)",
"kernel": "(3, 1, 1)",
"layout": "NCDHW",
"no_bias": "True",
"num_filter": "64",
"num_group": "1",
"pad": "(1, 0, 0)",
"stride": "(1, 1, 1)"
},
"inputs": [[9, 0, 0], [10, 0, 0]]
},
{
"op": "null",
"name": "layer1_0_batchnorm0_gamma",
"attrs": {
"__dtype__": "0",
"__init__": "ones",
"__lr_mult__": "1.0",
"__shape__": "(64,)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "null",
"name": "layer1_0_batchnorm0_beta",
"attrs": {
"__dtype__": "0",
"__init__": "zeros",
"__lr_mult__": "1.0",
"__shape__": "(64,)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "null",
"name": "layer1_0_batchnorm0_running_mean",
"attrs": {
"__dtype__": "0",
"__init__": "zeros",
"__lr_mult__": "1.0",
"__shape__": "(64,)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
},
"inputs": []
},
{
"op": "null",
"name": "layer1_0_batchnorm0_running_var",
"attrs": {
"__dtype__": "0",
"__init__": "ones",
"__lr_mult__": "1.0",
"__shape__": "(64,)",
"__storage_type__": "0",
"__wd_mult__": "1.0"
.
.
. Continued
```
3. Saving weights of the model using <a
href="https://mxnet.apache.org/versions/1.7.0/api/python/docs/tutorials/packages/gluon/blocks/save_load_params.html#Saving-model-parameters-to-file";>save_parameters()</a>.
```
>>> model.save_parameters("params_file")
>>> import mxnet.ndarray as nd
>>> tmp = nd.load("params_file.params")
>>> tmp.keys()
dict_keys(['first_stage.0.weight', 'first_stage.1.gamma', 'first_stage.1.beta',
'first_stage.1.running_mean', 'first_stage.1.running_var',
'res_layers.0.0.bottleneck.0.weight', 'res_layers.0.0.bottleneck.1.gamma',
'res_layers.0.0.bottleneck.1.beta', 'res_layers.0.0.bottleneck.1.running_mean',
'res_layers.0.0.bottleneck.1.running_var',
'res_layers.0.0.bottleneck.3.weight', 'res_layers.0.0.bottleneck.4.gamma',
'res_layers.0.0.bottleneck.4.beta', 'res_layers.0.0.bottleneck.4.running_mean',
'res_layers.0.0.bottleneck.4.running_var',
'res_layers.0.0.bottleneck.6.weight', 'res_layers.0.0.bottleneck.7.gamma',
'res_layers.0.0.bottleneck.7.beta', 'res_layers.0.0.bottleneck.7.running_mean',
'res_layers.0.0.bottleneck.7.running_var', 'res_layers.0.0.conv1.weight',
'res_layers.0.0.conv2.weight', 'res_layers.0.0.bn1.gamma',
'res_layers.0.0.bn1.beta', 'res_layers.0.0.bn1.running_mean',
'res_layers.0.0.bn1.running_var', 'res_layers.0.0.bn2.gamma',
'res_layers.0.0.bn2.beta', 'res_layers.0.0.bn2.running_mean',
'res_layers.0.0.bn2.running_var', 'res_layers.0.0.conv3.weight',
'res_layers.0.0.bn3.gamma', 'res_layers.0.0.bn3.beta',
'res_layers.0.0.bn3.running_mean', 'res_layers.0.0.bn3.running_var',
'res_layers.0.0.downsample.0.weight', 'res_layers.0.0.downsample.1.gamma',
'res_layers.0.0.downsample.1.beta', 'res_layers.0.0.downsample.1.running_mean',
'res_layers.0.0.downsample.1.running_var',
'res_layers.0.1.bottleneck.0.weight', 'res_layers.0.1.bottleneck.1.gamma',
'res_layers.0.1.bottleneck.1.beta', 'res_layers.0.1.bottleneck.1.running_mean',
'res_layers.0.1.bottleneck.1.running_var',
'res_layers.0.1.bottleneck.3.weight', 'res_layers.0.1.bottleneck.4.gamma',
'res_layers.0.1.bottleneck.4.beta', 'res_layers.0.1.bottleneck.4.running_mean',
'res_layers.0.1.bottleneck.4.running_var',
'res_layers.0.1.bottleneck.6.weight', 'res_layers.0.1.bottleneck.7.gamma',
'res_layers.0.1.bottleneck.7.beta', 'res_layers.0.1.bottleneck.7.running_mean',
'res_layers.0.1.bottleneck.7.running_var', 'res_layers.0.1.conv1.weight',
'res_layers.0.1.conv2.weight', 'res_layers.0.1.bn1.gamma',
'res_layers.0.1.bn1.beta', 'res_layers.0.1.bn1.running_mean',
'res_layers.0.1.bn1.running_var', 'res_layers.0.1.bn2.gamma',
'res_layers.0.1.bn2.beta', 'res_layers.0.1.bn2.running_mean',
'res_layers.0.1.bn2.running_var', 'res_layers.0.1.conv3.weight',
'res_layers.0.1.bn3.gamma', 'res_layers.0.1.bn3.beta',
'res_layers.0.1.bn3.running_mean', 'res_layers.0.1.bn3.running_var',
'res_layers.0.2.bottleneck.0.weight', 'res_layers.0.2.bottleneck.1.gamma',
'res_layers.0.2.bottleneck.1.beta', 'res_layers.0.2.bottleneck.1.running_mean',
'res_layers.0.2.bottleneck.1.running_var',
'res_layers.0.2.bottleneck.3.weight', 'res_layers.0.2.bottleneck.4.gamma',
'res_layers.0.2.bottleneck.4.beta', 'res_layers.0.2.bottleneck.4.running_mean',
'res_layers.0.2.bottleneck.4.running_var',
'res_layers.0.2.bottleneck.6.weight', 'res_layers.0.2.bottleneck.7.gamma',
'res_layers.0.2.bottleneck.7.beta', 'res_layers.0.2.bottleneck.7.running_mean',
'res_layers.0.2.bottleneck.7.running_var', 'res_layers.0.2.conv1.weight',
'res_layers.0.2.conv2.weight', 'res_layers.0.2.bn1.gamma',
'res_layers.0.2.bn1.beta', 'res_layers.0.2.bn1.running_mean',
'res_layers.0.2.bn1.running_var', 'res_layers.0.2.bn2.gamma',
'res_layers.0.2.bn2.beta', 'res_layers.0.2.bn2.running_mean',
'res_layers.0.2.bn2.running_var', 'res_layers.0.2.conv3.weight',
'res_layers.0.2.bn3.gamma', 'res_layers.0.2.bn3.beta',
'res_layers.0.2.bn3.running_mean', 'res_layers.0.2.bn3.running_var',
'res_layers.1.0.bottleneck.0.weight', 'res_layers.1.0.bottleneck.1.gamma',
'res_layers.1.0.bottleneck.1.beta', 'res_layers.1.0.bottleneck.1.running_mean',
'res_layers.1.0.bottleneck.1.running_var',
'res_layers.1.0.bottleneck.3.weight', 'res_layers.1.0.bottleneck.4.gamma',
'res_layers.1.0.bottleneck.4.beta', 'res_layers.1.0.bottleneck.4.running_mean',
'res_layers.1.0.bottleneck.4.running_var',
'res_layers.1.0.bottleneck.6.weight', 'res_layers.1.0.bottleneck.7.gamma',
'res_layers.1.0.bottleneck.7.beta', 'res_layers.1.0.bottleneck.7.running_mean',
'res_layers.1.0.bottleneck.7.running_var', 'res_layers.1.0.conv1.weight',
'res_layers.1.0.conv2.weight', 'res_layers.1.0.bn1.gamma',
'res_layers.1.0.bn1.beta', 'res_layers.1.0.bn1.running_mean',
'res_layers.1.0.bn1.running_var', 'res_layers.1.0.bn2.gamma',
'res_layers.1.0.bn2.beta', 'res_layers.1.0.bn2.running_mean',
'res_layers.1.0.bn2.running_var', 'res_layers.1.0.conv3.weight',
'res_layers.1.0.bn3.gamma', 'res_layers.1.0.bn3.beta',
'res_layers.1.0.bn3.running_mean', 'res_layers.1.0.bn3.running_var',
'res_layers.1.0.downsample.0.weight', 'res_layers.1.0.downsample.1.gamma',
'res_layers.1.0.downsample.1.beta', 'res_layers.1.0.downsample.1.running_mean',
'res_layers.1.0.downsample.1.running_var',
'res_layers.1.1.bottleneck.0.weight', 'res_layers.1.1.bottleneck.1.gamma',
'res_layers.1.1.bottleneck.1.beta', 'res_layers.1.1.bottleneck.1.running_mean',
'res_layers.1.1.bottleneck.1.running_var',
'res_layers.1.1.bottleneck.3.weight', 'res_layers.1.1.bottleneck.4.gamma',
'res_layers.1.1.bottleneck.4.beta', 'res_layers.1.1.bottleneck.4.running_mean',
'res_layers.1.1.bottleneck.4.running_var',
'res_layers.1.1.bottleneck.6.weight', 'res_layers.1.1.bottleneck.7.gamma',
'res_layers.1.1.bottleneck.7.beta', 'res_layers.1.1.bottleneck.7.running_mean',
'res_layers.1.1.bottleneck.7.running_var', 'res_layers.1.1.conv1.weight',
'res_layers.1.1.conv2.weight', 'res_layers.1.1.bn1.gamma',
'res_layers.1.1.bn1.beta', 'res_layers.1.1.bn1.running_mean',
'res_layers.1.1.bn1.running_var', 'res_layers.1.1.bn2.gamma',
'res_layers.1.1.bn2.beta', 'res_layers.1.1.bn2.running_mean',
'res_layers.1.1.bn2.running_var', 'res_layers.1.1.conv3.weight',
'res_layers.1.1.bn3.gamma', 'res_layers.1.1.bn3.beta',
'res_layers.1.1.bn3.running_mean', 'res_layers.1.1.bn3.running_var',
'res_layers.1.2.bottleneck.0.weight', 'res_layers.1.2.bottleneck.1.gamma',
'res_layers.1.2.bottleneck.1.beta', 'res_layers.1.2.bottleneck.1.running_mean',
'res_layers.1.2.bottleneck.1.running_var',
'res_layers.1.2.bottleneck.3.weight', 'res_layers.1.2.bottleneck.4.gamma',
'res_layers.1.2.bottleneck.4.beta', 'res_layers.1.2.bottleneck.4.running_mean',
'res_layers.1.2.bottleneck.4.running_var',
'res_layers.1.2.bottleneck.6.weight', 'res_layers.1.2.bottleneck.7.gamma',
'res_layers.1.2.bottleneck.7.beta', 'res_layers.1.2.bottleneck.7.running_mean',
'res_layers.1.2.bottleneck.7.running_var', 'res_layers.1.2.conv1.weight',
'res_layers.1.2.conv2.weight', 'res_layers.1.2.bn1.gamma',
'res_layers.1.2.bn1.beta', 'res_layers.1.2.bn1.running_mean',
'res_layers.1.2.bn1.running_var', 'res_layers.1.2.bn2.gamma',
'res_layers.1.2.bn2.beta', 'res_layers.1.2.bn2.running_mean',
'res_layers.1.2.bn2.running_var', 'res_layers.1.2.conv3.weight',
'res_layers.1.2.bn3.gamma', 'res_layers.1.2.bn3.beta',
'res_layers.1.2.bn3.running_mean', 'res_layers.1.2.bn3.running_var',
'res_layers.1.3.bottleneck.0.weight', 'res_layers.1.3.bottleneck.1.gamma',
'res_layers.1.3.bottleneck.1.beta', 'res_layers.1.3.bottleneck.1.running_mean',
'res_layers.1.3.bottleneck.1.running_var',
'res_layers.1.3.bottleneck.3.weight', 'res_layers.1.3.bottleneck.4.gamma',
'res_layers.1.3.bottleneck.4.beta', 'res_layers.1.3.bottleneck.4.running_mean',
'res_layers.1.3.bottleneck.4.running_var',
'res_layers.1.3.bottleneck.6.weight', 'res_layers.1.3.bottleneck.7.gamma',
'res_layers.1.3.bottleneck.7.beta', 'res_layers.1.3.bottleneck.7.running_mean',
'res_layers.1.3.bottleneck.7.running_var', 'res_layers.1.3.conv1.weight',
'res_layers.1.3.conv2.weight', 'res_layers.1.3.bn1.gamma',
'res_layers.1.3.bn1.beta', 'res_layers.1.3.bn1.running_mean',
'res_layers.1.3.bn1.running_var', 'res_layers.1.3.bn2.gamma',
'res_layers.1.3.bn2.beta', 'res_layers.1.3.bn2.running_mean',
'res_layers.1.3.bn2.running_var', 'res_layers.1.3.conv3.weight',
'res_layers.1.3.bn3.gamma', 'res_layers.1.3.bn3.beta',
'res_layers.1.3.bn3.running_mean', 'res_layers.1.3.bn3.running_var',
'res_layers.2.0.bottleneck.0.weight', 'res_layers.2.0.bottleneck.1.gamma',
'res_layers.2.0.bottleneck.1.beta', 'res_layers.2.0.bottleneck.1.running_mean',
'res_layers.2.0.bottleneck.1.running_var',
'res_layers.2.0.bottleneck.3.weight', 'res_layers.2.0.bottleneck.4.gamma',
'res_layers.2.0.bottleneck.4.beta', 'res_layers.2.0.bottleneck.4.running_mean',
'res_layers.2.0.bottleneck.4.running_var',
'res_layers.2.0.bottleneck.6.weight', 'res_layers.2.0.bottleneck.7.gamma',
'res_layers.2.0.bottleneck.7.beta', 'res_layers.2.0.bottleneck.7.running_mean',
'res_layers.2.0.bottleneck.7.running_var', 'res_layers.2.0.conv1.weight',
'res_layers.2.0.conv2.weight', 'res_layers.2.0.bn1.gamma',
'res_layers.2.0.bn1.beta', 'res_layers.2.0.bn1.running_mean',
'res_layers.2.0.bn1.running_var', 'res_layers.2.0.bn2.gamma',
'res_layers.2.0.bn2.beta', 'res_layers.2.0.bn2.running_mean',
'res_layers.2.0.bn2.running_var', 'res_layers.2.0.conv3.weight',
'res_layers.2.0.bn3.gamma', 'res_layers.2.0.bn3.beta',
'res_layers.2.0.bn3.running_mean', 'res_layers.2.0.bn3.running_var',
'res_layers.2.0.downsample.0.weight', 'res_layers.2.0.downsample.1.gamma',
'res_layers.2.0.downsample.1.beta', 'res_layers.2.0.downsample.1.running_mean',
'res_layers.2.0.downsample.1.running_var',
'res_layers.2.1.bottleneck.0.weight', 'res_layers.2.1.bottleneck.1.gamma',
'res_layers.2.1.bottleneck.1.beta', 'res_layers.2.1.bottleneck.1.running_mean',
'res_layers.2.1.bottleneck.1.running_var',
'res_layers.2.1.bottleneck.3.weight', 'res_layers.2.1.bottleneck.4.gamma',
'res_layers.2.1.bottleneck.4.beta', 'res_layers.2.1.bottleneck.4.running_mean',
'res_layers.2.1.bottleneck.4.running_var',
'res_layers.2.1.bottleneck.6.weight', 'res_layers.2.1.bottleneck.7.gamma',
'res_layers.2.1.bottleneck.7.beta', 'res_layers.2.1.bottleneck.7.running_mean',
'res_layers.2.1.bottleneck.7.running_var', 'res_layers.2.1.conv1.weight',
'res_layers.2.1.conv2.weight', 'res_layers.2.1.bn1.gamma',
'res_layers.2.1.bn1.beta', 'res_layers.2.1.bn1.running_mean',
'res_layers.2.1.bn1.running_var', 'res_layers.2.1.bn2.gamma',
'res_layers.2.1.bn2.beta', 'res_layers.2.1.bn2.running_mean',
'res_layers.2.1.bn2.running_var', 'res_layers.2.1.conv3.weight',
'res_layers.2.1.bn3.gamma', 'res_layers.2.1.bn3.beta',
'res_layers.2.1.bn3.running_mean', 'res_layers.2.1.bn3.running_var',
'res_layers.2.2.bottleneck.0.weight', 'res_layers.2.2.bottleneck.1.gamma',
'res_layers.2.2.bottleneck.1.beta', 'res_layers.2.2.bottleneck.1.running_mean',
'res_layers.2.2.bottleneck.1.running_var',
'res_layers.2.2.bottleneck.3.weight', 'res_layers.2.2.bottleneck.4.gamma',
'res_layers.2.2.bottleneck.4.beta', 'res_layers.2.2.bottleneck.4.running_mean',
'res_layers.2.2.bottleneck.4.running_var',
'res_layers.2.2.bottleneck.6.weight', 'res_layers.2.2.bottleneck.7.gamma',
'res_layers.2.2.bottleneck.7.beta', 'res_layers.2.2.bottleneck.7.running_mean',
'res_layers.2.2.bottleneck.7.running_var', 'res_layers.2.2.conv1.weight',
'res_layers.2.2.conv2.weight', 'res_layers.2.2.bn1.gamma',
'res_layers.2.2.bn1.beta', 'res_layers.2.2.bn1.running_mean',
'res_layers.2.2.bn1.running_var', 'res_layers.2.2.bn2.gamma',
'res_layers.2.2.bn2.beta', 'res_layers.2.2.bn2.running_mean',
'res_layers.2.2.bn2.running_var', 'res_layers.2.2.conv3.weight',
'res_layers.2.2.bn3.gamma', 'res_layers.2.2.bn3.beta',
'res_layers.2.2.bn3.running_mean', 'res_layers.2.2.bn3.running_var',
'res_layers.2.3.bottleneck.0.weight', 'res_layers.2.3.bottleneck.1.gamma',
'res_layers.2.3.bottleneck.1.beta', 'res_layers.2.3.bottleneck.1.running_mean',
'res_layers.2.3.bottleneck.1.running_var',
'res_layers.2.3.bottleneck.3.weight', 'res_layers.2.3.bottleneck.4.gamma',
'res_layers.2.3.bottleneck.4.beta', 'res_layers.2.3.bottleneck.4.running_mean',
'res_layers.2.3.bottleneck.4.running_var',
'res_layers.2.3.bottleneck.6.weight', 'res_layers.2.3.bottleneck.7.gamma',
'res_layers.2.3.bottleneck.7.beta', 'res_layers.2.3.bottleneck.7.running_mean',
'res_layers.2.3.bottleneck.7.running_var', 'res_layers.2.3.conv1.weight',
'res_layers.2.3.conv2.weight', 'res_layers.2.3.bn1.gamma',
'res_layers.2.3.bn1.beta', 'res_layers.2.3.bn1.running_mean',
'res_layers.2.3.bn1.running_var', 'res_layers.2.3.bn2.gamma',
'res_layers.2.3.bn2.beta', 'res_layers.2.3.bn2.running_mean',
'res_layers.2.3.bn2.running_var', 'res_layers.2.3.conv3.weight',
'res_layers.2.3.bn3.gamma', 'res_layers.2.3.bn3.beta',
'res_layers.2.3.bn3.running_mean', 'res_layers.2.3.bn3.running_var',
'res_layers.2.4.bottleneck.0.weight', 'res_layers.2.4.bottleneck.1.gamma',
'res_layers.2.4.bottleneck.1.beta', 'res_layers.2.4.bottleneck.1.running_mean',
'res_layers.2.4.bottleneck.1.running_var',
'res_layers.2.4.bottleneck.3.weight', 'res_layers.2.4.bottleneck.4.gamma',
'res_layers.2.4.bottleneck.4.beta', 'res_layers.2.4.bottleneck.4.running_mean',
'res_layers.2.4.bottleneck.4.running_var',
'res_layers.2.4.bottleneck.6.weight', 'res_layers.2.4.bottleneck.7.gamma',
'res_layers.2.4.bottleneck.7.beta', 'res_layers.2.4.bottleneck.7.running_mean',
'res_layers.2.4.bottleneck.7.running_var', 'res_layers.2.4.conv1.weight',
'res_layers.2.4.conv2.weight', 'res_layers.2.4.bn1.gamma',
'res_layers.2.4.bn1.beta', 'res_layers.2.4.bn1.running_mean',
'res_layers.2.4.bn1.running_var', 'res_layers.2.4.bn2.gamma',
'res_layers.2.4.bn2.beta', 'res_layers.2.4.bn2.running_mean',
'res_layers.2.4.bn2.running_var', 'res_layers.2.4.conv3.weight',
'res_layers.2.4.bn3.gamma', 'res_layers.2.4.bn3.beta',
'res_layers.2.4.bn3.running_mean', 'res_layers.2.4.bn3.running_var',
'res_layers.2.5.bottleneck.0.weight', 'res_layers.2.5.bottleneck.1.gamma',
'res_layers.2.5.bottleneck.1.beta', 'res_layers.2.5.bottleneck.1.running_mean',
'res_layers.2.5.bottleneck.1.running_var',
'res_layers.2.5.bottleneck.3.weight', 'res_layers.2.5.bottleneck.4.gamma',
'res_layers.2.5.bottleneck.4.beta', 'res_layers.2.5.bottleneck.4.running_mean',
'res_layers.2.5.bottleneck.4.running_var',
'res_layers.2.5.bottleneck.6.weight', 'res_layers.2.5.bottleneck.7.gamma',
'res_layers.2.5.bottleneck.7.beta', 'res_layers.2.5.bottleneck.7.running_mean',
'res_layers.2.5.bottleneck.7.running_var', 'res_layers.2.5.conv1.weight',
'res_layers.2.5.conv2.weight', 'res_layers.2.5.bn1.gamma',
'res_layers.2.5.bn1.beta', 'res_layers.2.5.bn1.running_mean',
'res_layers.2.5.bn1.running_var', 'res_layers.2.5.bn2.gamma',
'res_layers.2.5.bn2.beta', 'res_layers.2.5.bn2.running_mean',
'res_layers.2.5.bn2.running_var', 'res_layers.2.5.conv3.weight',
'res_layers.2.5.bn3.gamma', 'res_layers.2.5.bn3.beta',
'res_layers.2.5.bn3.running_mean', 'res_layers.2.5.bn3.running_var',
'res_layers.3.0.bottleneck.0.weight', 'res_layers.3.0.bottleneck.1.gamma',
'res_layers.3.0.bottleneck.1.beta', 'res_layers.3.0.bottleneck.1.running_mean',
'res_layers.3.0.bottleneck.1.running_var',
'res_layers.3.0.bottleneck.3.weight', 'res_layers.3.0.bottleneck.4.gamma',
'res_layers.3.0.bottleneck.4.beta', 'res_layers.3.0.bottleneck.4.running_mean',
'res_layers.3.0.bottleneck.4.running_var',
'res_layers.3.0.bottleneck.6.weight', 'res_layers.3.0.bottleneck.7.gamma',
'res_layers.3.0.bottleneck.7.beta', 'res_layers.3.0.bottleneck.7.running_mean',
'res_layers.3.0.bottleneck.7.running_var', 'res_layers.3.0.conv1.weight',
'res_layers.3.0.conv2.weight', 'res_layers.3.0.bn1.gamma',
'res_layers.3.0.bn1.beta', 'res_layers.3.0.bn1.running_mean',
'res_layers.3.0.bn1.running_var', 'res_layers.3.0.bn2.gamma',
'res_layers.3.0.bn2.beta', 'res_layers.3.0.bn2.running_mean',
'res_layers.3.0.bn2.running_var', 'res_layers.3.0.conv3.weight',
'res_layers.3.0.bn3.gamma', 'res_layers.3.0.bn3.beta',
'res_layers.3.0.bn3.running_mean', 'res_layers.3.0.bn3.running_var',
'res_layers.3.0.downsample.0.weight', 'res_layers.3.0.downsample.1.gamma',
'res_layers.3.0.downsample.1.beta', 'res_layers.3.0.downsample.1.running_mean',
'res_layers.3.0.downsample.1.running_var',
'res_layers.3.1.bottleneck.0.weight', 'res_layers.3.1.bottleneck.1.gamma',
'res_layers.3.1.bottleneck.1.beta', 'res_layers.3.1.bottleneck.1.running_mean',
'res_layers.3.1.bottleneck.1.running_var',
'res_layers.3.1.bottleneck.3.weight', 'res_layers.3.1.bottleneck.4.gamma',
'res_layers.3.1.bottleneck.4.beta', 'res_layers.3.1.bottleneck.4.running_mean',
'res_layers.3.1.bottleneck.4.running_var',
'res_layers.3.1.bottleneck.6.weight', 'res_layers.3.1.bottleneck.7.gamma',
'res_layers.3.1.bottleneck.7.beta', 'res_layers.3.1.bottleneck.7.running_mean',
'res_layers.3.1.bottleneck.7.running_var', 'res_layers.3.1.conv1.weight',
'res_layers.3.1.conv2.weight', 'res_layers.3.1.bn1.gamma',
'res_layers.3.1.bn1.beta', 'res_layers.3.1.bn1.running_mean',
'res_layers.3.1.bn1.running_var', 'res_layers.3.1.bn2.gamma',
'res_layers.3.1.bn2.beta', 'res_layers.3.1.bn2.running_mean',
'res_layers.3.1.bn2.running_var', 'res_layers.3.1.conv3.weight',
'res_layers.3.1.bn3.gamma', 'res_layers.3.1.bn3.beta',
'res_layers.3.1.bn3.running_mean', 'res_layers.3.1.bn3.running_var',
'res_layers.3.2.bottleneck.0.weight', 'res_layers.3.2.bottleneck.1.gamma',
'res_layers.3.2.bottleneck.1.beta', 'res_layers.3.2.bottleneck.1.running_mean',
'res_layers.3.2.bottleneck.1.running_var',
'res_layers.3.2.bottleneck.3.weight', 'res_layers.3.2.bottleneck.4.gamma',
'res_layers.3.2.bottleneck.4.beta', 'res_layers.3.2.bottleneck.4.running_mean',
'res_layers.3.2.bottleneck.4.running_var',
'res_layers.3.2.bottleneck.6.weight', 'res_layers.3.2.bottleneck.7.gamma',
'res_layers.3.2.bottleneck.7.beta', 'res_layers.3.2.bottleneck.7.running_mean',
'res_layers.3.2.bottleneck.7.running_var', 'res_layers.3.2.conv1.weight',
'res_layers.3.2.conv2.weight', 'res_layers.3.2.bn1.gamma',
'res_layers.3.2.bn1.beta', 'res_layers.3.2.bn1.running_mean',
'res_layers.3.2.bn1.running_var', 'res_layers.3.2.bn2.gamma',
'res_layers.3.2.bn2.beta', 'res_layers.3.2.bn2.running_mean',
'res_layers.3.2.bn2.running_var', 'res_layers.3.2.conv3.weight',
'res_layers.3.2.bn3.gamma', 'res_layers.3.2.bn3.beta',
'res_layers.3.2.bn3.running_mean', 'res_layers.3.2.bn3.running_var',
'head.1.weight', 'head.1.bias', 'fc.weight', 'fc.bias'])
>>>
```
---
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