There are very little information about how to fine-tuning parameters and it really confuses me a lot about how to fine-tune a network in caffe2. Could anybody show me some codes about the fine-tuning part. Many thanks.
By the way, in the link:Food101 SqueezeNet Caffe2 number of iterations, it seems that the author has successfully fine-tuned the network.
add: Here are some codes of my train part,
train_model = cnn.CNNModelHelper(order="NCHW", name="train")
train_model.param_init_net.AppendNet(core.Net(init_net))
train_model.net.AppendNet(core.Net(predict_net))
train_model.param_init_net.RunAllOnGPU(gpu_id=0)
train_model.net.RunAllOnGPU(gpu_id=0)
workspace.RunNetOnce(train_model.param_init_net)
AddTrainingOperators(train_model, 'softmaxout', 'label')
AddBookkeepingOperators(train_model)
workspace.RunNetOnce(train_model.param_init_net)
data, label = AddInput(train_model, batch_size=3,
db=os.path.join(data_folder, 'toy_train.lmdb'),
db_type='lmdb')
workspace.FeedBlob('data', data)
workspace.FeedBlob('label', label)
workspace.CreateNet(train_model.net)
However, when i run the code, an error which warns
Traceback (most recent call last):
File "lenetForChineseFinetune.py", line 62, in <module>
workspace.FeedBlob('data', data)
File "/opt/caffe2/caffe2/local/caffe2/python/workspace.py", line 262, in FeedBlob
return C.feed_blob(name, arr)
RuntimeError: [enforce fail at pybind_state.cc:825] . Unexpected type of argument - only numpy array or string are supported for feeding
occured. How should i modify the codes?
