kamathhrishi / pate

Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/1610.05755)

Hi there 👋.

I just learnt how to add a README to my Github profile while I was procastrinating. I will update this soon

pate's Issues

Problem When I run Main.py

the error msg is as follows:

Traceback (most recent call last):
  File "Main.py", line 3, in 
    from Teacher import Teacher
  File "E:\1-Research\0-DP+GCN\Code\(2020-09-20)PATE\Teacher.py", line 6, in 
    from syft.frameworks.torch.differential_privacy import pate
  File "D:\Anaconda\envs\torch\lib\site-packages\syft-0.2.9-py3.7.egg\syft\__init__.py", line 14, in 
    import syft.frameworks.torch.hook.hook_args
  File "D:\Anaconda\envs\torch\lib\site-packages\syft-0.2.9-py3.7.egg\syft\frameworks\torch\hook\hook_args.py", line 4, in 
    from syft.frameworks.torch.tensors.interpreters.native import TorchTensor
  File "D:\Anaconda\envs\torch\lib\site-packages\syft-0.2.9-py3.7.egg\syft\frameworks\torch\tensors\interpreters\native.py", line 11, in 
    from syft.messaging.message import TensorCommandMessage
  File "D:\Anaconda\envs\torch\lib\site-packages\syft-0.2.9-py3.7.egg\syft\messaging\message.py", line 17, in 
    from syft.execution.action import Action
  File "D:\Anaconda\envs\torch\lib\site-packages\syft-0.2.9-py3.7.egg\syft\execution\action.py", line 5, in 
    from syft.execution.placeholder import PlaceHolder
  File "D:\Anaconda\envs\torch\lib\site-packages\syft-0.2.9-py3.7.egg\syft\execution\placeholder.py", line 7, in 
    from syft_proto.execution.v1.placeholder_pb2 import Placeholder as PlaceholderPB
  File "D:\Anaconda\envs\torch\lib\site-packages\syft_proto-0.5.2-py3.7.egg\syft_proto\execution\v1\placeholder_pb2.py", line 14, in 
    from syft_proto.types.syft.v1 import id_pb2 as syft__proto_dot_types_dot_syft_dot_v1_dot_id__pb2
  File "D:\Anaconda\envs\torch\lib\site-packages\syft_proto-0.5.2-py3.7.egg\syft_proto\types\syft\v1\id_pb2.py", line 21, in 
    create_key=_descriptor._internal_create_key,
AttributeError: module 'google.protobuf.descriptor' has no attribute '_internal_create_key'

Problem when I run /PATE/SHVN/Main.py

$ python Main.py
Using downloaded and verified file: ../data/train_32x32.mat
Using downloaded and verified file: ../data/test_32x32.mat
TRAINING model_0
EPOCH: 1
Traceback (most recent call last):
File "Main.py", line 35, in
teacher.train(train_loader)
File "/home/liujj/PATE/SHVN/Teacher.py", line 116, in train
self.loop_body(split[index],model_name,1)
File "/home/liujj/PATE/SHVN/Teacher.py", line 129, in loop_body
output = model(data)
File "/mnt/data/conda/envs/pytorch/lib/python3.6/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/home/liujj/PATE/SHVN/Model.py", line 18, in forward
x = F.relu(self.conv1(x))
File "/mnt/data/conda/envs/pytorch/lib/python3.6/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/mnt/data/conda/envs/pytorch/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 338, in forward
self.padding, self.dilation, self.groups)
RuntimeError: Given groups=1, weight of size 20 1 5 5, expected input[64, 3, 32, 32] to have 1 channels, but got 3 channels instead

what is the RuntimeError mean? Can you help me solve?

Can't seem to finish running Main.py (not SHVN)

Hey,

Love the repo, but I have an issue, whenever I run it it seems to get stuck at the last two lines of Main.py it does not show an error, but after a while i press force it to stop and its stuck at the same line every time. I run it on less epochs than in your file (1-2) just for testing purposes. My hyperparameters look like this:

    def __init__(self):

        self.batchsize = 64
        self.test_batchsize = 10
        self.epochs = **1**
        self.student_epochs = **1**
        self.lr = 0.01
        self.momentum = 0.5
        self.no_cuda = False
        self.seed = 1
        self.log_interval = 30
        self.n_teachers = **1**
        self.save_model = **True**

Last four lines of code look like this:

counts_lol = torch.stack(counts).contiguous().view(**1**, 10000)
predict_lol = torch.tensor(predict).view(10000)

data_dep_eps, data_ind_eps = teacher.analyze(counts_lol, predict_lol, moments=20)
print("Epsilon: ", teacher.analyze(counts_lol, predict_lol))

And it seems that my file is stuck at:

Traceback (most recent call last):
  File "main.py", line 91, in <module>
    #data_dep_eps, data_ind_eps = teacher.analyze(counts_lol, predict_lol, moments=20)
  File "C:\Users\Koen\PycharmProjects\pate-g\PATE\Teacher.py", line 176, in analyze
    preds, indices, noise_eps=0.1, delta=self.epsilon, moments=moments, beta=0.09
  File "C:\Users\Koen\Anaconda3\envs\pysyft\lib\site-packages\syft-0.2.0a2-py3.7.egg\syft\frameworks\torch\differential_privacy\pate.py", line 484, in perform_analysis_torch
  File "C:\Users\Koen\Anaconda3\envs\pysyft\lib\site-packages\syft-0.2.0a2-py3.7.egg\syft\frameworks\torch\differential_privacy\pate.py", line 484, in <listcomp>
  File "C:\Users\Koen\Anaconda3\envs\pysyft\lib\site-packages\syft-0.2.0a2-py3.7.egg\syft\frameworks\torch\differential_privacy\pate.py", line 379, in logmgf_from_counts_torch
  File "C:\Users\Koen\Anaconda3\envs\pysyft\lib\site-packages\syft-0.2.0a2-py3.7.egg\syft\frameworks\torch\differential_privacy\pate.py", line 354, in compute_q_noisy_max_torch
  File "C:\Users\Koen\Anaconda3\envs\pysyft\lib\site-packages\syft-0.2.0a2-py3.7.egg\syft\frameworks\torch\differential_privacy\pate.py", line 294, in tensors_to_literals
  File "C:\Users\Koen\Anaconda3\envs\pysyft\lib\site-packages\torch\tensor.py", line 427, in <lambda>
    return iter(imap(lambda i: self[i], range(self.size(0))))

Would you have any idea what I'm doing wrong here? I'm hesitant to run it for 1000 epochs as it would take a lot of time and I might still get stuck at the same point.
I am very curious to what the epsilon is and want to play around to see what the actual loss of accuracy would be with my own datasets.

Thanks in advance!