Group-Buying Recommendation for Social E-Commerce

Hi,

Since I always fail to run the testing mode (for both GBMF and GBGCN) due to lack of "model.json", I'm wondering how to save a pretrained (GBMF) model as a json file and how to run the testing mode. Thanks.

Hi,

After resolving the issues of testing execution, I'm wondering if the following error is due to the lack of test.negative.txt.

If so, how can I generate negative samples? Thanks.

hello，I want to know what the computer configuration should be to successfully reproduce these jobs. I can't reproduce it on 2080ti with 11gb of memory, and it's useless when I try to make the batchsize small enough. Or can you specify the hyperparameter setting?

Hi, After installing setup.py file from the mentioned frame work in the GitHub, I tried to run the GBGCN.py file by this command in Google Colab, "! python GBGCN.py train --tag 'true' --SL2 0.001 --L2 0.001 --lr 1e-2 --layer 2 --alpha 0.6 --beta 0.01 ". The below Errors showed: ( Any help to solve these errors and run the file properly would be appreciated! Just to mentioned that when I tried to run the whole data on GBGCN.py, it was not successful. I think the not enough RAM on colab was the problem( my colab RAM is around 12 GB) so I tried to reduce the size of BeiBei data set( 0.01 of the data set) to tackle this issue. Then these errors showed)

INFO:root:Environment Arguments(OrderedDict([('dataset', 'BeiBei'), ('device', [0]), ('sample_epoch', 500), ('sample_worker', 16), ('epoch', 500), ('tag', 'true')])) INFO:root:Dataloader Arguments(OrderedDict([('batch_size', 4096), ('batch_worker', 2), ('test_batch_size', 128), ('test_batch_worker', 2)])) INFO:root:Hyperparameter Arguments(OrderedDict([('embedding_size', 32), ('act', 'sigmoid'), ('pretrain', True), ('SL2', [0.001]), ('L2', [0.001]), ('lr', [0.01]), ('layer', [2]), ('alpha', [0.6]), ('beta', [0.01])])) INFO:root:{'comment': '固定参数', 'user': 'user', 'visdom': {'server': '127.0.0.1', 'port': {'BeiBei_itemrec': 16670, 'BeiBei_grouprec': 16670, 'BeiBei_SIGR': 16670, 'BeiBei': 16670, 'comment': '16671 is temporary'}}, 'training': {'test_interval': 5, 'early_stop': 50, 'overfit': {'protected_epoch': 10, 'threshold': 1}}, 'dataset': {'path': './BeiBei', 'seed': 123, 'use_backup': True}, 'logger': {'path': './log', 'policy': 'best'}, 'metric': {'target': {'type': 'NDCG', 'topk': 10}, 'metrics': [{'type': 'Recall', 'topk': 3}, {'type': 'Recall', 'topk': 5}, {'type': 'Recall', 'topk': 10}, {'type': 'Recall', 'topk': 20}, {'type': 'NDCG', 'topk': 3}, {'type': 'NDCG', 'topk': 5}, {'type': 'NDCG', 'topk': 10}, {'type': 'NDCG', 'topk': 20}]}} INFO:root:{'BeiBei': {'GBMF': ''}} DEBUG:root:Load BeiBei/BeiBei/BeiBei-neg-500-123-default.pkl DEBUG:root:finish loading neg sample INFO:root:GPU search space: [0] INFO:root:Auto select GPU 0 WARNING:visdom:Setting up a new session... Exception in user code:

Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/urllib3/connection.py", line 159, in _new_conn (self._dns_host, self.port), self.timeout, **extra_kw) File "/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py", line 80, in create_connection raise err File "/usr/local/lib/python3.7/dist-packages/urllib3/util/connection.py", line 70, in create_connection sock.connect(sa) ConnectionRefusedError: [Errno 111] Connection refused

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py", line 600, in urlopen chunked=chunked) File "/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py", line 354, in _make_request conn.request(method, url, **httplib_request_kw) File "/usr/lib/python3.7/http/client.py", line 1277, in request self._send_request(method, url, body, headers, encode_chunked) File "/usr/lib/python3.7/http/client.py", line 1323, in _send_request self.endheaders(body, encode_chunked=encode_chunked) File "/usr/lib/python3.7/http/client.py", line 1272, in endheaders self._send_output(message_body, encode_chunked=encode_chunked) File "/usr/lib/python3.7/http/client.py", line 1032, in _send_output self.send(msg) File "/usr/lib/python3.7/http/client.py", line 972, in send self.connect() File "/usr/local/lib/python3.7/dist-packages/urllib3/connection.py", line 181, in connect conn = self._new_conn() File "/usr/local/lib/python3.7/dist-packages/urllib3/connection.py", line 168, in _new_conn self, "Failed to establish a new connection: %s" % e) urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPConnection object at 0x7fd8435d5c50>: Failed to establish a new connection: [Errno 111] Connection refused

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/requests/adapters.py", line 449, in send timeout=timeout File "/usr/local/lib/python3.7/dist-packages/urllib3/connectionpool.py", line 638, in urlopen _stacktrace=sys.exc_info()[2]) File "/usr/local/lib/python3.7/dist-packages/urllib3/util/retry.py", line 399, in increment raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='127.0.0.1', port=16670): Max retries exceeded with url: /env/GBGCN_true-32-0.01-0.001-0.001-2-0.6-0.01-sigmoid-True-True (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fd8435d5c50>: Failed to establish a new connection: [Errno 111] Connection refused'))

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/visdom/init.py", line 711, in _send data=json.dumps(msg), File "/usr/local/lib/python3.7/dist-packages/visdom/init.py", line 677, in _handle_post r = self.session.post(url, data=data) File "/usr/local/lib/python3.7/dist-packages/requests/sessions.py", line 578, in post return self.request('POST', url, data=data, json=json, **kwargs) File "/usr/local/lib/python3.7/dist-packages/requests/sessions.py", line 530, in request resp = self.send(prep, **send_kwargs) File "/usr/local/lib/python3.7/dist-packages/requests/sessions.py", line 643, in send r = adapter.send(request, **kwargs) File "/usr/local/lib/python3.7/dist-packages/requests/adapters.py", line 516, in send raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=16670): Max retries exceeded with url: /env/GBGCN_true-32-0.01-0.001-0.001-2-0.6-0.01-sigmoid-True-True (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fd8435d5c50>: Failed to establish a new connection: [Errno 111] Connection refused')) INFO:visdom:Socket refused connection, running socketless ERROR:visdom:[Errno 111] Connection refused ERROR:websocket:error from callback <function Visdom.setup_socket..on_close at 0x7fd84346ec20>: on_close() takes 1 positional argument but 3 were given File "/usr/local/lib/python3.7/dist-packages/websocket/_app.py", line 407, in _callback callback(self, *args) Traceback (most recent call last): File "GBGCN.py", line 556, in torch.optim.SGD) File "/usr/local/lib/python3.7/dist-packages/librecframework-1.3.0-py3.7.egg/librecframework/pipeline.py", line 633, in during_running model_class, other_args, trainhooks, optim_type) File "/usr/local/lib/python3.7/dist-packages/librecframework-1.3.0-py3.7.egg/librecframework/pipeline.py", line 239, in during_running model.load_pretrain(self._pretrain[self._eam['dataset']]) File "GBGCN.py", line 102, in load_pretrain pretrain = torch.load(path, map_location='cpu') File "/usr/local/lib/python3.7/dist-packages/torch/serialization.py", line 381, in load f = open(f, 'rb') FileNotFoundError: [Errno 2] No such file or directory: ''

Hi,

I'm wondering if it is possible to evaluate the ranking metrics of MAP(mean average precision) @ K and HR(hit ratio) @ K of GBMF/GBGCN under librecframework. If yes, how can I modify the code? Thanks.

命令： python GBGCN.py train [-h] 错误： Using backend: pytorch usage: GBGCN.py train [-h] [-DS DATASET] [-D DEVICE [DEVICE ...]] -T TAG [-SEP SAMPLE_EPOCH] [-SW SAMPLE_WORKER] [-EP EPOCH] [-BS BATCH_SIZE] [-BW BATCH_WORKER] [-TBS TEST_BATCH_SIZE] [-TBW TEST_BATCH_WORKER] [-EB EMBEDDING_SIZE] [--lr LR [LR ...]] --L2 L2 [L2 ...] --SL2 SL2 [SL2 ...] -L LAYER [LAYER ...] -A ALPHA [ALPHA ...] -B BETA [BETA ...] [--act ACT] [--pretrain | --no-pretrain] GBGCN.py train: error: the following arguments are required: -T/--tag, --L2, --SL2, -L/--layer, -A/--alpha, -B/--beta

Hi, My question is how to use negative sample file in order to run the whole model correctly? should I copy the file in BeiBei folder? Can I run the model correctly without "negative sample file"? Any instruction from scratch would be of any help. Thanks

作者您好，我安装了requirements.txt和librecframework之后运行GBGCN.py，遇到了以下错误： Traceback (most recent call last): File "GBGCN.py", line 14, in from librecframework.argument.manager import HyperparamManager File "C:\Users\ZSX\AppData\Roaming\Python\Python36\site-packages\librecframework\argument_init_.py", line 11, in class Argument(NamedTuple, Generic[T]): TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases

请问这是什么情况呢