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2022-07-18 05:29:39,733 - INFO - Loaded file PEMSD3.geo, num_nodes=358
2022-07-18 05:29:39,735 - INFO - set_weight_link_or_dist: link
2022-07-18 05:29:39,735 - INFO - init_weight_inf_or_zero: zero
2022-07-18 05:29:39,738 - INFO - Loaded file PEMSD3.rel, shape=(358, 358)
2022-07-18 05:29:39,738 - INFO - Loading file PEMSD3.dyna
TypeError: only size-1 arrays can be converted to Python scalars

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "run_model.py", line 36, in
run_model(task=args.task, model_name=args.model, dataset_name=args.dataset,
File "/root/Bigscity-LibCity/libcity/pipeline/pipeline.py", line 48, in run_model
train_data, valid_data, test_data = dataset.get_data()
File "/root/Bigscity-LibCity/libcity/data/dataset/traffic_state_datatset.py", line 932, in get_data
x_train, y_train, x_val, y_val, x_test, y_test = self._generate_train_val_test()
File "/root/Bigscity-LibCity/libcity/data/dataset/traffic_state_datatset.py", line 851, in _generate_train_val_test
x, y = self._generate_data()
File "/root/Bigscity-LibCity/libcity/data/dataset/traffic_state_datatset.py", line 777, in _generate_data
df = self._load_dyna(filename) # (len_time, ..., feature_dim)
File "/root/Bigscity-LibCity/libcity/data/dataset/traffic_state_point_dataset.py", line 39, in _load_dyna
return super()._load_dyna_3d(filename)
File "/root/Bigscity-LibCity/libcity/data/dataset/traffic_state_datatset.py", line 269, in _load_dyna_3d
data = np.array(data, dtype=np.float) # (len(self.geo_ids), len_time, feature_dim)
ValueError: setting an array element with a sequence.

选择这个数据集时，出现如上错误

作者您好，我在使用Graph wavenet的模型训练后，将evaluate_cache的npz导出为xlsx，但是真实值出现了问题。其中导出的12个xlsx文件，这12个xlsx文件的真实值完全不同，都跟我的raw_data中的真实值不同，不知道哪里出了问题。您方便的时候回答一下，十分感谢！

同步到最新版本后，运行程序，例如python run_model.py --task traffic_state_pred --model GRU --dataset METR_LA都会提示json文件解析错误（如下），不知道是哪出了问题..之前的版本并不会出现这个问题
Traceback (most recent call last):
File "run_model.py", line 49, in
run_model(task=args.task, model_name=args.model, dataset_name=args.dataset,
File "/root/Bigscity-LibCity/libcity/pipeline/pipeline.py", line 30, in run_model
config = ConfigParser(task, model_name, dataset_name,
File "/root/Bigscity-LibCity/libcity/config/config_parser.py", line 25, in init
self._load_default_config()
File "/root/Bigscity-LibCity/libcity/config/config_parser.py", line 69, in _load_default_config
task_config = json.load(f)
File "/root/miniconda/lib/python3.8/json/init.py", line 293, in load
return loads(fp.read(),
File "/root/miniconda/lib/python3.8/json/init.py", line 357, in loads
return _default_decoder.decode(s)
File "/root/miniconda/lib/python3.8/json/decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "/root/miniconda/lib/python3.8/json/decoder.py", line 353, in raw_decode
obj, end = self.scan_once(s, idx)
json.decoder.JSONDecodeError: Expecting ',' delimiter: line 408 column 9 (char 15204)

geo_coord key值为地点的原始编号，[loc_lati, loc_longi]为对应的经纬度。

            loc_id, loc_longi, loc_lati = int(tokens[0]), eval(tokens[2]), eval(tokens[3])
            self.geo_coord[loc_id] = [loc_lati, loc_longi]

strnn_encoder.py中
原始：

87            lati = self.geo_coord[self.location2id[current_points[-1]]][0]
89            longi = self.geo_coord[self.location2id[current_points[-1]]][1]

self.location2id是将 原始的地点编号映射到地点的重新编号，这里存在问题。

认为应该修改成：

87            lati = self.geo_coord[current_points[-1]][0]
89            longi = self.geo_coord[current_points[-1]][1]

你好，我在用AGCRN模型在PEMSD4,和PEMSD8这两个数据集上跑的时候，实验结果出现了一些问题，MAPE指标本身值有问题之外还没有规律性，其他指标与原文也有较大的出入

您好，我用你们提供的处理好的数据“NYCTAXI202004-202006_OD”运行GEML模型进行模型训练，训练后结果进行相应预测。目前存在以下问题：1.训练后模型预测结果接近为0，加载cache中npz结果，使用np.max函数提取预测值的最大值，结果接近0；2.而在训练过程中，通过log发现，模型loss基本上没有大规模下降。
在迁移到我自己的数据中时，也出现该现象。

It seems that some files are missing when i run STDN model with TAXIBJ dataset:
FileNotFoundError: [Errno 2] No such file or directory: './raw_data/TAXIBJ/TAXIBJ2013.gridod'

Hi, thanks for the awesome work.
A logging error happened during the evaluation process. The default task in code https://github.com/LibCity/Bigscity-LibCity/blob/master/run_model.py is working well. However, there was an error that occurred when I switch the task to traj_loc_pred using foursquare_nyc dataset.

Code to Reproduce

    # code changes of main function in run_model.py
    parser.add_argument('--task', type=str, default='traj_loc_pred', help='the name of task')
    parser.add_argument('--model', type=str, default='DeepMove', help='the name of model')
    parser.add_argument('--dataset', type=str, default='foursquare_nyc', help='the name of dataset')

Actual result

--- Logging error ---

Traceback (most recent call last):
  File "D:\Software\Anaconda3\envs\LibCitybased\lib\logging\__init__.py", line 1025, in emit
    msg = self.format(record)
  File "D:\Software\Anaconda3\envs\LibCitybased\lib\logging\__init__.py", line 869, in format
    return fmt.format(record)
  File "D:\Software\Anaconda3\envs\LibCitybased\lib\logging\__init__.py", line 608, in format
    record.message = record.getMessage()
  File "D:\Software\Anaconda3\envs\LibCitybased\lib\logging\__init__.py", line 369, in getMessage
    msg = msg % self.args
TypeError: not all arguments converted during string formatting
Call stack:
  File "xx/Bigscity-LibCity-master/run_model.py", line 43, in <module>
    train=args.train, other_args=other_args)
  File "xx\Bigscity-LibCity-master\libcity\pipeline\pipeline.py", line 63, in run_model
    executor.evaluate(test_data)
  File "xx\Bigscity-LibCity-master\libcity\executor\traj_loc_pred_executor.py", line 108, in evaluate
    self.evaluator.save_result(self.evaluate_res_dir)
  File "xx\Bigscity-LibCity-master\libcity\evaluator\traj_loc_pred_evaluator.py", line 96, in save_result
    self._logger.info('evaluate result is ', json.dumps(self.result, indent=1))
Message: 'evaluate result is '
Arguments: ('{\n "Recall@1": 0.16751398997842068\n}',)
--- Logging error ---
Traceback (most recent call last):
  File "D:\Software\Anaconda3\envs\LibCitybased\lib\logging\__init__.py", line 1025, in emit
    msg = self.format(record)
  File "D:\Software\Anaconda3\envs\LibCitybased\lib\logging\__init__.py", line 869, in format
    return fmt.format(record)
  File "D:\Software\Anaconda3\envs\LibCitybased\lib\logging\__init__.py", line 608, in format
    record.message = record.getMessage()
  File "D:\Software\Anaconda3\envs\LibCitybased\lib\logging\__init__.py", line 369, in getMessage
    msg = msg % self.args
TypeError: not all arguments converted during string formatting
Call stack:
  File "xx/Bigscity-LibCity-master/run_model.py", line 43, in <module>
    train=args.train, other_args=other_args)
  File "xx\Bigscity-LibCity-master\libcity\pipeline\pipeline.py", line 63, in run_model
    executor.evaluate(test_data)
  File "xx\Bigscity-LibCity-master\libcity\executor\traj_loc_pred_executor.py", line 108, in evaluate
    self.evaluator.save_result(self.evaluate_res_dir)
  File "xx\Bigscity-LibCity-master\libcity\evaluator\traj_loc_pred_evaluator.py", line 96, in save_result
    self._logger.info('evaluate result is ', json.dumps(self.result, indent=1))
Message: 'evaluate result is '
Arguments: ('{\n "Recall@1": 0.16751398997842068\n}',)

Process finished with exit code 0

I have already installed the necessary requirements and now about to try to run run_model.py (with map matching task, STMatching model and T_DRIVE_SMALL dataset, and the rest remains default) however I am getting a key error. I am not sure how I can resolve the error? Thank you so much.

gcalix@tiger:~/Bigscity-LibCity$ python run_model.py --task map_matching --model STMatching --dataset T_DRIVE_SMALL 2022-07-28 20:24:15,996 - INFO - Log directory: ./libcity/log 2022-07-28 20:24:15,996 - INFO - Begin pipeline, task=map_matching, model_name=STMatching, dataset_name=T_DRIVE_SMALL, exp_id=87895 2022-07-28 20:24:15,996 - INFO - {'task': 'map_matching', 'model': 'STMatching', 'dataset': 'T_DRIVE_SMALL', 'saved_model': True, 'train': False, 'seed': 0, 'dataset_class': 'MapMatchingDataset', 'executor': 'MapMatchingExecutor', 'evaluator': 'MapMatchingEvaluator', 'k': 5, 'r': 200, 'mu': 0, 'sigma': 20, 'window_size': 40, 'delta_time': True, 'metrics': ['RMF', 'AN', 'AL'], 'save_modes': ['csv'], 'geo': {'including_types': ['Polygon'], 'Polygon': {'row_id': 'num', 'column_id': 'num'}}, 'grid': {'including_types': ['state'], 'state': {'row_id': 32, 'column_id': 32, 'inflow': 'num', 'outflow': 'num'}}, 'data_col': ['inflow', 'outflow'], 'data_files': ['T_DRIVE_SMALL'], 'geo_file': 'T_DRIVE_SMALL', 'output_dim': 2, 'init_weight_inf_or_zero': 'inf', 'set_weight_link_or_dist': 'dist', 'calculate_weight_adj': False, 'weight_adj_epsilon': 0.1, 'time_intervals': 3600, 'device': device(type='cuda', index=0), 'exp_id': 87895} Traceback (most recent call last): File "run_model.py", line 38, in <module> train=args.train, other_args=other_args) File "/home/gcalix/Bigscity-LibCity/libcity/pipeline/pipeline.py", line 46, in run_model dataset = get_dataset(config) File "/home/gcalix/Bigscity-LibCity/libcity/data/utils.py", line 22, in get_dataset config['dataset_class'])(config) File "/home/gcalix/Bigscity-LibCity/libcity/data/dataset/map_matching_dataset.py", line 48, in __init__ self.with_rd_speed = ('speed' in config['rel']['geo'].keys()) File "/home/gcalix/Bigscity-LibCity/libcity/config/config_parser.py", line 141, in __getitem__ raise KeyError('{} is not in the config'.format(key)) KeyError: 'rel is not in the config

我在安装你们的requirement.txt时遇到了无法安装torch_scatter的问题，于是我从网址上下载了这个库的whl文件，但是运行过程中依旧出现了错误。

代码中对于gridod数据的处理方法如下：

代码位置：libcity/data/dataset/traffic_state_grid_od_dataset.py里边的_load_grid_od_6d和_load_grid_od_4d。

他的这个遍历顺序是起点行、列，终点行、列，然后直接取整个len_time长度的数据进行赋值。但是现在的gridod数据格式如下：

按照现在的代码读进来的数据是错误的。现在数据读取的代码对于所有的数据都是统一的（先行后列、先起点后终点），所以数据集需要修复一下。 @l782993610

Nice work!!!

I tried to run quick start according to the readme, but found the following error:

TypeError: Descriptors cannot not be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are:
1. Downgrade the protobuf package to 3.20.x or lower.
2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).
 
More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates

This seems to conflict with the package ‘ray’, here is my solution:

pip uninstall protobuf
pip install protobuf==3.20.1

In addition, do you have a plan to support single machine-multi card and multi machine-multi card ?

1.用STMGAT模型进行实验时，提示“dgl._ffi.base.DGLError: There are 0-in-degree nodes in the graph, output for those nodes will be invalid. This is harmful for some applications, causing silent performance regression. Adding self-loop on the input graph by calling g = dgl.add_self_loop(g) will resolve the issue. Setting allow_zero_in_degree to be True when constructing this module will suppress the check and let the code run.”
2.用HGCN模型进行实验时，提示“IndexError: index 8 is out of bounds for dimension 0 with size 7”
3.用ATDM模型进行实验时，提示“RuntimeError: shape '[64, 3, 12, 307]' is invalid for input of size 235776”
4.用DKFN模型进行实验时，提示“ValueError: Input contains NaN, infinity or a value too large for dtype('float32').”
希望能得到您的帮助

我发现您在百度网盘提供的CSTN数据版本 落后于您在Bigscity-LibCity-Datasets脚本生成的数据 因为我发现这俩者数据不一致 显然新脚本生产的数据才是较为准备的 但是我也发现了一些其他问题

我发现row_id 与col_id 在定义与存储的时候好像错位了 但我不知道究竟是哪一个在前 希望能得到您的帮助

可改进目前的数据读取的不足：

• geo文件的geo_id和dyna文件中entity_id的顺序必须保持一致
• 网格则必须按照先遍历行后遍历列的顺序编码geo_id

是不是一定要安装pytorch-GPU版才能使用？谢谢

从百度云盘上下载的数据集Chengdu_Taxi_Sample1 和Beijing_Taxi_Sample 无法使用，前者缺失geo文件，后者Error tokenizing data. C error: EOF inside string starting at row 92677

• DeepMove 放到轨迹下一跳任务文件夹下
• DeepMove 未继承 AbstractModel

当数据集使用PEMSD3,并且模型选择 ASTGCN, MSTGCN,ASTGCNCommon, MSTGCNCommon会提示一个’scipy.sparse.linalg.eigen.arpack.arpack.ArpackNoConvergence: ARPACK error -1: No convergence (3581 iterations, 0/1 eigenvectors converged) [ARPACK error -14: SNAUPD did not find any eigenvalues to sufficient accuracy.]‘
请问如何修改

百度云中NYCTAXI202004-202006数据集的NYCTAXI202004-202006.od文件中显示This file is too big, please connect the author.请问下这个文件需要在哪里下载
希望能得到您的帮助

如题

有两个问题：
1、在处理最后以每个点为终点的转移概率矩阵的时候，需要用到马尔科夫链 𝑉 = 𝐷 + 𝑄 ⋅ 𝐷 + 𝑄2 ⋅ 𝐷 + ⋅⋅⋅ + 𝑄𝑡−1 ⋅ 𝐷 因为用的矩阵是稀疏矩阵 所以乘法的复杂度有O2 而且通常需要sys.MAXSIZE的乘方 感觉不太跑得动 不知如何处理
2、在聚类处理后很多轨迹会出现重复的情况 比如原来轨迹是1 2 3 4 聚类以后1 3 变成1个点了 轨迹就变成1 2 1 4了 前两步相当于无效轨迹 最终测试集量准确度的时候会有很大的误差 但如果去重又会毁坏轨迹数据的真实性

看了一下其他dataset里基本都有config.json文件，但MGD这个dataset的不知道是不是漏放了

我搜索了全文好像没看到NOTE2和NOTE3，请问这俩分别在哪呢？
只看到该页面出现过的NOTE

CARA.py 取出‘poi_profile’。

258        self.poi_profile = data_feature['poi_profile']

但是在cara_encoder.py中并没有'poi_profile'这个key值。
cara_encoder.py

126        self.data_feature = {
127           'loc_size': self.loc_id + 1,
128            'tim_size': self.tim_max + 2,
129            'uid_size': self.uid,
130           'loc_pad': loc_pad,
131            'tim_pad': tim_pad,
132            'id2locid': self.id2locid
133        }

已解决

def collator(indices): batch = Batch(feature_name, pad_item, pad_max_len) for item in indices: batch.append(copy.deepcopy(item)) batch.padding() return batch
为啥这里加了deepcopy呢，append()函数感觉并不会修改item本身。会不会影响速度？

您好，我用你们提供的处理好的数据“NYCTAXI202004-202006_OD”运行GEML模型发生错误。
命令行为：python run_model.py --task traffic_state_pred --model GEML --dataset NYCTAXI202004-202006_OD。
一开始提示错误为 No such file or directory: './raw_data/NYCTAXI202004-202006_OD/NYCTAXI202004-202006_OD.rel'。
然后我将文件中NYCTAXI202004-202006.rel 文件改为 NYCTAXI202004-202006_OD.rel 运行。
“- INFO - Loading file NYCTAXI202004-202006.od”时又发生错误：KeyError: "['inflow', 'outflow'] not in index"
请问这个模型使用哪个数据集运行？是数据集的问题还是代码的问题？

python hyper_tune.py --task traffic_state_pred --model GRU --dataset METR_LA --space_file sample_space_file
使用后提示

AttributeError: module 'idna' has no attribute 'IDNAError'
和
(raylet) ModuleNotFoundError: No module named 'aiohttp.signals'

Traceback (most recent call last):
  File "hyper_tune.py", line 65, in <module>
    other_args=other_args)
  File "/home/jy/Bigscity-LibCity/libcity/pipeline/pipeline.py", line 196, in hyper_parameter
    local_dir='./libcity/cache/hyper_tune', num_samples=num_samples)
  File "/home/jy/.local/lib/python3.7/site-packages/ray/tune/tune.py", line 364, in run
    callbacks, sync_config, metric=metric, loggers=loggers)
  File "/home/jy/.local/lib/python3.7/site-packages/ray/tune/utils/callback.py", line 120, in create_default_callbacks
    _sync_to_driver = detect_sync_to_driver(sync_config.sync_to_driver)
  File "/home/jy/.local/lib/python3.7/site-packages/ray/tune/syncer.py", line 461, in detect_sync_to_driver
    from ray.tune.integration.docker import DockerSyncer
  File "/home/jy/.local/lib/python3.7/site-packages/ray/tune/integration/docker.py", line 5, in <module>
    from ray.autoscaler.sdk import rsync, configure_logging
  File "/home/jy/.local/lib/python3.7/site-packages/ray/autoscaler/sdk.py", line 9, in <module>
    from ray.autoscaler._private import commands
  File "/home/jy/.local/lib/python3.7/site-packages/ray/autoscaler/_private/commands.py", line 28, in <module>
    from ray.autoscaler._private.util import validate_config, hash_runtime_conf, \
  File "/home/jy/.local/lib/python3.7/site-packages/ray/autoscaler/_private/util.py", line 6, in <module>
    import jsonschema
  File "/home/jy/anaconda3/envs/Pytorch171/lib/python3.7/site-packages/jsonschema/__init__.py", line 14, in <module>
    from jsonschema._format import (
  File "/home/jy/anaconda3/envs/Pytorch171/lib/python3.7/site-packages/jsonschema/_format.py", line 240, in <module>
    @_checks_drafts(draft7="idn-hostname", raises=idna.IDNAError)
AttributeError: module 'idna' has no attribute 'IDNAError'
(raylet) Traceback (most recent call last):
(raylet)   File "/home/jy/.local/lib/python3.7/site-packages/ray/new_dashboard/agent.py", line 22, in <module>
(raylet)     import ray.new_dashboard.utils as dashboard_utils
(raylet)   File "/home/jy/.local/lib/python3.7/site-packages/ray/new_dashboard/utils.py", line 20, in <module>
(raylet)     import aiohttp.signals
(raylet) ModuleNotFoundError: No module named 'aiohttp.signals'

在'task_config.json'确定待运行模型的执行器为TrafficStateExecutor，于是在在'TrafficStateExecutor.json'将"max_epoch": 1000更改为1000以后，发现实验过程中max_epoch仍为100，请问如何更改相关参数改变max_epoch呀？

目前好像只能一块卡训练，能不能你们把这个需求集成处理一下，自己一个个加太麻烦了，感谢

这个dyna有些数据集没有 是应该怎么生成

轨迹下一跳任务中的CARA模型 在task_config.json中指定"evaluator": "CARALocPredEvaluator"
但是config/evaluator中不包含CARALocPreEvaluator.json文件。
可能要添加CARALocPreEvaluator.json。

Thanks for building this excellent library!

I read the ranking of the models here: https://libcity.ai/#/ranking/METR-LA, and try to reproduce the results using METR-LA data.

I used the default setting (input_window 12 and output_window 12) but found the metrics of MTGNN is strange:

You can find that MTGNN only learns the first two steps well, then the performance almost remains unchanged.

Gensim是什么模型？只看到了executor

I have read your code for a long time, thank you for your great job! but, I think it has some bugs.
when I want to use STRNN to test trajectory location prediction with dataset--foursquare_tky, I get this bug:

File "/workdir/Bigscity-LibTraffic-master/libtraffic/model/trajectory_loc_prediction/STRNN.py", line 21, in init
self.poi_profile = data_feature['poi_profile']
KeyError: 'poi_profile'

and I think the input format of STRNN has some problems too：
you used：
"dataset_class": "TrajectoryDataset",
"executor": "TrajLocPredExecutor",
"evaluator": "TrajLocPredEvaluator",
"traj_encoder": "StandardTrajectoryEncoder"
I'm afraid they don't match，because I see there exists StrnnEncoder，but，I still can find the “data_feature['poi_profile']“

• 通过 feature_name 将特征对应的数据类型传入

感谢开源这么好的框架，第一次上手发现如下问题：

1. quick start 不详细，我按照quick start的教程开始做，python run_model.py 是运行不了的，因为没有指定参数。 而且你们没有说清楚需要下载哪些数据集之类的，让人找不到北。对新手不太友好。 之后运行python run_model.py --task traffic_state_pred --model DCRNN --dataset METR_LA的时候发现了很多安装包的问题，即使安装了requirements里面的包还是有很多包没覆盖到。 再次运行还是报错：代码import 库的时候是这样：import torch.tensor as tensor. 报错表示找不到tensor，修改为 from torch import tensor 解决了。

2. 到现在还是有问题没解决，torch-sparse 安装不上，我猜测是库和库之间依赖的问题！版本要对应起来！
   网上的解决办法是：
   pip install torch==1.2.0
   pip install torch_geometric==1.4.1
   pip install torch_sparse==0.4.4
   pip install torch_scatter==1.4.0
   pip install torch_cluster==1.4.5
   但你们的torch版本很高，我怕重装torch会出现其他的版本兼容问题。
   这个问题不知道该如何解决。
   总之，你们的框架写的很全面，早上起来刷到你们，我被震惊了，很佩服！这么大的工作量，代码，数据，文档，还有网站等等一些工作，对技术要求也很高，你们做到了，敬佩难以言表，但是使用体验很差，望改进！
   最后还是向你们致敬。

时间序列预测模型没有分步评估。
时间序列预测模型统一代码。

Traceback (most recent call last):
File "E:\conda\envs\pytorch\lib\site-packages\ray_private\services.py", line 655, in wait_for_redis_to_start
redis_client.client_list()
File "E:\conda\envs\pytorch\lib\site-packages\redis\client.py", line 1194, in client_list
return self.execute_command('CLIENT LIST')
File "E:\conda\envs\pytorch\lib\site-packages\redis\client.py", line 898, in execute_command
conn = self.connection or pool.get_connection(command_name, **options)
File "E:\conda\envs\pytorch\lib\site-packages\redis\connection.py", line 1192, in get_connection
connection.connect()
File "E:\conda\envs\pytorch\lib\site-packages\redis\connection.py", line 567, in connect
self.on_connect()
File "E:\conda\envs\pytorch\lib\site-packages\redis\connection.py", line 643, in on_connect
auth_response = self.read_response()
File "E:\conda\envs\pytorch\lib\site-packages\redis\connection.py", line 739, in read_response
response = self._parser.read_response()
File "E:\conda\envs\pytorch\lib\site-packages\redis\connection.py", line 484, in read_response
raise response
redis.exceptions.AuthenticationError: Client sent AUTH, but no password is set

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "hyper_tune.py", line 52, in
other_args=other_args)
File "H:\Bigscity-LibCity\libcity\pipeline\pipeline.py", line 211, in hyper_parameter
local_dir='./libcity/cache/hyper_tune', num_samples=num_samples)
File "E:\conda\envs\pytorch\lib\site-packages\ray\tune\tune.py", line 298, in run
_ray_auto_init()
File "E:\conda\envs\pytorch\lib\site-packages\ray\tune\tune.py", line 681, in _ray_auto_init
ray.init()
File "E:\conda\envs\pytorch\lib\site-packages\ray_private\client_mode_hook.py", line 82, in wrapper
return func(*args, **kwargs)
File "E:\conda\envs\pytorch\lib\site-packages\ray\worker.py", line 896, in init
ray_params=ray_params)
File "E:\conda\envs\pytorch\lib\site-packages\ray\node.py", line 248, in init
self.start_head_processes()
File "E:\conda\envs\pytorch\lib\site-packages\ray\node.py", line 894, in start_head_processes
self.start_redis()
File "E:\conda\envs\pytorch\lib\site-packages\ray\node.py", line 714, in start_redis
port_denylist=self._ray_params.reserved_ports)
File "E:\conda\envs\pytorch\lib\site-packages\ray_private\services.py", line 881, in start_redis
port_denylist=port_denylist)
File "E:\conda\envs\pytorch\lib\site-packages\ray_private\services.py", line 1029, in _start_redis_instance
wait_for_redis_to_start("127.0.0.1", port, password=password)
File "E:\conda\envs\pytorch\lib\site-packages\ray_private\services.py", line 666, in wait_for_redis_to_start
redis_ip_address, redis_port)) from authEx
RuntimeError: Unable to connect to Redis at 127.0.0.1:6379.

Thanks for your great job!

I am interested in the CCRNN model for the on-demand service prediction task. However, I don't know which dataset can be used in this model. Could you please help tell me the answer?
By the way, a list to introduce which dataset is suitable for the corresponding task may be greatly helpful for us.

Thanks again and look forward to your reply~

https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/get_started/quick_start.html
这里支持的模型没显示，按照英文版本 就是复现的模型吧

CSTNDataset 在dataset_subclass/init.py 遗漏

网格数据配合一般的模型，输出没保存成网格