IBM Watson CPLEX 在求解 LP 文件时不显示变量，也没有解决方案

Question

我正在将以前在 IBM 的 DoCloud 上运行的应用程序迁移到基于 Watson 的新 API。由于我们的应用程序没有 CSV 格式的数据，也没有模型层和数据层之间的分离，上传一个 LP 文件和一个读取 LP 文件并解决它的模型文件似乎更简单。我可以上传并且它声称可以正确解决但返回空的解决状态。我还输出了各种模型信息（例如变量的数量），并且一切都归零了。我已经确认 LP 不是空白的 - 它有一个微不足道的 MILP。

这是我的模型代码（其中大部分直接取自https://dataplatform.cloud.ibm.com/exchange/public/entry/view/50fa9246181026cd7ae2a5bc7e4ac7bd 上的示例）：

import os
import sys
from os.path import splitext

import pandas
from docplex.mp.model_reader import ModelReader
from docplex.util.environment import get_environment
from six import iteritems


def loadModelFiles():
    """Load the input CSVs and extract the model and param data from it
    """
    env = get_environment()
    inputModel = params = None
    modelReader = ModelReader()

    for inputName in [f for f in os.listdir('.') if splitext(f)[1] != '.py']:
        inputBaseName, ext = splitext(inputName)

        print(f'Info: loading {inputName}')

        try:
            if inputBaseName == 'model':
                inputModel = modelReader.read_model(inputName, model_name=inputBaseName)
            elif inputBaseName == 'params':
                params = modelReader.read_prm(inputName)
        except Exception as e:
            with env.get_input_stream(inputName) as inStream:
                inData = inStream.read()
            raise Exception(f'Error: {e} found while processing {inputName} with contents {inData}')

    if inputModel is None or params is None:
        print('Warning: error loading model or params, see earlier messages for details')

    return inputModel, params


def writeOutputs(outputs):
    """Write all dataframes in ``outputs`` as .csv.

    Args:
        outputs: The map of outputs 'outputname' -> 'output df'
    """
    for (name, df) in iteritems(outputs):
        csv_file = '%s.csv' % name
        print(csv_file)
        with get_environment().get_output_stream(csv_file) as fp:
            if sys.version_info[0] < 3:
                fp.write(df.to_csv(index=False, encoding='utf8'))
            else:
                fp.write(df.to_csv(index=False).encode(encoding='utf8'))
    if len(outputs) == 0:
        print("Warning: no outputs written")


# load and solve model
model, modelParams = loadModelFiles()
ok = model.solve(cplex_parameters=modelParams)

solution_df = pandas.DataFrame(columns=['name', 'value'])

for index, dvar in enumerate(model.solution.iter_variables()):
    solution_df.loc[index, 'name'] = dvar.to_string()
    solution_df.loc[index, 'value'] = dvar.solution_value

outputs = {}
outputs['solution'] = solution_df

# Generate output files
writeOutputs(outputs)

try:
    with get_environment().get_output_stream('test.txt') as fp:
        fp.write(f'{model.get_statistics()}'.encode('utf-8'))

except Exception as e:
    with get_environment().get_output_stream('excInfo') as fp:
        fp.write(f'Got exception {e}')

以及运行它的代码存根（再次从示例中大量提取）：

prmFile = NamedTemporaryFile()
prmFile.write(self.ctx.cplex_parameters.export_prm_to_string().encode())
modelFile = NamedTemporaryFile()
modelFile.write(self.solver.export_as_lp_string(hide_user_names=True).encode())
modelMetadata = {
    self.client.repository.ModelMetaNames.NAME: self.name,
    self.client.repository.ModelMetaNames.TYPE: 'do-docplex_12.9',
    self.client.repository.ModelMetaNames.RUNTIME_UID: 'do_12.9'
}
baseDir = os.path.dirname(os.path.realpath(__file__))

def reset(tarinfo):
    tarinfo.uid = tarinfo.gid = 0
    tarinfo.uname = tarinfo.gname = 'root'
    return tarinfo

with NamedTemporaryFile() as tmp:
    tar = tarfile.open(tmp.name, 'w:gz')
    tar.add(f'{baseDir}/ibm_model.py', arcname='main.py', filter=reset)
    tar.add(prmFile.name, arcname='params.prm', filter=reset)
    tar.add(modelFile.name, arcname='model.lp', filter=reset)
    tar.close()

    modelDetails = self.client.repository.store_model(
        model=tmp.name,
        meta_props=modelMetadata
    )

    modelUid = self.client.repository.get_model_uid(modelDetails)

metaProps = {
    self.client.deployments.ConfigurationMetaNames.NAME: self.name,
    self.client.deployments.ConfigurationMetaNames.BATCH: {},
    self.client.deployments.ConfigurationMetaNames.COMPUTE: {'name': 'S', 'nodes': 1}
}
deployDetails = self.client.deployments.create(modelUid, meta_props=metaProps)
deployUid = self.client.deployments.get_uid(deployDetails)

solvePayload = {
    # we upload input data as part of model since only CSV data is supported in this interface
    self.client.deployments.DecisionOptimizationMetaNames.INPUT_DATA: [],
    self.client.deployments.DecisionOptimizationMetaNames.OUTPUT_DATA: [
        {
            "id": ".*"
        }
    ]
}

jobDetails = self.client.deployments.create_job(deployUid, solvePayload)
jobUid = self.client.deployments.get_job_uid(jobDetails)

while jobDetails['entity']['decision_optimization']['status']['state'] not in ['completed', 'failed',
                                                                                'canceled']:
    logger.debug(jobDetails['entity']['decision_optimization']['status']['state'] + '...')
    time.sleep(5)
    jobDetails = self.client.deployments.get_job_details(jobUid)

logger.debug(jobDetails['entity']['decision_optimization']['status']['state'])

# cleanup
self.client.repository.delete(modelUid)
prmFile.close()
modelFile.close()

关于什么可能导致这种情况或什么是好的测试途径的任何想法？似乎没有办法查看模型的输出进行调试，我在 Watson Studio 中遗漏了什么吗？

Answer 1

感谢 Alain 验证了整体方法，但主要问题是我的代码中存在一个错误：

调用后，modelFile.write(...)需要调用modelFile.seek(0)重置文件指针 - 否则它将向 tar 存档写入一个空文件