LearningSolver: Keep original H5 file unmodified

This commit is contained in:
2024-02-02 14:34:20 -06:00
parent 687c271d4d
commit e75850fab8
5 changed files with 25 additions and 8 deletions

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@@ -695,7 +695,7 @@
"source": [
"## Accessing the solution\n",
"\n",
"In the example above, we used `LearningSolver.solve` together with data files to solve both the training and the test instances. The optimal solutions were saved to HDF5 files in the train/test folders, and could be retrieved by reading theses files, but that is not very convenient. In the following example, we show how to build and solve a Pyomo model entirely in-memory, using our trained solver."
"In the example above, we used `LearningSolver.solve` together with data files to solve both the training and the test instances. In the following example, we show how to build and solve a Pyomo model entirely in-memory, using our trained solver."
]
},
{

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@@ -592,7 +592,7 @@
"source": [
"## Accessing the solution\n",
"\n",
"In the example above, we used `LearningSolver.solve` together with data files to solve both the training and the test instances. The optimal solutions were saved to HDF5 files in the train/test folders, and could be retrieved by reading theses files, but that is not very convenient. In the following example, we show how to build and solve a JuMP model entirely in-memory, using our trained solver."
"In the example above, we used `LearningSolver.solve` together with data files to solve both the training and the test instances. In the following example, we show how to build and solve a JuMP model entirely in-memory, using our trained solver."
]
},
{

View File

@@ -712,7 +712,7 @@
"source": [
"## Accessing the solution\n",
"\n",
"In the example above, we used `LearningSolver.solve` together with data files to solve both the training and the test instances. The optimal solutions were saved to HDF5 files in the train/test folders, and could be retrieved by reading theses files, but that is not very convenient. In the following example, we show how to build and solve a Pyomo model entirely in-memory, using our trained solver."
"In the example above, we used `LearningSolver.solve` together with data files to solve both the training and the test instances. In the following example, we show how to build and solve a Pyomo model entirely in-memory, using our trained solver."
]
},
{