refactor(exp/tf20): Convert experiment into integration test

This change removes the `TensorFlowExperiment` in favour of an
integration test that can be run during CI invocations. Given that the
experiment was not very sophisticated (in terms of data collection), we
believe it is better suited as an integration test.

2 files changed, 3 insertions, 65 deletions

diff --git a/opendc-experiments/opendc-experiments-tf20/src/main/kotlin/org/opendc/experiments/tf20/Models.kt b/opendc-experiments/opendc-experiments-tf20/src/main/kotlin/org/opendc/experiments/tf20/Models.kt
index 9ef5b621..be166bd5 100644
--- a/opendc-experiments/opendc-experiments-tf20/src/main/kotlin/org/opendc/experiments/tf20/Models.kt
+++ b/opendc-experiments/opendc-experiments-tf20/src/main/kotlin/org/opendc/experiments/tf20/Models.kt
@@ -20,8 +20,10 @@
  * SOFTWARE.
  */
 
-package org.opendc.experiments.tf20.keras
+package org.opendc.experiments.tf20
 
+import org.opendc.experiments.tf20.keras.Sequential
+import org.opendc.experiments.tf20.keras.TrainableModel
 import org.opendc.experiments.tf20.keras.activations.Activation
 import org.opendc.experiments.tf20.keras.layer.conv.Conv2D
 import org.opendc.experiments.tf20.keras.layer.conv.ConvPadding
diff --git a/opendc-experiments/opendc-experiments-tf20/src/main/kotlin/org/opendc/experiments/tf20/TensorFlowExperiment.kt b/opendc-experiments/opendc-experiments-tf20/src/main/kotlin/org/opendc/experiments/tf20/TensorFlowExperiment.kt
deleted file mode 100644
index 19236029..00000000
--- a/opendc-experiments/opendc-experiments-tf20/src/main/kotlin/org/opendc/experiments/tf20/TensorFlowExperiment.kt
+++ /dev/null
@@ -1,64 +0,0 @@
-/*
- * Copyright (c) 2021 AtLarge Research
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to deal
- * in the Software without restriction, including without limitation the rights
- * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
- * copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-
-package org.opendc.experiments.tf20
-
-import org.opendc.experiments.tf20.core.SimTFDevice
-import org.opendc.experiments.tf20.distribute.*
-import org.opendc.experiments.tf20.keras.AlexNet
-import org.opendc.experiments.tf20.util.MLEnvironmentReader
-import org.opendc.harness.dsl.Experiment
-import org.opendc.harness.dsl.anyOf
-import org.opendc.simulator.compute.power.LinearPowerModel
-import org.opendc.simulator.core.runBlockingSimulation
-
-/**
- * Experiments with the TensorFlow simulation model.
- */
-public class TensorFlowExperiment : Experiment(name = "tf20") {
-    /**
-     * The environment file to use.
-     */
-    private val environmentFile by anyOf("/kth.json")
-
-    /**
-     * The batch size used.
-     */
-    private val batchSize by anyOf(16, 32, 64, 128)
-
-    override fun doRun(repeat: Int): Unit = runBlockingSimulation {
-        val envInput = checkNotNull(TensorFlowExperiment::class.java.getResourceAsStream(environmentFile))
-        val def = MLEnvironmentReader().readEnvironment(envInput).first()
-        val device = SimTFDevice(
-            def.uid, def.meta["gpu"] as Boolean, coroutineContext, clock, def.model.cpus[0], def.model.memory[0],
-            LinearPowerModel(250.0, 60.0)
-        )
-        val strategy = OneDeviceStrategy(device)
-
-        val model = AlexNet(batchSize.toLong())
-        model.use {
-            it.compile(strategy)
-
-            it.fit(epochs = 9088 / batchSize, batchSize = batchSize)
-        }
-    }
-}