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fvlankveltfvlankvelt
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Convert to scala-infer 0.3, add ARD notebook
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+454
-104
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4 files changed

+454
-104
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Diff for: ‎AutoDiff.ipynb

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@@ -9,72 +9,63 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"interp.repositories() ++= Seq(\n",
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" coursier.MavenRepository(\"https://dl.bintray.com/scala-infer/maven\")\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": true
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Downloading https://repo1.maven.org/maven2/org/bytedeco/javacpp-presets/mkl-platform/2019.0-1.4.3/mkl-platform-2019.0-1.4.3-sources.jar\n",
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"Downloading https://repo1.maven.org/maven2/org/bytedeco/javacpp-presets/mkl-platform/2019.0-1.4.3/mkl-platform-2019.0-1.4.3-sources.jar.sha1\n",
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"Downloading https://repo1.maven.org/maven2/org/bytedeco/javacpp-presets/mkl-dnn-platform/0.16-1.4.3/mkl-dnn-platform-0.16-1.4.3-sources.jar\n",
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"Downloading https://repo1.maven.org/maven2/org/bytedeco/javacpp-presets/mkl-dnn-platform/0.16-1.4.3/mkl-dnn-platform-0.16-1.4.3-sources.jar.sha1\n",
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"Downloading https://repo1.maven.org/maven2/org/nd4j/nd4j-backend-impls/1.0.0-beta3/nd4j-backend-impls-1.0.0-beta3-sources.jar\n",
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"Downloading https://repo1.maven.org/maven2/org/nd4j/nd4j-backend-impls/1.0.0-beta3/nd4j-backend-impls-1.0.0-beta3-sources.jar.sha1\n",
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"Downloading https://repo1.maven.org/maven2/org/bytedeco/javacpp-presets/openblas-platform/0.3.3-1.4.3/openblas-platform-0.3.3-1.4.3-sources.jar\n",
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"Downloading https://repo1.maven.org/maven2/org/bytedeco/javacpp-presets/openblas-platform/0.3.3-1.4.3/openblas-platform-0.3.3-1.4.3-sources.jar.sha1\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"\u001b[32mimport \u001b[39m\u001b[36m$ivy.$ \u001b[39m"
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"\u001b[32mimport \u001b[39m\u001b[36m$ivy.$ \u001b[39m"
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]
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},
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"execution_count": 9,
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"interp.repositories() ++= Seq(\n",
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" coursier.MavenRepository(\"https://dl.bintray.com/fvlankvelt/maven\")\n",
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")\n",
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"import $ivy.`fvlankvelt::scala-infer:0.1`"
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"import $ivy.`scala-infer::scala-infer:0.3`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\u001b[32mimport \u001b[39m\u001b[36mscappla._\n",
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"\u001b[39m\n",
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"\u001b[32mimport \u001b[39m\u001b[36mscappla.Real._\n",
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"\u001b[39m\n",
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"\u001b[32mimport \u001b[39m\u001b[36mscappla.Functions._\n",
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"\n",
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"\u001b[39m\n",
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"defined \u001b[32mclass\u001b[39m \u001b[36mParam\u001b[39m"
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"defined \u001b[32mclass\u001b[39m \u001b[36mVar\u001b[39m"
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]
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},
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"execution_count": 10,
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import scappla._\n",
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"import scappla.Real._\n",
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"import scappla.Functions._\n",
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"\n",
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"case class Param(name: String, v: Double = 0.0) extends Real {\n",
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"case class Var(name: String, v: Double = 0.0) extends AbstractReal {\n",
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" \n",
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" override def dv(d: Double): Unit = {\n",
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" println(s\"grad $name = $d\")\n",
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\u001b[36mx\u001b[39m: \u001b[32mParam\u001b[39m = \u001b[33mParam\u001b[39m(\u001b[32m\"x\"\u001b[39m, \u001b[32m2.0\u001b[39m)\n",
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"\u001b[36my\u001b[39m: \u001b[32mParam\u001b[39m = \u001b[33mParam\u001b[39m(\u001b[32m\"y\"\u001b[39m, \u001b[32m3.0\u001b[39m)\n",
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"\u001b[36mz\u001b[39m: \u001b[32mExpr\u001b[39m[\u001b[32mDouble\u001b[39m] = \u001b[33mDAdd\u001b[39m(\u001b[33mParam\u001b[39m(\u001b[32m\"x\"\u001b[39m, \u001b[32m2.0\u001b[39m), \u001b[33mParam\u001b[39m(\u001b[32m\"y\"\u001b[39m, \u001b[32m3.0\u001b[39m))\n",
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"\u001b[36mres10_3\u001b[39m: \u001b[32mDouble\u001b[39m = \u001b[32m5.0\u001b[39m"
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"\u001b[36mx\u001b[39m: \u001b[32mVar\u001b[39m = \u001b[33mVar\u001b[39m(\u001b[32m\"x\"\u001b[39m, \u001b[32m2.0\u001b[39m)\n",
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"\u001b[36my\u001b[39m: \u001b[32mVar\u001b[39m = \u001b[33mVar\u001b[39m(\u001b[32m\"y\"\u001b[39m, \u001b[32m3.0\u001b[39m)\n",
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"\u001b[36mz\u001b[39m: \u001b[32mValue\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = \u001b[33mVPlus\u001b[39m(\u001b[33mVar\u001b[39m(\u001b[32m\"x\"\u001b[39m, \u001b[32m2.0\u001b[39m), \u001b[33mVar\u001b[39m(\u001b[32m\"y\"\u001b[39m, \u001b[32m3.0\u001b[39m))\n",
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"\u001b[36mres4_3\u001b[39m: \u001b[32mDouble\u001b[39m = \u001b[32m5.0\u001b[39m"
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]
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},
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"execution_count": 11,
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"val x = Param(\"x\", 2.0)\n",
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"val y = Param(\"y\", 3.0)\n",
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"val x = Var(\"x\", 2.0)\n",
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"val y = Var(\"y\", 3.0)\n",
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"val z = x + y\n",
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"z.v"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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"data": {
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"text/plain": [
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"\u001b[36mw\u001b[39m: \u001b[32mReal\u001b[39m = Log(x)\n",
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"\u001b[36mres12_1\u001b[39m: \u001b[32mDouble\u001b[39m = \u001b[32m0.6931471805599453\u001b[39m"
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"\u001b[36mw\u001b[39m: \u001b[32mValue\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = \u001b[33mVLog\u001b[39m(\u001b[33mVar\u001b[39m(\u001b[32m\"x\"\u001b[39m, \u001b[32m2.0\u001b[39m))\n",
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"\u001b[36mres6_1\u001b[39m: \u001b[32mDouble\u001b[39m = \u001b[32m0.6931471805599453\u001b[39m"
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]
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},
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"execution_count": 13,
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
@@ -176,7 +167,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\u001b[36mu\u001b[39m: \u001b[32mReal\u001b[39m = Log(Const(1.0000) / (Exp(-x) + Const(1.0000)))\n",
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"\u001b[36mres14_1\u001b[39m: \u001b[32mDouble\u001b[39m = \u001b[32m-0.12692801104297263\u001b[39m"
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"\u001b[36mu\u001b[39m: \u001b[32mValue\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = \u001b[33mVLog\u001b[39m(\u001b[33mVSigmoid\u001b[39m(\u001b[33mVar\u001b[39m(\u001b[32m\"x\"\u001b[39m, \u001b[32m2.0\u001b[39m)))\n",
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"\u001b[36mres8_1\u001b[39m: \u001b[32mDouble\u001b[39m = \u001b[32m-0.12692801104297263\u001b[39m"
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]
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},
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"execution_count": 15,
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"execution_count": 9,
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"metadata": {},
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}
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{

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