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Cleanup outputs
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Diff for: ‎Automatic Relevance Determination.ipynb

+21-172
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@@ -28,114 +28,36 @@
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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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"data": {
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"text/plain": [
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"\u001b[32mimport \u001b[39m\u001b[36m$ivy.$ \n",
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"\u001b[39m\n",
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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": 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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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import $ivy.`scala-infer::scala-infer:0.3`\n",
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"import $ivy.`org.jupyter-scala::kernel-api:0.4.1`"
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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": 3,
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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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"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.Functions._\n",
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"\u001b[39m\n",
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"\u001b[32mimport \u001b[39m\u001b[36mscappla.distributions._\n",
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"\u001b[39m\n",
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"\u001b[32mimport \u001b[39m\u001b[36mscappla.guides._\n",
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"\u001b[39m\n",
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"\u001b[32mimport \u001b[39m\u001b[36mscappla.optimization._\n",
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"\u001b[39m\n",
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"\u001b[32mimport \u001b[39m\u001b[36mscappla.tensor.Tensor._\n",
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"\u001b[39m\n",
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"\u001b[32mimport \u001b[39m\u001b[36mscappla.tensor._\u001b[39m"
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]
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},
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"execution_count": 3,
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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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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import scappla._\n",
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"import scappla.Functions._\n",
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"import scappla.distributions._\n",
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"import scappla.guides._\n",
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"import scappla.optimization._\n",
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"import scappla.tensor.Tensor._\n",
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"import scappla.tensor._"
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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": 4,
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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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"data": {
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"text/plain": [
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"\u001b[32mimport \u001b[39m\u001b[36mscala.util.Random\u001b[39m"
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]
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},
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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.tensor._\n",
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"\n",
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"import scala.util.Random"
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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": 5,
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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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"data": {
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"text/plain": [
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"defined \u001b[32mclass\u001b[39m \u001b[36mRecord\u001b[39m\n",
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"defined \u001b[32mclass\u001b[39m \u001b[36mBatch\u001b[39m\n",
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"\u001b[36mbatch\u001b[39m: \u001b[32mBatch\u001b[39m = \u001b[33mBatch\u001b[39m(\u001b[32m1000\u001b[39m)\n",
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"\u001b[36ma_vals\u001b[39m: \u001b[32mValue\u001b[39m[\u001b[32mArrayTensor\u001b[39m, \u001b[32mBatch\u001b[39m] = scappla.Constant@12f3f093\n",
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"\u001b[36mb_vals\u001b[39m: \u001b[32mValue\u001b[39m[\u001b[32mArrayTensor\u001b[39m, \u001b[32mBatch\u001b[39m] = scappla.Constant@31e80b51\n",
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"\u001b[36my_vals\u001b[39m: \u001b[32mValue\u001b[39m[\u001b[32mArrayTensor\u001b[39m, \u001b[32mBatch\u001b[39m] = scappla.Constant@5f6ae152"
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]
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},
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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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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"case class Record(a: Float, b: Float, y: Float)\n",
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"\n",
@@ -165,39 +87,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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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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"data": {
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"text/plain": [
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"\u001b[36ma_prior_s\u001b[39m: \u001b[32mParam\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = scappla.Param@7e13f371\n",
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"\u001b[36mb_prior_s\u001b[39m: \u001b[32mParam\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = scappla.Param@314da4f9\n",
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"\u001b[36ma_post_mu\u001b[39m: \u001b[32mParam\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = scappla.Param@33764907\n",
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"\u001b[36ma_post_s\u001b[39m: \u001b[32mParam\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = scappla.Param@3a272583\n",
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"\u001b[36ma_guide\u001b[39m: \u001b[32mReparamGuide\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = \u001b[33mReparamGuide\u001b[39m(\n",
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" \u001b[33mNormal\u001b[39m(scappla.Param@33764907, \u001b[33mApply1\u001b[39m(scappla.Param@3a272583, <function1>))\n",
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")\n",
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"\u001b[36mb_post_mu\u001b[39m: \u001b[32mParam\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = scappla.Param@5cbb302d\n",
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"\u001b[36mb_post_s\u001b[39m: \u001b[32mParam\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = scappla.Param@5d9b0110\n",
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"\u001b[36mb_guide\u001b[39m: \u001b[32mReparamGuide\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = \u001b[33mReparamGuide\u001b[39m(\n",
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" \u001b[33mNormal\u001b[39m(scappla.Param@5cbb302d, \u001b[33mApply1\u001b[39m(scappla.Param@5d9b0110, <function1>))\n",
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")\n",
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"\u001b[36mnoise_mu\u001b[39m: \u001b[32mParam\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = scappla.Param@33f65cad\n",
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"\u001b[36mnoise_s\u001b[39m: \u001b[32mParam\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = scappla.Param@58927bd0\n",
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"\u001b[36mnoise_guide\u001b[39m: \u001b[32mReparamGuide\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m] = \u001b[33mReparamGuide\u001b[39m(\n",
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" \u001b[33mNormal\u001b[39m(scappla.Param@33f65cad, \u001b[33mApply1\u001b[39m(scappla.Param@58927bd0, <function1>))\n",
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")\n",
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"\u001b[36mmodel\u001b[39m: \u001b[32mModel\u001b[39m[\u001b[32mUnit\u001b[39m] = ammonite.$sess.cmd5$Helper$$anon$1@67449597"
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]
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},
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"execution_count": 6,
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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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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"val a_prior_s = Param(0.0)\n",
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"val b_prior_s = Param(0.0)\n",
@@ -229,34 +121,13 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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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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"data": {
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"text/plain": [
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"\u001b[36mopt\u001b[39m: \u001b[32mAdam\u001b[39m = scappla.optimization.Adam@7bc3e74f\n",
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"\u001b[36minterpreter\u001b[39m: \u001b[32mOptimizingInterpreter\u001b[39m = scappla.OptimizingInterpreter@115f4b3"
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]
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},
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"execution_count": 7,
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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 opt = new Adam(0.1)\n",
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"val interpreter = new OptimizingInterpreter(opt)"
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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": 15,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"val opt = new Adam(0.1)\n",
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"val interpreter = new OptimizingInterpreter(opt)\n",
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"\n",
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"for { _ <- 0 until 10000 } {\n",
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" interpreter.reset()\n",
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" model.sample(interpreter)\n",
@@ -265,31 +136,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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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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"data": {
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"text/plain": [
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"\u001b[36mparams\u001b[39m: \u001b[32mSeq\u001b[39m[(\u001b[32mString\u001b[39m, \u001b[32mExpr\u001b[39m[\u001b[32mDouble\u001b[39m, \u001b[32mUnit\u001b[39m])] = \u001b[33mList\u001b[39m(\n",
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" (\u001b[32m\"a_prior\"\u001b[39m, \u001b[33mApply1\u001b[39m(scappla.Param@7e13f371, <function1>)),\n",
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" (\u001b[32m\"b_prior\"\u001b[39m, \u001b[33mApply1\u001b[39m(scappla.Param@314da4f9, <function1>)),\n",
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" (\u001b[32m\"a_post_mu\"\u001b[39m, scappla.Param@33764907),\n",
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" (\u001b[32m\"a_post_s\"\u001b[39m, \u001b[33mApply1\u001b[39m(scappla.Param@3a272583, <function1>)),\n",
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" (\u001b[32m\"b_post_mu\"\u001b[39m, scappla.Param@5cbb302d),\n",
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" (\u001b[32m\"b_post_s\"\u001b[39m, \u001b[33mApply1\u001b[39m(scappla.Param@5d9b0110, <function1>)),\n",
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" (\u001b[32m\"noise_mu\"\u001b[39m, \u001b[33mApply1\u001b[39m(scappla.Param@33f65cad, <function1>)),\n",
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" (\u001b[32m\"noise_s\"\u001b[39m, \u001b[33mApply1\u001b[39m(scappla.Param@58927bd0, <function1>))\n",
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")"
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]
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},
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"execution_count": 17,
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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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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"val params = Seq(\n",
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" \"a_prior\" -> exp(a_prior_s),\n",

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