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romeokienzler/gist:760f4a3879ea9d9f73cff1980e1235af Secret

Created July 11, 2017 20:49
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gistfile1.txt
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"class Neural_Network(object):\n",
" def __init__(self): \n",
" #Define Hyperparameters\n",
" self.inputLayerSize = 2\n",
" self.outputLayerSize = 1\n",
" self.hiddenLayerSize = 3\n",
" \n",
" #Weights (parameters)\n",
" self.W1 = np.random.randn(self.inputLayerSize, self.hiddenLayerSize)\n",
" self.W2 = np.random.randn(self.hiddenLayerSize, self.outputLayerSize)\n",
" \n",
" def forward(self, X):\n",
" #Propagate inputs though network\n",
" self.z2 = np.dot(X, self.W1)\n",
" self.a2 = self.sigmoid(self.z2)\n",
" self.z3 = np.dot(self.a2, self.W2)\n",
" yHat = self.sigmoid(self.z3) \n",
" return yHat\n",
" \n",
" def sigmoid(self, z):\n",
" #Apply sigmoid activation function to scalar, vector, or matrix\n",
" return 1/(1+np.exp(-z))\n",
" \n",
" def costFunction(self, X, y):\n",
" #Compute cost for given X,y, use weights already stored in class.\n",
" self.yHat = self.forward(X)\n",
" #print y\n",
" #print self.yHat\n",
" J = 0.5*sum((y-self.yHat)**2)\n",
" return J\n",
" \n",
" def sigmoidPrime(self,z):\n",
" #Gradient of sigmoid\n",
" return np.exp(-z)/((1+np.exp(-z))**2)\n",
" \n",
" def tanh(self,x):\n",
" return np.tanh(x)\n",
"\n",
" def tanh_deriv(self,x):\n",
" return 1.0 - np.tanh(x)**2\n",
"\n",
" def logistic(x):\n",
" return 1/(1 + np.exp(-x))\n",
"\n",
" def logistic_derivative(x):\n",
" return logistic(x)*(1-logistic(x))\n",
"\n",
" def costFunctionPrime(self, X, y):\n",
" #Compute derivative with respect to W and W2 for a given X and y:\n",
" self.yHat = self.forward(X)\n",
" \n",
" delta3 = np.multiply(-(y-self.yHat), self.sigmoidPrime(self.z3))\n",
" #delta3 = np.multiply(-(y-self.yHat), self.z3)\n",
" dJdW2 = np.dot(self.a2.T, delta3)\n",
" \n",
" delta2 = np.dot(delta3, self.W2.T)*self.sigmoidPrime(self.z2)\n",
" dJdW1 = np.dot(X.T, delta2) \n",
" \n",
" return dJdW1, dJdW2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"X = np.array(([3,5], [5,1], [10,2]), dtype=float)\n",
"y = np.array(([75], [82], [93]), dtype=float)\n",
"print X.shape\n",
"print y.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"X = np.random.rand(10000,2)\n",
"y = np.apply_along_axis( lambda element: element[0]+element[1], axis=1, arr=X )\n",
"y.shape=(10000,1)\n",
"print X.shape\n",
"print y.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"NN = Neural_Network()\n",
"max_iterations = 100\n",
"iter = 0\n",
"learningRate = 0.00001\n",
"while iter < max_iterations:\n",
" dJdW1, dJdW2 = NN.costFunctionPrime(X,NN.sigmoid(y))\n",
"\n",
" \n",
" #update\n",
" upd_W1 = NN.W1 - learningRate * dJdW1\n",
" upd_W2 = NN.W2 - learningRate * dJdW2\n",
" NN.W1 = NN.W1 + upd_W1\n",
" NN.W2 = NN.W2 + upd_W2\n",
" \n",
" print NN.costFunction(X,NN.sigmoid(y))\n",
" \n",
" iter = iter + 1\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print NN.tanh(y)\n",
"print NN.forward(X)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Archiver-Version: Plexus Archiver\n",
"Artifact-Id: systemml\n",
"Build-Jdk: 1.8.0_131\n",
"Build-Time: 2017-07-06 16:46:00 UTC\n",
"Built-By: reinwald\n",
"Created-By: Apache Maven 3.3.9\n",
"Group-Id: org.apache.systemml\n",
"Main-Class: org.apache.sysml.api.DMLScript\n",
"Manifest-Version: 1.0\n",
"Minimum-Recommended-Spark-Version: 2.1.0\n",
"Version: 1.0.0-SNAPSHOT\n",
"\n"
]
},
{
"data": {
"text/plain": [
"u'2.1.0'"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from systemml import MLContext, dml\n",
"ml = MLContext(sc)\n",
"print(ml.info())\n",
"sc.version"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"sigmoid = function(z) {\n",
" z=1/(1+exp(-z))\n",
"}\n",
"\n",
"X=matrix(c(3,5,5,1,10,2), nrow=3, ncol=2) \n",
"inputLayerSize = 2\n",
"outputLayerSize = 1\n",
"hiddenLayerSize = 3\n",
"\n",
"W1 = replicate(hiddenLayerSize, rnorm(inputLayerSize)) \n",
"W2 = replicate(outputLayerSize, rnorm(hiddenLayerSize)) \n",
"\n",
"feedForward = function (X,\n",
" W1,\n",
" W2) {\n",
" a2 = sigmoid(X %*% W1) \n",
" Y = sigmoid(a2 %*% W2)\n",
"}\n",
"\n",
"Yhat=feedForward(X,W1,W2)\n",
"print(nrow(X))\n",
"print(ncol(X))\n",
"print(nrow(W1))\n",
"print(ncol(W1))\n",
"print(Yhat)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"replicate(2, rnorm(20)) "
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"script = \"\"\"\n",
"\n",
"#\n",
"sigmoid = function(matrix[double] z) return (matrix[double] z) {\n",
" z = 1/(1+exp(-z))\n",
"}\n",
"\n",
"\n",
"sigmoidPrime = function(matrix[double] z) return (matrix[double] z) {\n",
" #Gradient of sigmoid\n",
" z = exp(-z)/(1+exp(-z))\n",
"}\n",
"\n",
"inputLayerSize = 2\n",
"outputLayerSize = 1\n",
"hiddenLayerSize = 3\n",
"\n",
"W1 = rand(rows=inputLayerSize,cols=hiddenLayerSize)\n",
"W2 = rand(rows=hiddenLayerSize,cols=outputLayerSize)\n",
"\n",
"feedForward = function (matrix[double] X,\n",
" matrix[double] W1,\n",
" matrix[double] W2) return (matrix[double] z2,matrix[double] a2,matrix[double] z3,matrix[double] Y) {\n",
" z2 = X %*% W1\n",
" a2 = sigmoid(z2)\n",
" z3 = (a2 %*% W2)\n",
" Y = sigmoid(z3)\n",
"}\n",
"\n",
"\n",
"gradient = function(matrix[double] X,\n",
" matrix[double] W1,\n",
" matrix[double] W2,\n",
" matrix[double] Y) return (matrix[double] dJdW1,matrix[double] dJdW1) {\n",
" #Compute derivative with respect to W and W2 for a given X and y:\n",
" [z2,a2,z3,Yhat] = feedForward(X,W1,W2)\n",
" \n",
" smpz3 = sigmoidPrime(z3)\n",
" delta3 = -(Y-Yhat) * smpz3\n",
" dJdW2 = t(a2) %*% delta3\n",
" \n",
" smpz2 = sigmoidPrime(z2)\n",
" delta2 = (delta3 %*% t(W2))*smpz2\n",
" dJdW1 = t(X) %*% delta2 \n",
"}\n",
"\n",
"max_iterations = 100\n",
"iter = 0\n",
"learningRate = 0.00001\n",
"while( iter < max_iterations ){\n",
" smy = sigmoid(y)\n",
" [dJdW1, dJdW2] = gradient(X,W1,W2,smy)\n",
"\n",
" \n",
" #update\n",
" W1 = W1 - learningRate * dJdW1\n",
" W2 = W2 - learningRate * dJdW2\n",
" \n",
" iter = iter + 1\n",
"}\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"ename": "Py4JJavaError",
"evalue": "An error occurred while calling o79.execute.\n: org.apache.sysml.api.mlcontext.MLContextException: Exception when executing script\n\tat org.apache.sysml.api.mlcontext.MLContext.execute(MLContext.java:320)\n\tat org.apache.sysml.api.mlcontext.MLContext.execute(MLContext.java:293)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:95)\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:55)\n\tat java.lang.reflect.Method.invoke(Method.java:507)\n\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\n\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\n\tat py4j.Gateway.invoke(Gateway.java:280)\n\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\n\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\n\tat py4j.GatewayConnection.run(GatewayConnection.java:214)\n\tat java.lang.Thread.run(Thread.java:785)\nCaused by: org.apache.sysml.api.mlcontext.MLContextException: Exception occurred while executing runtime program\n\tat org.apache.sysml.api.mlcontext.ScriptExecutor.executeRuntimeProgram(ScriptExecutor.java:397)\n\tat org.apache.sysml.api.mlcontext.ScriptExecutor.execute(ScriptExecutor.java:311)\n\tat org.apache.sysml.api.mlcontext.MLContext.execute(MLContext.java:316)\n\t... 12 more\nCaused by: org.apache.sysml.runtime.DMLRuntimeException: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in while program block generated from while statement block between lines 52 and 62 -- Error evaluating while program block\n\tat org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:130)\n\tat org.apache.sysml.api.ScriptExecutorUtils.executeRuntimeProgram(ScriptExecutorUtils.java:95)\n\tat org.apache.sysml.api.ScriptExecutorUtils.executeRuntimeProgram(ScriptExecutorUtils.java:54)\n\tat org.apache.sysml.api.mlcontext.ScriptExecutor.executeRuntimeProgram(ScriptExecutor.java:395)\n\t... 14 more\nCaused by: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in while program block generated from while statement block between lines 52 and 62 -- Error evaluating while program block\n\tat org.apache.sysml.runtime.controlprogram.WhileProgramBlock.execute(WhileProgramBlock.java:177)\n\tat org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:123)\n\t... 17 more\nCaused by: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in program block generated from statement block between lines 58 and 61 -- Error evaluating instruction: CP°-*°W2·MATRIX·DOUBLE°1.0E-5·SCALAR·DOUBLE·true°dJdW2·MATRIX·DOUBLE°_mVar117·MATRIX·DOUBLE\n\tat org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:320)\n\tat org.apache.sysml.runtime.controlprogram.ProgramBlock.executeInstructions(ProgramBlock.java:221)\n\tat org.apache.sysml.runtime.controlprogram.ProgramBlock.execute(ProgramBlock.java:167)\n\tat org.apache.sysml.runtime.controlprogram.WhileProgramBlock.execute(WhileProgramBlock.java:165)\n\t... 18 more\nCaused by: java.lang.RuntimeException: Block sizes are not matched for binary cell operations: 3x1 vs 2x3\n\tat org.apache.sysml.runtime.matrix.data.MatrixBlock.binaryOperations(MatrixBlock.java:2872)\n\tat org.apache.sysml.runtime.instructions.cp.PlusMultCPInstruction.processInstruction(PlusMultCPInstruction.java:66)\n\tat org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:290)\n\t... 21 more\n",
"output_type": "error",
"traceback": [
"\u001b[0;31m\u001b[0m",
"\u001b[0;31mPy4JJavaError\u001b[0mTraceback (most recent call last)",
"\u001b[0;32m<ipython-input-15-0641ddf39557>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprog\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdml\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mml\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprog\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;31m#print result.get(\"Yhat\").toNumPy()\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/gpfs/fs01/user/s4c2-1e12ab68a45670-980ba6aaa6c3/.local/lib/python2.7/site-packages/systemml/mlcontext.pyc\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, script)\u001b[0m\n\u001b[1;32m 338\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mval\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mscript\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_output\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 339\u001b[0m \u001b[0mscript_java\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 340\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mMLResults\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_ml\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscript_java\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 341\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 342\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0msetStatistics\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatistics\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/src/spark21master/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 1131\u001b[0m \u001b[0manswer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgateway_client\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend_command\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcommand\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1132\u001b[0m return_value = get_return_value(\n\u001b[0;32m-> 1133\u001b[0;31m answer, self.gateway_client, self.target_id, self.name)\n\u001b[0m\u001b[1;32m 1134\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1135\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mtemp_arg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtemp_args\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/src/spark21master/spark/python/pyspark/sql/utils.py\u001b[0m in \u001b[0;36mdeco\u001b[0;34m(*a, **kw)\u001b[0m\n\u001b[1;32m 61\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mdeco\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 62\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 63\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 64\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mpy4j\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPy4JJavaError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 65\u001b[0m \u001b[0ms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjava_exception\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtoString\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/src/spark21master/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py\u001b[0m in \u001b[0;36mget_return_value\u001b[0;34m(answer, gateway_client, target_id, name)\u001b[0m\n\u001b[1;32m 317\u001b[0m raise Py4JJavaError(\n\u001b[1;32m 318\u001b[0m \u001b[0;34m\"An error occurred while calling {0}{1}{2}.\\n\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 319\u001b[0;31m format(target_id, \".\", name), value)\n\u001b[0m\u001b[1;32m 320\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 321\u001b[0m raise Py4JError(\n",
"\u001b[0;31m<type 'str'>\u001b[0m: (<type 'exceptions.UnicodeEncodeError'>, UnicodeEncodeError('ascii', u'An error occurred while calling o79.execute.\\n: org.apache.sysml.api.mlcontext.MLContextException: Exception when executing script\\n\\tat org.apache.sysml.api.mlcontext.MLContext.execute(MLContext.java:320)\\n\\tat org.apache.sysml.api.mlcontext.MLContext.execute(MLContext.java:293)\\n\\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\\n\\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:95)\\n\\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:55)\\n\\tat java.lang.reflect.Method.invoke(Method.java:507)\\n\\tat py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\\n\\tat py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)\\n\\tat py4j.Gateway.invoke(Gateway.java:280)\\n\\tat py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\\n\\tat py4j.commands.CallCommand.execute(CallCommand.java:79)\\n\\tat py4j.GatewayConnection.run(GatewayConnection.java:214)\\n\\tat java.lang.Thread.run(Thread.java:785)\\nCaused by: org.apache.sysml.api.mlcontext.MLContextException: Exception occurred while executing runtime program\\n\\tat org.apache.sysml.api.mlcontext.ScriptExecutor.executeRuntimeProgram(ScriptExecutor.java:397)\\n\\tat org.apache.sysml.api.mlcontext.ScriptExecutor.execute(ScriptExecutor.java:311)\\n\\tat org.apache.sysml.api.mlcontext.MLContext.execute(MLContext.java:316)\\n\\t... 12 more\\nCaused by: org.apache.sysml.runtime.DMLRuntimeException: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in while program block generated from while statement block between lines 52 and 62 -- Error evaluating while program block\\n\\tat org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:130)\\n\\tat org.apache.sysml.api.ScriptExecutorUtils.executeRuntimeProgram(ScriptExecutorUtils.java:95)\\n\\tat org.apache.sysml.api.ScriptExecutorUtils.executeRuntimeProgram(ScriptExecutorUtils.java:54)\\n\\tat org.apache.sysml.api.mlcontext.ScriptExecutor.executeRuntimeProgram(ScriptExecutor.java:395)\\n\\t... 14 more\\nCaused by: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in while program block generated from while statement block between lines 52 and 62 -- Error evaluating while program block\\n\\tat org.apache.sysml.runtime.controlprogram.WhileProgramBlock.execute(WhileProgramBlock.java:177)\\n\\tat org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:123)\\n\\t... 17 more\\nCaused by: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in program block generated from statement block between lines 58 and 61 -- Error evaluating instruction: CP\\xb0-*\\xb0W2\\xb7MATRIX\\xb7DOUBLE\\xb01.0E-5\\xb7SCALAR\\xb7DOUBLE\\xb7true\\xb0dJdW2\\xb7MATRIX\\xb7DOUBLE\\xb0_mVar117\\xb7MATRIX\\xb7DOUBLE\\n\\tat org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:320)\\n\\tat org.apache.sysml.runtime.controlprogram.ProgramBlock.executeInstructions(ProgramBlock.java:221)\\n\\tat org.apache.sysml.runtime.controlprogram.ProgramBlock.execute(ProgramBlock.java:167)\\n\\tat org.apache.sysml.runtime.controlprogram.WhileProgramBlock.execute(WhileProgramBlock.java:165)\\n\\t... 18 more\\nCaused by: java.lang.RuntimeException: Block sizes are not matched for binary cell operations: 3x1 vs 2x3\\n\\tat org.apache.sysml.runtime.matrix.data.MatrixBlock.binaryOperations(MatrixBlock.java:2872)\\n\\tat org.apache.sysml.runtime.instructions.cp.PlusMultCPInstruction.processInstruction(PlusMultCPInstruction.java:66)\\n\\tat org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:290)\\n\\t... 21 more\\n', 2559, 2560, 'ordinal not in range(128)'))"
]
}
],
"source": [
"import numpy as np\n",
"X = np.random.rand(10000,2)\n",
"y = np.apply_along_axis( lambda element: element[0]+element[1], axis=1, arr=X )\n",
"y.shape=(10000,1)\n",
"prog = dml(script).input(X=X).input(y=y)\n",
"\n",
"result = ml.execute(prog)\n",
"\n",
"#print result.get(\"Yhat\").toNumPy()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2 with Spark 2.1",
"language": "python",
"name": "python2-spark21"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.11"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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