Added TensorFlow sample (#541)
* Added TensorFlow sample * Added graph to TensorFlow sample * Added session to TensorFlow sample * added description to readme, cleaned up tensorflow.def, used lambda for deallocator, call Status.delete on error
This commit is contained in:
Julius Kunze
committed by
Nikolay Igotti
Nikolay Igotti
parent
717f9ebc74
commit
7afa5e395a
@@ -0,0 +1,228 @@
|
||||
import kotlinx.cinterop.*
|
||||
import tensorflow.*
|
||||
|
||||
typealias Status = CPointer<TF_Status>
|
||||
typealias Operation = CPointer<TF_Operation>
|
||||
typealias Tensor = CPointer<TF_Tensor>
|
||||
|
||||
val Status.isOk: Boolean get() = TF_GetCode(this) == TF_OK
|
||||
val Status.errorMessage: String get() = TF_Message(this)!!.toKString()
|
||||
fun Status.delete() = TF_DeleteStatus(this)
|
||||
fun Status.validate() {
|
||||
try {
|
||||
if (!isOk) {
|
||||
throw Error("Status is not ok: $errorMessage")
|
||||
}
|
||||
} finally {
|
||||
delete()
|
||||
}
|
||||
}
|
||||
|
||||
inline fun <T> statusValidated(block: (Status) -> T): T {
|
||||
val status = TF_NewStatus()!!
|
||||
val result = block(status)
|
||||
status.validate()
|
||||
return result
|
||||
}
|
||||
|
||||
fun scalarTensor(value: Int): Tensor {
|
||||
val data = nativeHeap.allocArray<IntVar>(1)
|
||||
data[0] = value
|
||||
|
||||
return TF_NewTensor(TF_INT32,
|
||||
dims = null, num_dims = 0,
|
||||
data = data, len = IntVar.size,
|
||||
deallocator = staticCFunction { dataToFree, _, _ -> nativeHeap.free(dataToFree!!.reinterpret<IntVar>()) },
|
||||
deallocator_arg = null)!!
|
||||
}
|
||||
|
||||
val Tensor.scalarIntValue: Int get() {
|
||||
if (TF_INT32 != TF_TensorType(this) || IntVar.size != TF_TensorByteSize(this)) {
|
||||
throw Error("Tensor is not of type int.")
|
||||
}
|
||||
if (0 != TF_NumDims(this)) {
|
||||
throw Error("Tensor is not scalar.")
|
||||
}
|
||||
|
||||
return TF_TensorData(this)!!.reinterpret<IntVar>().pointed.value
|
||||
}
|
||||
|
||||
|
||||
class Graph {
|
||||
val tensorflowGraph = TF_NewGraph()!!
|
||||
|
||||
inline fun operation(type: String, name: String, initDescription: (CPointer<TF_OperationDescription>) -> Unit): Operation {
|
||||
val description = TF_NewOperation(tensorflowGraph, type, name)!!
|
||||
initDescription(description)
|
||||
return statusValidated { TF_FinishOperation(description, it)!! }
|
||||
}
|
||||
|
||||
fun constant(value: Int, name: String = "scalarIntConstant") = operation("Const", name) { description ->
|
||||
statusValidated { TF_SetAttrTensor(description, "value", scalarTensor(value), it) }
|
||||
TF_SetAttrType(description, "dtype", TF_INT32)
|
||||
}
|
||||
|
||||
fun intInput(name: String = "input") = operation("Placeholder", name) { description ->
|
||||
TF_SetAttrType(description, "dtype", TF_INT32)
|
||||
}
|
||||
|
||||
fun add(left: Operation, right: Operation, name: String = "add") = memScoped {
|
||||
val inputs = allocArray<TF_Output>(2)
|
||||
inputs[0].apply { oper = left; index = 0 }
|
||||
inputs[1].apply { oper = right; index = 0 }
|
||||
|
||||
operation("AddN", name) { description ->
|
||||
TF_AddInputList(description, inputs, 2)
|
||||
}
|
||||
}
|
||||
|
||||
// TODO set unique operation names
|
||||
operator fun Operation.plus(right: Operation) = add(this, right)
|
||||
|
||||
inline fun <T> withSession(block: Session.() -> T): T {
|
||||
val session = Session(this)
|
||||
try {
|
||||
return session.block()
|
||||
} finally {
|
||||
session.dispose()
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
class Session(val graph: Graph) {
|
||||
private val inputs = mutableListOf<TF_Output>()
|
||||
private val inputValues = mutableListOf<Tensor>()
|
||||
private var outputs = mutableListOf<TF_Output>()
|
||||
private val outputValues = mutableListOf<Tensor?>()
|
||||
private val targets = listOf<Operation>()
|
||||
|
||||
private fun createNewSession(): CPointer<TF_Session> {
|
||||
val options = TF_NewSessionOptions()
|
||||
val session = statusValidated { TF_NewSession(graph.tensorflowGraph, options, it)!! }
|
||||
TF_DeleteSessionOptions(options)
|
||||
return session
|
||||
}
|
||||
|
||||
private var tensorflowSession: CPointer<TF_Session>? = createNewSession()
|
||||
|
||||
private fun clearInputValues() {
|
||||
for (inputValue in inputValues) {
|
||||
TF_DeleteTensor(inputValue)
|
||||
}
|
||||
|
||||
inputValues.clear()
|
||||
}
|
||||
|
||||
private fun clearOutputValues() {
|
||||
for (outputValue in outputValues) {
|
||||
if (outputValue != null)
|
||||
TF_DeleteTensor(outputValue)
|
||||
}
|
||||
outputValues.clear()
|
||||
}
|
||||
|
||||
fun dispose() {
|
||||
clearInputValues()
|
||||
clearOutputValues()
|
||||
clearInputs()
|
||||
clearOutputs()
|
||||
|
||||
if (tensorflowSession != null) {
|
||||
statusValidated { TF_CloseSession(tensorflowSession, it) }
|
||||
statusValidated { TF_DeleteSession(tensorflowSession, it) }
|
||||
tensorflowSession = null
|
||||
}
|
||||
}
|
||||
|
||||
private fun setInputsWithValues(inputsWithValues: List<Pair<Operation, Tensor>>) {
|
||||
clearInputValues()
|
||||
clearInputs()
|
||||
for ((input, inputValue) in inputsWithValues) {
|
||||
this.inputs.add(nativeHeap.alloc<TF_Output>().apply { oper = input; index = 0 })
|
||||
inputValues.add(inputValue)
|
||||
}
|
||||
}
|
||||
|
||||
private fun setOutputs(outputs: List<Operation>) {
|
||||
clearOutputValues()
|
||||
clearOutputs()
|
||||
this.outputs = outputs.map { nativeHeap.alloc<TF_Output>().apply { oper = it; index = 0 } }.toMutableList()
|
||||
}
|
||||
|
||||
private fun clearOutputs() {
|
||||
this.outputs.forEach { nativeHeap.free(it) }
|
||||
this.outputs.clear()
|
||||
}
|
||||
|
||||
private fun clearInputs() {
|
||||
this.inputs.forEach { nativeHeap.free(it) }
|
||||
this.inputs.clear()
|
||||
}
|
||||
|
||||
operator fun invoke(outputs: List<Operation>, inputsWithValues: List<Pair<Operation, Tensor>> = listOf()): List<Tensor?> {
|
||||
setInputsWithValues(inputsWithValues)
|
||||
setOutputs(outputs)
|
||||
|
||||
return invoke()
|
||||
}
|
||||
|
||||
operator fun invoke(output: Operation, inputsWithValues: List<Pair<Operation, Tensor>> = listOf()) =
|
||||
invoke(listOf(output), inputsWithValues).single()!!
|
||||
|
||||
operator fun invoke(): List<Tensor?> {
|
||||
if (inputs.size != inputValues.size) {
|
||||
throw Error("Call SetInputs() before Run()")
|
||||
}
|
||||
clearOutputValues()
|
||||
|
||||
val inputsCArray = if (inputs.any()) nativeHeap.allocArray<TF_Output>(inputs.size) else null
|
||||
|
||||
inputs.forEachIndexed { i, input ->
|
||||
inputsCArray!![i].apply {
|
||||
oper = input.oper
|
||||
index = input.index
|
||||
}
|
||||
}
|
||||
|
||||
val outputsCArray = if (outputs.any()) nativeHeap.allocArray<TF_Output>(outputs.size) else null
|
||||
|
||||
outputs.forEachIndexed { i, output ->
|
||||
outputsCArray!![i].apply {
|
||||
oper = output.oper
|
||||
index = output.index
|
||||
}
|
||||
}
|
||||
|
||||
memScoped {
|
||||
val outputValuesCArray = allocArrayOfPointersTo<TF_Tensor>(outputs.map { null })
|
||||
|
||||
statusValidated {
|
||||
TF_SessionRun(tensorflowSession, null,
|
||||
inputsCArray, inputValues.toCValues(), inputs.size,
|
||||
outputsCArray, outputValuesCArray, outputs.size,
|
||||
targets.toCValues(), targets.size,
|
||||
null, it)
|
||||
}
|
||||
|
||||
for (index in outputs.indices) {
|
||||
outputValues.add(outputValuesCArray[index])
|
||||
}
|
||||
}
|
||||
|
||||
clearInputValues()
|
||||
|
||||
return outputValues
|
||||
}
|
||||
}
|
||||
|
||||
fun main(args: Array<String>) {
|
||||
println("Hello, TensorFlow ${TF_Version()!!.toKString()}!")
|
||||
|
||||
val result = Graph().run {
|
||||
val input = intInput()
|
||||
|
||||
withSession { invoke(input + constant(2), inputsWithValues = listOf(input to scalarTensor(3))).scalarIntValue }
|
||||
}
|
||||
|
||||
println("3 + 2 is $result.")
|
||||
}
|
||||
@@ -0,0 +1,21 @@
|
||||
# TensorFlow demo
|
||||
|
||||
Small Hello World calculation on the [TensorFlow](https://www.tensorflow.org/) backend,
|
||||
arranging simple operations into a graph and running it on a session.
|
||||
Like other [TensorFlow clients](https://www.tensorflow.org/extend/language_bindings)
|
||||
(e. g. for [Python](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python/client)),
|
||||
this example is built on top of the
|
||||
[TensorFlow C API](https://github.com/tensorflow/tensorflow/blob/r1.1/tensorflow/c/c_api.h),
|
||||
showing how a TensorFlow client in Kotlin/Native could look like.
|
||||
|
||||
##Installation
|
||||
|
||||
[Install TensorFlow for C](https://www.tensorflow.org/versions/r1.1/install/install_c) into `/usr/local`.
|
||||
|
||||
Compile:
|
||||
|
||||
./build.sh
|
||||
|
||||
Run:
|
||||
|
||||
./HelloTensorflow.kexe
|
||||
Executable
+23
@@ -0,0 +1,23 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
PATH=../../dist/bin:../../bin:$PATH
|
||||
DIR=.
|
||||
|
||||
if [ x$TARGET == x ]; then
|
||||
case "$OSTYPE" in
|
||||
darwin*) TARGET=macbook ;;
|
||||
linux*) TARGET=linux ;;
|
||||
*) echo "unknown: $OSTYPE" && exit 1;;
|
||||
esac
|
||||
fi
|
||||
|
||||
var=CFLAGS_${TARGET}
|
||||
CFLAGS=${!var}
|
||||
var=LINKER_ARGS_${TARGET}
|
||||
LINKER_ARGS=${!var}
|
||||
var=COMPILER_ARGS_${TARGET}
|
||||
COMPILER_ARGS=${!var} # add -opt for an optimized build.
|
||||
|
||||
cinterop -def $DIR/tensorflow.def -copt "$CFLAGS" -target $TARGET -o tensorflow.kt.bc || exit 1
|
||||
konanc $COMPILER_ARGS -target $TARGET $DIR/HelloTensorflow.kt -library tensorflow.kt.bc -o HelloTensorflow.kexe \
|
||||
-linkerArgs "-L/usr/local/lib -ltensorflow" || exit 1
|
||||
@@ -0,0 +1,2 @@
|
||||
headers = tensorflow/c/c_api.h
|
||||
compilerOpts = -I/usr/local/include -L/usr/local/lib
|
||||
Reference in New Issue
Block a user