diff --git a/build.sbt b/build.sbt
index 7dae9c9..4ac0f03 100644
--- a/build.sbt
+++ b/build.sbt
@@ -6,7 +6,7 @@ lazy val scala211Version = "2.11.12"
 lazy val scala212Version = "2.12.11"
 lazy val scala213Version = "2.13.2"
 
-lazy val dottyVersion = "0.26.0-RC1"
+lazy val dottyVersion = "3.0.0-M3"
 
 organization in ThisBuild := "me.shadaj"
 scalaVersion in ThisBuild := scala212Version
@@ -43,7 +43,7 @@ lazy val dottyTensorFlow = project
   .settings(
     name := "dotty-tensorflow",
     scalaVersion := dottyVersion,
-    libraryDependencies += "com.github.VirtuslabRnD.scalapy" % "scalapy-core_2.13" % "b3d8ddc81753a72d11e46601f7a9ad719e452e5c",
+    libraryDependencies += "me.shadaj" % "scalapy-core_2.13" % "0.4.0+11-aea09719",
     fork := true,
     javaOptions += s"-Djna.library.path=${"python3-config --prefix".!!.trim}/lib",
     projectDependencies ~=(_.map(_.withDottyCompat(dottyVersion))),
@@ -68,8 +68,8 @@ lazy val scalaPyTensorFlowCross = crossProject(JVMPlatform, NativePlatform)
   .settings(
     name := "scalapy-tensorflow-cross",
     // scalapy-core version will replace the one in scalapy-numpy (maintaining binary compatibility)
-    libraryDependencies += "com.github.VirtuslabRnD.scalapy" %%% "scalapy-core" % "b3d8ddc81753a72d11e46601f7a9ad719e452e5c",
-    libraryDependencies += "com.github.VirtuslabRnD.scalapy-numpy" %%% "scalapy-numpy" % "8a85b7068e9a377ba4b97e2cf9b7bbe008066202" exclude("me.shadaj", "scalapy-core"),
+    libraryDependencies += "me.shadaj" %%% "scalapy-core" % "0.4.0+11-aea09719",
+    libraryDependencies += "me.shadaj" %%% "scalapy-numpy" % "0.1.0+13-442717a6+20210113-0045" excludeAll("com.github.shadaj.scalapy", "scalapy-core_2.13"),
     projectDependencies ~=(_.map(_.withDottyCompat(dottyVersion))),
   ).jvmSettings(
     scalaVersion := scala213Version,
@@ -122,7 +122,7 @@ lazy val scalaPyTensorFlowExamplesCross = crossProject(JVMPlatform, NativePlatfo
   .dependsOn(scalaPyTensorFlowCross)
 
 lazy val scalaPyTensorFlowExamplesJVM = scalaPyTensorFlowExamplesCross.jvm.settings(name := "tensorflow-example-jvm")
-lazy val scalaPyTensorFlowExamplesNative = scalaPyTensorFlowExamplesCross.native.settings(name := "tensorflow-example-native") 
+lazy val scalaPyTensorFlowExamplesNative = scalaPyTensorFlowExamplesCross.native.settings(name := "tensorflow-example-native")
 
 
 // To make sure that changes to project structure are picked up by sbt without an explicit `reload`
diff --git a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/BidirectionalLSTMExample.scala b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/BidirectionalLSTMExample.scala
index ac0c83f..3bf879c 100644
--- a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/BidirectionalLSTMExample.scala
+++ b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/BidirectionalLSTMExample.scala
@@ -1,5 +1,6 @@
 package me.shadaj.scalapy.tensorflow.example
 
+import me.shadaj.scalapy.numpy.{NDArray, PythonSeq}
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.api.TensorFlow
 import me.shadaj.scalapy.tensorflow.nd2Tensor
@@ -8,6 +9,24 @@ import me.shadaj.scalapy.tensorflow.api.keras.optimizers.OptimizerEnum
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules.{numpy => np}
 import me.shadaj.scalapy.tensorflow.api.keras.metrics.Metric
 import me.shadaj.scalapy.tensorflow.api.keras.activations.Activation
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.tensorflow.ndd2Tensor
+import me.shadaj.scalapy.py
+import me.shadaj.scalapy.py.Dynamic.global
+import me.shadaj.scalapy.readwrite._
+import me.shadaj.scalapy.readwrite.Reader._
+import me.shadaj.scalapy.py
+import me.shadaj.scalapy.tensorflow.TensorFlow
+import me.shadaj.scalapy.tensorflow.scala.utils.Modules
+import me.shadaj.scalapy.tensorflow.nd2Tensor
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.tensorflow.scala.utils.Modules._
+import me.shadaj.scalapy.numpy.{NDArray, PythonSeq}
+
+import Int.int2long
+import scala.language.implicitConversions
+
+
 import Int.int2long
 import scala.language.implicitConversions
 
@@ -33,10 +52,10 @@ object BidirectionalLSTMExample extends Runnable {
     println(s"${xTest.length} test sequences")
 
     println("Pad sequences (samples x time)")
-    val xTrain1 = sequence.padSequences(xTrain, maxLen = Some(maxLen)).astype(np.float32)
-    val xTest1 = sequence.padSequences(xTest, maxLen = Some(maxLen)).astype(np.float32)
-    val yTrain1 = yTrain.astype(np.float32)
-    val yTest1 = yTest.astype(np.float32)
+    val xTrain1 = sequence.padSequences(xTrain, maxLen = Some(maxLen)).astype(np.float32).as[NDArray[Float]]
+    val xTest1 = sequence.padSequences(xTest, maxLen = Some(maxLen)).astype(np.float32).as[NDArray[Float]]
+    val yTrain1 = yTrain.astype(np.float32).as[NDArray[Float]]
+    val yTest1 = yTest.astype(np.float32).as[NDArray[Float]]
 
     println(s"xTrain shape: ${xTrain1.shape}")
     println(s"xTest shape: ${xTest1.shape}")
@@ -48,8 +67,8 @@ object BidirectionalLSTMExample extends Runnable {
       layers.Dense(1, activation = Some(Activation.Sigmoid))
     ))
     
-    model.compile(OptimizerEnum.Adam, Some(keras1.backend.binaryCrossentropy), metrics = Seq(Metric.Accuracy))
-
+    model.compile(OptimizerEnum.Adam, Some(keras1.backend.binaryCrossentropy), metrics = Seq[String]("accuracy"))
+    
     println("Train...")
     val epochs = Option(System.getenv("EPOCH_COUNT")).map(_.toInt).getOrElse(2)
     model.fit(xTrain1, yTrain1, batchSize = Some(batchSize), epochs = epochs, validationData = Some((xTest1, yTest1)))
diff --git a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/GradientDescentOptimizerExample.scala b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/GradientDescentOptimizerExample.scala
index 592b2c1..266ce47 100644
--- a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/GradientDescentOptimizerExample.scala
+++ b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/GradientDescentOptimizerExample.scala
@@ -1,12 +1,17 @@
 package me.shadaj.scalapy.tensorflow.example
 
+import me.shadaj.scalapy.numpy.{NDArray, PythonSeq}
 import me.shadaj.scalapy.py
-import me.shadaj.scalapy.tensorflow.api.Tensor
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.numpy.PythonSeq.seqToPythonSeq
+import me.shadaj.scalapy.tensorflow.{Tensor => PyTensor}
+import me.shadaj.scalapy.tensorflow.{Variable => PyVariable}
 import me.shadaj.scalapy.tensorflow.api.scalaUtils.CloseableResourceManager
-import me.shadaj.scalapy.tensorflow.api.Tensor.{TensorToPyTensor}
+import me.shadaj.scalapy.tensorflow.api.Tensor.TensorToPyTensor
 import me.shadaj.scalapy.tensorflow.{nd2Tensor => nd2TensorPy}
-import me.shadaj.scalapy.tensorflow.api.{TensorFlow => tf}
+import me.shadaj.scalapy.tensorflow.api.{Variable, Tensor, TensorFlow => tf}
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules.{numpy => np}
+
 import scala.language.implicitConversions
 
 /**
@@ -21,7 +26,7 @@ object GradientDescentOptimizerExample extends Runnable {
 
   def run(): Unit = {
     // Starting data
-    val xData = np.random.rand(100).astype(np.float32)
+    val xData = np.random.rand(100).astype(np.float32).as[NDArray[Float]]
     val yData = (xData * 0.1f) + 0.3f
 
     // Variables
@@ -35,11 +40,11 @@ object GradientDescentOptimizerExample extends Runnable {
     def loss = () => tf.reduceMean(tf.square(y() - yData))
 
     // Function to calculate gradients
-    def grad(): Option[(Tensor, Seq[Tensor])] =
+    def grad(): Option[(PyTensor, Seq[PyTensor])] =
       CloseableResourceManager.withResource(tf.GradientTape()) { tape =>
         val lossValue = loss()
         val gradients: Seq[Tensor] = tape.gradient(lossValue, Seq(W, b))
-        (lossValue, gradients)
+        (lossValue.underlying, gradients.map(_.underlying))
       }
 
     // Select optimizer SGD
@@ -52,7 +57,9 @@ object GradientDescentOptimizerExample extends Runnable {
     val num_epochs = Option(System.getenv("EPOCH_COUNT")).map(_.toInt).getOrElse(400)
     for (epoch <- 1 to num_epochs) {
       val (lossValue, grads) = grad().get
-      optimizer.applyGradients(grads.zip(Seq(W, b)))
+      val aa = grads.zip(Seq(W.underlying, b.underlying))
+      optimizer.applyGradients(aa)
+      //optimizer.applyGradients(grads.zip(Seq(W, b)))
       if (epoch % 50 == 0)
         println(s"Epoch ${epoch}: Loss: ${lossValue.numpy()}")
     }
diff --git a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/LambdaExample.scala b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/LambdaExample.scala
new file mode 100644
index 0000000..b2ade51
--- /dev/null
+++ b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/LambdaExample.scala
@@ -0,0 +1,49 @@
+package me.shadaj.scalapy.tensorflow.example
+
+import me.shadaj.scalapy.py
+import me.shadaj.scalapy.py.{Any, Dynamic, PyQuote, SeqConverters, local}
+import me.shadaj.scalapy.readwrite.Reader._
+
+
+object LambdaExample extends Runnable {
+  def run(): Unit = {
+    println("Hello, World")
+    val listLengthPython = py.Dynamic.global.len(List(1, 2, 3).toPythonProxy)
+
+    local {
+      var count = 0
+      val testLambda = Any.from(() => {
+        count += 1
+        s"count: $count"
+      })
+
+      val testLambda2 = Any.from((x: Seq[Int]) => x.sum)
+
+      assert(py"$testLambda()".as[String] == "count: 1")
+      assert(py"$testLambda()".as[String] == "count: 2")
+      assert(py"$testLambda2([1, 2, 3])".as[Int] == 6)
+    }
+
+    val lambdaToScala = Dynamic.global.len.as[Any => Int]
+    assert(lambdaToScala(Seq[Any]().toPythonProxy) == 0)
+    assert(lambdaToScala(Seq(1, 2, 3).toPythonProxy) == 3)
+
+    /*@py.native trait PyString extends py.Object {
+      def count(subsequence: String): Int = py.native
+    }*/
+
+    /*{
+      @py.native trait PythonRandomModule extends py.Object {
+        def Random(a: String, s: Seq[Int]): py.Dynamic = py.native
+      }
+
+      val random = py.module("random").as[PythonRandomModule]
+      //println(random.Random("123", 4))
+
+      val string1 = py.module("string").digits.as[PyString]
+      val string2 = py.module("string").digits.as[PyString]
+      // string: PyString = 0123456789
+      println(string1.count("123"))
+    }*/
+  }
+}
diff --git a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/Main.scala b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/Main.scala
index a98bb6e..b7abaa8 100644
--- a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/Main.scala
+++ b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/Main.scala
@@ -6,6 +6,7 @@ object Main {
       case Array("BidirectionalLSTMExample")        => BidirectionalLSTMExample
       case Array("GradientDescentOptimizerExample") => GradientDescentOptimizerExample
       case Array("MnistExample")                    => MnistExample
+      case Array("LambdaExample")                   => LambdaExample
       case _                                        => throw new IllegalArgumentException("usage: sbt 'run <simple class name>'")
     }).run()
   }
diff --git a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/MnistExample.scala b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/MnistExample.scala
index ddd1c06..d708500 100644
--- a/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/MnistExample.scala
+++ b/dotty-tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/MnistExample.scala
@@ -1,6 +1,6 @@
 package me.shadaj.scalapy.tensorflow.example
 
-import me.shadaj.scalapy.numpy.NumPy
+import me.shadaj.scalapy.numpy.{NDArray, NumPy, PythonSeq}
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules._
 import me.shadaj.scalapy.tensorflow.api.{TensorFlow => tf}
@@ -8,6 +8,8 @@ import me.shadaj.scalapy.tensorflow.api.keras.datasets.Mnist
 import me.shadaj.scalapy.tensorflow.api.keras.models._
 import me.shadaj.scalapy.tensorflow.api.keras.metrics.Metric
 import me.shadaj.scalapy.tensorflow.api.keras.activations.Activation
+import me.shadaj.scalapy.py.SeqConverters
+
 import Int.int2long
 import scala.language.implicitConversions
 
@@ -28,8 +30,8 @@ object MnistExample extends Runnable {
     val mnist: Mnist = kerasA.datasets.mnist
     val ((xTrainOrig, yTrainOrig), (xTest, yTest)) = mnist.loadData()
     val trainingSetSize = Option(System.getenv("TRAINING_SET_SIZE")).map(_.toInt)
-    val xTrain = trainingSetSize.map(tss => xTrainOrig.slice(0, tss)).getOrElse(xTrainOrig)
-    val yTrain = trainingSetSize.map(tss => yTrainOrig.slice(0, tss)).getOrElse(yTrainOrig)
+    val xTrain = trainingSetSize.map(tss => xTrainOrig.slice(0, tss)).getOrElse(xTrainOrig).asInstanceOf[NDArray[Long]]
+    val yTrain = trainingSetSize.map(tss => yTrainOrig.slice(0, tss)).getOrElse(yTrainOrig).asInstanceOf[NDArray[Long]]
 
     val (train, test, inputShape) =
       if (K.imageDataFormat() == "channels_first") {
@@ -46,8 +48,8 @@ object MnistExample extends Runnable {
         (train, test, inputShape)
       }
 
-    val trainImages = train.astype(np.float32) / 255.0f
-    val testImages = test.astype(np.float32) / 255.0f
+    val trainImages = train.astype(np.float32).as[NDArray[Float]] / 255.0f
+    val testImages = test.astype(np.float32).as[NDArray[Float]] / 255.0f
 
     println(s"xTrain shape: ${trainImages.shape}")
     println(s"${trainImages.shape(0)} train samples")
@@ -70,12 +72,13 @@ object MnistExample extends Runnable {
     model.compile(
       loss = Some(kerasA.losses.categoricalCrossentropy),
       optimizer = kerasA.optimizers.Adadelta(),
-      metrics = Seq(Metric.Accuracy)
+      metrics = Seq[String](Metric.Accuracy)
     )
 
-    model.fit(x = trainImages, y = trainLabels, batchSize = Some(batchSize), epochs = epochs, verbose = 1, validationData = Some((testImages, testLabels)))
+    model.fit(x = trainImages, y = trainLabels.as[NDArray[Float]], batchSize = Some(batchSize), epochs = epochs, verbose = 1, 
+      validationData = Some((testImages.as[NDArray[Float]], testLabels.as[NDArray[Float]])))
 
-    val score = model.evaluate(x = testImages, y = testLabels, verbose = 0)
+    val score = model.evaluate(x = testImages, y = testLabels.as[NDArray[Float]], verbose = 0)
 
     println(s"Test loss: ${score(0)}")
     println(s"Test accuracy: ${score(1)}")
diff --git a/dotty-tensorflow/project/build.properties b/dotty-tensorflow/project/build.properties
index 0837f7a..d91c272 100644
--- a/dotty-tensorflow/project/build.properties
+++ b/dotty-tensorflow/project/build.properties
@@ -1 +1 @@
-sbt.version=1.3.13
+sbt.version=1.4.6
diff --git a/dotty-tensorflow/project/plugins.sbt b/dotty-tensorflow/project/plugins.sbt
new file mode 100644
index 0000000..9033973
--- /dev/null
+++ b/dotty-tensorflow/project/plugins.sbt
@@ -0,0 +1,2 @@
+
+addSbtPlugin("ch.epfl.lamp" % "sbt-dotty" % "0.5.1")
diff --git a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/TensorFlow.scala b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/TensorFlow.scala
index e9d8a6b..0a53057 100644
--- a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/TensorFlow.scala
+++ b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/TensorFlow.scala
@@ -1,19 +1,26 @@
 package me.shadaj.scalapy.tensorflow.api
 
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules.{tensorflow => pyTensorflow}
-import me.shadaj.scalapy.tensorflow.{TensorFlow => PyTensorFlow, Tensor => PyTensor}
+import me.shadaj.scalapy.tensorflow.{TensorFlow => PyTensorFlow}
+import me.shadaj.scalapy.numpy.PythonSeq.seqToPythonSeq
+import me.shadaj.scalapy.tensorflow.seq2Tensor
 import random.Random
 import keras.Keras
 import compat.Compat
 import nn.NN
 import train.Train
+
 import scala.language.implicitConversions
 import scalaUtils.PythonOption._
 import scalaUtils.PythonUnion._
-import me.shadaj.scalapy.tensorflow.seq2Tensor
-
 import me.shadaj.scalapy.py.PyFunction
 import me.shadaj.scalapy.py
+import me.shadaj.scalapy.py.|.fromLeft
+import me.shadaj.scalapy.py.|.fromRight
+import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonUnion.fromSingleAndTupleUnion
+import me.shadaj.scalapy.tensorflow.api.Tensor.TensorToPyTensor
+import me.shadaj.scalapy.tensorflow.api.Tensor.PyTensorToTensor
+
 
 object TensorFlow {
   private val tf: PyTensorFlow = pyTensorflow
diff --git a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/layers/Conv2D.scala b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/layers/Conv2D.scala
index a0e3897..46f4b8f 100644
--- a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/layers/Conv2D.scala
+++ b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/layers/Conv2D.scala
@@ -3,7 +3,10 @@ package me.shadaj.scalapy.tensorflow.api.keras.layers
 import me.shadaj.scalapy.tensorflow.keras.layers.{Conv2D => PyConv2D}
 import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonUnion._
 import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonOption._
+
 import scala.language.implicitConversions
+import me.shadaj.scalapy.tensorflow.api.scalaUtils
+import me.shadaj.scalapy.py.|
 
 class Conv2D private[api] (override val underlying: PyConv2D) extends Layer(underlying) {
   def filters: Int = underlying.filters
diff --git a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/models/Sequential.scala b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/models/Sequential.scala
index 449f1b7..06edc89 100644
--- a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/models/Sequential.scala
+++ b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/models/Sequential.scala
@@ -5,12 +5,22 @@ import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonOption._
 import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonUnion._
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules.{numpy => np}
 import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonEnum._
-import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonEnum
 import me.shadaj.scalapy.tensorflow.api.keras.layers._
 import me.shadaj.scalapy.tensorflow.api.keras.optimizers._
 import me.shadaj.scalapy.numpy.NDArray
 import me.shadaj.scalapy.py.PyFunction
+
 import scala.language.implicitConversions
+import me.shadaj.scalapy.numpy.PythonSeq
+import me.shadaj.scalapy.py
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.tensorflow.TensorFlow
+import me.shadaj.scalapy.tensorflow.nd2Tensor
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.tensorflow.scala.utils.Modules._
+import me.shadaj.scalapy.numpy.{NDArray, PythonSeq}
+import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonOption.toScalaOption
+import me.shadaj.scalapy.readwrite.Writer
 
 class Sequential private[api] (val underlying: PySequential) extends PythonType[PySequential] {
 
@@ -19,11 +29,11 @@ class Sequential private[api] (val underlying: PySequential) extends PythonType[
   def compile(
       optimizer: OptimizerEnum | Optimizer = OptimizerEnum.RMSprop,
       loss: Option[PyFunction] = None,
-      metrics: Seq[String] = Seq.empty,
-      lossWeights: Option[Seq[(Double, Double)]] = None,
-      sampleWeightMode: Option[String] = None,
-      weightedMetrics: Seq[String] = Seq.empty,
-      targetTensors: Option[String] = None
+      metrics: PythonSeq[String] = PythonSeq.emptyString,
+      lossWeights: py.NoneOr[PythonSeq[(Double, Double)]] = py.None,
+      sampleWeightMode: py.NoneOr[String] = None,
+      weightedMetrics: PythonSeq[String] = PythonSeq.emptyString,
+      targetTensors: py.NoneOr[String] = None
   ) =
     underlying.compile(
       optimizer,
diff --git a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/optimizers/Optimizer.scala b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/optimizers/Optimizer.scala
index 2d46349..cf66b83 100644
--- a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/optimizers/Optimizer.scala
+++ b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/keras/optimizers/Optimizer.scala
@@ -2,9 +2,13 @@ package me.shadaj.scalapy.tensorflow.api.keras.optimizers
 
 import me.shadaj.scalapy.tensorflow.compat.v1.Operation
 import me.shadaj.scalapy.tensorflow.api.{Tensor, Variable}
-
+import me.shadaj.scalapy.tensorflow.{Variable => PyVariable}
+import me.shadaj.scalapy.tensorflow.{Tensor => PyTensor}
 import me.shadaj.scalapy.tensorflow.keras.optimizers.{Optimizer => PyOptimizer}
 import me.shadaj.scalapy.tensorflow.api.scalaUtils.PythonType
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.numpy.PythonSeq
+
 import scala.language.implicitConversions
 import me.shadaj.scalapy.py
 
@@ -12,8 +16,7 @@ trait Optimizer private[api] (val underlying: PyOptimizer) extends PythonType[Py
   // TODO loss should be a function () => py.Any
   def minimize(loss: py.Any, varList: Seq[Variable]): Operation = underlying.minimize(loss, varList.map(_.underlying))
 
-  def applyGradients(gradsAndVars: Seq[(Tensor, Variable)]): Operation =
-    underlying.apply_gradients(gradsAndVars.map {
-      case (tensor, variable) => (tensor.underlying, variable.underlying)
-    })
+  def applyGradients(gradsAndVars: PythonSeq[(PyTensor, PyVariable)]): Operation = {
+    underlying.apply_gradients(gradsAndVars)
+  }
 }
diff --git a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/scalaUtils/PythonUnion.scala b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/scalaUtils/PythonUnion.scala
index 1f56b6f..745ee4f 100644
--- a/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/scalaUtils/PythonUnion.scala
+++ b/dotty-tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/api/scalaUtils/PythonUnion.scala
@@ -1,5 +1,6 @@
 package me.shadaj.scalapy.tensorflow.api.scalaUtils
 
+import me.shadaj.scalapy.numpy.PythonSeq
 import me.shadaj.scalapy.py
 import scala.language.implicitConversions
 import scala.reflect.ClassTag
@@ -15,10 +16,11 @@ object PythonUnion {
   }
 
   implicit def fromPythonUnion[A, B](u: py.|[A, B]): A | B = {
-    if (u.isLeft) {
-      u.value.asInstanceOf[A]
+    val uu: py.|[A, B] = u.asInstanceOf[py.|[A, B]]
+    if (uu.isLeft) {
+      uu.value.asInstanceOf[A]
     } else {
-      u.value.asInstanceOf[B]
+      uu.value.asInstanceOf[B]
     }
   }
 
@@ -39,7 +41,7 @@ object PythonUnion {
 
   implicit def fromPythonTypeSeqsUnion[X <: py.Any, Y <: py.Any, A <: PythonType[X], B <: Seq[PythonType[Y]]](
       u: A | B
-  )(implicit ev1: ClassTag[A], ev2: ClassTag[B]): py.|[X, Seq[Y]] =
+  )(implicit ev1: ClassTag[A], ev2: ClassTag[B]): py.|[X, PythonSeq[Y]] =
     u match {
       case a: A => py.|.fromLeft(a.underlying)
       case b: B => py.|.fromRight(b.map(_.underlying))
diff --git a/project/build.properties b/project/build.properties
index 797e7cc..d91c272 100644
--- a/project/build.properties
+++ b/project/build.properties
@@ -1 +1 @@
-sbt.version=1.3.10
+sbt.version=1.4.6
diff --git a/project/plugins.sbt b/project/plugins.sbt
index 240571c..90ff9c4 100644
--- a/project/plugins.sbt
+++ b/project/plugins.sbt
@@ -1,6 +1,6 @@
 addSbtPlugin("org.portable-scala" % "sbt-scalajs-crossproject"      % "1.0.0")
 addSbtPlugin("org.portable-scala" % "sbt-scala-native-crossproject" % "1.0.0")
-addSbtPlugin("org.scala-native"   % "sbt-scala-native"              % "0.3.9")
+addSbtPlugin("org.scala-native"   % "sbt-scala-native"              % "0.4.0-M2")
 
 addSbtPlugin("com.dwijnand" % "sbt-dynver" % "4.0.0")
 
@@ -14,3 +14,7 @@ addSbtPlugin("ch.epfl.lamp" % "sbt-dotty" % "0.4.0")
 
 // "2.4.0" is just sbt plugin version and NOT scalafmt version itself
 addSbtPlugin("org.scalameta" % "sbt-scalafmt" % "2.4.0")
+
+addSbtPlugin("net.virtual-void" % "sbt-dependency-graph" % "0.10.0-RC1")
+
+addSbtPlugin("ch.epfl.lamp" % "sbt-dotty" % "0.5.1")
\ No newline at end of file
diff --git a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/BidirectionalLSTMExample.scala b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/BidirectionalLSTMExample.scala
index 5de9376..a11bd1e 100644
--- a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/BidirectionalLSTMExample.scala
+++ b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/BidirectionalLSTMExample.scala
@@ -4,7 +4,10 @@ import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.TensorFlow
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules
 import me.shadaj.scalapy.tensorflow.nd2Tensor
+import me.shadaj.scalapy.py.SeqConverters
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules._
+import me.shadaj.scalapy.numpy.{NDArray, PythonSeq}
+
 import Int.int2long
 import scala.language.implicitConversions
 
@@ -32,10 +35,10 @@ object BidirectionalLSTMExample extends Runnable {
     println(s"${xTest.length} test sequences")
 
     println("Pad sequences (samples x time)")
-    val xTrain1 = sequence.pad_sequences(xTrain, maxlen = maxlen).astype(np.float32)
-    val xTest1 = sequence.pad_sequences(xTest, maxlen = maxlen).astype(np.float32)
-    val yTrain1 = yTrain.astype(np.float32)
-    val yTest1 = yTest.astype(np.float32)
+    val xTrain1 = sequence.pad_sequences(xTrain, maxlen = maxlen).astype(np.float32).as[NDArray[Float]]
+    val xTest1 = sequence.pad_sequences(xTest, maxlen = maxlen).astype(np.float32).as[NDArray[Float]]
+    val yTrain1 = yTrain.astype(np.float32).as[NDArray[Float]]
+    val yTest1 = yTest.astype(np.float32).as[NDArray[Float]]
     println(s"xTrain shape: ${xTrain1.shape}")
     println(s"xTest shape: ${xTest1.shape}")
 
@@ -45,7 +48,7 @@ object BidirectionalLSTMExample extends Runnable {
     model.add(layers.Dropout(0.5))
     model.add(layers.Dense(1, activation = "sigmoid"))
 
-    model.compile("adam", keras1.backend.binary_crossentropy, metrics = Seq("accuracy"))
+    model.compile("adam", keras1.backend.binary_crossentropy, metrics = Seq("accuracy")
 
     println("Train...")
     val epochs = Option(System.getenv("EPOCH_COUNT")).map(_.toInt).getOrElse(4)
diff --git a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/GradientDescentOptimizerExample.scala b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/GradientDescentOptimizerExample.scala
index 767c551..8487201 100644
--- a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/GradientDescentOptimizerExample.scala
+++ b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/GradientDescentOptimizerExample.scala
@@ -1,9 +1,18 @@
 package me.shadaj.scalapy.tensorflow.example
 
+import me.shadaj.scalapy.numpy.PythonSeq
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules._
 import me.shadaj.scalapy.tensorflow.Tensor
 import me.shadaj.scalapy.tensorflow.scala.utils.ContextManager
 import me.shadaj.scalapy.tensorflow._
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.numpy.PythonSeq.seqToPythonSeq
+import me.shadaj.scalapy.py
+import me.shadaj.scalapy.py.Dynamic.global
+import me.shadaj.scalapy.readwrite.Writer
+import me.shadaj.scalapy.readwrite.Reader
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.tensorflow.ndd2Tensor
 
 /**
   * This example performs linear regression on randomized input conforming to y= 0.1 * x + 0.3.
@@ -23,8 +32,8 @@ object GradientDescentOptimizerExample extends Runnable {
     val yData = (xData * 0.1f) + 0.3f
 
     // Variables
-    val W = tf.Variable(tf.random.uniform(shape = Seq(1), minval = -1, maxval = 1))
-    val b = tf.Variable(tf.zeros(Seq(1)))
+    val W: Variable = tf.Variable(tf.random.uniform(shape = Seq(1), minval = -1, maxval = 1))
+    val b: Variable = tf.Variable(tf.zeros(Seq(1)))
 
     // Function to calculate output
     def y = () => W * xData + b
@@ -34,9 +43,9 @@ object GradientDescentOptimizerExample extends Runnable {
 
     // Function to calculate gradients
     def grad(): Option[(Tensor, Seq[Tensor])] =
-      ContextManager.withContext(tf.GradientTape()) { tape =>
-        val loss_value = loss()
-        val gradients = tape.gradient(loss_value, Seq(W, b))
+      ContextManager.withContext(tf.GradientTape()) { tape: GradientTape =>
+        val loss_value: Tensor = loss()
+        val gradients: Seq[Tensor] = tape.gradient(target=loss_value, sources=Seq(W, b))
         (loss_value, gradients)
       }
 
@@ -44,14 +53,15 @@ object GradientDescentOptimizerExample extends Runnable {
     val optimizer = tf.keras.optimizers.SGD(learning_rate = 0.1, momentum = 0.9)
 
     // Initial Learning step
-    val (loss_value, grads) = grad().get
+    val (loss_value, _) = grad().get
     println(s"Step: 0, Initial Loss: ${loss_value.numpy()}")
 
     // Learning steps
-    val num_epochs = Option(System.getenv("EPOCH_COUNT")).map(_.toInt).getOrElse(400)
+    val num_epochs: Int = Option(System.getenv("EPOCH_COUNT")).map(_.toInt).getOrElse(400)
     for (epoch <- 1 to num_epochs) {
-      val (loss_value, grads) = grad().get
-      optimizer.apply_gradients(grads.zip(Seq(W, b)))
+      val (loss_value, grads: Seq[Tensor]) = grad().get
+      val aa: Seq[(Tensor, Variable)] = grads.zip(Seq(W, b))
+      optimizer.apply_gradients(aa.toPythonProxy.as[PythonSeq[(Tensor, Variable)]])
       if (epoch % 50 == 0)
         println(s"Epoch ${epoch}: Loss: ${loss_value.numpy()}")
     }
diff --git a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/LambdaExample.scala b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/LambdaExample.scala
new file mode 100644
index 0000000..9f81dd0
--- /dev/null
+++ b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/LambdaExample.scala
@@ -0,0 +1,49 @@
+package me.shadaj.scalapy.tensorflow.example
+
+import me.shadaj.scalapy.readwrite.Reader._
+import me.shadaj.scalapy.py
+import me.shadaj.scalapy.py.{Any, Dynamic, PyQuote, SeqConverters, local}
+
+
+object LambdaExample extends Runnable {
+  def run(): Unit = {
+    println("Hello, World")
+    val listLengthPython = py.Dynamic.global.len(List(1, 2, 3).toPythonProxy)
+
+    local {
+      var count = 0
+      val testLambda = Any.from(() => {
+        count += 1
+        s"count: $count"
+      })
+
+      val testLambda2 = Any.from((x: Seq[Int]) => x.sum)
+
+      assert(py"$testLambda()".as[String] == "count: 1")
+      assert(py"$testLambda()".as[String] == "count: 2")
+      assert(py"$testLambda2([1, 2, 3])".as[Int] == 6)
+    }
+
+    val lambdaToScala = Dynamic.global.len.as[Any => Int]
+    assert(lambdaToScala(Seq[Any]().toPythonProxy) == 0)
+    assert(lambdaToScala(Seq(1, 2, 3).toPythonProxy) == 3)
+
+    @py.native trait PyString extends py.Object {
+      def count(subsequence: String): Int = py.native
+    }
+
+    /*{
+      @py.native trait PythonRandomModule extends py.Object {
+        def Random(a: String, s: Seq[Int]): py.Dynamic = py.native
+      }
+
+      val random = py.module("random").as[PythonRandomModule]
+      //println(random.Random("123", 4))
+
+      val string1 = py.module("string").digits.as[PyString]
+      val string2 = py.module("string").digits.as[PyString]
+      // string: PyString = 0123456789
+      println(string1.count("123"))
+    }*/
+  }
+}
diff --git a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/Main.scala b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/Main.scala
index 5057d31..ea80280 100644
--- a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/Main.scala
+++ b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/Main.scala
@@ -6,6 +6,7 @@ object Main {
       case Array("MnistExample")                    => MnistExample
       case Array("GradientDescentOptimizerExample") => GradientDescentOptimizerExample
       case Array("BidirectionalLSTMExample")        => BidirectionalLSTMExample
+      case Array("LambdaExample")                   => LambdaExample
       case _                                        => throw new IllegalArgumentException("usage: sbt 'run <simple class name>'")
     }).run()
   }
diff --git a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/MnistExample.scala b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/MnistExample.scala
index df5b0cf..62b71ea 100644
--- a/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/MnistExample.scala
+++ b/tensorflow-examples/src/main/scala/me/shadaj/scalapy/tensorflow/example/MnistExample.scala
@@ -2,6 +2,11 @@ package me.shadaj.scalapy.tensorflow.example
 
 import me.shadaj.scalapy.tensorflow.scala.utils.Modules._
 import me.shadaj.scalapy.tensorflow.keras.datasets.Mnist
+import me.shadaj.scalapy.numpy.{NDArray, PythonSeq}
+import me.shadaj.scalapy.py.Dynamic.global.{applyDynamic, applyDynamicNamed}
+import me.shadaj.scalapy.py.SeqConverters
+import me.shadaj.scalapy.tensorflow.compat.v1.{PythonDict, Session}
+import me.shadaj.scalapy.tensorflow.keras.layers.Layer
 
 object MnistExample extends Runnable {
 
@@ -19,10 +24,10 @@ object MnistExample extends Runnable {
     val img_rows, img_cols = 28
 
     val mnist: Mnist = keras.datasets.mnist
-    val ((x_train_orig, y_train_orig), (x_test, y_test)) = mnist.load_data()
+    val ((x_train_orig: NDArray[Long], y_train_orig), (x_test, y_test)) = mnist.load_data()
     val trainingSetSize = Option(System.getenv("TRAINING_SET_SIZE")).map(_.toInt)
-    val x_train = trainingSetSize.map(tss => x_train_orig.slice(0, tss)).getOrElse(x_train_orig)
-    val y_train = trainingSetSize.map(tss => y_train_orig.slice(0, tss)).getOrElse(y_train_orig)
+    val x_train = trainingSetSize.map(tss => x_train_orig.slice(0, tss)).getOrElse(x_train_orig).asInstanceOf[NDArray[Long]]
+    val y_train = trainingSetSize.map(tss => y_train_orig.slice(0, tss)).getOrElse(y_train_orig).asInstanceOf[NDArray[Long]]
 
     val (train, test, input_shape) =
       if (K.image_data_format == "channels_first") {
@@ -40,19 +45,19 @@ object MnistExample extends Runnable {
       }
 
     // TODO: not type safe
-    val trainImages = train.astype(np.float32) / 255.0f
-    val testImages = test.astype(np.float32) / 255.0f
+    val trainImages = train.astype(np.float32).as[NDArray[Float]] / 255.0f
+    val testImages = test.astype(np.float32).as[NDArray[Float]] / 255.0f
 
     println(s"x_train shape: ${trainImages.shape}")
     println(s"${trainImages.shape(0)} train samples")
     println(s"${testImages.shape(0)} test samples")
 
-    val trainLabels = keras.utils.to_categorical(y_train, num_classes).astype(np.float32)
-    val testLabels = keras.utils.to_categorical(y_test, num_classes).astype(np.float32)
+    val trainLabels = keras.utils.to_categorical(y_train, num_classes).astype(np.float32).as[NDArray[Float]]
+    val testLabels = keras.utils.to_categorical(y_test, num_classes).astype(np.float32).as[NDArray[Float]]
 
     val model = keras.models.Sequential()
     model.add(
-      layers.Conv2D(filters = 32, kernel_size = (3, 3), activation = "relu", kwargs = Map("input_shape" -> input_shape))
+      layers.Conv2D(filters = 32, kernel_size = (3, 3), activation = "relu", kwargs = Map("input_shape" -> input_shape)).as[Layer]
     )
     model.add(layers.Conv2D(filters = 64, kernel_size = (3, 3), activation = "relu"))
     model.add(layers.MaxPooling2D((2, 2)))
@@ -65,12 +70,13 @@ object MnistExample extends Runnable {
     model.compile(
       loss = keras.losses.categorical_crossentropy,
       optimizer = keras.optimizers.Adadelta(),
-      metrics = Seq("accuracy")
+      metrics = Seq("accuracy").toPythonCopy.as[PythonSeq[String]]
     )
 
-    model.fit(x = trainImages, y = trainLabels, batch_size = batch_size, epochs = epochs, verbose = 1, validation_data = (testImages, testLabels))
+    model.fit(x = trainImages, y = trainLabels.as[NDArray[Float]], batch_size = batch_size, epochs = epochs, verbose = 1,
+      validation_data = (testImages.as[NDArray[Float]], testLabels.as[NDArray[Float]]))
 
-    val score = model.evaluate(x = testImages, y = testLabels, verbose = 0)
+    val score = model.evaluate(x = testImages, y = testLabels.as[NDArray[Float]], verbose = 0)
 
     println(s"Test loss: ${score(0)}")
     println(s"Test accuracy: ${score(1)}")
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/GradientTape.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/GradientTape.scala
index 00d852d..491e21a 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/GradientTape.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/GradientTape.scala
@@ -1,13 +1,13 @@
 package me.shadaj.scalapy.tensorflow
 
+import me.shadaj.scalapy.numpy.PythonSeq
 import me.shadaj.scalapy.py
-import me.shadaj.scalapy.py.{PyValue, Reader}
 import me.shadaj.scalapy.tensorflow.scala.utils.Context
 
 @py.native
 trait GradientTape extends py.Object with Context {
   // TODO: returns Tensor or None
-  def gradient(target: Tensor, sources: Seq[Variable]): Seq[Tensor] = py.native
+  def gradient(target: Tensor, sources: PythonSeq[Variable], output_gradients: py.Any = py.None): Seq[Tensor] = py.native
   def watch(tensor: Tensor): Unit = py.native
   def __enter__(): Unit = py.native
   def __exit__(typ: py.Any = py.None, value: py.Any = py.None, traceback: py.Any = py.None): Unit = py.native
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/Tensor.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/Tensor.scala
index 354ea1f..8d04f39 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/Tensor.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/Tensor.scala
@@ -1,6 +1,5 @@
 package me.shadaj.scalapy.tensorflow
 
-import me.shadaj.scalapy.numpy.NDArray
 import me.shadaj.scalapy.py
 
 @py.native
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/TensorFlow.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/TensorFlow.scala
index 11cc93f..544b3ba 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/TensorFlow.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/TensorFlow.scala
@@ -1,7 +1,8 @@
 package me.shadaj.scalapy.tensorflow
 
+import me.shadaj.scalapy.numpy.PythonSeq
 import me.shadaj.scalapy.py
-import me.shadaj.scalapy.py.{PyFunction, Writer, |}
+import me.shadaj.scalapy.py.{PyFunction, |}
 import me.shadaj.scalapy.tensorflow.compat.Compat
 import me.shadaj.scalapy.tensorflow.keras.Keras
 import me.shadaj.scalapy.tensorflow.nn.NN
@@ -41,7 +42,7 @@ trait TensorFlow extends py.Object {
 
   def reshape(tensor: Tensor, shape: Tensor): Tensor = py.native
 
-  def add_n(ts: Seq[Tensor]): Tensor = py.native
+  def add_n(ts: PythonSeq[Tensor]): Tensor = py.native
 
   def square(t: Tensor): Tensor = py.native
 
@@ -49,9 +50,9 @@ trait TensorFlow extends py.Object {
 
   def reduce_mean(t: Tensor): Tensor = py.native
 
-  def gradients(ys: Tensor | Seq[Tensor], xs: Tensor | Seq[Tensor]): Seq[Tensor] = py.native
+  def gradients(ys: Tensor | PythonSeq[Tensor], xs: Tensor | PythonSeq[Tensor]): Seq[Tensor] = py.native
 
-  def gradients(ys: Tensor, xs: Seq[Tensor], grad_ys: Tensor): Seq[Tensor] = py.native
+  def gradients(ys: Tensor, xs: PythonSeq[Tensor], grad_ys: Tensor): Seq[Tensor] = py.native
 
   def cond(c: Tensor, ifTrue: py.Object, ifFalse: py.Object): Tensor = py.native
 
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/compat/v1/Session.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/compat/v1/Session.scala
index 605c56b..2d316b3 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/compat/v1/Session.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/compat/v1/Session.scala
@@ -1,15 +1,15 @@
 package me.shadaj.scalapy.tensorflow.compat.v1
 
-import me.shadaj.scalapy.numpy._
+import me.shadaj.scalapy.numpy.{NDArray, PythonSeq}
 import me.shadaj.scalapy.py
-import me.shadaj.scalapy.py.Writer
+import me.shadaj.scalapy.readwrite.Writer
 import me.shadaj.scalapy.tensorflow.{Tensor, Variable}
 
 @py.native
 trait PythonDict[K, V] extends py.Object
 object PythonDict {
   implicit def mapToPythonDict[K, V](map: Map[K, V])(implicit writer: Writer[Map[K, V]]): PythonDict[K, V] = {
-    py.global.dict(map).as[PythonDict[K, V]]
+    py.Dynamic.global.dict(map).as[PythonDict[K, V]]
   }
 }
 
@@ -25,5 +25,5 @@ trait Session extends py.Object {
 
   def run(fetches: Tensor, feedDict: PythonDict[Tensor, py.Object]): Seq[NDArray[Double]] = py.native
 
-  def run(fetches: Seq[Tensor], feedDict: PythonDict[Tensor, py.Object]): Seq[Seq[NDArray[Double]]] = py.native
+  def run(fetches: PythonSeq[Tensor], feedDict: PythonDict[Tensor, py.Object]): Seq[Seq[NDArray[Double]]] = py.native
 }
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/compat/v1/V1.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/compat/v1/V1.scala
index 20805ab..577b8b8 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/compat/v1/V1.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/compat/v1/V1.scala
@@ -1,5 +1,6 @@
 package me.shadaj.scalapy.tensorflow.compat.v1
 
+import me.shadaj.scalapy.numpy.PythonSeq
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.Tensor
 import me.shadaj.scalapy.tensorflow.scala.utils.PythonModule
@@ -8,7 +9,7 @@ import me.shadaj.scalapy.tensorflow.scala.utils.PythonModule
 trait V1 extends py.Object with PythonModule {
   def placeholder(`type`: String): Tensor = py.native
 
-  def placeholder(`type`: String, shape: Seq[py.NoneOr[Int]]): Tensor = py.native
+  def placeholder(`type`: String, shape: PythonSeq[py.NoneOr[Int]]): Tensor = py.native
 
   def global_variables_initializer(): Operation = py.native
 
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/Keras.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/Keras.scala
index f93cc29..7548927 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/Keras.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/Keras.scala
@@ -1,5 +1,6 @@
 package me.shadaj.scalapy.tensorflow.keras
 
+import me.shadaj.scalapy.numpy.PythonSeq
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.Tensor
 import me.shadaj.scalapy.tensorflow.keras.backend.Backend
@@ -24,7 +25,7 @@ trait Keras extends py.Object with PythonModule {
   def preprocessing: Preprocessing = py.native
 
   def Input(
-      shape: Seq[py.NoneOr[Int]] = Seq(),
+      shape: PythonSeq[py.NoneOr[Int]] = Seq.empty[py.NoneOr[Int]].toPythonProxy.as[PythonSeq[py.NoneOr[Int]]],
 //     batch_size: py.NoneOr[Int]=py.None,
       name: py.NoneOr[String] = py.None,
       dtype: py.NoneOr[String] = py.None,
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/datasets/Mnist.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/datasets/Mnist.scala
index 2c3a7e0..a99a526 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/datasets/Mnist.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/datasets/Mnist.scala
@@ -1,7 +1,7 @@
 package me.shadaj.scalapy.tensorflow.keras.datasets
 
-import me.shadaj.scalapy.py
 import me.shadaj.scalapy.numpy.NDArray
+import me.shadaj.scalapy.py
 
 @py.native
 trait Mnist extends py.Object {
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/layers/Layers.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/layers/Layers.scala
index 37b72ce..09970f2 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/layers/Layers.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/layers/Layers.scala
@@ -4,9 +4,11 @@ import me.shadaj.scalapy.numpy.NDArray
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.Tensor
 import me.shadaj.scalapy.tensorflow.scala.utils.PythonModule
+import me.shadaj.scalapy.tensorflow.compat.v1.{PythonDict, Session}
 
 @py.native
 trait Layers extends py.Object with PythonModule {
+  private val origDynamic = this.as[py.Dynamic]
   def Conv2D(
       filters: Int,
       kernel_size: py.|[Int, (Int, Int)],
@@ -23,7 +25,7 @@ trait Layers extends py.Object with PythonModule {
       activity_regularizer: py.NoneOr[String] = py.None,
       kernel_constraint: py.NoneOr[String] = py.None,
       bias_constraint: py.NoneOr[String] = py.None,
-      kwargs: Map[String, py.Any] = Map()
+      kwargs: Map[String, py.Any] = Map.empty[String, py.Any]
   ): Conv2D = py.nativeNamed
 
   def Dropout(rate: Double, noise_shape: py.NoneOr[Tensor] = py.None, seed: py.NoneOr[Int] = py.None): Dropout = py.nativeNamed
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/layers/package.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/layers/package.scala
index 6acb43f..ce51ecc 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/layers/package.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/layers/package.scala
@@ -1,8 +1,10 @@
 package me.shadaj.scalapy.tensorflow.keras
 
+import me.shadaj.scalapy.interpreter.PyValue
+
 import scala.util.control.NonFatal
-import me.shadaj.scalapy.py.{PyValue, Reader}
 import me.shadaj.scalapy.py
+import me.shadaj.scalapy.readwrite.Reader
 
 package object layers {
   implicit val tupleReader: Reader[py.|[Int, (Int, Int)]] = new Reader[py.|[Int, (Int, Int)]] {
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/models/Models.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/models/Models.scala
index 37b23ca..f6ef744 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/models/Models.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/models/Models.scala
@@ -1,10 +1,11 @@
 package me.shadaj.scalapy.tensorflow.keras.models
 
+import me.shadaj.scalapy.numpy.PythonSeq
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.scala.utils.PythonModule
 import me.shadaj.scalapy.tensorflow.keras.layers.Layer
 
 @py.native
 trait Models extends py.Object with PythonModule {
-  def Sequential(layers: Seq[Layer] = Seq()): Sequential = py.native
+  def Sequential(layers: PythonSeq[Layer] = Seq()): Sequential = py.native
 }
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/models/Sequential.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/models/Sequential.scala
index 29c8c68..7b5cc32 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/models/Sequential.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/models/Sequential.scala
@@ -1,9 +1,9 @@
 package me.shadaj.scalapy.tensorflow.keras
 package models
 
+import me.shadaj.scalapy.numpy.{NDArray, PythonSeq}
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.keras.layers.Layer
-import me.shadaj.scalapy.numpy.NDArray
 import me.shadaj.scalapy.py.PyFunction
 import me.shadaj.scalapy.tensorflow.keras.optimizers.Optimizer
 
@@ -16,10 +16,10 @@ trait Sequential extends py.Object {
   def compile(
       optimizer: py.|[String, Optimizer] = "rmsprop",
       loss: py.NoneOr[PyFunction] = py.None,
-      metrics: Seq[String] = Seq.empty,
-      loss_weights: py.NoneOr[Seq[(Double, Double)]] = py.None,
+      metrics: PythonSeq[String] = PythonSeq.emptyString,
+      loss_weights: py.NoneOr[PythonSeq[(Double, Double)]] = py.None,
       sample_weight_mode: py.NoneOr[String] = py.None,
-      weighted_metrics: Seq[String] = Seq.empty,
+      weighted_metrics: PythonSeq[String] = PythonSeq.emptyString,
       target_tensors: py.NoneOr[String] = py.None
   ) =
     origDynamic
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Adadelta.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Adadelta.scala
index 49eb042..659d87e 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Adadelta.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Adadelta.scala
@@ -1,7 +1,6 @@
 package me.shadaj.scalapy.tensorflow.keras.optimizers
 
 import me.shadaj.scalapy.py
-import me.shadaj.scalapy.py.{PyValue, Reader}
 
 @py.native
 trait Adadelta extends Optimizer
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Adam.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Adam.scala
index 93ee331..289d2f8 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Adam.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Adam.scala
@@ -1,7 +1,6 @@
 package me.shadaj.scalapy.tensorflow.keras.optimizers
 
 import me.shadaj.scalapy.py
-import me.shadaj.scalapy.py.{PyValue, Reader}
 
 @py.native
 trait Adam extends Optimizer
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Optimizer.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Optimizer.scala
index 4651cc9..d0d7789 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Optimizer.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/Optimizer.scala
@@ -1,5 +1,6 @@
 package me.shadaj.scalapy.tensorflow.keras.optimizers
 
+import me.shadaj.scalapy.numpy.PythonSeq
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.compat.v1.Operation
 import me.shadaj.scalapy.tensorflow.{Tensor, Variable}
@@ -7,7 +8,7 @@ import me.shadaj.scalapy.tensorflow.{Tensor, Variable}
 @py.native
 trait Optimizer extends py.Object {
   // TODO loss should be a function () => py.Any
-  def minimize(loss: py.Any, var_list: Seq[Variable]): Operation = py.native
+  def minimize(loss: py.Any, var_list: PythonSeq[Variable]): Operation = py.native
 
-  def apply_gradients(grads_and_vars: Seq[(Tensor, Variable)]): Operation = py.native
+  def apply_gradients(grads_and_vars: PythonSeq[(Tensor, Variable)]): Operation = py.native
 }
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/SGD.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/SGD.scala
index e480497..a6204e6 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/SGD.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/optimizers/SGD.scala
@@ -1,7 +1,6 @@
 package me.shadaj.scalapy.tensorflow.keras.optimizers
 
 import me.shadaj.scalapy.py
-import me.shadaj.scalapy.py.{PyValue, Reader}
 
 @py.native
 trait SGD extends Optimizer
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/utils/Utils.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/utils/Utils.scala
index 7242cc4..9a904a6 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/utils/Utils.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/keras/utils/Utils.scala
@@ -1,7 +1,7 @@
 package me.shadaj.scalapy.tensorflow.keras.utils
 
-import me.shadaj.scalapy.py
 import me.shadaj.scalapy.numpy.NDArray
+import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.scala.utils.PythonModule
 
 @py.native
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/package.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/package.scala
index bdff239..552ea83 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/package.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/package.scala
@@ -1,7 +1,9 @@
 package me.shadaj.scalapy
 
+import me.shadaj.scalapy.interpreter.PyValue
 import me.shadaj.scalapy.numpy.NDArray
-import me.shadaj.scalapy.py.Writer
+import me.shadaj.scalapy.readwrite.{Reader, Writer}
+import me.shadaj.scalapy.py.SeqConverters
 
 import scala.language.implicitConversions
 
@@ -14,7 +16,17 @@ package object tensorflow {
     nd.as[Tensor]
   }
 
+  implicit def ndd2Tensor(nd: NDArray[Double]): Tensor = {
+    nd.as[Tensor]
+  }
+
   implicit def seq2Tensor(s: Seq[Int]): Tensor = {
-    py.Any.from(s)(Writer.seqWriter).as[Tensor]
+    s.toPythonProxy.as[Tensor]
   }
+
 }
+
+
+
+
+
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/random/Random.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/random/Random.scala
index d2c00f3..b194aec 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/random/Random.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/random/Random.scala
@@ -3,6 +3,7 @@ package me.shadaj.scalapy.tensorflow.random
 import me.shadaj.scalapy.py
 import me.shadaj.scalapy.tensorflow.scala.utils.PythonModule
 import me.shadaj.scalapy.tensorflow.Tensor
+import me.shadaj.scalapy.tensorflow.seq2Tensor
 
 @py.native
 trait Random extends py.Object with PythonModule {
diff --git a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/train/ExponentialMovingAverage.scala b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/train/ExponentialMovingAverage.scala
index 1b353c8..a00ccc6 100644
--- a/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/train/ExponentialMovingAverage.scala
+++ b/tensorflow/src/main/scala/me/shadaj/scalapy/tensorflow/train/ExponentialMovingAverage.scala
@@ -1,7 +1,6 @@
 package me.shadaj.scalapy.tensorflow.train
 
 import me.shadaj.scalapy.py
-import me.shadaj.scalapy.py.{PyValue, Reader}
 
 @py.native
 trait ExponentialMovingAverage extends py.Object