Add ctc loss to TF import

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/loss/CtcLoss.java

@@ -22,6 +22,7 @@ package org.nd4j.linalg.api.ops.impl.loss;
 
 import org.nd4j.autodiff.samediff.SDVariable;
 import org.nd4j.autodiff.samediff.SameDiff;
+import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.api.ops.DynamicCustomOp;
 import org.nd4j.linalg.api.ops.impl.loss.bp.CtcLossBp;
 
@@ -30,6 +31,11 @@ import java.util.List;
 public class CtcLoss extends DynamicCustomOp {
 
 
+    public CtcLoss(INDArray targetLabels, INDArray logitInputs, INDArray targetLabelLengths, INDArray logitInputLengths) {
+        super(new INDArray[]{targetLabels,logitInputs,targetLabelLengths,logitInputLengths},null);
+    }
+
+
     public CtcLoss(SameDiff sameDiff, SDVariable targetLabels,SDVariable logitInputs,SDVariable targetLabelLengths,SDVariable logitInputLengths){
         super(sameDiff,new SDVariable[]{targetLabels,logitInputs,targetLabelLengths,logitInputLengths});
     }

nd4j/samediff-import/samediff-import-tensorflow/src/main/kotlin/org/nd4j/samediff/frameworkimport/tensorflow/definitions/TensorflowOpDeclarations.kt

@@ -419,6 +419,16 @@ val checkNumerics = TensorflowMappingProcess(
         tensorMappingRules = listOf(mappingNDArrayInputs(mutableMapOf("input" to "tensor")))
 )
 
+val ctcLoss = TensorflowMappingProcess(
+        opName = "ctc_loss",
+        inputFrameworkOpName = "CTCLoss",
+        opMappingRegistry = tensorflowOpRegistry,
+        attributeMappingRules = listOf(),
+        tensorMappingRules = listOf(mappingNDArrayInputs(mutableMapOf("logitInput" to "inputs","targetLabels" to "labels_values",
+                "targetLabelLengths" to "labels_indices","logitInputLengths" to "sequence_length")))
+)
+
+
 //only exists in tf2, tf-java can't run it
 
 val checkNumericsV2 = TensorflowMappingProcess(

nd4j/samediff-import/samediff-import-tensorflow/src/main/resources/tensorflow-mapping-ruleset.pbtxt

@@ -10307,6 +10307,41 @@ mappings {
     inputFrameworkOpName: "UniqueWithCounts"
   }
 }
+mappings {
+  frameworkName: "tensorflow"
+  opName: "ctc_loss"
+  inputFrameworkOpName: "CTCLoss"
+  rule {
+    ruleName: "ndarraymapping"
+    functionName: "ndarraymapping"
+    inputTensorName: "inputs"
+    inputTensorName: "labels_values"
+    inputTensorName: "labels_indices"
+    inputTensorName: "sequence_length"
+    outputTensorName: "logitInput"
+    outputTensorName: "targetLabels"
+    outputTensorName: "targetLabelLengths"
+    outputTensorName: "logitInputLengths"
+    inputToOutput {
+      key: "logitInput"
+      value: "inputs"
+    }
+    inputToOutput {
+      key: "targetLabels"
+      value: "labels_values"
+    }
+    inputToOutput {
+      key: "targetLabelLengths"
+      value: "labels_indices"
+    }
+    inputToOutput {
+      key: "logitInputLengths"
+      value: "sequence_length"
+    }
+    ruleType: "tensor"
+    inputFrameworkOpName: "CTCLoss"
+  }
+}
 mappings {
   frameworkName: "tensorflow"
   opName: "randomuniform"