Tensorflow import tests and fixes (#435)

* ignored ops checked

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* reconfigured AdjustContrast + commented primitive_gru

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* minor changes + exception ops commented

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* figured out non existent tf ops and random ops check

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* minor changes to tensorflowop and randomness cheks

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* deconv2d tensorfloname removed

* Fix Flatbuffers ser/de with character fields

Signed-off-by: Alex Black <blacka101@gmail.com>

* TFGraphTestAllSameDiff tests passed except NonMaxSuppression

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* minor changes

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* temporary ignored section added

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* ignores removed

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* org.nd4j.base.Preconditions -> org.nd4j.common.base.Preconditions

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* temsorflownames reverts and replace CopyHost

* ignored mod op tests due to known issue

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* rsestored mod after fixing in cpp level

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* ignored random_shuffle op test due to known issue

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* increased random_uniform mean/std comparator sensitivity

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

* igmored random tests due to SameDiff RNG seed is not set.

Signed-off-by: Andrii Tuzhykov <andrewtuzhykov@gmail.com>

Co-authored-by: Alex Black <blacka101@gmail.com>

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/autodiff/functions/DifferentialFunction.java

@@ -261,6 +261,10 @@ public abstract class DifferentialFunction {
                 if(target.getType() == float.class && value instanceof Double){
                     value = ((Double) value).floatValue();
                 }
+                //Edge case: we store char fields as integers, rather than introduce an extra property
+                if(target.getType() == char.class && value instanceof Integer){
+                    value = (char)((Integer)value).intValue();
+                }
 
                 target.set(this,value);
             } catch (IllegalAccessException e) {

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/autodiff/samediff/serde/FlatBuffersMapper.java

@@ -483,6 +483,8 @@ public class FlatBuffersMapper {
                 //No op
             } else if (v instanceof Boolean) {
                 b = new boolean[]{(Boolean) v};
+            } else if(v instanceof Character){
+                i = new int[]{(Character)v};
             } else if (v instanceof Number) {
                 if (v instanceof Double) {
                     d = new double[]{(Double) v};

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/autodiff/validation/OpValidation.java

@@ -1220,7 +1220,12 @@ public class OpValidation {
                 "absargmax",
                 "absargmin",
                 "entropy_shannon",   //This is a thing, but quite different from our op: https://www.tensorflow.org/versions/r1.2/api_docs/python/tf/contrib/bayesflow/entropy/entropy_shannon
-                "count_zero"
+                "count_zero",
+
+                "SaveV2",
+                "LoadV2",
+                "RestoreV2",
+                "RandomCrop" // NotImplementedError: Op RandomCrop is not available in GraphDef version 134. It has been removed in version 8. Random crop is now pure Python.
         );
 
         return new HashSet<>(list);

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/imports/converters/ImportClassMapping.java

@@ -625,7 +625,6 @@ public class ImportClassMapping {
             org.nd4j.linalg.api.ops.compat.CompatSparseToDense.class,
             org.nd4j.linalg.api.ops.compat.CompatStringSplit.class,
             org.nd4j.linalg.api.ops.custom.AdjustContrast.class,
-            org.nd4j.linalg.api.ops.custom.AdjustContrastV2.class,
             org.nd4j.linalg.api.ops.custom.HsvToRgb.class,
             org.nd4j.linalg.api.ops.custom.RgbToHsv.class,
             org.nd4j.linalg.api.ops.custom.RgbToYiq.class,

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/AdjustContrast.java

@@ -1,4 +1,3 @@
-
 /* ******************************************************************************
  * Copyright (c) 2019 Konduit K.K.
  *
@@ -19,14 +18,27 @@ package org.nd4j.linalg.api.ops.custom;
 import lombok.NonNull;
 import org.nd4j.autodiff.samediff.SDVariable;
 import org.nd4j.autodiff.samediff.SameDiff;
+import org.nd4j.common.base.Preconditions;
+import org.nd4j.linalg.api.buffer.DataType;
 import org.nd4j.linalg.api.ndarray.INDArray;
+import org.nd4j.linalg.api.ops.DynamicCustomOp;
 
-public class AdjustContrast extends BaseAdjustContrast {
+import java.util.Collections;
+import java.util.List;
 
-    public AdjustContrast() {super();}
+public class AdjustContrast extends DynamicCustomOp {
+
+    public AdjustContrast() {
+        super();
+    }
 
     public AdjustContrast(@NonNull INDArray in, double factor, INDArray out) {
-        super(in, factor, out);
+        Preconditions.checkArgument(in.rank() >= 3,
+                "AdjustContrast: op expects rank of input array to be >= 3, but got %s instead", in.rank());
+        inputArguments.add(in);
+        outputArguments.add(out);
+
+        addTArgument(factor);
     }
 
     public AdjustContrast(@NonNull INDArray in, double factor) {
@@ -34,21 +46,28 @@ public class AdjustContrast extends BaseAdjustContrast {
     }
 
     public AdjustContrast(@NonNull SameDiff sameDiff, @NonNull SDVariable in, @NonNull SDVariable factor) {
-        super(sameDiff,new SDVariable[]{in,factor});
+        super(sameDiff, new SDVariable[]{in, factor});
     }
 
     public AdjustContrast(@NonNull SameDiff sameDiff, @NonNull SDVariable in, double factor) {
-        super(sameDiff,new SDVariable[]{in});
+        super(sameDiff, new SDVariable[]{in});
         addTArgument(factor);
     }
 
     @Override
     public String opName() {
-        return "adjust_contrast";
+        return "adjust_contrast_v2";
     }
 
     @Override
-    public String tensorflowName() {
+    public String[] tensorflowNames() {
-        return "AdjustContrast";
+        return new String[]{"AdjustContrast", "AdjustContrastv2"};
+    }
+
+    @Override
+    public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes) {
+        int n = args().length;
+        Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == n, "Expected %s input data types for %s, got %s", n, getClass(), inputDataTypes);
+        return Collections.singletonList(inputDataTypes.get(0));
     }
 }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/AdjustContrastV2.java

@@ -1,44 +0,0 @@
-/* ******************************************************************************
- * Copyright (c) 2019 Konduit K.K.
- *
- * This program and the accompanying materials are made available under the
- * terms of the Apache License, Version 2.0 which is available at
- * https://www.apache.org/licenses/LICENSE-2.0.
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
- * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
- * License for the specific language governing permissions and limitations
- * under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- ******************************************************************************/
-package org.nd4j.linalg.api.ops.custom;
-
-import lombok.NonNull;
-import org.nd4j.autodiff.samediff.SDVariable;
-import org.nd4j.autodiff.samediff.SameDiff;
-import org.nd4j.linalg.api.ndarray.INDArray;
-
-public class AdjustContrastV2 extends BaseAdjustContrast {
-
-    public AdjustContrastV2() {super();}
-
-    public AdjustContrastV2(@NonNull INDArray in, double factor, INDArray out) {
-        super(in, factor, out);
-    }
-
-    public AdjustContrastV2(@NonNull SameDiff sameDiff, @NonNull SDVariable in, @NonNull SDVariable factor) {
-        super( sameDiff,new SDVariable[]{in,factor});
-    }
-
-    @Override
-    public String opName() {
-        return "adjust_contrast_v2";
-    }
-
-    @Override
-    public String tensorflowName() {
-        return "AdjustContrastv2";
-    }
-}

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/BaseAdjustContrast.java

@@ -1,52 +0,0 @@
-/* ******************************************************************************
- * Copyright (c) 2019 Konduit K.K.
- *
- * This program and the accompanying materials are made available under the
- * terms of the Apache License, Version 2.0 which is available at
- * https://www.apache.org/licenses/LICENSE-2.0.
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
- * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
- * License for the specific language governing permissions and limitations
- * under the License.
- *
- * SPDX-License-Identifier: Apache-2.0
- ******************************************************************************/
-package org.nd4j.linalg.api.ops.custom;
-
-import lombok.NonNull;
-import org.nd4j.autodiff.samediff.SDVariable;
-import org.nd4j.autodiff.samediff.SameDiff;
-import org.nd4j.common.base.Preconditions;
-import org.nd4j.linalg.api.buffer.DataType;
-import org.nd4j.linalg.api.ndarray.INDArray;
-import org.nd4j.linalg.api.ops.DynamicCustomOp;
-
-import java.util.Collections;
-import java.util.List;
-
-public abstract class BaseAdjustContrast extends DynamicCustomOp {
-    public BaseAdjustContrast() {
-    }
-
-    public BaseAdjustContrast(@NonNull INDArray in, double factor, INDArray out) {
-        Preconditions.checkArgument(in.rank() >= 3,
-                "AdjustContrast: op expects rank of input array to be >= 3, but got %s instead", in.rank());
-        inputArguments.add(in);
-        outputArguments.add(out);
-
-        addTArgument(factor);
-    }
-
-    public BaseAdjustContrast(@NonNull SameDiff sameDiff, @NonNull SDVariable[] vars) {
-        super("", sameDiff, vars);
-    }
-
-    @Override
-    public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes){
-        int n = args().length;
-        Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == n, "Expected %s input data types for %s, got %s", n, getClass(), inputDataTypes);
-        return Collections.singletonList(inputDataTypes.get(0));
-    }
-}

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/CompareAndBitpack.java

@@ -17,10 +17,15 @@ package org.nd4j.linalg.api.ops.custom;
 
 import org.nd4j.autodiff.samediff.SDVariable;
 import org.nd4j.autodiff.samediff.SameDiff;
+import org.nd4j.common.base.Preconditions;
+import org.nd4j.linalg.api.buffer.DataType;
 import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.api.ops.DynamicCustomOp;
 import org.nd4j.linalg.factory.Nd4j;
 
+import java.util.Collections;
+import java.util.List;
+
 public class CompareAndBitpack extends DynamicCustomOp {
     public CompareAndBitpack() {}
 
@@ -47,4 +52,11 @@ public class CompareAndBitpack extends DynamicCustomOp {
     public String tensorflowName() {
         return "CompareAndBitpack";
     }
+
+    @Override
+    public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes){
+        Preconditions.checkState(dataTypes != null && dataTypes.size() == 2, "Expected exactly 2 input datatypes for %s, got input %s", getClass(), dataTypes);
+        Preconditions.checkState(dataTypes.get(0) == dataTypes.get(1), "Input data types must be the same: got %s", dataTypes);
+        return Collections.singletonList(DataType.UINT8);
+    }
 }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/RgbToGrayscale.java

@@ -37,8 +37,4 @@ public class RgbToGrayscale extends DynamicCustomOp {
         return "rgb_to_grs";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "RgbToGrs";
-    }
 }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/RgbToYiq.java

@@ -42,11 +42,6 @@ public class RgbToYiq extends DynamicCustomOp {
         return "rgb_to_yiq";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "RgbToYiq";
-    }
-
     @Override
     public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes){
         int n = args().length;

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/RgbToYuv.java

@@ -42,11 +42,6 @@ public class RgbToYuv extends DynamicCustomOp {
         return "rgb_to_yuv";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "RgbToYuv";
-    }
-
     @Override
     public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes){
         int n = args().length;

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/YiqToRgb.java

@@ -41,11 +41,6 @@ public class YiqToRgb extends DynamicCustomOp {
         return "yiq_to_rgb";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "YiqToRgb";
-    }
-
     @Override
     public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes){
         int n = args().length;

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/custom/YuvToRgb.java

@@ -42,10 +42,6 @@ public class YuvToRgb extends DynamicCustomOp {
         return "yuv_to_rgb";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "YuvToRgb";
-    }
 
     @Override
     public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes){

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/image/NonMaxSuppressionV3.java

@@ -53,7 +53,7 @@ public class NonMaxSuppressionV3 extends DynamicCustomOp {
 
     @Override
     public String[] tensorflowNames() {
-        return new String[]{"NonMaxSuppressionV3","NonMaxSuppressionV4"};
+        return new String[]{"NonMaxSuppressionV3","NonMaxSuppressionV4","NonMaxSuppressionV5"};
     }
 
     @Override

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/layers/convolution/DeConv2D.java

@@ -306,11 +306,6 @@ public class DeConv2D extends DynamicCustomOp {
         return "ConvTranspose";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "Conv2DTranspose";
-    }
-
 
     @Override
     public List<SDVariable> doDiff(List<SDVariable> f1) {

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/transforms/custom/IsNonDecreasing.java

@@ -62,12 +62,6 @@ public class IsNonDecreasing extends DynamicCustomOp {
         return "is_non_decreasing";
     }
 
-
-    @Override
-    public String tensorflowName() {
-        return "IsNonDecreasing";
-    }
-
     @Override
     public List<SDVariable> doDiff(List<SDVariable> f1) {
         return Collections.singletonList(sameDiff.zerosLike(arg()));

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/transforms/pairwise/arithmetic/CopyOp.java

@@ -78,7 +78,7 @@ public class CopyOp extends BaseTransformSameOp {
 
     @Override
     public String[] tensorflowNames() {
-        return new String[]{"Copy","DeepCopy","CopyHost"};
+        return new String[]{"Copy"};
     }
 
     @Override

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/transforms/same/Identity.java

@@ -64,7 +64,7 @@ public class Identity extends BaseDynamicTransformOp {
 
     @Override
     public String[] tensorflowNames() {
-        return new String[]{"Identity"};
+        return new String[]{"Identity", "DeepCopy", "CopyHost"};
     }
 
     @Override

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/transforms/segment/UnsortedSegmentMean.java

@@ -55,10 +55,6 @@ public class UnsortedSegmentMean extends DynamicCustomOp {
         return "unsorted_segment_mean";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "UnsortedSegmentMean";
-    }
 
     @Override
     public List<SDVariable> doDiff(List<SDVariable> gradients){

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/transforms/segment/UnsortedSegmentSqrtN.java

@@ -55,11 +55,6 @@ public class UnsortedSegmentSqrtN extends DynamicCustomOp {
         return "unsorted_segment_sqrt_n";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "UnsortedSegmentSqrtN";
-    }
-
     @Override
     public List<SDVariable> doDiff(List<SDVariable> gradients){
         return new UnsortedSegmentSqrtNBp(sameDiff, arg(0), arg(1), gradients.get(0), numSegments).outputs();

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/random/custom/RandomGamma.java

@@ -71,9 +71,7 @@ public class RandomGamma extends DynamicCustomOp {
 
     @Override
     public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String, AttrValue> attributesForNode, GraphDef graph) {
-        if(attributesForNode.containsKey("alpha")) {
+            outputDataType = DataTypeAdapter.dtypeConv(attributesForNode.get("T").getType());
-            outputDataType = DataTypeAdapter.dtypeConv(attributesForNode.get("alpha").getType());
-        }
     }
 
     @Override

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/random/impl/DropOutInverted.java

@@ -84,12 +84,6 @@ public class DropOutInverted extends BaseRandomOp {
         return "Dropout";
     }
 
-    @Override
-    public String tensorflowName() {
-        return "Dropout";
-    }
-
-
     @Override
     public List<SDVariable> doDiff(List<SDVariable> f1) {
         return null;

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/random/impl/UniformDistribution.java

@@ -100,12 +100,6 @@ public class UniformDistribution extends BaseRandomOp {
         throw new NoOpNameFoundException("No onnx op opName found for " +  opName());
     }
 
-    @Override
-    public String tensorflowName() {
-        return "RandomUniformGG";
-    }
-
-
     @Override
     public List<SDVariable> doDiff(List<SDVariable> f1) {
         return Collections.emptyList();

nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/imports/TFGraphs/TFGraphTestAllHelper.java

@@ -851,7 +851,68 @@ public class TFGraphTestAllHelper {
             return (t, s) -> Nd4j.sort(t, true).equals(Nd4j.sort(s, true));
         }
 
-        if(modelName.startsWith("alpha_dropout") || modelName.startsWith("layers_dropout") || modelName.equals("dropout"))
+        if(modelName.startsWith("empty")){
+            return (t, s) -> {
+                boolean areEqualShapes = t.equalShapes(s);
+                boolean areEqualDataTypes = t.dataType() == s.dataType();
+                return areEqualShapes && areEqualDataTypes;
+            };        }
+
+        // sum of all elements along dimesions before and after shuffle has to be the same
+        if(modelName.startsWith("random_shuffle")){
+            return (t, s) -> Nd4j.sort(t, true).equals(Nd4j.sort(s, true));
+        }
+
+        if(modelName.startsWith("random_normal")){
+            return (t, s) -> {
+                boolean areEqualShapes = t.equalShapes(s);
+                double meanS = s.meanNumber().doubleValue();
+                double meanT = t.meanNumber().doubleValue();
+                double stdS = s.stdNumber().doubleValue();
+                double stdT = t.stdNumber().doubleValue();
+                double eps = 1;
+                return areEqualShapes && (Math.abs(meanS-meanT) < eps) && (Math.abs(stdS-stdT) < eps);
+            };        }
+
+        if(modelName.startsWith("random_gamma")){
+            return (t, s) -> {
+                boolean areEqualShapes = t.equalShapes(s);
+                boolean nonNegativeValues = (t.minNumber().doubleValue() > 0) && (t.minNumber().doubleValue() > 0);
+                double meanS = s.meanNumber().doubleValue();
+                double meanT = t.meanNumber().doubleValue();
+                double stdS = s.stdNumber().doubleValue();
+                double stdT = t.stdNumber().doubleValue();
+                double eps = 1;
+                return areEqualShapes && nonNegativeValues && (Math.abs(meanS-meanT) < eps) && (Math.abs(stdS-stdT) < eps);
+            };
+         }
+
+        if(modelName.startsWith("random_poisson") || modelName.startsWith("random_poisson_v2")){
+            return (t, s) -> {
+                boolean areEqualShapes = t.equalShapes(s);
+                boolean nonNegativeValues = (t.minNumber().doubleValue() >= 0) && (t.minNumber().doubleValue() >= 0);
+                double meanS = s.meanNumber().doubleValue();
+                double meanT = t.meanNumber().doubleValue();
+                double stdS = s.stdNumber().doubleValue();
+                double stdT = t.stdNumber().doubleValue();
+                double eps = 1;
+                return areEqualShapes && nonNegativeValues && (Math.abs(meanS-meanT) < eps) && (Math.abs(stdS-stdT) < eps);
+            };
+        }
+
+        if(modelName.startsWith("random_uniform")|| modelName.startsWith("random_uniform_int")){
+            return (t, s) -> {
+                boolean areEqualShapes = t.equalShapes(s);
+                double meanS = s.meanNumber().doubleValue();
+                double meanT = t.meanNumber().doubleValue();
+                double stdS = s.stdNumber().doubleValue();
+                double stdT = t.stdNumber().doubleValue();
+                double eps = 1;
+                return areEqualShapes && (Math.abs(stdS-stdT) < eps) && (Math.abs(meanS-meanT) < eps);
+            };
+        }
+
+        if(modelName.startsWith("alpha_dropout") || modelName.startsWith("layers_dropout") || modelName.startsWith("dropout"))
             //We can't compare dropout using simple equality due to randomness
             return (t, s) -> {
                 double[] tfNums = t.ravel().toDoubleVector();

nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/imports/TFGraphs/TFGraphTestAllSameDiff.java

@@ -66,23 +66,29 @@ public class TFGraphTestAllSameDiff {   //Note: Can't extend BaseNd4jTest here a
     public static final String[] IGNORE_REGEXES = new String[]{
             //Failing 2019/07/01 - Issue 10, https://github.com/deeplearning4j/deeplearning4j/issues/6958
             //Still failing 2019/09/11
+            //Still failing 2020/04/27
+            //java.lang.IllegalStateException: Requested output variable LogMatrixDeterminant:1 does not exist in SameDiff instance
             "slogdet/.*",
 
             //Failing 2019/09/11 - https://github.com/eclipse/deeplearning4j/issues/7965
+            // Still failing 2020/04/27 java.lang.IllegalStateException: Requested output variable Bincount does not exist in SameDiff instance
             "bincount/.*",
             // Failing 2019/11/14 https://github.com/eclipse/deeplearning4j/issues/8393
             "is_strictly_increasing/emptyArrayTest/.*",
 
             //TODO floormod and truncatemod behave differently - i.e., "c" vs. "python" semantics. Need to check implementations too
+            // Still failing 2020/04/27 java.lang.IllegalStateException: Could not find class for TF Ops: TruncateMod
             "truncatemod/.*",
 
             //Still failing as of 2019/09/11 - https://github.com/deeplearning4j/deeplearning4j/issues/6464 - not sure if related to: https://github.com/deeplearning4j/deeplearning4j/issues/6447
             "cnn2d_nn/nhwc_b1_k12_s12_d12_SAME",
 
             //2019/09/11 - No tensorflow op found for SparseTensorDenseAdd
+            // 2020/04/27 java.lang.IllegalStateException: Could not find class for TF Ops: SparseTensorDenseAdd
             "confusion/.*",
 
             //2019/09/11 - Couple of tests failing (InferenceSession issues)
+            // Still failing 2020/04/27 Requested output variable concat does not exist in SameDiff instance
             "rnn/bstack/d_.*",
 
             //2019/05/21 - Failing on AVX2/512 intermittently (Linux, OSX), passing elsewhere
@@ -97,87 +103,68 @@ public class TFGraphTestAllSameDiff {   //Note: Can't extend BaseNd4jTest here a
             "g_11",
 
             //2019/07/09 - Need "Multinomial" op - https://github.com/eclipse/deeplearning4j/issues/7913
+            // Still failing 2020/04/27 java.lang.IllegalStateException: Could not find class for TF Ops: Multinomial
             "multinomial/.*",
 
             //2019/11/04 AB - disabled, pending libnd4j deconv3d_tf implementation
+            // Still failing 2020/04/27 java.lang.IllegalStateException: Could not find descriptor for op: deconv3d_tf - class: org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv3DTF
             "conv3d_transpose.*",
 
             //2019/11/15 - mapping is not present yet https://github.com/eclipse/deeplearning4j/issues/8397
+            // Still failing 2020/04/27 java.lang.AssertionError: Predictions do not match on ragged/reduce_mean/2d_a1, node RaggedReduceMean/truediv
             "ragged/reduce_mean/.*",
 
             // 2019/11/15 - missing dtype argument in nd4j, tests are useless https://github.com/eclipse/deeplearning4j/issues/8398
-            "zeros_like/rank2_float32_dtype_int.*",
+            // Still failing 2020/04/27 java.lang.IndexOutOfBoundsException: 1
+           "zeros_like/rank2_float32_dtype_int.*",
 
             // 11.26.2019 failing - https://github.com/eclipse/deeplearning4j/issues/8453
+            // Still failing 2020/04/27 java.lang.AssertionError: Predictions do not match on roll/rank2_float32_zeroshift, node Roll
             "roll/.*",
 
             // 11.26.2019 failing https://github.com/eclipse/deeplearning4j/issues/8455
+            // still failing 2020/04/27
+            // java.lang.IllegalStateException: Failed to calculate output shapes for op matrix_band_part (MatrixBandPart) - no shapes were returned by calculateOutputShape()
             "matrix_band_part/.*",
 
             // 12.20.2019 - https://github.com/eclipse/deeplearning4j/issues/8559
+            // Still failing 2020/27/04 java.lang.AssertionError: Predictions do not match on fused_batch_norm/float32_nhcw, node FusedBatchNormV3
             "fused_batch_norm/.*",
 
-            // AB 2020/01/04 - https://github.com/eclipse/deeplearning4j/issues/8592
+            // 01.05.2020 -  https://github.com/eclipse/deeplearning4j/issues/8898
-            "emptyArrayTests/reshape/rank2_shape2-0_2-0--1",
+             "primitive_gru",
 
-            //AB 2020/01/07 - Known issues
+            // 05.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8921
-            "bitcast/from_float64_to_int64",
+            "random_poisson/rank1_float16", "random_poisson/rank1_float32", "random_poisson/rank1_float16", "random_poisson/rank1_half",
-            "bitcast/from_rank2_float64_to_int64",
+            "random_poisson_v2/rank1_float64", "random_poisson_v2/rank1_float16", "random_poisson_v2/rank1_half",
-            "bitcast/from_float64_to_uint64",
 
-
+            //08.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8927
-            //NEWLY ADDED TESTCASES from 27/04/2020
-            "non_max_suppression_v2/.*", "non_max_suppression/.*",
             "random_gamma/.*",
-            "non_max_suppression_v5/.*",
+
-            "non_max_suppression_v4/.*",
+            //08.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8928
-            "non_max_suppression_v3/.*",
-            "dropout/.*",
-            "max_pool_with_argmax/.*",
-            "conv2d_transpose/.*",
             "Conv3DBackpropInputV2/.*",
-            "Conv3DBackpropInput/.*",
+
-            "mod/.*",
+            //12.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8940
-            "leaky_relu/.*",
+            "compare_and_bitpack/.*",
-            "DeepCopy/.*",
+
-            "empty/.*",
+            //12.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8943
-            "ones_like/.*",
+            "max_pool_with_argmax/int64_int64_padding_SAME", "max_pool_with_argmax/int32_int64_padding_SAME",
-            "is_non_decreasing/.*",
+
-            "div/.*",
+            //12.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8946
-            "lgamma/.*",
+            "non_max_suppression_v4/.*","non_max_suppression_v5/.*",
+
+            // 18.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8960
+            "random_shuffle/.*",
+            // 18.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8963
             "random_uniform/.*",
             "random_uniform_int/.*",
-            "resize_area/.*",
-            "zeros_like_tf1/.*",
-            "Conv2DTranspose/.*",
-            "rgb_to_yuv/.*",
-            "rgb_to_grayscale/.*",
-            "rgb_to_yiq/.*",
-            "losses/.*",
-            "yiq_to_rgb/.*",
-            "yuv_to_rgb/.*",
-            "emptyArrayTests/.*",
             "random_normal/.*",
-            "random_shuffle/.*",
+            "random_gamma/.*",
-            "random_poisson_v2/.*",
             "random_poisson/.*",
-            "random_crop/.*",
+            "random_poisson/.*",
-            "compare_and_bitpack/.*",
+            "random_poisson_v2/.*",
-            "adjust_contrast/.*",
-            "confusion/.*",
-            "bitcast/.*",
-            "roll/.*",
-            "matrix_band_part/.*",
-            "conv3d_transpose_layers/.*",
-            "multinomial/.*",
-            "unsorted_segment/.*",
-            "cnn2d_nn/.*",
-            "truncatemod/.*",
-            "bincount/.*",
-            "slogdet/.*",
-            "adjust_contrast_v2/.*"
 
-};
+  };
 
     /* As per TFGraphTestList.printArraysDebugging - this field defines a set of regexes for test cases that should have
        all arrays printed during execution.

nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/linalg/custom/CustomOpsTests.java

@@ -847,22 +847,6 @@ public class CustomOpsTests extends BaseNd4jTest {
         assertArrayEquals(new long[]{256, 256, 3}, lsd.get(0).getShape());
     }
 
-    @Test
-    public void testAdjustContrastV2() {
-        INDArray in = Nd4j.linspace(DataType.DOUBLE,1.0,1.0, 4*4*3).reshape(4,4,3);
-        INDArray out = Nd4j.createUninitialized(4,4,3);
-
-        INDArray expected = Nd4j.createFromArray(new double[]{-21.5, -20.5, -19.5,  -15.5, -14.5, -13.5,  -9.5,  -8.5,  -7.5,  -3.5,  -2.5,  -1.5,
-                2.5,   3.5,   4.5,    8.5,   9.5,  10.5,  14.5,  15.5,  16.5,  20.5,  21.5,  22.5,
-                26.5,  27.5,  28.5,   32.5,  33.5,  34.5,  38.5,  39.5,  40.5,  44.5,  45.5,  46.5,
-                50.5,  51.5,  52.5,   56.5,  57.5,  58.5,  62.5,  63.5,  64.5,  68.5,  69.5,  70.5
-        }).reshape(4,4,3);
-
-        Nd4j.exec(new AdjustContrastV2(in, 2.0, out));
-
-        assertArrayEquals(out.shape(), in.shape());
-        assertEquals(expected, out);
-    }
 
     @Ignore("AS 11/13/2019 https://github.com/eclipse/deeplearning4j/issues/8374")
     @Test