Various pre-release fixes (#111)

* Various fixes

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

* Fix default dtypes for MaxPoolWithArgmax

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

libnd4j/include/ops/declarable/generic/nn/pooling/maxpool_with_argmax.cpp

@@ -46,7 +46,7 @@ namespace nd4j {
             getOpDescriptor()
                     ->setAllowedInputTypes(nd4j::DataType::ANY)
                     ->setAllowedOutputTypes(0, DataType::INHERIT)
-                    ->setAllowedOutputTypes(1, DataType::INT64);
+                    ->setAllowedOutputTypes(1, {ALL_INTS});
 
         }
 

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

@@ -103,6 +103,7 @@ public class ImportClassMapping {
             org.nd4j.linalg.api.ops.impl.layers.convolution.BatchNormDerivative.class,
             org.nd4j.linalg.api.ops.impl.layers.convolution.Col2Im.class,
             org.nd4j.linalg.api.ops.impl.layers.convolution.Conv1D.class,
+            org.nd4j.linalg.api.ops.impl.layers.convolution.Conv1DDerivative.class,
             org.nd4j.linalg.api.ops.impl.layers.convolution.Conv2D.class,
             org.nd4j.linalg.api.ops.impl.layers.convolution.Conv2DDerivative.class,
             org.nd4j.linalg.api.ops.impl.layers.convolution.Conv3D.class,

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

@@ -60,7 +60,7 @@ public class NonMaxSuppression extends DynamicCustomOp {
 
     @Override
     public String[] tensorflowNames() {
-        return new String[]{"NonMaxSuppression", "NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV4"};
+        return new String[]{"NonMaxSuppression", "NonMaxSuppressionV2"};
     }
 
     @Override

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

@@ -204,7 +204,7 @@ public class MaxPoolWithArgmax extends DynamicCustomOp {
         if(attributesForNode.containsKey("argmax")) {
             outputType = TFGraphMapper.convertType(attributesForNode.get("argmax").getType());
         } else {
-            outputType = DataType.UINT32;
+            outputType = DataType.LONG;
         }
     }
 
@@ -278,7 +278,7 @@ public class MaxPoolWithArgmax extends DynamicCustomOp {
         Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == 1, "Expected 1 input data type for %s, got %s", getClass(), inputDataTypes);
         List<DataType> result = new ArrayList<>();
         result.add(inputDataTypes.get(0));
-        result.add(outputType == null ? DataType.UINT32 : outputType);
+        result.add(outputType == null ? DataType.INT : outputType);
         return result;
     }
 }

nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/autodiff/opvalidation/LayerOpValidation.java

@@ -760,7 +760,7 @@ public class LayerOpValidation extends BaseOpValidation {
                 .isSameMode(true)
                 .build();
 
-        SDVariable[] results = sd.nn().maxPoolWithArgmax(new String[]{"",""}, in, pooling2DConfig);
+        SDVariable[] results = sd.nn().maxPoolWithArgmax(new String[]{"out","idx"}, in, pooling2DConfig);
         assertArrayEquals(inArr.shape(), results[0].eval().shape());
         assertArrayEquals(inArr.shape(), results[1].eval().shape());
     }
@@ -1050,7 +1050,7 @@ public class LayerOpValidation extends BaseOpValidation {
         SDVariable in = sd.var("in", inArr);
         SDVariable w = sd.var("w", wArr);
 
-        SDVariable res = sd.cnn.conv1d(in, w, Conv1DConfig.builder().k(kernel).build());
+        SDVariable res = sd.cnn.conv1d(in, w, Conv1DConfig.builder().k(kernel).paddingMode(PaddingMode.VALID).build());
 
         INDArray expected = Nd4j.createFromArray(
                 new double[][][]{

nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/autodiff/samediff/ConvConfigTests.java

@@ -23,13 +23,7 @@ import static org.junit.Assert.fail;
 import org.junit.Assert;
 import org.junit.Test;
 import org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv2D;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Conv1DConfig;
+import org.nd4j.linalg.api.ops.impl.layers.convolution.config.*;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Conv2DConfig;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Conv3DConfig;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.DeConv2DConfig;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.DeConv3DConfig;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Pooling2DConfig;
-import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Pooling3DConfig;
 
 public class ConvConfigTests {
 
@@ -489,24 +483,24 @@ public class ConvConfigTests {
 
     @Test
     public void testConv1D(){
-        Conv1DConfig.builder().k(2).build();
+        Conv1DConfig.builder().k(2).paddingMode(PaddingMode.SAME).build();
 
         try{
-            Conv1DConfig.builder().k(0).build();
+            Conv1DConfig.builder().k(0).paddingMode(PaddingMode.SAME).build();
             fail();
         } catch (IllegalArgumentException e){
             assertTrue(e.getMessage().contains("Kernel"));
         }
 
         try{
-            Conv1DConfig.builder().k(4).s(-2).build();
+            Conv1DConfig.builder().k(4).s(-2).paddingMode(PaddingMode.SAME).build();
             fail();
         } catch (IllegalArgumentException e){
             assertTrue(e.getMessage().contains("Stride"));
         }
 
         try{
-            Conv1DConfig.builder().k(3).p(-2).build();
+            Conv1DConfig.builder().k(3).p(-2).paddingMode(PaddingMode.SAME).build();
             fail();
         } catch (IllegalArgumentException e){
             assertTrue(e.getMessage().contains("Padding"));