diff --git a/src/nodes/averagepool.h b/src/nodes/averagepool.h
index 1818cc8..a650d59 100644
--- a/src/nodes/averagepool.h
+++ b/src/nodes/averagepool.h
@@ -17,7 +17,7 @@ class AveragePool : public Pooling {
 
 	virtual void print_output_cell_init(std::ostream &dst, const std::string &y_idx) const override
 	{
-		INDT_3  << y->data_type_str() << " curavg = 0.0;" << std::endl;
+		INDT_3  << get_Y()->data_type_str() << " curavg = 0.0;" << std::endl;
 		INDT_3  << "int numavg = 0;" << std::endl;
 	}
 	virtual void print_output_cell_calc(
@@ -52,12 +52,7 @@ class AveragePool : public Pooling {
  
 	virtual void resolve(void) override
 	{
-		x = inputs[0];
-		register_input(x, "x");
-
-		if( !(  typeConstraint_plainFloatingPoints(x)
-		      ||typeConstraint_8bit(x)) )
-			ERROR("Incorrect input for node"); 
+		register_input(inputs[0], "x");
 
 		resolve_strides();
 		resolve_dilations();
@@ -66,8 +61,7 @@ class AveragePool : public Pooling {
 
 		Tensor *rv = new Tensor;
 		rv->data_dim = resolve_output_size();
-		rv->data_type = x->data_type;
-		y=rv;
+		rv->data_type = get_X()->data_type;
 		register_output(rv, "y");
 
 		update_pads();
diff --git a/src/nodes/conv.h b/src/nodes/conv.h
index c4b2794..9bd641f 100644
--- a/src/nodes/conv.h
+++ b/src/nodes/conv.h
@@ -16,7 +16,7 @@ class Conv : public SpatialFilter {
 	virtual void print_output_cell_init(std::ostream &dst, const std::string &y_idx) const override
 	{
 		std::string outidx="";
-		for(unsigned i=0; i<x->rank()-2; i++)
+		for(unsigned i=0; i<get_numDataDim(); i++)
 			outidx += "[o" + std::to_string(i) + "]";
 		INDT_3 << "y[b][m]" << outidx << " = ";
 		if( inputs.size() < 3 ) // bias is the 3rd input, optional
@@ -33,7 +33,7 @@ class Conv : public SpatialFilter {
 		std::string outidx="";
 		std::string iididx="";
 		std::string kidx="";
-		for(unsigned i=0; i<x->rank()-2; i++){
+		for(unsigned i=0; i<get_numDataDim(); i++){
 			outidx += "[o" + std::to_string(i) + "]";
 			iididx+= "[ii" + std::to_string(i) + "]";
 			kidx+= "[k" + std::to_string(i) + "]";
@@ -55,18 +55,12 @@ class Conv : public SpatialFilter {
  
 	virtual void resolve(void) override
 	{
-		x = inputs[0]; // data
-		register_input(x,"x");
-		w = inputs[1]; // weights
-		register_input(w,"w");
+		register_input(inputs[0],"x");
+		register_input(inputs[1],"w");
 		if( inputs.size() == 3 ) {
 			register_input(inputs[2],"bias");
 		}
 
-		if(  typeConstraint_highPrecisionNumeric(x) == false
-		   ||typeConstraint_highPrecisionNumeric(w) == false)
-			ERROR("Incorrect input for node");
-
 		resolve_strides();
 		resolve_dilations();
 		resolve_pads();
@@ -74,8 +68,7 @@ class Conv : public SpatialFilter {
 
 		Tensor *rv = new Tensor;
 		rv->data_dim = resolve_output_size();
-		rv->data_type = x->data_type;
-		y=rv;
+		rv->data_type = get_X()->data_type;
 		register_output(rv, "y");
 	}
 };
diff --git a/src/nodes/convinteger.h b/src/nodes/convinteger.h
index c29b3f5..777841d 100644
--- a/src/nodes/convinteger.h
+++ b/src/nodes/convinteger.h
@@ -18,7 +18,6 @@ class ConvInteger : public SpatialFilter {
 		op_name = "ConvInteger";
 		auto_pad = "NOTSET";
 		group = 1;
-		x=w=y=NULL;
 	}
 
 	virtual void print_output_cell_init(std::ostream &dst, const std::string &y_idx) const override
@@ -41,7 +40,7 @@ class ConvInteger : public SpatialFilter {
 		else
 			x_zero = "0";
 
-		INDT_4 << w->data_type_str() << " w_ = " << constant_acces_code("w[m][c][k0][k1]") << ";" << std::endl;
+		INDT_4 << get_W()->data_type_str() << " w_ = " << constant_acces_code("w[m][c][k0][k1]") << ";" << std::endl;
 		std::string dest;
 		if( options.quantize )
 			dest = "cell";
@@ -72,10 +71,8 @@ class ConvInteger : public SpatialFilter {
 
 	virtual void resolve(void) override
 	{
-		x = inputs[0]; // data
-		register_input(x, "x");
-		w = inputs[1]; // weights
-		register_input(w, "w");
+		register_input(inputs[0], "x");
+		register_input(inputs[1], "w");
 
 		if( inputs.size() > 2 )
 			register_input(inputs[2], "x_zero_point");
@@ -84,7 +81,7 @@ class ConvInteger : public SpatialFilter {
 			ERROR("unimplemented: weight zero points");
 		}
 
-		if( x->data_dim.size() != 4 )
+		if( get_X()->data_dim.size() != 4 )
 			ERROR("Unimplemented: ConvInteger for non 2D images");
 
 
@@ -107,7 +104,6 @@ class ConvInteger : public SpatialFilter {
 			rv->data_type = onnx::TensorProto_DataType_INT8;
 		else
 			rv->data_type = onnx::TensorProto_DataType_INT32;
-		y=rv;
 		register_output(rv, "y");
 	}
 };
diff --git a/src/nodes/maxpool.h b/src/nodes/maxpool.h
index a1975a5..12abb24 100644
--- a/src/nodes/maxpool.h
+++ b/src/nodes/maxpool.h
@@ -12,25 +12,10 @@ class MaxPool : public Pooling {
 	public:
 	MaxPool() {
 		op_name = "MaxPool";
-		Indices=NULL;
 	}
 
-	// optional outputs
-	const Tensor *Indices;
-
 	std::vector<int> pad_shapes;
 
-	virtual void print_parameters(std::ostream &dst, bool decorate ) const override
-	{
-		x->print_tensor_as_const(dst, !decorate);
-		dst << ", ";
-		y->print_tensor(dst, !decorate);
-		if( Indices->name != "" ) {
-			dst << ", ";
-			Indices->print_tensor(dst, !decorate);
-		}
-	}
-
 	virtual void parseAttributes( onnx::NodeProto &node ) override {
 
 		Pooling::parseAttributes(node);
@@ -43,7 +28,7 @@ class MaxPool : public Pooling {
 
 	virtual void print_output_cell_init(std::ostream &dst, const std::string &y_idx) const override
 	{
-		std::string type = x->data_type_str();
+		std::string type = get_X()->data_type_str();
 		std::string type_min_value;
 		if( type == "float" )
 			type_min_value = "-FLT_MAX";
@@ -57,7 +42,7 @@ class MaxPool : public Pooling {
 			ERROR("Unimplemented: minimum value for this type");
 
 		INDT_3  << type << " curmax = " << type_min_value << ";" << std::endl;
-		if( Indices->name != "" )
+		if( get_Indices() )
 			INDT_3 << "int64_t curmaxind = -1;" << std::endl;
 
 
@@ -68,7 +53,9 @@ class MaxPool : public Pooling {
 		const std::string &w_idx,
 		const std::string &y_idx) const override
 	{
-		unsigned n_data_dims = x->data_dim.size()-2;
+		unsigned n_data_dims = get_numDataDim();
+		const Tensor *x = get_X();
+
 		// Calculate how much one index means in terms of the Indices output.
 		// Generate helper string for the next step.
 		std::vector<int>size_of_dim(x->rank());
@@ -80,9 +67,9 @@ class MaxPool : public Pooling {
 			indices_value += "+(ii" + std::to_string(i) + "*" + std::to_string(size_of_dim[i+2]) + ")";
 
 		// Update the max and index value
-		INDT_4 << "if( curmax < " << x->cname() << x_idx << ") {" <<std::endl;
-		INDT_4 << "curmax = MAX( curmax, " << x->cname() << x_idx << ");" <<std::endl;
-		if( Indices->name != "" )
+		INDT_4 << "if( curmax < x" << x_idx << ") {" <<std::endl;
+		INDT_4 << "curmax = MAX( curmax, x" << x_idx << ");" <<std::endl;
+		if( get_Indices() )
 			INDT_4  << "curmaxind = " << indices_value << ";" <<std::endl;
 		INDT_4 << "}" << std::endl;
 
@@ -91,9 +78,9 @@ class MaxPool : public Pooling {
 	virtual void print_output_cell_finalize(std::ostream &dst, const std::string &y_idx) const override
 	{
 		// Store the calculated values into output tensors
-		INDT_3  << y->cname() << y_idx << "= curmax;" << std::endl;
-		if( Indices->name != "" )
-			INDT_3 << Indices->cname() << y_idx << "= curmaxind;" << std::endl;
+		INDT_3  << "y" << y_idx << "= curmax;" << std::endl;
+		if( get_Indices() )
+			INDT_3 << "Indices " << y_idx << "= curmaxind;" << std::endl;
 	}
 
 
@@ -105,7 +92,7 @@ class MaxPool : public Pooling {
 
 	virtual void resolve(void) override
 	{
-		x = inputs[0];
+		register_input(inputs[0], "x");
 
 		resolve_strides();
 		resolve_dilations();
@@ -118,9 +105,8 @@ class MaxPool : public Pooling {
 		Tensor *rv = new Tensor;
 		rv->data_dim = resolve_output_size();
 
-		rv->data_type = x->data_type;
-		y=rv;
-		outputs.push_back(rv);
+		rv->data_type = get_X()->data_type;
+		register_output(rv, "y");
 
 		update_pads();
 
@@ -128,10 +114,13 @@ class MaxPool : public Pooling {
 		Tensor *indices_out = new Tensor;
 		indices_out->data_type = onnx::TensorProto_DataType::TensorProto_DataType_INT64;
 		indices_out->data_dim = rv->data_dim;
-		Indices = indices_out;
-		outputs.push_back(indices_out);
-
-
+		register_output(indices_out, "Indices");
+	}
+	const Tensor* get_Indices(void) const {
+		if( outputs[1]->name != "" )
+			return outputs[1];
+		else
+			return nullptr;
 	}
 };
 }
diff --git a/src/nodes/pooling.h b/src/nodes/pooling.h
index 9f58c79..8bd83f2 100644
--- a/src/nodes/pooling.h
+++ b/src/nodes/pooling.h
@@ -46,19 +46,19 @@ class Pooling : public SpatialFilter {
 	virtual std::vector<int> resolve_output_size(void) override
 	{
 		std::vector<int> rv;
-		rv.push_back(x->data_dim[0]);//batch
-		rv.push_back(x->data_dim[1]);//channel
+		rv.push_back(get_X()->data_dim[0]);//batch
+		rv.push_back(get_X()->data_dim[1]);//channel
 	
-		unsigned data_dims = x->data_dim.size()-2;
+		unsigned data_dims = get_numDataDim();
 		std::vector<int> pad_shapes;
 		for( unsigned i=0; i<data_dims; i++ ) {
 			pad_shapes.push_back(pads[i]+pads[data_dims+i]);
 		}
 		// Calculate output shape. Pads are now calculated
 		// for those auto_pad modes that need them.
-		for( unsigned i=2; i<x->data_dim.size(); i++ ) {
+		for( unsigned i=2; i<get_X()->data_dim.size(); i++ ) {
 			int d;
-			int in_dim = x->data_dim[i];
+			int in_dim = get_X()->data_dim[i];
 			int kernel = kernel_shape[i-2];
 			int dilation = dilations.size()==0 ? 1 : dilations[i-2];
 			int stride = strides[i-2];
@@ -92,7 +92,7 @@ class Pooling : public SpatialFilter {
 		if ( auto_pad == "VALID" )
 			return;
 
-		unsigned data_dims = x->data_dim.size()-2;
+		unsigned data_dims = get_numDataDim();
 
 		// Calculate pads for the "SAME_*" cases that need the output shape 
 		for(unsigned i=0; i<data_dims; i++) {
@@ -101,8 +101,8 @@ class Pooling : public SpatialFilter {
 			// The auto_pad attribute for AveragePool is deprecated anyway. Probably just for this confusion.
 			// This tries to be some sort of band-aid: assume the output size is the same as input size
 			// which is the usual(?) reason to use "same" padding on the network design level. 
-			int input_size = x->data_dim[i+2];
-			int output_size = y->data_dim[i+2];
+			int input_size = get_X()->data_dim[i+2];
+			int output_size = get_Y()->data_dim[i+2];
 			int pad_shape = (output_size - 1) * strides[i] + (( kernel_shape[i] -1) * dilations[i]+1) - input_size; 
 			pads[i] = pad_shape/2;
 			pads[i+data_dims] = pad_shape/2;
diff --git a/src/nodes/spatialfilter.h b/src/nodes/spatialfilter.h
index 5d420fd..96bd35a 100644
--- a/src/nodes/spatialfilter.h
+++ b/src/nodes/spatialfilter.h
@@ -17,14 +17,8 @@ class SpatialFilter : public Node {
 	public:
 	SpatialFilter() {
 		auto_pad = "NOTSET";
-		x=w=y=NULL;
 		group=1;
 	}
-	// inputs
-	const Tensor *x;
-	const Tensor *w;
-	// outputs
-	const Tensor *y;
 
 	// Attributes
 	std::vector<int64_t> kernel_shape;
@@ -34,6 +28,16 @@ class SpatialFilter : public Node {
 	std::vector<int64_t> pads;
 	std::vector<int64_t> strides;
 
+	const Tensor* get_X(void) const { return inputs[0]; }
+	const Tensor* get_W(void) const {
+		if( inputs.size() > 1 )
+			return inputs[1];
+		else
+			return nullptr;
+	}
+	const Tensor* get_Y(void) const { return outputs[0]; }
+	uint32_t get_numDataDim(void) const {return get_X()->rank() - 2; }
+
 	virtual void parseAttributes( onnx::NodeProto &node ) override {
 		for( const auto& a : node.attribute() ) {
 			if( a.name() == "auto_pad" )
@@ -54,9 +58,8 @@ class SpatialFilter : public Node {
 
 	void resolve_strides(void)
 	{
-		unsigned num_data_dim = x->rank()-2;
 		if( strides.size() == 0 )
-			for( unsigned i=0; i<num_data_dim; i++)
+			for( unsigned i=0; i<get_numDataDim(); i++)
 				strides.push_back(1);
 	}
 
@@ -65,21 +68,20 @@ class SpatialFilter : public Node {
 		//if kernel shape is not given, infer from w
 		if( kernel_shape.size() == 0 ) {
 			// skip M and C/group dimensions
-			for( unsigned i=2; i<w->rank(); i++)
-				kernel_shape.push_back(w->data_dim[i]);
+			for( unsigned i=2; i<get_W()->rank(); i++)
+				kernel_shape.push_back(get_W()->data_dim[i]);
 		}
 	}
 
 	void resolve_dilations(void)
 	{
-		unsigned num_data_dim = x->rank()-2;
 		if( dilations.size() == 0 )
-			for( unsigned i=0; i< num_data_dim; i++ )
+			for( unsigned i=0; i< get_numDataDim(); i++ )
 				dilations.push_back(1);
 	}
 	void resolve_pads(void)
 	{
-		unsigned num_data_dim = x->rank()-2;
+		unsigned num_data_dim = get_numDataDim();
 		if( pads.size() == 0 ) {
 			pads.resize(num_data_dim*2);
 			for( unsigned i=0; i< num_data_dim; i++ ) {
@@ -100,13 +102,14 @@ class SpatialFilter : public Node {
 	virtual std::vector<int> resolve_output_size(void)
 	{
 		std::vector<int> rv;
-		unsigned num_data_dim = x->rank()-2;
-		rv.push_back(x->data_dim[0]);//batch size
-		rv.push_back(w->data_dim[0]);//"number of feature maps"
+		unsigned num_data_dim = get_numDataDim();
+		rv.push_back(get_X()->data_dim[0]);//batch size
+		rv.push_back(get_W()->data_dim[0]);//"number of feature maps"
 
-		for( unsigned xdim=2; xdim < x->data_dim.size(); xdim++) {
+		for( unsigned dim=0, xdim=2;
+		     dim < num_data_dim;
+		     dim++, xdim++) {
 			int outdim;
-			unsigned dim = xdim-2;
 			// Not sure if the naming is correct. Here
 			// kernel: the (number of) weights of the filter
 			// filter: the spatial placement of the kernel weights
@@ -118,10 +121,10 @@ class SpatialFilter : public Node {
 			// SAME_UPPER or SAME_LOWER mean pad the input so that the output spatial size match the input.
 			// "match" here means "is equal".
 			if( auto_pad == "SAME_UPPER" || auto_pad == "SAME_LOWER" )
-				outdim = x->data_dim[xdim];
+				outdim = get_X()->data_dim[xdim];
 			else if( auto_pad == "NOTSET" || auto_pad == "VALID") {
 				//padded input
-				int input_size = x->data_dim[xdim] + pads[dim]+pads[dim+num_data_dim];
+				int input_size = get_X()->data_dim[xdim] + pads[dim]+pads[dim+num_data_dim];
 				// [ 0 1 2 3 4 5 6 7 8 9  ]
 				//                |kern=3|
 				// last output=7
@@ -185,10 +188,10 @@ class SpatialFilter : public Node {
 	virtual void print_output_cell_finalize(std::ostream &dst, const std::string &y_idx="") const = 0;
 	void print_loop_with_padding_checks(std::ostream &dst) const
 	{
-		unsigned n_data_dims = x->data_dim.size() -2;
-		unsigned batch_size = x->data_dim[0];
-		unsigned channels = x->data_dim[1];
-		unsigned maps=y->data_dim[1];
+		unsigned n_data_dims = get_numDataDim();
+		unsigned batch_size = get_X()->data_dim[0];
+		unsigned channels = get_X()->data_dim[1];
+		unsigned maps=get_Y()->data_dim[1];
 
 		/* Create various indexing strings. This makes generating the loops much cleaner,
 		 * and makes possible the code sharing in child classes. */
@@ -213,7 +216,7 @@ class SpatialFilter : public Node {
 		}
 		if( direct_channel_map() )
 			INDT_1 << "for( uint32_t m=0, c=0; m<" << maps << "; m++, c=m) {" << std::endl;
-		else if( w && group > 1 ) {
+		else if( get_W() && group > 1 ) {
 			INDT_1 << "uint32_t go = " << maps/group     << "; // output group size, i.e. maps/group" << std::endl;
 			INDT_1 << "uint32_t gi = " << channels/group << "; // inptput group size, i.e. channels/group" << std::endl;
 			INDT_1 << "for( uint32_t g=0; g<" << group << "; g++) {" << std::endl;
@@ -229,7 +232,7 @@ class SpatialFilter : public Node {
 			std::string i_idx = "i" + std::to_string(i);
 			INDT_2 << "for( int32_t " << o_idx << "=0, ";
 			   dst <<       i_idx << "=" << -pads[i] << "; ";
-			   dst <<       o_idx << "<" << y->data_dim[2+i] << "; ";
+			   dst <<       o_idx << "<" << get_Y()->data_dim[2+i] << "; ";
 			   dst <<       o_idx <<"++, "<< i_idx << "+=" << strides[i] << ") {" << std::endl;
 		}
 
@@ -237,7 +240,7 @@ class SpatialFilter : public Node {
 
 		if (direct_channel_map())
 			;
-		else if( w && group > 1 )
+		else if( get_W() && group > 1 )
 			INDT_3 <<   "for( int32_t c=gi*g; c<gi*(g+1); c++ ) {" << std::endl;
 		else    // same as above, just cleaner to read :)
 			INDT_3 <<   "for( int32_t c=0; c<" << channels << "; c++ ) {" << std::endl;
@@ -255,7 +258,7 @@ class SpatialFilter : public Node {
 			std::string i_str = std::to_string(i);
 			INDT_4 <<  "int ii" << i_str << " = i" << i_str << "+k" << i_str <<" * " << dilations[i] <<";" << std::endl;
 			INDT_4 <<  "if( ii" << i_str << "<0) continue;" << std::endl;
-			INDT_4 <<  "if( ii" << i_str << ">=" << x->data_dim[2+i] << ") continue;" << std::endl;
+			INDT_4 <<  "if( ii" << i_str << ">=" << get_X()->data_dim[2+i] << ") continue;" << std::endl;
 		}
 
 		print_output_cell_calc(dst, in_kern_idxs, "", y_idx);