# How to use DynamicCustomOps objects for their name-sake operations

**URL:** <https://community.konduit.ai/t/how-to-use-dynamiccustomops-objects-for-their-name-sake-operations/1503>\
**Category:** ND4J\
**Created:** [July 16, 2021, 5:01pm UTC](https://community.konduit.ai/t/how-to-use-dynamiccustomops-objects-for-their-name-sake-operations/1503 "2021-07-16T17:01:32Z")\
**Posts on this page:** 6\
**Page:** 1

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**Author:** ![wcneill](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/wcneill/32/559_2.png) [@wcneill](https://community.konduit.ai/u/wcneill)\
**Post date:** [July 16, 2021, 5:01pm UTC](https://community.konduit.ai/t/how-to-use-dynamiccustomops-objects-for-their-name-sake-operations/1503/1 "2021-07-16T17:01:32Z")

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Looking through the docs,I see a lot of names I recognize from NumPy as extensions/implementations of `CustomOp` or `DynamicCustomOp`

These objects don’t have any methods that seem meant for the operations implied by the class names. In fact, I looked at “Direct Known Subclasses” of `DynamicCustomOp` and I see a lot of functionality that I would love to use, but don’t know how to implement.

For example `BinCount()`: [https://deeplearning4j.org/api/latest/org/nd4j/linalg/api/ops/impl/transforms/BinCount.html](https://deeplearning4j.org/api/latest/org/nd4j/linalg/api/ops/impl/transforms/BinCount.html)

What is the methodology for putting these objects to use?

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**Author:** ![agibsonccc](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/agibsonccc/32/697_2.png) [@agibsonccc](https://community.konduit.ai/u/agibsonccc)\
**Post date:** [July 16, 2021, 11:23pm UTC](https://community.konduit.ai/t/how-to-use-dynamiccustomops-objects-for-their-name-sake-operations/1503/2 "2021-07-16T23:23:37Z")

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> [@wcneill](#):
>
> bclasses” of `DynamicCustomOp` and I see a lot of functionality that I would love to use, but don’t know ho

@wcneill you will generally want to access those through samediff if possible, but if there is a c++ op that doesn’t have java bindings, you can access it via DynamicCustomOp.

Nd4j’s ops can be found here:

> <https://github.com/deeplearning4j/deeplearning4j/blob/master/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/resources/nd4j-op-def.pbtxt>

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<div class="post-metadata">

**Author:** ![wcneill](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/wcneill/32/559_2.png) [@wcneill](https://community.konduit.ai/u/wcneill)\
**Post date:** [August 2, 2021, 9:25pm UTC](https://community.konduit.ai/t/how-to-use-dynamiccustomops-objects-for-their-name-sake-operations/1503/3 "2021-08-02T21:25:44Z")

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Is there a code snippet somewhere that I’m not seeing that explains how to use these ops via SameDiff or other?

I’ve been peaking at the SameDiff docs, as well as `linalg.api.ops.custom` which has a lot of familiar names from Numpy but it’s not very clear how to use these objects. For example, the constructor of the `Roll` object looks like the method signature for `np.roll`:

```auto
Roll(@NonNull INDArray input, @NonNull INDArray axes, @NonNull INDArray shifts) 

```

But, I don’t see any methods in the Roll class that actually do the operation. I only see `opName()`, `tensorflowName()` and `calculateOutputDatatypes()`.

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<div class="post-metadata">

**Author:** ![agibsonccc](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/agibsonccc/32/697_2.png) [@agibsonccc](https://community.konduit.ai/u/agibsonccc)\
**Post date:** [August 2, 2021, 10:28pm UTC](https://community.konduit.ai/t/how-to-use-dynamiccustomops-objects-for-their-name-sake-operations/1503/4 "2021-08-02T22:28:35Z")

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@wcneill DynanicCustomOps are a way of accessing underlying c++ ops that may not be already mapped by us. You can see the full list of ops here:  
[https://github.com/eclipse/deeplearning4j/blob/master/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/resources/nd4j-op-def.pbtxt](https://github.com/eclipse/deeplearning4j/blob/master/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/resources/nd4j-op-def.pbtxt)

All you need to know is DyamicCustomOps have addInput(…), addTArgs (add float argument), addIArg(…) which allow you to add arguments that you want to pass to the underlying c++ runtime following the schema above.

Here’s the roll declaration:

```auto
opList {
  name: "roll"
  argDescriptor {
    name: "shift"
    argType: INT64
  }
  argDescriptor {
    name: "outputs"
    argType: OUTPUT_TENSOR
  }
  argDescriptor {
    name: "input"
    argType: INPUT_TENSOR
  }
  argDescriptor {
    name: "shiftsI"
    argType: INPUT_TENSOR
    argIndex: 1
  }
  argDescriptor {
    name: "dimensions"
    argType: INPUT_TENSOR
    argIndex: 2
  }
  opDeclarationType: CONFIGURABLE_OP_IMPL
}

```

These signatures are generated from our code gen tool found in contrib:

> **[deeplearning4j/contrib/codegen-tools/libnd4j-gen at master ·...](https://github.com/eclipse/deeplearning4j/tree/master/contrib/codegen-tools/libnd4j-gen)**
>
> master/contrib/codegen-tools/libnd4j-gen

I generally run this by importing in intellij. There hasn’t been a need to streamline this too much but I would like to eventually get around to tthat.

This is all generated from the c++. Generally dynamic ops allow some parameters to be passed in either via integer arguments or via ndarray arguments. This is to allow flexibility in situations where the dimensions of a computation are themselves a variable in a computation graph rather than static.

Hopefully that clarifies the situation a bit.

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<div class="post-metadata">

**Author:** ![treo](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/treo/32/47_2.png) [@treo](https://community.konduit.ai/u/treo)\
**Post date:** [August 3, 2021, 6:35am UTC](https://community.konduit.ai/t/how-to-use-dynamiccustomops-objects-for-their-name-sake-operations/1503/5 "2021-08-03T06:35:14Z")

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> [@wcneill](#):
>
> What is the methodology for putting these objects to use?

If you just want to run the op directly, you can use `Nd4j.exec(op)`. That will run the op in INDArray mode and give you the results immediately.

If you instead want to use the op in a SameDiff graph, you can use its `op.outputVariable()` method to get a reference to its output.

If you look into the SameDiff namespaces, that is exactly how it is done there:

> <https://github.com/deeplearning4j/deeplearning4j/blob/master/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/autodiff/samediff/ops/SDMath.java#L44-L63>

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<div class="post-metadata">

**Author:** ![wcneill](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/wcneill/32/559_2.png) [@wcneill](https://community.konduit.ai/u/wcneill)\
**Post date:** [August 3, 2021, 1:22pm UTC](https://community.konduit.ai/t/how-to-use-dynamiccustomops-objects-for-their-name-sake-operations/1503/6 "2021-08-03T13:22:22Z")

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> [@treo](#):
>
> If you just want to run the op directly, you can use `Nd4j.exec(op)` . That will run the op in INDArray mode and give you the results immediately.

Thank you, this is exactly what I need.

And thank you also to @agibsonccc that does clarify things a lot and is going to be very useful in the future.