}
    }
  },
  "info": {
    "title": "Kubernetes",
    "version": "unversioned"
  },
  "openapi": "3.0.0",
  "paths": {
    "/apis/events.k8s.io/v1/": {
      "get": {
        "description": "get available resources",
        "operationId": "getEventsV1APIResources",
        "responses": {
          "200": {
            "content": {
              "application/json": {

server on Linux hosts running 64-bit Intel/AMD architectures. Replace ``/data`` with the path to the drive or directory in which you want MinIO to store data. ```sh wget https://dl.min.io/server/minio/release/linux-amd64/minio chmod +x minio ./minio server /data ``` The following table lists supported architectures. Replace the `wget` URL with the architecture for your Linux host. | Architecture | URL | | -------- | ------ | | 64-bit Intel/AMD | <https://dl.min.io/server/minio/release/linux-amd64/minio>...

// For instance, OpAdd can be 32 or 64 bit, signed or unsigned, float or complex, depending on Value.Type.
// Semantics of each op are described in the opcode files in _gen/*Ops.go.
// There is one file for generic (architecture-independent) ops and one file
// for each architecture.
type Op int32

type opInfo struct {
	name              string
	reg               regInfo

	sget := func() (string, error) {
		kidx := slr.ReadULEB128()
		if int(kidx) >= cdr.stab.Entries() {
			return "", fmt.Errorf("malformed string table ref")
		}
		return cdr.stab.Get(uint32(kidx)), nil
	}
	nents := slr.ReadULEB128()
	cdr.args = make(map[string]string, int(nents))
	for i := uint64(0); i < nents; i++ {
		k, errk := sget()
		if errk != nil {
			return errk
		}

  },
  "info": {
    "title": "Kubernetes",
    "version": "unversioned"
  },
  "openapi": "3.0.0",
  "paths": {
    "/apis/admissionregistration.k8s.io/v1alpha1/": {
      "get": {
        "description": "get available resources",
        "operationId": "getAdmissionregistrationV1alpha1APIResources",
        "responses": {
          "200": {
            "content": {
              "application/json": {

      TypeID::get<TF::AbsOp>(),
      TypeID::get<TF::AtanOp>(),
      TypeID::get<TF::AvgPool3DOp>(),
      TypeID::get<TF::BiasAddGradOp>(),
      TypeID::get<TF::CeilOp>(),
      TypeID::get<TF::CheckNumericsOp>(),
      TypeID::get<TF::CosOp>(),
      TypeID::get<TF::TanOp>(),
      TypeID::get<TF::DiagPartOp>(),
      TypeID::get<TF::EinsumOp>(),
      TypeID::get<TF::ExpOp>(),
      TypeID::get<TF::Expm1Op>(),

      TestScalarTensorHandle(context.get(), 111.f), TFE_DeleteTensorHandle);
  op.reset(TFE_NewOp(context.get(), "AssignVariableOp", status.get()));
  TFE_OpSetAttrType(op.get(), "dtype", TF_FLOAT);
  TFE_OpAddInput(op.get(), var_handle, status.get());
  TFE_OpAddInput(op.get(), one.get(), status.get());
  TFE_OpSetDevice(op.get(), name, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

    assertEquals(Long.valueOf(0), ArbitraryInstances.get(Long.class));
    assertEquals(Float.valueOf(0), ArbitraryInstances.get(float.class));
    assertEquals(Float.valueOf(0), ArbitraryInstances.get(Float.class));
    assertEquals(Double.valueOf(0), ArbitraryInstances.get(double.class));
    assertEquals(Double.valueOf(0), ArbitraryInstances.get(Double.class));

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  TF_OutputListSetNumOutputs(mm_outputs, 1, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TF_ExecuteOperation(fn_op, 1, &input_t, mm_outputs, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

        Multiply(context.get(), combined_value.get(), combined_value.get(),
                 status.get()));
    ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
    std::array<TensorHandlePtr, 2> out_components;
    ExtractPerDeviceValues(context.get(), multiply_result.get(),
                           &out_components, status.get());
    ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());