++++
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        <span class="badge-text">Take courses on DPE University&nbsp;&nbsp;&nbsp;&gt;</span>
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++++

== For Software Developers

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++++

Build engineers that are ready to configure custom build logic and write their own plugins should start here.

const (
	_ traceEv = 127 + iota

	// Experimental events for ExperimentAllocFree.

	// Experimental heap span events. IDs map reversibly to base addresses.
	traceEvSpan      // heap span exists [timestamp, id, npages, type/class]
	traceEvSpanAlloc // heap span alloc [timestamp, id, npages, type/class]
	traceEvSpanFree  // heap span free [timestamp, id]

	// Experimental heap object events. IDs map reversibly to addresses.

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    TF_DeleteTensor(numerical_tensor);
    delete[] danalytical;
    delete[] dnumerical;
    outputs[i]->Unref();
  }
}

void CheckTensorValue(AbstractTensorHandle* t, absl::Span<const float> manuals,
                      absl::Span<const int64_t> dims, double abs_error) {
  TF_Tensor* analytical_tensor;
  auto s = GetValue(t, &analytical_tensor);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

  int num_retvals = 1;
  return op_ptr->Execute(absl::MakeSpan(product, 1), &num_retvals);
}

// Op: IdentityN()
// Summary:
//
// Description:
Status IdentityN(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> input, absl::Span<AbstractTensorHandle*> output, const char* name, const char* raw_device_name) {
  AbstractOperationPtr op_ptr(ctx->CreateOperation());
  TF_RETURN_IF_ERROR(op_ptr->Reset("IdentityN", raw_device_name));

    LogLevel getLogLevel();

    @Override
    List<? extends Span> getSpans();

    @UsedByScanPlugin("Non-internal replacement available since Gradle 7.4")
    @Deprecated
    @SuppressWarnings("DeprecatedIsStillUsed")
    interface Span extends org.gradle.internal.operations.logging.StyledTextBuildOperationProgressDetails.Span {
    }

Status ReluModel(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> inputs,
                 absl::Span<AbstractTensorHandle*> outputs) {
  return ops::Relu(ctx, inputs[0], &outputs[0], "Relu");
}

Status SparseSoftmaxCrossEntropyWithLogitsModel(
    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
    absl::Span<AbstractTensorHandle*> outputs) {
  AbstractTensorHandle* loss;

		return fmt.Errorf("PrepareObjectForStorage failed: %v", err)
	}
	span.AddEvent("About to Encode")
	data, err := runtime.Encode(s.codec, obj)
	if err != nil {
		span.AddEvent("Encode failed", attribute.Int("len", len(data)), attribute.String("err", err.Error()))
		return err
	}
	span.AddEvent("Encode succeeded", attribute.Int("len", len(data)))

	opts, err := s.ttlOpts(ctx, int64(ttl))

					Addresses: []string{"1.2.3.4"},
					Hosts:     []string{"a.example.com", "b.example.com"},
					Ports: []*networking.ServicePort{{
						Number: 80,
						Name:   "http",
					}},
					SubjectAltNames: []string{"san1"},
					Resolution:      networking.ServiceEntry_DNS,
				},
			},
			result: []*workloadapi.Service{
				{
					Name:      "name",
					Namespace: "ns",
					Hostname:  "a.example.com",