build:cuda_clang --copt=-Qunused-arguments
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current

                                    TF_Status* status, TF_Output* dy);

// Adds operations to compute the partial derivatives of sum of `y`s w.r.t `x`s,
// i.e., d(y_1 + y_2 + ...)/dx_1, d(y_1 + y_2 + ...)/dx_2...
// This is a variant of TF_AddGradients that allows to caller to pass a custom
// name prefix to the operations added to a graph to compute the gradients.
//
// `dx` are used as initial gradients (which represent the symbolic partial

      }
    }

    @Override
    @CheckForNull
    public V compute(
        K key,
        BiFunction<? super K, ? super @Nullable V, ? extends @Nullable V> remappingFunction) {
      synchronized (mutex) {
        return delegate().compute(key, remappingFunction);
      }
    }

    @Override
    @CheckForNull
    public V merge(

cel.dev/expr v0.16.0/go.mod h1:TRSuuV7DlVCE/uwv5QbAiW/v8l5O8C4eEPHeu7gf7Sg=
cloud.google.com/go v0.26.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw=
cloud.google.com/go/compute/metadata v0.5.2 h1:UxK4uu/Tn+I3p2dYWTfiX4wva7aYlKixAHn3fyqngqo=
cloud.google.com/go/compute/metadata v0.5.2/go.mod h1:C66sj2AluDcIqakBq/M8lw8/ybHgOZqin2obFxa/E5k=
dario.cat/mergo v1.0.1 h1:Ra4+bf83h2ztPIQYNP99R6m+Y7KfnARDfID+a+vLl4s=

cloud.google.com/go/auth/oauth2adapt v0.2.4/go.mod h1:jC/jOpwFP6JBxhB3P5Rr0a9HLMC/Pe3eaL4NmdvqPtc=
cloud.google.com/go/compute/metadata v0.5.0 h1:Zr0eK8JbFv6+Wi4ilXAR8FJ3wyNdpxHKJNPos6LTZOY=
cloud.google.com/go/compute/metadata v0.5.0/go.mod h1:aHnloV2TPI38yx4s9+wAZhHykWvVCfu7hQbF+9CWoiY=
cloud.google.com/go/iam v1.2.0 h1:kZKMKVNk/IsSSc/udOb83K0hL/Yh/Gcqpz+oAkoIFN8=

        // so we rely on the JDK services to eventually look up a custom RootLocator.
        // This is used to compute {@code session.rootDirectory} but all {@code project.rootDirectory}
        // properties will be computed through the RootLocator found in the container.
        RootLocator rootLocator =
                ServiceLoader.load(RootLocator.class).iterator().next();

				return
			}

			if g.Status == statusDisabled {
				err = errGroupDisabled
				return
			}
		}
		mp, _ = cache.iamGroupPolicyMap.Load(name)
	}

	// Compute net policy change effect and updated policy mapping
	existingPolicySet := mp.policySet()
	policiesToUpdate := set.CreateStringSet(policies...)
	var newPolicySet set.StringSet
	newPolicyMapping := mp
	if isAttach {

class TestUnavailableErrorOp : public tensorflow::OpKernel {
 public:
  explicit TestUnavailableErrorOp(tensorflow::OpKernelConstruction* ctx)
      : tensorflow::OpKernel(ctx) {}
  void Compute(tensorflow::OpKernelContext* ctx) override {
    ctx->SetStatus(tensorflow::errors::Unavailable("Test error."));
  }
};
REGISTER_KERNEL_BUILDER(
    Name("TestNonCommUnavailable").Device(tensorflow::DEVICE_DEFAULT),

Please be aware of them as you test your workloads.

* PVC Volume not detached if pod deleted via namespace deletion ([29051](https://github.com/kubernetes/kubernetes/issues/29051))
* Google Compute Engine PD Detach fails if node no longer exists ([29358](https://github.com/kubernetes/kubernetes/issues/29358))

  TF_DeleteBuffer(op_list_buf);
}

class DummyKernel : public tensorflow::OpKernel {
 public:
  explicit DummyKernel(tensorflow::OpKernelConstruction* context)
      : OpKernel(context) {}
  void Compute(tensorflow::OpKernelContext* context) override {}
};

// Test we can query kernels
REGISTER_OP("TestOpWithSingleKernel")
    .Input("a: float")
    .Input("b: float")
    .Output("o: float");