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

 * }
 * }
 *
 * <p>would be flagged as having called {@code sqrt()} with an illegal argument.
 *
 * <h3>Performance</h3>
 *
 * <p>Avoid passing message arguments that are expensive to compute; your code will always compute
 * them, even though they usually won't be needed. If you have such arguments, use the conventional
 * if/throw idiom instead.
 *

cloud.google.com/go/auth/oauth2adapt v0.2.8/go.mod h1:XQ9y31RkqZCcwJWNSx2Xvric3RrU88hAYYbjDWYDL+c=
cloud.google.com/go/compute/metadata v0.6.0 h1:A6hENjEsCDtC1k8byVsgwvVcioamEHvZ4j01OwKxG9I=
cloud.google.com/go/compute/metadata v0.6.0/go.mod h1:FjyFAW1MW0C203CEOMDTu3Dk1FlqW3Rga40jzHL4hfg=
cloud.google.com/go/iam v1.5.2 h1:qgFRAGEmd8z6dJ/qyEchAuL9jpswyODjA2lS+w234g8=

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");

				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 {

		Description:    "The provided 'x-amz-content-sha256' header does not match what was computed.",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrContentChecksumMismatch: {
		Code:           "XAmzContentChecksumMismatch",
		Description:    "The provided 'x-amz-checksum' header does not match what was computed.",
		HTTPStatusCode: http.StatusBadRequest,
	},

	// MinIO extensions.
	ErrStorageFull: {

  Supplier<? extends StatsCounter> getStatsCounterSupplier() {
    return statsCounterSupplier;
  }

  /**
   * Builds a cache, which either returns an already-loaded value for a given key or atomically
   * computes or retrieves it using the supplied {@code CacheLoader}. If another thread is currently
   * loading the value for this key, simply waits for that thread to finish and returns its loaded

  }

  public void testInvalidateDuringLoading() throws InterruptedException, ExecutionException {
    // computation starts; invalidate() is called on the key being computed, computation finishes
    CountDownLatch computationStarted = new CountDownLatch(2);
    CountDownLatch letGetFinishSignal = new CountDownLatch(1);
    CountDownLatch getFinishedSignal = new CountDownLatch(2);