{} ## Configure resource requests and limits ## ref: http://kubernetes.io/docs/user-guide/compute-resources/ ## resources: requests: memory: 16Gi ## List of users to be created after minio install ## users: ## Username, password and policy to be assigned to the user ## Default policies are [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## Add new policies as explained here https://docs.min.io/docs/minio-multi-user-quickstart-guide.html ## NOTE: this will fail if LDAP is enabled in your MinIO...

{} ## Configure resource requests and limits ## ref: http://kubernetes.io/docs/user-guide/compute-resources/ ## resources: requests: memory: 16Gi ## List of users to be created after minio install ## users: ## Username, password and policy to be assigned to the user ## Default policies are [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## Add new policies as explained here https://docs.min.io/docs/minio-multi-user-quickstart-guide.html ## NOTE: this will fail if LDAP is enabled in your MinIO...

{} ## Configure resource requests and limits ## ref: http://kubernetes.io/docs/user-guide/compute-resources/ ## resources: requests: memory: 16Gi ## List of users to be created after minio install ## users: ## Username, password and policy to be assigned to the user ## Default policies are [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## Add new policies as explained here https://docs.min.io/docs/minio-multi-user-quickstart-guide.html ## NOTE: this will fail if LDAP is enabled in your MinIO...

{} ## Configure resource requests and limits ## ref: http://kubernetes.io/docs/user-guide/compute-resources/ ## resources: requests: memory: 16Gi ## List of users to be created after minio install ## users: ## Username, password and policy to be assigned to the user ## Default policies are [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## Add new policies as explained here https://docs.min.io/docs/minio-multi-user-quickstart-guide.html ## NOTE: this will fail if LDAP is enabled in your MinIO...

{} ## Configure resource requests and limits ## ref: http://kubernetes.io/docs/user-guide/compute-resources/ ## resources: requests: memory: 16Gi ## List of users to be created after minio install ## users: ## Username, password and policy to be assigned to the user ## Default policies are [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## Add new policies as explained here https://docs.min.io/docs/minio-multi-user-quickstart-guide.html ## NOTE: this will fail if LDAP is enabled in your MinIO...

		return ErrFormat
	}

	return nil
}

func readDataDescriptor(r io.Reader, f *File) error {
	var buf [dataDescriptorLen]byte
	// The spec says: "Although not originally assigned a
	// signature, the value 0x08074b50 has commonly been adopted
	// as a signature value for the data descriptor record.
	// Implementers should be aware that ZIP files may be

        assertTrue(cancellationSuccess.get());
        // cancellation can interleave in 3 ways
        // 1. prior to setFuture
        // 2. after setFuture before set() on the future assigned
        // 3. after setFuture and set() are called but before the listener completes.
        if (!setFutureSetSuccess.get() || !setFutureCompletionSuccess.get()) {

        repository, which adds uniqueVersion property to usual repositories for download.</description>
      <fields>
        <field>
          <name>uniqueVersion</name>
          <description>Whether to assign snapshots a unique version comprised of the timestamp and
            build number, or to use the same version each time</description>
          <type>boolean</type>
          <defaultValue>true</defaultValue>

        [guide on input distribution](https://www.tensorflow.org/tutorials/distribute/input).
*   Allow var.assign on MirroredVariables with aggregation=NONE in replica
    context. Previously this would raise an error. We now allow this because
    many users and library writers find using `.assign` in replica context to be
    more convenient, instead of having to use `Strategy.extended.update` which

    std::unique_ptr<CSession> expected_csession(
        new CSession(expected_graph_, s_));

    std::vector<TF_Output> grad_outputs_vec;
    grad_outputs_vec.assign(grad_outputs, grad_outputs + 2);
    csession->SetOutputs(grad_outputs_vec);
    csession->Run(s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
    TF_Tensor* out0 = csession->output_tensor(0);