vania-janet/multiturn-rag-retrieval-data huggingface dataset:
Understanding your responsibilities when you use Power Virtual Server for SAP HANA deployable architecture 

Learn about the management responsibilities and terms and conditions that you have when you use the Power Systems Virtual Server for SAP HANA deployable architecture.



*  For more information about the responsibilities for you and for IBM® when you use a deployable architecture, see [Understanding your responsibilities when you use deployable architectures](https://cloud.ibm.com/docs/secure-enterprise?topic=secure-enterprise-responsibilities-deployable-architectures).
*  For a high-level view of the service types in IBM Cloud® and the breakdown of responsibilities between the customer and IBM for each type, see [Shared responsibilities for using IBM Cloud products](https://cloud.ibm.com/docs/overview?topic=overview-shared-responsibilities).
*  For the overall terms of use, see [IBM Cloud® Terms and Notices](https://cloud.ibm.com/docs/overview/terms-of-use?topic=overview-terms).



Review the following section for the specific responsibilities for you and for IBM when you use the Power Systems Virtual Server for SAP HANA deployable architecture.



  Security and regulation compliance 

Security and regulation compliance includes tasks such as security controls implementation and compliance certification.



Table 1. Security and compliance responsibilities for provisioned components

                                                                                IBM Responsibilities                                                                                                                                                                                                                                                                                                     Your Responsibilities                                                                                                                          

 Ensure that the operating system image does not contain any vulnerabilities.   IBM Cloud provided and verified RHEL and SLES operating system images are used. After deployment, operating system images are updated to the newest state in the defined minor release. Official RHEL and SLES software repositories are used for installation of additional software components (like SQUID proxy).     Customer is responsible to keep the operating system secure and compliant after deployment.                                                    
 Ensure that the SAP software does not contain any vulnerabilities.             N/A                                                                                                                                                                                                                                                                                                                      Customer is responsible to provide the SAP software. Customer is responsible to keep the SAP software secure and compliant after deployment.
The choice of implementation depends on the use case - whether you are interested in accessing the probability distribution corresponding to a quantum state (SamplingVQE) or an estimation of the ground state energy which might require, for example, measurements in multiple bases ( VQE).

Let's see the workflow changes for the Estimator-based VQE implementation:



 Step 1: Problem Definition 

The problem definition step is common to the old and new workflow: defining the hamiltonian, ansatz, optimizer and initial point.

The only difference is that the operator definition now relies on qiskit.quantum_info instead of qiskit.opflow . In practice, this means that all PauliSumOp dependencies should be replaced by SparsePauliOp.

All of the refactored classes in qiskit.algorithms now take in operators as instances of SparsePauliOp instead of PauliSumOp.



 The ansatz, optimizer and initial point are defined identically: 

from qiskit.algorithms.optimizers import SLSQP
from qiskit.circuit.library import TwoLocal

 define ansatz and optimizer
num_qubits = 2
ansatz = TwoLocal(num_qubits, "ry", "cz")
optimizer = SLSQP(maxiter=100)

 define initial point
init_pt = [-0.1, -0.1, -0.1, -0.1, -0.1, -0.1, -0.1, -0.1]

 hamiltonian/operator --> use SparsePauliOp or Operator
from qiskit.quantum_info import SparsePauliOp

hamiltonian = SparsePauliOp.from_list(
[
("II", -1.052373245772859),
("IZ", 0.39793742484318045),
("ZI", -0.39793742484318045),
("ZZ", -0.01128010425623538),
It imports the view FirstName, with no module qualifier, to the namespace of the current module, person. The imported view can be accessed only through the alias name PersonFirstName and not through any other form. For example, you cannot refer to the imported view as personName.FirstName because it is imported only through the alias name.

module person;

import view FirstName from module personName as PersonFirstName;

output view PersonFirstName;

Example 3: Importing the view NotFirstname without using alias import

This sample import statement imports the qualified name personName.NotFirstName (not the unqualified name of the view) to the namespace of the current module, person. Always refer to the imported view by using only the qualified name. Any other mode of reference is flagged as compiler error.

module person;

import view NotFirstName from module personName;

output view personName.NotFirstName;







 The import module statement 

You can use the import module statement to import and reuse existing AQL modules.



 Syntax 

import module <module-name>;





 Description 



* <module-name>

Specifies the module to import. The <module-name> must be a simple identifier.







 Usage notes 



* The import statement is only used to import AQL objects from other modules, not from the current module.
* All import statements must follow immediately after the module declaration and must precede all other types of statements. Only those AQL objects that are explicitly exported from any module can be imported in another module. If this requirement is not observed, a compilation error results.
* A compilation error is introduced when an import view statement introduces a naming conflict with any create view or other import statement within the same module (not just within the current file). This restriction applies to the import of other AQL objects in addition to views.
* A compilation error is introduced when an AQL file inside a module tries to reference another exported view of a module without using the import view statement. The same applies to dictionaries, tables, or functions.
JAPANESE TEXT [protoc-gen-validate](https://github.com/bufbuild/protoc-gen-validate/releases/tag/v0.1.0)





 Creative Commons Attribution 2.5 Generic 

The Program includes some or all the following works licensed under the Creative Commons. \n The URL to the license is [https://creativecommons.org/licenses/by-sa/2.5/legalcode](https://creativecommons.org/licenses/by-sa/2.5/legalcode).

CHINESE TEXT [protoc-gen-validate](https://github.com/bufbuild/protoc-gen-validate/releases/tag/v0.1.0)





 Creative Commons Attribution Share Alike 3.0 Generic 

The Program includes some or all the following works licensed under the Creative Commons. \n The URL to the license is [https://creativecommons.org/licenses/by-sa/3.0/legalcode](https://creativecommons.org/licenses/by-sa/3.0/legalcode).

VIETNAMESE TEXT [protoc-gen-validate](https://github.com/bufbuild/protoc-gen-validate/releases/tag/v0.1.0)





 Creative Commons Attribution Share Alike 4.0 Generic 

The Program includes some or all the following works licensed under the Creative Commons. \n The URL to the license is [https://creativecommons.org/licenses/by-sa/4.0/legalcode](https://creativecommons.org/licenses/by-sa/4.0/legalcode).



* HYDRATION [facebook/react](https://github.com/facebook/react/releases)
* DATA.GO [go-openapi/runtime](https://github.com/go-openapi/runtime/releases/tag/v0.19.15)
"jq19q22Sm19Sp22","jq15q18Sp15Sm18","jq15q18Sm15Sp18","jq25q26Sp25Sm26","jq25q26Sm25Sp26","omegad1X0||U0","omegad0X1||U1","omegad4X1||U3","omegad2X1||U2","omegad3X2||U5","omegad1X2||U4","omegad2X3||U6","omegad5X3||U7","omegad7X4||U9","omegad1X4||U8","omegad8X5||U11","omegad3X5||U10","omegad7X6||U12","omegad6X7||U14","omegad4X7||U13","omegad10X7||U15","omegad11X8||U18","omegad5X8||U16","omegad9X8||U17","omegad8X9||U19","omegad7X10||U20","omegad12X10||U21","omegad8X11||U22","omegad14X11||U23","omegad10X12||U24","omegad13X12||U25","omegad15X12||U26","omegad14X13||U28","omegad12X13||U27","omegad16X14||U31","omegad13X14||U30","omegad11X14||U29","omegad18X15||
| - 10:0:0:169 sde 8:64 active ready running
-+- policy='round-robin 0' prio=10 status=enabled
- 9:0:0:169 sdf 8:80 active ready running
…

You can now use the multipath device as you would use any disk device. A device path appears under /dev/mapper/3600a098038303452543f464142755a42.

Take the sample /etc/multipath.conf from the [example multipath.conf](https://cloud.ibm.com/docs/sap?topic=sap-quickstudy-bm-netweaver-rhelsample) and create it on your server. Any copied special characters, DOS-like carriage returns, line-feed entries might lead to unexpected behavior. Make sure that you have an ASCII Unix file after you copy the contents.

Adapt the multipath block from /etc/multipath.conf to create an alias of the path to access the device under 1/dev/mapper/mpath1.

multipaths {
multipath {
wwid 3600a098038303452543f464142755a42
alias mpath1
}
}



1. Restart multipathd. You can now create the /backup file system and mount on the block device.



[root@sdb192 ] service multipathd restart
[root@sdb192 ] mkfs.ext4 /dev/mapper/mpath1
[root@sdb192 ] mkdir /backup



1. Check the file systems on both servers. Your output should be similar to the following output.



[root@e2e1270 ] df -h
Filesystem		 Size Used Avail Use% Mounted on
/dev/sda3 879G 1,5G 833G 1% /
tmpfs 16G 0 16G 0% /dev/shm
/dev/sda1 248M 63M 173M 27% /boot
"map": "function(user) { if(user.email_verified === true) { emit(user.email); } }"
}
}
}

The previous map function generates a secondary index suitable for selection only. The index is always ordered by the key (the emit function's first parameter) - in this case user.email. This view is ideal for fetching documents by a known user email or ranges of users email addresses.





 Built-in reduce functions 

For performance reasons, a few simple reduce functions are built in. Whenever possible, you must use one of these functions instead of writing your own.

To use one of the built-in functions, put the name into the reduce field of the view object in your design document.

{
"views": {
"sumPrices": {
"map": "function(user) { if(user.email_verified === true) { emit(user.name, user.email); } }",
"reduce": "_count"
}
}
}

The previous MapReduce view creates an index that is keyed on the username and whose counts all active email. As the reducer is _count, the view outputs the total email count for the selection of data queried. It is suitable for counting the registered users.

The numeric reducers _stats/_sum act upon the value (the emit function's second parameter) which can be a number, array, or object. Consider the following MapReduce definition on the products partitioned database:

{
"views": {
"statsReadingsObject": {
"map": "function(product) { emit(product.type, { price: product.price, tax: product.tax }); }",
"reduce": "_sum"
}
}
}

The view is keyed on the type of the product, and the value is an object that contains two values: price and tax. The _sum reduce calculates totals for each attribute of the object that it finds:

{"rows":[
[AC-20 - Use of External Information Systems](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20ac-20)



* [Control requirements](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20control-requirements)
* [Additional IBM Cloud for Financial Services specifications](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20additional-ibm-cloud-for-financial-services-specifications)
* [Implementation guidance](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20implementation-guidance)
* [IBM Cloud for Financial Services profile](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20scc-fs-cloud-profile)
* [NIST supplemental guidance](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20nist-supplemental-guidance)



[AC-20 (1) - Limits On Authorized Use](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20.1ac-20.1)



* [Control requirements](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20.1control-requirements)
* [NIST supplemental guidance](https://cloud.ibm.com/docs/framework-financial-services-controls?topic=framework-financial-services-controls-ac-20.1nist-supplemental-guidance)
collect-evidence script 

The collect-evidence script helps adopters, users, and contributors to send their compliance data into the DevSecOps [change Management data flow](https://cloud.ibm.com/docs/devsecops?topic=devsecops-cd-devsecops-automate-changemgmt).

The script does the following tasks:



* Attempts to process any attachments as results, and creates incident issues from those results. A limited number of tool output formats are supported.
* If issues are found, the script evaluates their grace periods (due dates) and exemption states.
* Creates an evidence asset in the evidence locker.
* Creates the [evidence](https://cloud.ibm.com/docs/devsecops?topic=devsecops-devsecops-evidence) itself, and attaches the issues and provided attachments.



For a status of success or failure, if no attachments are passed inside collect-evidence, the pipeline-logs for that particular task and the stage are captured as an attachment.

The collect-evidence script is provided by the pipeline. It does not need to be installed. The script has the following dependencies:



* bash
* libstdc++ shared library
* libgcc shared library



Make sure that the dependencies are installed in the base image that uses this tool for reporting evidence.



 Usage 

The script collect-evidence requires the following parameters:



* --tool-type
The ID of the tool that provides evidence data. For example: "owasp-zap-ui", "cra"
* --evidence-type
The ID of the evidence type. For example: com.ibm.image_vulnerability_scan, com.ibm.unit_tests
* --asset-key
The key in pipelinectl assets. For the following commands load_artifact <key> or load_repo <key>
* --asset-type
The asset type from pipelinectl and can be one of the following types: repo, artifact
* --status
The evidence status and can be one of the following: success, pending, failure
REGULAR_EXPRESSIONS [posix-character-classes](https://en.wikibooks.org/wiki/Regular_Expressions/POSIX_Basic_Regular_Expressions), TEXT IN FOREIGN LANGUAGE [golang/text](https://github.com/golang/text/archive/cbf43d21aaebfdfeb81d91a5f444d13a3046e686.zip), NEP-0012-MISSING-DATA.RST [NumPy](https://github.com/numpy/numpy/blob/master/doc/neps/nep-0012-missing-data.rst), VIETNAMESE TEXT [golang.org/x/text](https://proxy.golang.org/golang.org/x/text/@v/v0.3.3-0.20200430171850-afb9336c4530.zip), RAMDA LOGO [RAMda](http://registry.npmjs.org/ramda/-/ramda-0.27.1.tgz), NEP-0012-MISSING-DATA.RST [NumPy](https://pypi.org/project/numpy/files), DATA LICENSE (GEOLITE COUNTRY AND CITY DATABASES) [geoip](https://github.com/maxmind/geoip-api-c/releases/tag/v1.6.12), NEP12 [NumPy], MAP_TEST.GO [x/text]





 Creative Commons Attribution Share Alike 4.0 Generic 

The Program includes some or all of the following works licensed under the Creative Commons. The URL to the license is [https://creativecommons.org/licenses/by-sa/4.0/legalcode](https://creativecommons.org/licenses/by-sa/4.0/legalcode)
Show more





 Multiple parameterized circuits example 

Run three experiments in a single job, leveraging parameter values to increase circuit reusability. This line job = sampler.run([circuit] * 3, parameter_values) specifies which parameter to send to each circuit.

from qiskit.circuit.library import RealAmplitudes
from qiskit_ibm_runtime import QiskitRuntimeService, Sampler

service = QiskitRuntimeService()

 Run on a simulator
backend = service.get_backend("ibmq_qasm_simulator")
 Use the following line if you want to run on a system instead of a simulator:
 backend = service.least_busy(simulator=False)

circuit = RealAmplitudes(num_qubits=2, reps=2)
circuit.measure_all()
 Define three sets of parameters for the circuit
parameter_values = [
0, 1, 2, 3, 4, 5],
1, 1, 2, 3, 5, 8],
0, 0.1, 0.2, 0.3, 0.4, 0.5],
]

sampler = Sampler(backend)
job = sampler.run([circuit] * 3, parameter_values)
result = job.result()

print(f" > Quasiprobability distribution: {result.quasi_dists}")
Show more





 Sessions and advanced options example 

Explore sessions and advanced options to optimize circuit performance on quantum systems. With Qiskit Runtime primitives, we introduce the concept of a session that allows you to define a job as a collection of iterative calls to the quantum computer. When you start a session, it caches the data you send so it doesn't have to be transmitted to the quantum data center on each iteration. You can create a Runtime session by using the context manager (with ...:), which automatically opens and closes the session for you. See [Sessions](https://cloud.ibm.com/docs/quantum-computing?topic=quantum-computing-sessions) for details.
pipelinectl 

pipelinectl is a lightweight key-value store that you can use in DevSecOps pipelines to share data between tasks and the compliance automation scripts.

For more information about where this tool is used, see [Adding test and build steps to pipelines](https://cloud.ibm.com/docs/devsecops?topic=devsecops-cd-devsecops-add-pipeline-steps).



 Usage 

pipelinectl provides a single binary. Its behavior depends on its name (as in [busybox](https://www.busybox.net/about.html)). When invoked as pipelinectl, the program must be provided as the first argument, for example pipelinectl get_data.

Available aliases and methods:



* [set_env](https://cloud.ibm.com/docs/devsecops?topic=devsecops-devsecops-pipelinectlset_env)
* [get_env](https://cloud.ibm.com/docs/devsecops?topic=devsecops-devsecops-pipelinectlget_env)
* [save_file](https://cloud.ibm.com/docs/devsecops?topic=devsecops-devsecops-pipelinectlsave_file)
* [load_file](https://cloud.ibm.com/docs/devsecops?topic=devsecops-devsecops-pipelinectlload_file)
* [save_repo](https://cloud.ibm.com/docs/devsecops?topic=devsecops-devsecops-pipelinectlsave_repo)
* [list_repos](https://cloud.ibm.com/docs/devsecops?topic=devsecops-devsecops-pipelinectllist_repos)
","type":"control"},"u35":{"operates":{"qubits":[16,19]},"purpose":"cross-resonance","type":"control"},"u36":{"operates":{"qubits":[17,18]},"purpose":"cross-resonance","type":"control"},"u37":{"operates":{"qubits":[18,15]},"purpose":"cross-resonance","type":"control"},"u38":{"operates":{"qubits":[18,17]},"purpose":"cross-resonance","type":"control"},"u39":{"operates":{"qubits":[18,21]},"purpose":"cross-resonance","type":"control"},"u4":{"operates":{"qubits":[2,1]},"purpose":"cross-resonance","type":"control"},"u40":{"operates":{"qubits":[19,16]},"purpose":"cross-resonance","type":"control"},"u41":{"operates":{"qubits":[19,20]},"purpose":"cross-resonance","type":"control"},"u42":{"operates":{"qubits":[19,22]},"purpose":"cross-resonance","type":"control"},"u43":{"operates":{"qubits":[20,19]},"purpose":"cross-resonance","type":"control"},"u44":{"operates":{"qubits"
(https://cloud.ibm.com/docs-content/v1/content/ba89e173287b28d1453d2a327d8a1f74ae2f1662/schematics/images/checkmark.svg) ![Check mark icon.](https://cloud.ibm.com/docs-content/v1/content/ba89e173287b28d1453d2a327d8a1f74ae2f1662/schematics/images/checkmark.svg) ![Check mark icon.](https://cloud.ibm.com/docs-content/v1/content/ba89e173287b28d1453d2a327d8a1f74ae2f1662/schematics/images/checkmark.svg) ![Check mark icon.](https://cloud.ibm.com/docs-content/v1/content/ba89e173287b28d1453d2a327d8a1f74ae2f1662/schematics/images/checkmark.svg) 
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>>> print("quasi_dists: ", quasi_dists)
counts: {'0000': 255, '0001': 258, '0010': 243, '0011': 268}
quasi_dists: {'0000': 0.2490234375, '0001': 0.251953125, '0010': 0.2373046875, '0011': 0.26171875}





 2.b. New: Use the Sampler Runtime primitive 

While the user-side syntax of the Sampler is very similar to backend.run(), notice that the workflow is now simplified, as the quasi-probability distribution is returned directly (no need to perform post-processing), together with some key metadata.

Replace ibmq_qasm_simulator with your device name to see the complete workflow for a real device.

from qiskit_ibm_runtime import QiskitRuntimeService, Sampler

service = QiskitRuntimeService(channel="ibm_quantum")
backend = service.backend("ibmq_qasm_simulator")

sampler = Sampler(session=backend)

result = sampler.run(circuit, shots=1024).result()
quasi_dists = result.quasi_dists

>>> print("result: ", result)
>>> print("quasi_dists: ", quasi_dists)
result: SamplerResult(quasi_dists=[{0: 0.2802734375, 1: 0.2509765625, 2: 0.232421875, 3: 0.236328125}],
metadata=[{'header_metadata': {}, 'shots': 1024, 'readout_mitigation_overhead': 1.0,
'readout_mitigation_time': 0.03801989182829857}])
* [modules.module_type](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-moduletype)
* [modules.source options](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-sourceoptions)
* [modules.source.source_type](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-source-type)
* [modules.source.git.git_repo_url](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-git-repo-url)
* [modules.source.git.git_branch](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-git-branch)
* [modules.source.git.git_release](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-git-release)
* [modules.source.git.git_token](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-git-token)
* [modules.settings](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-settings)
* [modules.inputs options](https://cloud.ibm.com/docs/schematics?topic=schematics-bp-template-schema-yamlbp-modules-inputs-options)
[Available](https://cloud.ibm.com/docs-content/v1/content/11f96f96f8f4b60cf6f3fa4d904856a2c4528bc2/icons/checkmark-icon.svg) ![Available](https://cloud.ibm.com/docs-content/v1/content/11f96f96f8f4b60cf6f3fa4d904856a2c4528bc2/icons/checkmark-icon.svg) 
 vApp: Use Console ![Available](https://cloud.ibm.com/docs-content/v1/content/11f96f96f8f4b60cf6f3fa4d904856a2c4528bc2/icons/checkmark-icon.svg) ![Available](https://cloud.ibm.com/docs-content/v1/content/11f96f96f8f4b60cf6f3fa4d904856a2c4528bc2/icons/checkmark-icon.svg) ![Available](https://cloud.ibm.com/docs-content/v1/content/11f96f96f8f4b60cf6f3fa4d904856a2c4528bc2/icons/checkmark-icon.svg) 
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