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"---\n",
"title: \"Modos de ejecución utilizando la API REST\"\n",
"description: \"Cómo ejecutar un trabajo de computación cuántica en una sesión del Servicio de Computación de IBM Quantum.\"\n",
"---\n",
"\n",
"\n",
"\n",
"# Modos de ejecución utilizando la API REST\n",
"\n"
]
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"{/*\n",
" DO NOT EDIT THIS CELL!!!\n",
" This cell's content is generated automatically by a script. Anything you add\n",
" here will be removed next time the notebook is run. To add new content, create\n",
" a new cell before or after this one.\n",
" */}\n",
"\n",
"\n",
" Versiones del paquete
\n",
"\n",
" El código de esta página se ha desarrollado teniendo en cuenta los siguientes requisitos.\n",
" Recomendamos utilizar estas versiones o posteriores.\n",
"\n",
" ```\n",
" qiskit[all]~=2.3.0\n",
" ```\n",
" \n",
"\n"
]
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"Puedes ejecutar tus cargas de trabajo básicas de « IBM Quantum » mediante las API REST en uno de los tres modos de ejecución, según tus necesidades: trabajo, sesión y lote. En este apartado se explican dichos modos.\n",
"\n",
"\n",
" Esta documentación utiliza el módulo `requests` Python para mostrar el funcionamiento de la API REST del servicio de computación de IBM Quantum. No obstante, este flujo de trabajo se puede ejecutar utilizando cualquier lenguaje o marco de trabajo que permita trabajar con API REST. Consulta la [documentación de referencia](/docs/api/qiskit-ibm-runtime/tags/jobs) de la API para obtener más detalles.\n",
"\n",
"\n",
"\n",
"\n",
"## Modo de trabajo con API REST\n",
"\n",
"En el modo de trabajo, se realiza una única solicitud básica a Estimator o Sampler sin un gestor de contexto. Consulte cómo ejecutar un circuito cuántico utilizando [Estimator](/docs/guides/estimator-rest-api) y [Sampler](/docs/guides/sampler-rest-api) para ver algunos ejemplos.\n",
"\n",
"\n",
"\n",
"## Modo de sesión con API REST\n",
"\n",
"Una sesión es una función que permite ejecutar de forma eficiente cargas de trabajo iterativas con múltiples tareas en ordenadores cuánticos. El uso de sesiones ayuda a evitar los retrasos provocados por la puesta en cola de cada trabajo por separado, lo que puede resultar especialmente útil para tareas iterativas que requieren una comunicación frecuente entre los recursos clásicos y cuánticos. En la [documentación](/docs/guides/execution-modes) se puede encontrar más información sobre las sesiones.\n",
"\n",
"\n",
" Los usuarios de Open Plan no pueden enviar trabajos de sesión.\n",
"\n",
"\n",
"\n",
"\n",
"### Iniciar una sesión\n",
"\n",
"Comience por crear una sesión y obtener un ID de sesión.\n",
"\n",
"```python\n",
"import json\n",
"import requests\n",
"\n",
"sessionsUrl = \"https://quantum.cloud.ibm.com/api/v1/sessions\"\n",
"auth_id = \"Bearer \"\n",
"backend = \"\"\n",
"crn = \"\"\n",
"\n",
"headersList = {\n",
" \"Accept\": \"application/json\",\n",
" \"Content-Type\": \"application/json\",\n",
" \"Authorization\": auth_id,\n",
" \"Service-CRN\": crn\n",
"}\n",
"\n",
"payload = json.dumps({\n",
" \"backend\": backend,\n",
" \"mode\": 'dedicated',\n",
"})\n",
"\n",
"response = requests.request(\"POST\", sessionsUrl, data=payload, headers=headersList)\n",
"\n",
"sessionId = response.json()['id']\n",
"\n",
"print(response.json())\n",
"```\n",
"\n",
"Resultado\n",
"\n",
"```text\n",
"{'id': 'crw9s7cdbt40008jxesg'}\n",
"```\n",
"\n",
"\n",
"\n",
"### Cerrar sesión\n",
"\n",
"Es una buena práctica cerrar `Session` cuando todos los trabajos estén terminados. Esto reducirá el tiempo de espera para los usuarios posteriores.\n",
"\n",
"```python\n",
"closureURL=\"https://quantum.cloud.ibm.com/api/v1/sessions/\"+sessionId+\"/close\"\n",
"\n",
"headersList = {\n",
" \"Accept\": \"application/json\",\n",
" \"Authorization\": auth_id,\n",
" \"Service-CRN\": crn\n",
"}\n",
"\n",
"closure_response = requests.request(\n",
" \"DELETE\",\n",
" closureURL,\n",
" headers=headersList\n",
" )\n",
"\n",
"print(\"Session closure response ok?:\",closure_response.ok,closure_response.text)\n",
"```\n",
"\n",
"Resultado\n",
"\n",
"```text\n",
"Session closure response ok?: True\n",
"```\n",
"\n",
"\n",
"\n",
"## Modo por lotes con API REST\n",
"\n",
"También puedes enviar un trabajo por lotes especificando el `mode` en la carga útil de la solicitud. El modo por lotes puede ayudar a reducir el tiempo de procesamiento si todos los trabajos se pueden proporcionar desde el principio. Obtén más información sobre el modo por lotes en la guía [de introducción a los modos de ejecución](/docs/guides/execution-modes#batch-mode).\n",
"\n",
"```python\n",
"import json\n",
"import requests\n",
"\n",
"sessionsUrl = \"https://quantum.cloud.ibm.com/api/v1/sessions\"\n",
"\n",
"headersList = {\n",
" \"Accept\": \"application/json\",\n",
" \"Authorization\": auth_id,\n",
" \"Service-CRN\": crn,\n",
" 'Content-Type': 'application/json'\n",
"}\n",
"\n",
"payload = json.dumps({\n",
" \"backend\": backend,\n",
" \"instance\": \"hub1/group1/project1\",\n",
" \"mode\": \"batch\"\n",
"})\n",
"\n",
"response = requests.request(\"POST\", sessionsUrl, data=payload, headers=headersList)\n",
"\n",
"sessionId = response.json()['id']\n",
"```\n",
"\n",
"\n",
"\n",
"## Ejemplos de trabajos enviados en una sesión\n",
"\n",
"Una vez configurada una sesión, pueden enviarse a la misma uno o varios trabajos del Muestreador o del Estimador especificando el ID de sesión.\n",
"\n",
"\n",
" `` en `PUB` puede ser un único parámetro o una lista de parámetros. También admite la emisión `numpy` .\n",
"\n",
"\n",
"\n",
"\n",
"### Trabajos de estimación en modo sesión\n",
"\n",
"\n",
" \n",
" ```python\n",
" job_input = {\n",
" 'program_id': 'estimator',\n",
" \"backend\": backend,\n",
" \"session_id\": sessionId, # This specifies the previously created Session\n",
" \"params\": {\n",
" \"pubs\": [[resulting_qasm, [obs1, obs2, obs3, obs4]]], #primitive unified blocs (PUBs) containing one circuit each.\n",
" \"options\":{\n",
" \"transpilation\":{\"optimization_level\": 1},\n",
" \"twirling\": {\"enable_gates\": True,\"enable_measure\": True},\n",
" # \"dynamical_decoupling\": {\"enable\": True, \"sequence_type\": \"XpXm\"}, #(optional)\n",
" },\n",
" }\n",
"\n",
" }\n",
" ```\n",
" \n",
"\n",
" \n",
" ```python\n",
" job_input = {\n",
" 'program_id': 'estimator',\n",
" \"backend\": backend,\n",
" \"session_id\": sessionId, # This specifies the previously created Session\n",
" \"params\": {\n",
" \"pubs\": [[resulting_qasm, [[obs1], [obs2], [obs3], [obs4]], [[vals1], [vals2]]]], #primitive unified blocs (PUBs) containing one circuit each\n",
" \"options\":{\n",
" \"transpilation\":{\"optimization_level\": 1},\n",
" \"twirling\": {\"enable_gates\": True,\"enable_measure\": True},\n",
" # \"dynamical_decoupling\": {\"enable\": True, \"sequence_type\": \"XpXm\"}, #(optional)\n",
" },\n",
" }\n",
" }\n",
" ```\n",
" \n",
"\n",
" \n",
" ```python\n",
" job_input = {\n",
" 'program_id': 'estimator',\n",
" \"backend\": backend,\n",
" \"session_id\": sessionId, # This specifies the previously created Session\n",
" \"params\": {\n",
" \"pubs\": [[resulting_qasm, obs1],[resulting_qasm, obs2]], #primitive unified blocs (PUBs) containing one circuit each\n",
" \"options\":{\n",
" \"transpilation\":{\"optimization_level\": 1},\n",
" \"twirling\": {\"enable_gates\": True,\"enable_measure\": True},\n",
" # \"dynamical_decoupling\": {\"enable\": True, \"sequence_type\": \"XpXm\"}, #(optional)\n",
" },\n",
" }\n",
" }\n",
" ```\n",
" \n",
"\n",
"\n",
"\n",
"\n",
"### Trabajos de muestreo en modo sesión\n",
"\n",
"\n",
" \n",
" ```python\n",
" job_input = {\n",
" 'program_id': 'sampler',\n",
" \"backend\": backend,\n",
" \"session_id\": sessionId, # This specifies the previously created Session\n",
" \"params\": {\n",
" \"pubs\": [[resulting_qasm]], #primitive unified blocs (PUBs) containing one circuit each\n",
" \"options\":{\n",
" \"transpilation\":{\"optimization_level\": 1},\n",
" \"twirling\": {\"enable_gates\": True,\"enable_measure\": True},\n",
" # \"dynamical_decoupling\": {\"enable\": True, \"sequence_type\": \"XpXm\"}, #(optional)\n",
" },\n",
" }\n",
"\n",
" }\n",
" ```\n",
" \n",
"\n",
" \n",
" ```python\n",
" job_input = {\n",
" 'program_id': 'sampler',\n",
" \"backend\": backend,\n",
" \"session_id\": sessionId, # This specifies the previously created Session\n",
" \"params\": {\n",
" \"pubs\": [[resulting_qasm, [vals1, vals2, vals3]]], #primitive unified blocs (PUBs) containing one circuit each\n",
" \"options\":{\n",
" \"transpilation\":{\"optimization_level\": 1},\n",
" \"twirling\": {\"enable_gates\": True,\"enable_measure\": True},\n",
" # \"dynamical_decoupling\": {\"enable\": True, \"sequence_type\": \"XpXm\"}, #(optional)\n",
" },\n",
" }\n",
" }\n",
" ```\n",
" \n",
"\n",
" \n",
" ```python\n",
" job_input = {\n",
" 'program_id': 'sampler',\n",
" \"backend\": backend,\n",
" \"session_id\": sessionId, # This specifies the previously created Session\n",
" \"params\": {\n",
" \"pubs\": [[resulting_qasm, [val1]],[resulting_qasm,None,100]], #primitive unified blocs (PUBs) containing one circuit each\n",
" \"options\":{\n",
" \"transpilation\":{\"optimization_level\": 1},\n",
" \"twirling\": {\"enable_gates\": True,\"enable_measure\": True},\n",
" # \"dynamical_decoupling\": {\"enable\": True, \"sequence_type\": \"XpXm\"}, #(optional)\n",
" },\n",
" }\n",
" }\n",
" ```\n",
" \n",
"\n",
"\n",
"\n",
"\n",
"## Próximos pasos\n",
"\n",
"\n",
" * Consulte ejemplos detallados de primitivas [de Sampler](/docs/guides/sampler-rest-api) mediante la API REST.\n",
" * Consulte ejemplos detallados de primitivas [de Estimator](/docs/guides/estimator-rest-api) mediante la API REST.\n",
" * Practique con las primitivas trabajando en la [lección sobre la función de coste](/learning/courses/variational-algorithm-design/cost-functions) en IBM Quantum® Learning.\n",
" * Descubre cómo realizar la transpilación de forma local en la sección «[Transpilación](/docs/guides/transpile) ».\n",
"\n",
"\n"
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