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Managing Tensor One Resources via Python SDK

The Tensor One Python SDK provides comprehensive functions to dynamically manage platform resources including endpoints, templates, and GPU allocations.

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Get Endpoints

Retrieve all available endpoint configurations: 
import tensorone
import os

tensorone.api_key = os.getenv("TENSORONE_API_KEY")

# Fetch all endpoints
endpoints = tensorone.get_endpoints()
print(endpoints)

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Create a Template

Create a reusable template by specifying name and Docker image: 
import tensorone
import os

tensorone.api_key = os.getenv("TENSORONE_API_KEY")

try:
    new_template = tensorone.create_template(
        name="test",
        image_name="tensorone/base:0.1.0"
    )
    print(new_template)

except tensorone.error.QueryError as err:
    print(err)
    print(err.query)

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Create an Endpoint

Create a serverless endpoint using custom template and GPU configuration: 
import tensorone
import os

tensorone.api_key = os.getenv("TENSORONE_API_KEY")

try:
    # Create a serverless template
    new_template = tensorone.create_template(
        name="test",
        image_name="tensorone/base:0.4.4",
        is_serverless=True
    )
    print(new_template)

    # Create an endpoint using the template
    new_endpoint = tensorone.create_endpoint(
        name="test",
        template_id=new_template["id"],
        gpu_ids="AMPERE_16",
        workers_min=0,
        workers_max=1,
    )
    print(new_endpoint)

except tensorone.error.QueryError as err:
    print(err)
    print(err.query)

​
Get Available GPUs

List all GPUs available for allocation: 
import tensorone
import json
import os

tensorone.api_key = os.getenv("TENSORONE_API_KEY")

gpus = tensorone.get_gpus()
print(json.dumps(gpus, indent=2))

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Get GPU by ID

Fetch detailed information about a specific GPU: 
import tensorone
import json
import os

tensorone.api_key = os.getenv("TENSORONE_API_KEY")

gpu = tensorone.get_gpu("NVIDIA A100 80GB PCIe")
print(json.dumps(gpu, indent=2))
These SDK utilities enable efficient management and scaling of compute infrastructure for serverless, GPU-intensive, and custom container workloads within Tensor One.