BSD Portsai/py-sagemaker-serve 1.15.0_1 MidnightBSD
SageMaker: Library for training & deploying models on Amazon SageMaker
- System
- MidnightBSD
- Repository
- mports
- Maintainer
- [email protected]
- Port added
- Last update
- Commit
3396e5216c- License
- Apache-2.0
- Categories
- ai, python
Description
sagemaker-train is a part of the SageMaker Python SDK.
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker.
With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. If you have your own algorithms built into SageMaker compatible Docker containers, you can train and host models using these as well.
Version history 1
Upstream's version as each commit to the port's Makefile set it, or as this site first saw it in the system's packages; the tree's own revisions are not versions here.
Install
Binary package:
mport install ${PYTHON_PKGNAMEPREFIX}sagemaker-serveFrom mports:
cd /usr/mports/ai/py-sagemaker-serve && make install cleanTo depend on this port in another port's Makefile:
RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}sagemaker-serve>0:ai/py-sagemaker-serveDependency graph
Ports that need it on the left, what it needs to run on the right; at most 8 of each. "Dependencies" below lists them all.
Dependencies
As this port's Makefile names them.
Build 1
${PYTHON_PKGNAMEPREFIX}wheel>0: devel/py-wheel
Runtime 13
${PYTHON_PKGNAMEPREFIX}boto3>=1.42.2<2.0: www/py-boto3${PYTHON_PKGNAMEPREFIX}botocore>=1.35.75<2.0: devel/py-botocore${PYTHON_PKGNAMEPREFIX}deepdiff>0: devel/py-deepdiff${PYTHON_PKGNAMEPREFIX}mlflow-skinny>0: ai/py-mlflow-skinny${PYTHON_PKGNAMEPREFIX}onnx>0: ai/py-onnx${PYTHON_PKGNAMEPREFIX}psutil>=0: sysutils/py-psutil${PYTHON_PKGNAMEPREFIX}pytest>0: devel/py-pytest${PYTHON_PKGNAMEPREFIX}pytorch>0: ai/py-pytorch${PYTHON_PKGNAMEPREFIX}sagemaker-core>=2.14.0: ai/py-sagemaker-core${PYTHON_PKGNAMEPREFIX}sagemaker-schema-inference-artifacts>=0: ai/py-sagemaker-schema-inference-artifacts${PYTHON_PKGNAMEPREFIX}sagemaker-train>=1.14.0: ai/py-sagemaker-train${PYTHON_PKGNAMEPREFIX}tqdm>0: misc/py-tqdm${PYTHON_PKGNAMEPREFIX}tritonclient>0: ai/py-tritonclient
Build dependencies 1
Run dependencies 13
Required by 2
Configuration
Options name: ai_sagemaker-serve
| Option | Default | Description |
|---|---|---|
| ONNXRUNTIME | off | ONNX Runtime support (currently broken, disable to build) |
- USES
- python
- Service scripts
- none
Files
distinfo 1
| File | Size | SHA256 |
|---|---|---|
| sagemaker_serve-1.15.0.tar.gz | 181215 | 7ab813a54c373bb02ff616209ced0a0d4fc0fae21af51b44824e588c0ee72675 |
Master sites 1
- PYPI
Commit history 2
| Date | Commit | Credits | Log message |
|---|---|---|---|
3396e5216c |
Lucas Holt | www/py-boto3, devel/py-botocore, net/py-s3transfer: update to 1.43.95 / 0.19.2 (#1290) Closes #1270.
The AWS SDK ports were well behind upstream, blocking Python ports that
have picked up a recent `boto3` floor — `ai/py-litellm` had to stop at
1.91.4 because 1.98.0+ requires `boto3>=1.43.1`.
### Updates
| Port | Old | New |
| --- | --- | --- |
| `net/py-s3transfer` | 0.13.0 | 0.19.2 |
| `devel/py-botocore` | 1.38.22 | 1.43.95 |
| `www/py-boto3` | 1.38.22 | 1.43.95 |
These are in one branch because they are mutually unsatisfiable apart:
boto3 1.43.95 requires `botocore>=1.43.95,<1.44.0` and
`s3transfer>=0.19.0,<0.20.0`.
### Changes beyond version/distinfo
- `www/py-boto3`: `RUN_DEPENDS` s3transfer floor 0.13.0 → 0.19.0,
matching upstream.
- `devel/py-botocore`: regenerated `files/patch-setup.py` and
… |
|
b807d69740 |
Lucas Holt | Add LangChain AI ports and dependencies AI-Assisted-by: OpenAI Codex <[email protected]>
Signed-off-by: Lucas Holt <[email protected]> |