Simplified APIs for onnxruntime
Project description
onnxruntime-easy
Simplified APIs for onnxruntime
Usage
import onnxruntime_easy as ort
import numpy as np
model = ort.load("model.onnx", device="cpu")
input = np.random.rand(1, 3, 299, 299).astype(np.float32)
output = model(input)
import torch
input_tensor = torch.rand(1, 3, 299, 299)
output = model(input)
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file onnxruntime_easy-0.0.1.tar.gz.
File metadata
- Download URL: onnxruntime_easy-0.0.1.tar.gz
- Upload date:
- Size: 5.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4add6247730679b9d9c276c37240d796a57ffa8b48a24a43921c0111b472873a
|
|
| MD5 |
6b04b6c3efa4493ca4a49f86f63ec159
|
|
| BLAKE2b-256 |
011cdc2f6f8c743791e34ae82fa5f36a53b629e0789a8cc2ca3a2d78d578a62d
|
File details
Details for the file onnxruntime_easy-0.0.1-py3-none-any.whl.
File metadata
- Download URL: onnxruntime_easy-0.0.1-py3-none-any.whl
- Upload date:
- Size: 5.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b811a02d09b86ca0f2235518de10d4136ebbb9e5f11b8fa6aef1a4d7856133a7
|
|
| MD5 |
2b57f6c7ccff6502c646bd370b02077a
|
|
| BLAKE2b-256 |
51c08dea381e602ba82c19d8eabb4949c81bc29b30bd13c293c7b5d8173adaff
|
