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0.1.1
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com.unity.ml-agents_1.0.0
com.unity.ml-agents_1.0.2
com.unity.ml-agents_1.0.3
com.unity.ml-agents_1.0.4
com.unity.ml-agents_1.0.5
com.unity.ml-agents_1.0.6
com.unity.ml-agents_1.0.7
com.unity.ml-agents_1.0.8
com.unity.ml-agents_1.1.0
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com.unity.ml-agents_1.3.0
com.unity.ml-agents_1.4.0
com.unity.ml-agents_1.5.0
com.unity.ml-agents_1.6.0
com.unity.ml-agents_1.7.0
com.unity.ml-agents_1.7.2
com.unity.ml-agents_1.8.0
com.unity.ml-agents_1.8.1
com.unity.ml-agents_1.9.0
com.unity.ml-agents_1.9.1
com.unity.ml-agents_2.0.0
com.unity.ml-agents_2.1.0
latest_release
python-packages_0.16.0
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v0.1
5 次代码提交 (36ed3c16-ee11-421b-b3a7-c2b5af3cd81d)
| 作者 | SHA1 | 备注 | 提交日期 |
|---|---|---|---|
Vincent-Pierre BERGES
|
4a6ae4e0 |
Barracuda integration into ML-Agents (#1557)
* Switched default Mac GFX API to Metal * Added Barracuda pre-0.1.5 * Added basic integration with Barracuda Inference Engine * Use predefined outputs the same way as for TF engine * Fixed discrete action + LSTM support * Switch Unity Mac Editor to Metal GFX API * Fixed null model handling * All examples converted to support Barracuda * Added model conversion from Tensorflow to Barracuda copied the barracuda.py file to ml-agents/mlagents/trainers copied the tensorflow_to_barracuda.py file to ml-agents/mlagents/trainers modified the tensorflow_to_barracuda.py file so it could be called from mlagents modified ml-agents/mlagents/trainers/policy.py to convert the tf models to barracuda compatible .bytes file * Added missing iOS BLAS plugin * Added forgotten prefab changes * Removed GLCore GFX backend for Mac, because it doesn't support Compute shaders * Exposed GPU support for LearningBrain inference ... |
6 年前 |
Mantas Puida
|
27567062 | First stage of ML Agents update to Barracuda 0.2.x | 5 年前 |
|
Mantas Puida
|
8a5d17da | Upgraded to Barracuda 0.2.1, fixes issues with discrete action models | 5 年前 |
|
Mantas Puida
|
5566f8a8 | Added Barracuda 0.2.2 | 5 年前 |
Ervin T
|
9ea7fea8 |
Use Barracuda tensors and Barracuda 0.2.4 (#2308)
Bringing bucket of temp memory allocation optimizations: * switched to Barracuda backed tensor across the board, helps to leverage allocators and reuse of the internal buffers * added Barracuda 0.2.4 release, which bring another set of temp memory allocation fixes |
5 年前 |