mirror of
https://github.com/shivammehta25/Matcha-TTS.git
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updating readme
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17
README.md
17
README.md
@@ -154,7 +154,13 @@ or
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python matcha/train.py experiment=ljspeech
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```
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for multi-gpu training, run
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- for a minimum memory run
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```bash
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python matcha/train.py experiment=ljspeech_min_memory
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```
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- for multi-gpu training, run
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```bash
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python matcha/train.py experiment=ljspeech trainer.devices=[0,1]
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@@ -162,10 +168,11 @@ python matcha/train.py experiment=ljspeech trainer.devices=[0,1]
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## Acknowledgements
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Since this code uses: [Lightning-Hydra-Template](https://github.com/ashleve/lightning-hydra-template), you have all the powers attached to it.
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Since this code uses: [Lightning-Hydra-Template](https://github.com/ashleve/lightning-hydra-template), you have all the powers that comes with it.
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Other source codes I would like to acknowledge:
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- [Coqui-TTS](https://github.com/coqui-ai/TTS/tree/dev)
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- [Grad-TTS](https://github.com/huawei-noah/Speech-Backbones/tree/main/Grad-TTS)
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- [torchdyn](https://github.com/DiffEqML/torchdyn)
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- [Coqui-TTS](https://github.com/coqui-ai/TTS/tree/dev) : For helping me figure out how to make cython binaries pip installable
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- [Grad-TTS](https://github.com/huawei-noah/Speech-Backbones/tree/main/Grad-TTS): For source code of MAS
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- [torchdyn](https://github.com/DiffEqML/torchdyn): Useful for trying other ODE solvers during development
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- [labml.ai](https://nn.labml.ai/transformers/rope/index.html): For RoPE implementation
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3
setup.py
3
setup.py
@@ -2,7 +2,6 @@
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import os
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import numpy
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import pkg_resources
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from Cython.Build import cythonize
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from setuptools import Extension, find_packages, setup
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@@ -22,7 +21,7 @@ setup(
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url="https://shivammehta25.github.io/Matcha-TTS",
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install_requires=[
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str(r)
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for r in pkg_resources.parse_requirements(open(os.path.join(os.path.dirname(__file__), "requirements.txt")))
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for r in open(os.path.join(os.path.dirname(__file__), "requirements.txt"))
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],
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include_dirs=[numpy.get_include()],
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packages=find_packages(exclude=["tests", "tests/*", "examples", "examples/*"]),
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