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在执行训练命令时报错了。
命令:!python3.8 finetune_speaker_v2.py -m "./OUTPUT_MODEL" --max_epochs 1000 --drop_speaker_embed True
报错日志:
`INFO:OUTPUT_MODEL:{'train': {'log_interval': 10, 'eval_interval': 100, 'se…
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I have been trying to run the benchmarks on my 2019 (Intel) Macbook and this particular benchmark + framework combination seems broken on that machine. I get the following error (truncated; [full erro…
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scipy
numpy
statsmodels
scikit-learn
dask (include dataframe)
pandas
blosc?
To consider:
numba
blaze
sympy
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https://github.com/symengine/symengine.py
Looks easily adaptable. Some features are missing, but this probably is not a roadblocker. A lot of sympy's features is not used anyways. I propose definin…
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I am evaluating a big sympy generated expression to solve and ODE. I have been able to accelerate it by applying numba.jit to the lambdified expression. However, as the the compilation of the expressi…
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I had a really big SymPy expression which I lambdified using the 'numpy' option. The resulting function was called by an ode solver. As the function was very slow, I was looking for alternatives; fina…
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I would like something like the following to work:
``` python
import sympy
sympy.init_session()
f = -t + y*x
d = {x: lambda : param[0], y:lambda : param[1], t:lambda:param[2]}
param = sympy.Symbol('p…
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If numba is installed, we should `@jit(nopython=True, fastmath=True)` compile the model when we lambdify them. This should of course be optional. If numba is not installed everything should work out o…
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I am evaluating a big sympy generated expression to solve and ODE. I have been able to accelerate it by applying numba.jit to the lambdified expression. However, as the the compilation of the expressi…