NumPy

NumPy is an open source library for the Python programming language, adding support for large, multidimensional arrays, and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
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Array.reshape
"only allows for reshapings that collapse or merge dimensions" (xref dask/dask#2561). However, when you try to do one of these unsupported reshapings, the error message Shapes not compatible
does not make it at all clear that what you're asking for just isn't supported by dask. Instead, it sounds as though your inputs are invalid.
A more descriptive e
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I see comments suggesting adding this to understand how loops are being handled by numba, and in the their own FAQ (https://numba.pydata.org/numba-doc/latest/user/faq.html)
from llvmlite import binding as llvm
llvm.set_option('','--debug-only=loop-vectorize')
You would then create your njit function and run it, and I believe the idea is that it prints debug information about whether
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Bidirectional RNN
Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?
Description
https://numpy.org/doc/stable/reference/generated/numpy.corrcoef.html
https://docs.cupy.dev/en/stable/reference/generated/cupy.corrcoef.html
Seems args are different
Additional Information
dtype
argument added in NumPy version 1.20.
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环境
1.系统环境:
2.MegEngine版本:1.6.0rc1
3.python版本:Python 3.8.10
The program stuck at net.load when I was trying to use the MegFlow. I wait for more than 10min and there is no sign of finishing it.
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Wondering if this already exists? If not happy to create if valuable.
I'm looking for a mapping from the column names outputted, to the actual technical indicator it represents.
examples:
momentum_ao == "Momentum, Awesome Oscilator"
momentum_kama == "Momentum, Kaufman’s Adaptive Moving Average (KAMA)"
Can help quickly grasp what the features represent without having to refer back to do
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pydata/xarray#5865 (reply in thread)
I wonder if it's possible to implement a built-in function like:
da.str.format("%.2f")
or xr.string_format(da, "%.2f)
To wrap:
import xarray as xr
da = xr.DataArray([5., 6., 7.])
das = xr.DataArray("%.2f")
das.str % da
<xarray.DataArray (dim_0: 3)>
array(['5.00', '6.00', '7.00'], dtype='<U4')
Dim
Created by Travis Oliphant
Latest release 12 days ago
- Repository
- numpy/numpy
- Website
- numpy.org
- Wikipedia
- Wikipedia
After the revert of pytorch/pytorch@7cf9b94 we've identified a need to add a lint that checks file names to ensure that they're compatible with Windows machines.
Observed error: (from example commit)
A simple check on chang