转成了numpy之后,在用torch.jit.trace跟踪模型时,该值就会变成一个常量prim::Constant,如果没有转,会通过prim::GetAttr来获取变量。 没有转numpy 转了numpy之后 会有这样的一句提示 TracerWarning: Converting a tensor to a NumPy array might cause the trace to be incorrect. We can't record the data flow...
=4:raiseValueError("Length of filter must be 4(corner frequencies)")ifnotcheck_array_order(pre_filt, order="ascending"):raiseValueError("Frequency band should be in ascending order: %s"% pre_filt) data = tr.data.astype(np.float64) origin_len = len(data)iforigin_len ==0:return# smart...
:return: Smith Fidelity which is a scalar. """ if power < 0: raise ValueError("Power must be positive") if power >= 2: raise ValueError("Power must be less than 2") return np.sqrt(fidelity(rho, sigma)) ** power Example #3
(-1), but there must be at least one NUMA node, so returning NUMA node zero 2020-06-19 08:35:37.616699: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Found device 0 with properties: name: Tesla P100-PCIE-16GB major: 6 minor: 0 memoryClockRate(GHz): 1.3285 pciBusID: ...
If a pandas.DataFrame is provided, the output is returned as a pandas.DataFrame with named output columns.For example, inputs could be provided for the typical "OHLCV" data:import numpy as np # note that all ndarrays must be the same length! inputs = { 'open': np.random.random(100)...