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tx.math

sparse_dense_multiply

source 

.sparse_dense_multiply(
   sp_tensor, dense_tensor, name = 'sparse_multiply_dense'
)

element-wise sparse_multiply_dense

Info

Uses sparse_dense_cwise_mul from Tensorflow but returns a dense result and reshapes the result to match the shape of sp_tensor

Args

  • sp_tensor (SparseTensor) : a sparse tensor
  • dense_tensor (Tensor) : a dense tensor
  • name (str) : op name

Returns

  • tensor (Tensor) : the result for the multiplication between the sparse and dense tensors

rms

source 

.rms(
   x
)

Root mean square (RMS)

Also known as quadratic mean is defined as:

x_{\mathrm{RMS}}=\sqrt{\frac{x_{1}^{2}+x_{2}^{2}+\ldots+x_{n}^{2}}{n}}

In estimation theory, the root-mean-square deviation of an estimator is a measure of the imperfection of the fit of the estimator to the data.

Args

  • x (Tensor) : input tensor

Returns

  • result (Tensor) : scalar tensor with the result of applying the root mean square to the input tensor