Sparse routines¶

Create Arrays¶

`array`	Creates a sparse array from any object exposing the array interface.
`csr_matrix`	Creates a CSRNDArray, an 2D array with compressed sparse row (CSR) format.
`empty`	Returns a new array of given shape and type, without initializing entries.
`row_sparse_array`	Creates a RowSparseNDArray, a multidimensional row sparse array with a set of tensor slices at given indices.
`zeros`	Return a new array of given shape and type, filled with zeros.
`zeros_like`	Return an array of zeros with the same shape, type and storage type as the input array.

Casts tensor storage type to the new type.

`retain`	pick rows specified by user input index array from a row sparse matrix and save them in the output sparse matrix.
`slice`	Slices a region of the array.
`where`	Return the elements, either from x or y, depending on the condition.

`add_n`	Adds all input arguments element-wise.
`broadcast_add`	Returns element-wise sum of the input arrays with broadcasting.
`broadcast_div`	Returns element-wise division of the input arrays with broadcasting.
`broadcast_mul`	Returns element-wise product of the input arrays with broadcasting.
`broadcast_sub`	Returns element-wise difference of the input arrays with broadcasting.
`dot`	Dot product of two arrays.
`elemwise_add`	Adds arguments element-wise.
`elemwise_mul`	Multiplies arguments element-wise.
`elemwise_sub`	Subtracts arguments element-wise.
`negative`	Numerical negative of the argument, element-wise.

`arcsin`	Returns element-wise inverse sine of the input array.
`arctan`	Returns element-wise inverse tangent of the input array.
`degrees`	Converts each element of the input array from radians to degrees.
`radians`	Converts each element of the input array from degrees to radians.
`sin`	Computes the element-wise sine of the input array.
`tan`	Computes the element-wise tangent of the input array.

`arcsinh`	Returns the element-wise inverse hyperbolic sine of the input array, computed element-wise.
`arctanh`	Returns the element-wise inverse hyperbolic tangent of the input array, computed element-wise.
`sinh`	Returns the hyperbolic sine of the input array, computed element-wise.
`tanh`	Returns the hyperbolic tangent of the input array, computed element-wise.

`mean`	Computes the mean of array elements over given axes.
`norm`	Computes the norm on an NDArray.
`sum`	Computes the sum of array elements over given axes.

`ceil`	Returns element-wise ceiling of the input.
`fix`	Returns element-wise rounded value to the nearest integer towards zero of the input.
`floor`	Returns element-wise floor of the input.
`rint`	Returns element-wise rounded value to the nearest integer of the input.
`round`	Returns element-wise rounded value to the nearest integer of the input.
`trunc`	Return the element-wise truncated value of the input.

`expm1`	Returns `exp(x) - 1` computed element-wise on the input.
`log1p`	Returns element-wise `log(1 + x)` value of the input.

`sqrt`	Returns element-wise square-root value of the input.
`square`	Returns element-wise squared value of the input.

`abs`	Returns element-wise absolute value of the input.
`sign`	Returns element-wise sign of the input.

`adam_update`	Update function for Adam optimizer.
`adagrad_update`	Update function for AdaGrad optimizer.
`sgd_mom_update`	Momentum update function for Stochastic Gradient Descent (SGD) optimizer.
`sgd_update`	Update function for Stochastic Gradient Descent (SDG) optimizer.

`Embedding`	Maps integer indices to vector representations (embeddings).
`LinearRegressionOutput`	Computes and optimizes for squared loss during backward propagation.
`LogisticRegressionOutput`	Applies a logistic function to the input.
`make_loss`	Make your own loss function in network construction.
`stop_gradient`	Stops gradient computation.