torch_div function

Div

torch_div(self, other, rounding_mode)

Arguments

• self: (Tensor) the input tensor.

• other: (Number) the number to be divided to each element of input

• rounding_mode: (str, optional) – Type of rounding applied to the result:

  • NULL - default behavior. Performs no rounding and, if both input and other are integer types, promotes the inputs to the default scalar type. Equivalent to true division in Python (the / operator) and NumPy’s np.true_divide.
  • "trunc" - rounds the results of the division towards zero. Equivalent to C-style integer division.
  • "floor" - rounds the results of the division down. Equivalent to floor division in Python (the // operator) and NumPy’s np.floor_divide.

div(input, other, out=NULL) -> Tensor

Divides each element of the input input with the scalar other and returns a new resulting tensor.

Each element of the tensor input is divided by each element of the tensor other. The resulting tensor is returned.

The shapes of input and other must be broadcastable . If the torch_dtype of input and other differ, the torch_dtype of the result tensor is determined following rules described in the type promotion documentation . If out is specified, the result must be castable to the torch_dtype of the specified output tensor. Integral division by zero leads to undefined behavior.

Warning

Integer division using div is deprecated, and in a future release div will perform true division like torch_true_divide(). Use torch_floor_divide() to perform integer division, instead.

If the torch_dtype of input and other differ, the torch_dtype of the result tensor is determined following rules described in the type promotion documentation . If out is specified, the result must be castable to the torch_dtype of the specified output tensor. Integral division by zero leads to undefined behavior.

Examples

if (torch_is_installed()) {

a = torch_randn(c(5))
a
torch_div(a, 0.5)

a = torch_randn(c(4, 4))
a
b = torch_randn(c(4))
b
torch_div(a, b)
}