pypto.expm1

Applicable Products

Ascend 950PR/Ascend 950DT: Supported
Atlas A3 training products/Atlas A3 inference products: Supported
Atlas A2 training products/Atlas A2 inference products: Supported

Description

Computes the natural exponential of each element of the input tensor and then subtracts 1.

y_i = e^{x_i} - 1

Prototype

expm1(input: Tensor) -> Tensor

Parameters

Parameter	Input/Output	Description
input	Input	Source operand. Supported type: Tensor. The supported data type is DT_FP32, DT_FP16, DT_BF16, DT_INT32, and DT_INT16. Empty tensors are not supported. The shape supports only 1 to 4 dimensions. The shape size must not exceed 2147483647 (that is, INT32_MAX).

Return Value

Returns a tensor whose shape is the same as that of the input tensor. When the input data type is DT_FP32, DT_FP16, or DT_BF16, the output data type is the same as that of the input tensor. When the input data type is DT_INT32 or DT_INT16, the output data type is DT_FP32. Each element is the natural exponential of the corresponding element of the input tensor minus 1.

Constraints

Tensor inputs do not support the TileOpFormat.TILEOP_NZ format.

Examples

TileShape Setting Example

Note: Before calling this operation API, set the TileShape through set_vec_tile_shapes.

The dimensions of the TileShape must be the same as those of the output.

Example 1: If the input shape is [m, n], the output is [m, n], and the TileShape is set to [m1, n1], then m1 and n1 are used to tile the m and n axes, respectively.

pypto.set_vec_tile_shapes(4, 16)

API Call Example

x = pypto.tensor([2, 2], pypto.DT_FP32)
y = pypto.expm1(x)

The results are as follows:

Input data x: [[1., 2.], [3., 4.]]
Output data y: [[1.7183, 6.3891], [19.0855, 53.5981]]