ttnn.signbit

ttnn.signbit(input_tensor: ttnn.Tensor, *, memory_config: ttnn.MemoryConfig = None, output_tensor: ttnn.Tensor = None) → ttnn.Tensor

Applies signbit to input_tensor element-wise.

\[\mathrm{{output\_tensor}}_i = \verb|signbit|(\mathrm{{input\_tensor}}_i)\]

Parameters:

input_tensor (ttnn.Tensor) – the input tensor.

Keyword Arguments:

• memory_config (ttnn.MemoryConfig, optional) – memory configuration for the operation. Defaults to None.

• output_tensor (ttnn.Tensor, optional) – preallocated output tensor. Defaults to None.

Returns:

ttnn.Tensor – the output tensor.

Note

Supported dtypes, layouts, and ranks:

Dtypes	Layouts	Ranks
BFLOAT16, BFLOAT8_B, INT32, FLOAT32	TILE	2, 3, 4

Example

# Create a tensor with random values
tensor = ttnn.rand([2, 2], dtype=ttnn.bfloat16, layout=ttnn.TILE_LAYOUT, device=device)

# Test the sign bit of each element
output = ttnn.signbit(tensor)
logger.info(f"Sign bit: {output}")