ttnn.bitwise_not

ttnn.bitwise_not(input_tensor: ttnn.Tensor, *, memory_config: ttnn.MemoryConfig = None, output_tensor: ttnn.Tensor = None, sub_core_grids: ttnn.CoreRangeSet = None) → ttnn.Tensor

Applies bitwise_not to input_tensor element-wise.

\[\mathrm{{output\_tensor}}_i = \verb|bitwise_not|(\mathrm{{input\_tensor}}_i)\]
Parameters:

input_tensor (ttnn.Tensor) – the input tensor. Supported input range is [-2147483647, 2147483647].

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.

  • sub_core_grids (ttnn.CoreRangeSet, optional) – sub core grids for the operation. Defaults to None.

Returns:

ttnn.Tensor – the output tensor.

Note

Supported dtypes and layouts:

Dtypes

Layouts

INT32

TILE, ROW_MAJOR

torch.tensor([[1, 2], [3, 4]], dtype=torch.int32)

Example

# Create a tensor with specific integer values
tensor = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.int32), layout=ttnn.TILE_LAYOUT, device=device)

# Apply bitwise NOT operation
output = ttnn.bitwise_not(tensor)
logger.info(f"Bitwise NOT: {output}")