ttnn.fmod

ttnn.fmod(input_tensor_a: ttnn.Tensor, input_tensor_b: ttnn.Tensor or Number, *, memory_config: ttnn.MemoryConfig | None = None) → ttnn.Tensor

Performs an eltwise-fmod operation. Formula : a - a.div(b, rounding_mode=trunc) * b.

Parameters:

• input_tensor_a (ttnn.Tensor) – the input tensor.

• input_tensor_b (ttnn.Tensor or Number) – the input tensor.

Keyword Arguments:

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

Returns:

ttnn.Tensor – the output tensor.

Note

Supported dtypes, layouts, and ranks:

Dtypes	Layouts	Ranks
BFLOAT16	TILE	2, 3, 4

Support provided only for WH_B0.

Example

>>> tensor1 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> tensor2 = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device)
>>> output = ttnn.fmod(tensor1, tensor2/scalar)