ttnn.polygamma

ttnn.polygamma(input_tensor: ttnn.Tensor, k: int, *, memory_config: ttnn.MemoryConfig = None) → ttnn.Tensor

Performs polygamma function on input_tensor, decimals. it is supported for range 1 to 10 only

Parameters:

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

• k (int) – k value.

Keyword Arguments:

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

Returns:

ttnn.Tensor – the output tensor.

Note

Supported dtypes and layouts:

Dtypes	Layouts
BFLOAT16	TILE, ROW_MAJOR

Example

# Create a tensor with specific values
tensor = ttnn.from_torch(
    torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16),
    dtype=ttnn.bfloat16,
    layout=ttnn.TILE_LAYOUT,
    device=device,
)

# Compute the polygamma function
output = ttnn.polygamma(tensor, 3)
logger.info(f"Polygamma: {output}")