ttnn.logit

ttnn.logit = Operation(python_fully_qualified_name='ttnn.logit', function=<ttnn._ttnn.operations.unary.logit_t object>, preprocess_golden_function_inputs=<function default_preprocess_golden_function_inputs>, golden_function=<function _golden_function_logit>, postprocess_golden_function_outputs=<function default_postprocess_golden_function_outputs>, is_cpp_operation=True, is_experimental=False)

Performs logit function on input_tensor, eps.

Parameters:

input_tensor (ttnn.Tensor) – the input tensor.

Keyword Arguments:

• eps (float, optional) – eps. Defaults to 0.

• 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

Example

>>> tensor = ttnn.from_torch(torch.tensor([[1, 2], [3, 4]], dtype=torch.bfloat16), dtype=ttnn.bfloat16, layout=ttnn.TILE_LAYOUT, device=device)
>>> output = ttnn.logit(tensor, eps = 5)