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)