ttnn.threshold
- ttnn.threshold = Operation(python_fully_qualified_name='ttnn.threshold', function=<ttnn._ttnn.operations.unary.threshold_t object>, preprocess_golden_function_inputs=<function default_preprocess_golden_function_inputs>, golden_function=<function _golden_function_threshold>, postprocess_golden_function_outputs=<function default_postprocess_golden_function_outputs>, is_cpp_operation=True, is_experimental=False)
-
Performs threshold function on
input_tensor
,threshold
,value
.- Parameters:
-
input_tensor (ttnn.Tensor) – the input tensor.
threshold (float) – Threshold value.
value (float) – Replacing 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, 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) >>> threshold = 1.0 >>> value = 10.0 >>> output = ttnn.threshold(tensor, threshold, value)