ttnn.normalize_hw
- ttnn.normalize_hw = Operation(python_fully_qualified_name='ttnn.normalize_hw', function=<ttnn._ttnn.operations.unary.normalize_hw_t object>, preprocess_golden_function_inputs=<function default_preprocess_golden_function_inputs>, golden_function=<function _golden_function_normalize_hw>, postprocess_golden_function_outputs=<function default_postprocess_golden_function_outputs>, is_cpp_operation=True, is_experimental=False)
-
Performs normalize_hw function on
input_tensor
.- Parameters:
-
input_tensor (ttnn.Tensor) – 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
ROW_MAJOR, TILE
4
Example
>>> tensor = ttnn.from_torch(torch.rand([1, 1, 32, 32], dtype=torch.bfloat16), layout=ttnn.TILE_LAYOUT, device=device) >>> output = ttnn.normalize_hw(tensor)