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)