ttnn.group_norm

ttnn.group_norm = Operation(python_fully_qualified_name='ttnn.group_norm', function=<ttnn._ttnn.operations.normalization.group_norm_t object>, preprocess_golden_function_inputs=<function default_preprocess_golden_function_inputs>, golden_function=<function _golden_function>, postprocess_golden_function_outputs=<function _postprocess_golden_function_outputs>, is_cpp_operation=True, is_experimental=False)

Compute group_norm over 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.

• num_groups (int) –

• epsilon (float) – 1e-12.

• input_mask (ttnn.Tensor, optional) – Defaults to None.

• weight (ttnn.Tensor, optional) – Defaults to None.

• bias (ttnn.Tensor, optional) – Defaults to None.

• dtype (ttnn.DataType, optional) – Defaults to None.

• core_grid (CoreGrid, optional) – Defaults to None.

• inplace (bool, optional) – Defaults to True.

• output_layout (ttnn.Layout, optional) – Defaults to None.

Returns:

ttnn.Tensor – the output tensor.