ttnn.layer_norm

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

Compute layer_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.

• epsilon (float) – 1e-12.

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

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

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

• program_config (ttnn.ProgramConfig, optional) – Defaults to None.

• compute_kernel_config (ttnn.DeviceComputeKernelConfig) –

Returns:

ttnn.Tensor – the output tensor.