ttnn.layer_norm

ttnn.layer_norm = FastOperation(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.

Args:

input_tensor (ttnn.Tensor): the input tensor.

Keyword args:

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.