ttnn.log_sigmoid_bw

ttnn.log_sigmoid_bw = FastOperation(python_fully_qualified_name='ttnn.log_sigmoid_bw', function=<ttnn._ttnn.operations.unary_backward.log_sigmoid_bw_t object>, preprocess_golden_function_inputs=<function default_preprocess_golden_function_inputs>, golden_function=<function _golden_function_log_sigmoid>, postprocess_golden_function_outputs=<function default_postprocess_golden_function_outputs>, is_cpp_operation=True, is_experimental=False)

Performs backward operations for log sigmoid on input_tensor with given grad_tensor.

\[\mathrm{{output\_tensor}}_i = \verb|log_sigmoid_bw|(\mathrm{{grad\_tensor}}_i, \mathrm{{input\_tensor}}_i)\]
Parameters:

  • grad_tensor (ttnn.Tensor) – the input gradient tensor.

  • input_tensor_a (ttnn.Tensor) – the input tensor.

Keyword Arguments:

memory_config (ttnn.MemoryConfig, optional) – memory configuration for the operation. Defaults to None.

Returns:

List of ttnn.Tensor – the output tensor.

Note

Supported dtypes and layouts:

Dtypes

Layouts

BFLOAT16, BFLOAT8_B

TILE

For more details about BFLOAT8_B, refer to the BFLOAT8_B limitations.