ttnn.sub_bw

ttnn.sub_bw = FastOperation(python_fully_qualified_name='ttnn.sub_bw', function=<ttnn._ttnn.operations.binary_backward.sub_bw_t object>, preprocess_golden_function_inputs=<function default_preprocess_golden_function_inputs>, golden_function=<function _golden_function_bw>, postprocess_golden_function_outputs=<function default_postprocess_golden_function_outputs>, is_cpp_operation=True, is_experimental=False)

Performs backward operations for subtract of input_tensor_a and input_tensor_b or scalar with given grad_tensor. Supports broadcasting.

Parameters:

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

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

  • input_tensor_b (ComplexTensor or ttnn.Tensor or Number) – the input tensor.

Keyword Arguments:

  • are_required_outputs (List[bool], optional) – List of required outputs. Defaults to [True, True].

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

  • input_grad (ttnn.Tensor, optional) – Preallocated output tensor for gradient of input_tensor_a. Defaults to None.

  • other_grad (ttnn.Tensor, optional) – Preallocated output tensor for gradient of input_tensor_b. Defaults to None.

Note

Supported dtypes and layouts:

Dtypes

Layouts

BFLOAT16, BFLOAT8_B

TILE, ROW_MAJOR

bfloat8_b/bfloat4_b is only supported on TILE_LAYOUT