ttnn.tilize_with_val_padding

ttnn.tilize_with_val_padding = Operation(python_fully_qualified_name='ttnn.tilize_with_val_padding', function=<ttnn._ttnn.operations.data_movement.tilize_with_val_padding_t object>, preprocess_golden_function_inputs=<function default_preprocess_golden_function_inputs>, golden_function=None, postprocess_golden_function_outputs=<function default_postprocess_golden_function_outputs>, is_cpp_operation=True, is_experimental=False)

Changes data layout of input tensor to TILE. Pads to specified shape with a user-provided value.

Input tensor must be on TT accelerator device, in ROW_MAJOR layout, and have BFLOAT16 data type.

Output tensor will be on TT accelerator device, in TILE layout, and have BFLOAT16 data type.

Parameters:

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

  • output_tensor_shape (shape) – Shape of the output tensor.

  • pad_value (number) – Value to pad the output tensor.

Keyword Arguments:

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

  • dtype (data type, optional) – Data type of the output tensor. Defaults to None.

  • use_multicore (bool, optional) – Whether to use multicore. Defaults to True.

  • queue_id (int, optional) – command queue id. Defaults to 0.

Returns:

ttnn.Tensor – the output tensor.