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)
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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:
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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:
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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:
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ttnn.Tensor – the output tensor.