ttnn.empty

ttnn.empty(shape: List[int], dtype: ttnn.DataType | None = ttnn.bfloat16, layout: ttnn.Layout | None = ttnn.ROW_MAJOR, device: ttnn.Device | ttnn.MeshDevice, memory_config: ttnn.MemoryConfig | None = ttnn.DRAM_MEMORY_CONFIG) → ttnn.Tensor

Creates a device tensor with uninitialized values of the specified shape, data type, layout, and memory configuration.

Parameters:

• shape (List[int]) – The shape of the tensor to be created.

• dtype (ttnn.DataType, optional) – The tensor data type. Defaults to ttnn.bfloat16.

• layout (ttnn.Layout, optional) – The tensor layout. Defaults to ttnn.ROW_MAJOR.

• device (ttnn.Device | ttnn.MeshDevice) – The device where the tensor will be allocated.

• memory_config (ttnn.MemoryConfig, optional) – The memory configuration for the operation. Defaults to ttnn.DRAM_MEMORY_CONFIG.

Returns:

ttnn.Tensor – The output uninitialized tensor.

Note

Supported dtypes, layouts, and ranks:

Dtypes	Layouts	Ranks
BFLOAT16, FLOAT32	ROW_MAJOR, TILE	2, 3, 4
BFLOAT_8	TILE	2, 3, 4

Example

>>> tensor = ttnn.empty(shape=[2, 3], device=device)
>>> print(tensor)
ttnn.Tensor([[[[0.9, 0.21, 0.5], [0.67, 0.11, 0.30]]]], shape=Shape([2, 3]), dtype=DataType::BFLOAT16, layout=Layout::TILE)