# tensorplay.empty

Source: https://www.tensorplay.cn/docs/generated/tensorplay.empty.html

```python
tensorplay.empty()
```

empty(*size, *, out=None, dtype=None, layout=tensorplay.strided, device=None, requires_grad=False, pin_memory=False, memory_format=tensorplay.contiguous_format) -> Tensor

Returns a tensor filled with uninitialized data. The shape of the tensor is
defined by the variable argument [size](/docs/generated/tensorplay.size.html#tensorplay.size).

> **Note**
>
> The returned storage is uninitialized, and tensorplay.use_deterministic_algorithms() does not change that. If the contents matter, allocate with tensorplay.zeros() or fill the tensor before reading it, otherwise the output becomes a source of nondeterminism. Floating point and complex tensors are filled with NaN, and integer tensors are filled with the maximum value.

Parameters:

size ([int](https://docs.python.org/3/builtins/functions.html#int)...) – a sequence of integers defining the shape of the output tensor.
Can be a variable number of arguments or a collection like a list or tuple.

Keyword Arguments:

- out ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – the output tensor.

- dtype ([tensorplay.dtype](/docs/generated/tensorplay.DType.html#tensorplay.DType), optional) – the desired data type of returned tensor. Default: if None, uses a global default (see [tensorplay.set_default_dtype()](/docs/generated/tensorplay.set_default_dtype.html#tensorplay.set_default_dtype)).

- layout (tensorplay.layout, optional) – the desired layout of returned Tensor. Default: tensorplay.strided.

- device ([tensorplay.device](/docs/generated/tensorplay.Device.html#tensorplay.Device), optional) – the desired device of returned tensor. Default: if None, uses the current device for the default tensor type (see [tensorplay.set_default_device()](/docs/generated/tensorplay.set_default_device.html#tensorplay.set_default_device)). [device](/docs/generated/tensorplay.Device.html#tensorplay.Device) will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.

- requires_grad ([bool](https://docs.python.org/3/builtins/functions.html#bool), optional) – If autograd should record operations on the returned tensor. Default: False.

- pin_memory ([bool](https://docs.python.org/3/builtins/functions.html#bool), optional) – If set, returned tensor would be allocated in the pinned memory. Works only for CPU tensors. Default: False.

- memory_format ([tensorplay.memory_format](/docs/generated/tensorplay.MemoryFormat.html#tensorplay.MemoryFormat), optional) – the desired memory format of returned Tensor. Default: tensorplay.contiguous_format.

Example:

```
>>> tensorplay.empty((2,3), dtype=tensorplay.int64)
tensor([[ 9.4064e+13,  2.8000e+01,  9.3493e+13],
        [ 7.5751e+18,  7.1428e+18,  7.5955e+18]])
```