data.buffer.deque_buffer

deque_buffer

DequeBuffer

class ding.data.buffer.deque_buffer.DequeBuffer(size: int, sliced: bool = False)

Overview:

A buffer implementation based on the deque structure.

clear() → None

Overview:

The method that clear all data, indices, and the meta information in the buffer.

count() → int

Overview:

The method that returns the current length of the buffer.

delete(indices: str | Iterable[str]) → None

Overview:

The method that delete the data and related meta information by specific indices.

Arguments:

• indices (Union[str, Iterable[str]]): Where the data to be cleared in the buffer.

get(idx: int) → BufferedData

Overview:

The method that returns the BufferedData object by subscript idx (int).

push(data: Any, meta: dict | None = None) → BufferedData

Overview:

The method that input the objects and the related meta information into the buffer.

Arguments:

• data (Any): The input object which can be in any format.

• meta (Optional[dict]): A dict that helps describe data, such as category, label, priority, etc. Default to None.

sample(size: int | None = None, indices: List[str] | None = None, replace: bool = False, sample_range: slice | None = None, ignore_insufficient: bool = False, groupby: str | None = None, unroll_len: int | None = None) → List[BufferedData] | List[List[BufferedData]]

Overview:

The method that randomly sample data from the buffer or retrieve certain data by indices.

Arguments:

• size (Optional[int]): The number of objects to be obtained from the buffer.

  If indices is not specified, the size is required to randomly sample the corresponding number of objects from the buffer.

• indices (Optional[List[str]]): Only used when you want to retrieve data by indices.

  Default to None.

• replace (bool): As the sampling process is carried out one by one, this parameter determines whether the previous samples will be put back into the buffer for subsequent sampling. Default to False, it means that duplicate samples will not appear in one sample call.

• sample_range (Optional[slice]): The indices range to sample data. Default to None, it means no restrictions on the range of indices for the sampling process.

• ignore_insufficient (bool): whether throw `` ValueError`` if the sampled size is smaller than the required size. Default to False.

• groupby (Optional[str]): If this parameter is activated, the method will return a target size of object groups.

• unroll_len (Optional[int]): The unroll length of a trajectory, used only when the groupby is activated.

Returns:

• sampled_data (Union[List[BufferedData], List[List[BufferedData]]]): The sampling result.

update(index: str, data: Any | None = None, meta: dict | None = None) → bool

Overview:

the method that update data and the related meta information with a certain index.

Arguments:

• data (Any): The data which is supposed to replace the old one. If you set it to None, nothing will happen to the old record.

• meta (Optional[dict]): The new dict which is supposed to merge with the old one.