TensorDictBase.to_csv#

TensorDictBase.to_csv(path, *, separator: str | None = None, **kwargs)#

Writes the tensordict to a CSV file, with one column per leaf.

The tensordict is converted with to_pandas(), so the same rules apply, and written with pandas.DataFrame.to_csv() without the index. Requires pandas. from_csv() reads the file back.

Parameters:

path (str or Path) – the path of the CSV file.

Keyword Arguments:

separator (str, optional) – if given, joins the keys of nested entries with it to build the column names: with separator=".", the entry ("obs", "x") becomes the column "obs.x". Required when the tensordict has nested tensordicts. Defaults to None.
**kwargs – passed to pandas.DataFrame.to_csv().

Raises:

ValueError – as to_pandas().

Examples

>>> import os
>>> import tempfile
>>> import torch
>>> from tensordict import TensorDict
>>> td = TensorDict(a=torch.arange(2), b=TensorDict(c=torch.zeros(2)), batch_size=[2])
>>> with tempfile.TemporaryDirectory() as tmpdir:
...     path = os.path.join(tmpdir, "data.csv")
...     td.to_csv(path, separator=".")
...     with open(path) as f:
...         print(f.read())
a,b.c
0,0.0
1,0.0

Every tensordict class and every tensorclass has this method. For the other methods, see Methods by task.

TensorDictBase.to_csv#

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