Merge pull request #2593 from activeloopai/seed_docs

Updated deeplake.random.seed documentation
activeloopai · Sep 15, 2023 · 28f5fb0 · 28f5fb0
2 parents 3401ae1 + 4461304
commit 28f5fb0
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diff --git a/deeplake/core/seed.py b/deeplake/core/seed.py
@@ -4,13 +4,47 @@
 
 class DeeplakeRandom(object):
     def __new__(cls):
+        """Returns a :class:`~deeplake.core.seed.DeeplakeRandom` object singleton instance."""
         if not hasattr(cls, "instance"):
             cls.instance = super(DeeplakeRandom, cls).__new__(cls)
             cls.instance.internal_seed = None
             cls.instance.indra_api = None
         return cls.instance
 
     def seed(self, seed: Optional[int] = None):
+        """Set random seed to the deeplake engines
+
+        Args:
+            seed (int, optional): Integer seed for initializing the computational engines, used for bringing reproducibility to random operations.
+                Set to ``None`` to reset the seed. Defaults to ``None``.
+
+        Raises:
+            TypeError: If the provided value type is not supported.
+
+        Background
+        ----------
+
+        Specify a seed to train models and run randomized Deep Lake operations reproducibly. Features affected are:
+
+            - Dataloader shuffling
+            - Sampling and random operations in Tensor Query Language (TQL)
+            - :meth:`Dataset.random_split <deeplake.core.dataset.Dataset.random_split>`
+
+
+        The random seed can be specified using ``deeplake.random.seed``:
+
+            >>> import deeplake
+            >>> deeplake.random.seed(0)
+
+        Random number generators in other libraries
+        -------------------------------------------
+
+        The Deep Lake random seed does not affect random number generators in other libraries such as ``numpy``.
+
+        However, seeds in other libraries will affect code where Deep Lake uses those libraries, but it will not impact
+        the methods above where Deep Lake uses its internal seed.
+
+        """
         if seed is None or isinstance(seed, int):
             self.internal_seed = seed
             if self.indra_api is None:  # type: ignore
@@ -27,4 +61,5 @@ def seed(self, seed: Optional[int] = None):
             )
 
     def get_seed(self) -> Optional[int]:
+        """Returns the seed which set to the deeplake to control the flows"""
         return self.internal_seed
diff --git a/docs/source/Datasets.rst b/docs/source/Datasets.rst
@@ -69,6 +69,7 @@ Dataset Operations
     Dataset.flush
     Dataset.clear_cache
     Dataset.size_approx
+    Dataset.random_split
 
 Dataset Visualization
 ~~~~~~~~~~~~~~~~~~~~~

diff --git a/docs/source/deeplake.random.rst b/docs/source/deeplake.random.rst
@@ -0,0 +1,7 @@
+deeplake.random.seed
+====================
+
+.. currentmodule:: deeplake.core.seed
+
+.. autoclass:: DeeplakeRandom
+    :members:
diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -58,6 +58,7 @@ Deep Lake is an open-source database for AI.
    deeplake.client.log
    deeplake.core.transform
    deeplake.core.vectorstore
+   deeplake.random
 
 
 Indices and tables