seed docs

puyuanOT · Sep 14, 2023 · 31a1165 · 31a1165
1 parent 3401ae1
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diff --git a/deeplake/core/seed.py b/deeplake/core/seed.py
@@ -4,13 +4,23 @@
 
 class DeeplakeRandom(object):
     def __new__(cls):
+        """Returns a :class:`~deeplake.random.DeeplakeRandom` object songlton 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 to initialise the engines, used to control random behaviour and bring reproducability. Set number to initialise the engines to reset the seed set None. Defaults to None.
+
+        Raises:
+            TypeError: If the provided value is not expected one.
+
+        """
         if seed is None or isinstance(seed, int):
             self.internal_seed = seed
             if self.indra_api is None:  # type: ignore
@@ -27,4 +37,6 @@ 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/deeplake.random.rst b/docs/source/deeplake.random.rst
@@ -0,0 +1,46 @@
+Reproducibility
+===============
+
+Train and operate with the deeplake features and keep reproducibility between all the engines
+See the ``deeplake.random.seed`` method on hot to operate with the random engines:
+
+.. currentmodule:: deeplake.core.seed
+
+.. autosummary::
+    :toctree:
+    :nosignatures:
+
+    deeplake.random
+
+Deeplake random number generator
+-------------------------------
+Deeplake does not provide random in-house random number generator but to control the reproducibility
+and keep track on the stages of 
+You can use :meth:`deeplake.random.seed` to seed the RNG for all the engines (both
+enterprise and non enterprise)::
+
+    import deeplake
+    deeplake.random.seed(0)
+
+
+Random number generators in other libraries
+-------------------------------------------
+If you or any of the libraries you are using rely on NumPy, you can seed the global
+NumPy RNG with::
+
+    import numpy as np
+    np.random.seed(0)
+
+    import random
+    random.seed(0)
+
+those will impact to all the places where deeplake uses those libraries but with use of use :meth:`deeplake.random.seed` we are nor changing any library
+global state instead just initialising singlton instances in the random engines
+
+DeeplakeRandom
+~~~~~~~~~~~~~~~~~~
+
+.. 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