From bd4559abbee5413d322b8659929bdb203de6abaf Mon Sep 17 00:00:00 2001
From: Yi Wang <yiwang01@baidu.com>
Date: Fri, 23 Jun 2017 16:59:48 -0700
Subject: [PATCH] Add design doc

---
 paddle/framework/variable.md | 52 ++++++++++++++++++++++++++++++++++++
 1 file changed, 52 insertions(+)
 create mode 100644 paddle/framework/variable.md

diff --git a/paddle/framework/variable.md b/paddle/framework/variable.md
new file mode 100644
index 000000000..f44d5ea46
--- /dev/null
+++ b/paddle/framework/variable.md
@@ -0,0 +1,52 @@
+# Design Doc: Variable
+
+
+Variable is also known as *blob* in MxNet and Caffe2.  It is the input and output type of operators, where a neural network is a graph of operators.
+
+## Requirements: Lazy Memory Allocation
+
+For the flexibility of a DL system, a variable should be able to contain any typed value -- a tensor in most cases, but could also be some integer IDs or a scope of other variables in the case of RNN.
+
+To use the minimum amount of memory, we'd like that a variable to allocate memory when it has to, or, lazy memory allocation.  Let's take the following example:
+
+```cpp
+Variable vr, v1, v2;
+
+Tensor* t1 = new Tensor();
+Tensor* t2 = new Tensor();
+
+Randomize(
+  /* malloc */ v1.GetMutable<Tensor>().mutable_data<float16>(DDim(100,200)),
+  /* size */ t1.Size());
+  
+Randomize(
+  /* malloc */ v2.GetMutable<Tensor>().mutable_data<float16>(DDim(200,300)),
+  /* size */ t2.Size());
+  
+Mult(
+  /*result*/ vr.GetMutable<Tensor>().mutable_data<v1.Type()>(SizeOfMult(v1, v2)),
+  /*input1*/ v1.Get<Tensor>().data(),
+  /*input2*/ v2.Get<Tensor>().data());
+```
+     
+We see that a variable holds nothing until `Variable::GetMutable<Tensor>()` allocates a tensor and puts it in the variable.  Similarly, a tensor gets its memory until `Tensor::mutable_data()`.
+
+This syntax for lazy memory allocation when we call `Randomize` and `Mult`, those functions that mutate the variable, so it saves us some line of C++ code.
+
+
+## Implementation: Type Hiding
+
+To make memory allocation lazy, we cannot assume that we know the type held by a variable at definition time.  In other words, `class Variable` cannot be a template `template <T> class Variable`.
+
+Because we don't know the type `T`, we cannot save a `T*` as `Variable's` data member.  Instead, we save an interface object `Placeholder`, who can return the pointer to the saved object via `Placeholder::Ptr()` as `void*`.
+
+But anyway, Variable needs to know `T` so could it `delete<T>(ptr)` and so could `Variable::Get` checks the expected type and the saved object's type.
+
+We save `T` in `PlaceholderImpl`, the implementation of `Placeholder`.  Please be aware that `PlaceholderImpl` is a class template and `T` is passed in as a template parameter.
+
+Because `PlaceholderImpl` knows `T`, it can save and return `typeid(T)` for the type comparison in `Variable::Get` and `Variable::GetMutable`.
+
+
+## Conclusion
+
+The technique type hiding utilizes C++ class templates, interface and derivation, and C++ RTTI (typeid).  This combination saves us from definition something like `caffe2::TypeMata`, which takes hundreds of lines of C++ code.
-- 
GitLab