add var description design

doc/design/var_desc.md

+## Background
+PaddlePaddle divides the description of neural network computation graph into two stages: compile time and runtime.
+
+The data structure to describe the compile time graph should be able to be serialized for distributing training. So we use proto message OpDesc to describe computation and VarDesc to describe data.
+
+PaddlePaddle will generate these data structure according to user's description and do some optimization, such as:
+
+1. InferShape. Infer the Output size according to Input size and set them into VarDesc.
+1. memory optimise and reuse. Scan all the memory that will be used and reuse some memory that is allocated before but will not be used anymore to reduce memory.
+
+VarDesc is used to describe different kinds of Variable value, such as Tensor, scalar, and scope, we use a proto message to do this:
+
+## Definition of VarDesc in Proto
+
+```
+message LoDTensorDesc {
+  enum Type {
+    INT16 = 1;
+    INT32 = 2;
+    INT64 = 3;
+    FP16 = 4;
+    FP32 = 5;
+    DOUBLE = 6
+    BOOL = 7;
+  }
+
+  Type element_type = 1;
+  repeated int dims = 2; // [UNK, UNK, 6000] is saved as [-1, -1, 6000]
+  optional int lod_level [default=0] = 3;
+  repeated int32 int16_val = 4 [packed = true]; // INT16
+  repeated int32 int32_val = 5 [packed = true]; // INT32
+  repeated int64 int64_val = 6 [packed = true]; // INT64
+  repeated float float_val = 7 [packed = true]; // FP32
+  repeated double double_val = 8 [packed = true]; // DOUBLE
+  repeated bool bool_val = 9 [packed = true];  // BOOL
+}
+
+message VarDesc {
+  enum Type {
+    INT = 0;
+    FLOAT = 1;
+    STRING = 2;
+    INTS = 3;
+    FLOATS = 4;
+    STRINGS = 5;
+    LOD_TENSOR = 6;
+  }
+
+  message Value {
+    optional int32 i = 1;
+    optional float f = 2;
+    optional string s = 3;
+    repeated int32 ints = 4;
+    repeated float floats = 5;
+    repeated string strings = 6;
+    optional LodTesnorDesc lod_tensor = 7; // when type==LOD_TENSOR
+  }
+
+  required string name = 1;
+  required Type type = 2;
+  required Value value = 3;
+}
+
+```
+
+## Definition of Variable in Python
+
+There is a class `Variable` in python to help create Variable.
+
+```python
+class Variable(object):
+  def __init__(self,
+               name=None,
+               data_type=None,
+               shape=None,
+               value=None,
+               trainable=True):
+```
+
+create a variable with a tensor value.
+
+```python
+a = Variable("X", shape=[784, 10], data_type=INT32, value=0)
+```
+
+or create a Variable with a string value
+
+```python
+a = Variable("X", data_type=STRING, value="aa")
+```