Value Object

Expression: d = a * b + c

In [6]:

class Value:

    def __init__(self, data):
        self.data = data

    def __repr__(self):   # This basically allows us to print nicer looking expressions for the final output
        return f"Value(data={self.data})"
    
    def __add__(self, other):
        out = Value(self.data + other.data)
        return out
    
    def __mul__(self, other):
        out = Value(self.data * other.data)
        return out

class Value: def __init__(self, data): self.data = data def __repr__(self): # This basically allows us to print nicer looking expressions for the final output return f"Value(data={self.data})" def __add__(self, other): out = Value(self.data + other.data) return out def __mul__(self, other): out = Value(self.data * other.data) return out

In [12]:

a = Value(2.0)
b = Value(-3.0)
c = Value(10.0)

a = Value(2.0) b = Value(-3.0) c = Value(10.0)

In [9]:

a*b + c

a*b + c

Out[9]:

Value(data=4.0)

SAME THING!! (Up and Down cells)

In [10]:

(a.__mul__(b)).__add__(c)

(a.__mul__(b)).__add__(c)

Out[10]:

Value(data=4.0)

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Visualization of the expression

In [3]:

class Value:

    def __init__(self, data, _children=(), _op=''):
        self.data = data
        self._prev = set(_children)
        self._op = _op

    def __repr__(self):   # This basically allows us to print nicer looking expressions for the final output
        return f"Value(data={self.data})"
    
    def __add__(self, other):
        out = Value(self.data + other.data, (self, other), '+')
        return out
    
    def __mul__(self, other):
        out = Value(self.data * other.data, (self, other), '*')
        return out

class Value: def __init__(self, data, _children=(), _op=''): self.data = data self._prev = set(_children) self._op = _op def __repr__(self): # This basically allows us to print nicer looking expressions for the final output return f"Value(data={self.data})" def __add__(self, other): out = Value(self.data + other.data, (self, other), '+') return out def __mul__(self, other): out = Value(self.data * other.data, (self, other), '*') return out

In [13]:

d = a*b + c

d = a*b + c

In [14]:

d._prev

d._prev

Out[14]:

{Value(data=-6.0), Value(data=10.0)}

In [15]:

d._op

d._op

Out[15]:

'+'

---

In [4]:

a = Value(2.0)
b = Value(-3.0)
c = Value(10.0)

d= a*b + c
d

a = Value(2.0) b = Value(-3.0) c = Value(10.0) d= a*b + c d

Out[4]:

Value(data=4.0)

In [1]:

%pip install graphviz

%pip install graphviz

Collecting graphviz
  Downloading graphviz-0.20.3-py3-none-any.whl (47 kB)
Installing collected packages: graphviz
Successfully installed graphviz-0.20.3
Note: you may need to restart the kernel to use updated packages.

WARNING: You are using pip version 21.2.3; however, version 24.2 is available.
You should consider upgrading via the 'c:\Users\imdiv\OneDrive\Desktop\GitHub Portal\Micrograd\venv\Scripts\python.exe -m pip install --upgrade pip' command.

In [9]:

from graphviz import Digraph

def trace(root):
    #Builds a set of all nodes and edges in a graph
    nodes, edges = set(), set()
    def build(v):
        if v not in nodes:
            nodes.add(v)
            for child in v._prev:
                edges.add((child, v))
                build(child)
    build(root)
    return nodes, edges

def draw_dot(root):
    dot = Digraph(format='svg', graph_attr={'rankdir': 'LR'}) #LR == Left to Right

    nodes, edges = trace(root)
    for n in nodes:
        uid = str(id(n))
        #For any value in the graph, create a rectangular ('record') node for it
        dot.node(name = uid, label = "{ data %.4f }" % ( n.data, ), shape='record')
        if n._op:
            #If this value is a result of some operation, then create an op node (in a circle/oval shape to distinguish) for it
            dot.node(name = uid + n._op, label=n._op)
            #and connect this node to it
            dot.edge(uid + n._op, uid)

    for n1, n2 in edges:
        #Connect n1 to the node of n2
        dot.edge(str(id(n1)), str(id(n2)) + n2._op)

    return dot

from graphviz import Digraph def trace(root): #Builds a set of all nodes and edges in a graph nodes, edges = set(), set() def build(v): if v not in nodes: nodes.add(v) for child in v._prev: edges.add((child, v)) build(child) build(root) return nodes, edges def draw_dot(root): dot = Digraph(format='svg', graph_attr={'rankdir': 'LR'}) #LR == Left to Right nodes, edges = trace(root) for n in nodes: uid = str(id(n)) #For any value in the graph, create a rectangular ('record') node for it dot.node(name = uid, label = "{ data %.4f }" % ( n.data, ), shape='record') if n._op: #If this value is a result of some operation, then create an op node (in a circle/oval shape to distinguish) for it dot.node(name = uid + n._op, label=n._op) #and connect this node to it dot.edge(uid + n._op, uid) for n1, n2 in edges: #Connect n1 to the node of n2 dot.edge(str(id(n1)), str(id(n2)) + n2._op) return dot

In [ ]:

draw_dot(d)

draw_dot(d)

NOTE: The graph will only get generated if you have graphviz installed locally on your machine and the env variable path needs to be set.

If you want to avoid downloading it locally, you can directly run this on Google Colab to view the output, as graphviz is already preinstalled for you

Check 3_1-graph-visualisation.ipynb for viewing the outputs

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