I am following a book on deep learning and the book encourages understanding basic math operations behind the more convenient numpy alternatives in order to better understand the underlying principles. I am trying to reconstruct numpy's multiplication (*) operator in native Python 3.9 but I am getting some TypeErrors that I find very confusing. Hopefully somebody can help.
def multiply(a, b):
""" 1.) float * float
2.) float * vector
3.) float * matrix
4.) vector * vector
5.) vector * matrix
6.) matrix * matrix """
def float_float(float_a, float_b):
return float_a * float_b
def float_vector(float_a, vector_b):
return [float_float(float_a, component_b) for component_b in vector_b]
def float_matrix(float_a, matrix_b):
return [float_vector(float_a, vector_b) for vector_b in b]
def vector_vector(vector_a, vector_b):
return [a * b for a, b in dict(zip(vec_a, vec_b)).items()]
def vector_matrix(vector_a, matrix_b):
return [vector_vector(vector_a, vector_b) for vector_b in matrix_b]
def matrix_matrix(matrix_a, matrix_b):
return [vector_vector(a, b) for a, b in dict(zip(matrix_a, matrix_b)).items()]
def get_type(operand):
if type(operand) == float:
return "float"
elif type(operand) == list:
if any(isinstance(item, list) for item in operand):
return "matrix"
else:
return "vector"
types = (get_type(a), get_type(b))
print(types)
operations_table = {
("float", "float"): float_float(a, b),
("float", "vector"): float_vector(a, b),
("vector", "float"): float_vector(b, a),
("float", "matrix"): float_matrix(a, b),
("matrix", "float"): float_matrix(b, a),
("vector", "vector"): vector_vector(a, b),
("vector", "matrix"): vector_matrix(a, b),
("matrix", "vector"): vector_matrix(b, a),
("matrix", "matrix"): matrix_matrix(a, b)
}
return operations_table[types]
# float
f = 2.0
# vector
v = [0.5, 1.0, 2.0]
# matrix
m = [
[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]
]
# TEST
print(multiply(f, f))
print(multiply(f, v))
print(multiply(v, m))
Here is the first TypeError I get when trying to multiple 2 floats:
('float', 'float')
Traceback (most recent call last):
File "e:\OneDrive\Projects\Deep_Learning\CH05\CH05-000_NativeOps.py", line 62, in <module>
print(multiply(f, f))
File "e:\OneDrive\Projects\Deep_Learning\CH05\CH05-000_NativeOps.py", line 38, in multiply
("float", "vector"): float_vector(a, b),
File "e:\OneDrive\Projects\Deep_Learning\CH05\CH05-000_NativeOps.py", line 14, in float_vector
return [float_float(float_a, component_b) for component_b in vector_b]
TypeError: 'float' object is not iterable
Here is the second TypeError I get when trying to multiply float * vector
('float', 'vector')
Traceback (most recent call last):
File "e:\OneDrive\Projects\Deep_Learning\CH05\CH05-000_NativeOps.py", line 63, in <module>
print(multiply(f, v))
File "e:\OneDrive\Projects\Deep_Learning\CH05\CH05-000_NativeOps.py", line 37, in multiply
("float", "float"): float_float(a, b),
File "e:\OneDrive\Projects\Deep_Learning\CH05\CH05-000_NativeOps.py", line 12, in float_float
return float_a * float_b
TypeError: can't multiply sequence by non-int of type 'float'
Any help is greatly appreciated because in the example all of the values in the variables f, v, and m are made exclusively floats so I am very surprised at the types of errors that I get. Thank you!!!
The problem was with that operations_table dictionary. It caused all versions of multiplication to run always, regardless of operand type. I changed that for a much shorter solution using eval() and now the code works perfectly.
def multiply(a, b):
""" 1.) float * float
2.) float * vector
3.) float * matrix
4.) vector * vector
5.) vector * matrix
6.) matrix * matrix """
def float_float(float_a, float_b):
return float_a * float_b
def float_vector(float_a, vector_b):
return [float_float(float_a, component_b) for component_b in vector_b]
def float_matrix(float_a, matrix_b):
return [float_vector(float_a, vector_b) for vector_b in b]
def vector_vector(vector_a, vector_b):
return [a * b for a, b in list(zip(vector_a, vector_b))]
def vector_matrix(vector_a, matrix_b):
return [vector_vector(vector_a, vector_b) for vector_b in matrix_b]
def matrix_matrix(matrix_a, matrix_b):
return [vector_vector(a, b) for a, b in list(zip(matrix_a, matrix_b))]
def get_type(operand):
if type(operand) == float:
return "float"
elif type(operand) == list:
if any(isinstance(item, list) for item in operand):
return "matrix"
else:
return "vector"
types = (get_type(a), get_type(b))
print(types)
result = eval(f"{types[0]}_{types[1]}(a, b)")
return result