Migrating from Previous Versions¶
The Amplify SDK v1 has lost some compatibility with v0. If you have been using an older version, this section explains how to maintain your code so that it will continue to work.
Continue using the Amplify SDK v0¶
To keep your current code completely unchanged, you can continue to use the Amplify SDK v0.
$ python3 m pip install U 'amplify<1.0.0'
To include additional packages, use the following.
$ python3 m pip install U 'amplify[extra]<1.0.0'
Documentation for the Amplify SDK v0 is available at the following URL.
https://amplify.fixstars.com/en/docs/amplify/v0/
Important
The Amplify SDK v0 is not guaranteed to work continuously. Other than critical bug fixes, there will be no feature additions or updates to the supported solvers.
Please also note that it may stop working due to changes in the environment, such as the release of a new version of Python or changes in solver specifications.
Migrating to the Amplify SDK v1¶
You can use the following guidelines to migrate code written in v0 to v1
Creating decision variables¶
BinarySymbolGenerator
and IsingSymbolGenerator
have been replaced by VariableGenerator
with the addition of integer and real variables. The type of variable is specified by the array()
, scalar()
, and matrix()
method arguments.
Previous writing style:
from amplify import BinarySymbolGenerator, IsingSymbolGenerator
gen = BinarySymbolGenerator()
q = gen.array(10)
gen = IsingSymbolGenerator()
s = gen.array(shape=(4, 4))
New writing style:
from amplify import VariableGenerator
gen = VariableGenerator()
q = gen.array("Binary", 10)
s = gen.array("Ising", shape=(4, 4))
n = gen.array("Integer", shape=(3, 3), bounds=(0, 10))
x = gen.array("Real", shape=(2, 4), bounds=(0.5, 0.5))
Creating the objective function¶
Once you create the variables described above, you can construct a polynomial as in previous versions. However, dictionary construction is deprecated and will not be available.
Matrixstyle objective functions are now constructed using the matrix()
method instead of directly creating a matrix class. Also, the Matrix
class now includes quadratic, linear, and constant terms of the coefficients and the variables they contain. See “Objective Function with a Coefficient Matrix” for more information.
Previous writing style (currently not working):
from amplify import BinaryMatrix
m = BinaryMatrix(3)
m[0, 0] = 2
m[0, 1] = 1
m[1, 2] = 1
m[2, 2] = 1
New writing style:
from amplify import VariableGenerator
gen = VariableGenerator()
m = gen.matrix("Binary", shape=3)
# Obtain quadratic terms
m.quadratic[0, 0] = 2
m.quadratic[0, 1] = 1
m.quadratic[1, 2] = 1
m.quadratic[2, 2] = 1
# Obtain variables corresponding to the coefficient matrix
q = m.variable_array
Creating constraints¶
We have moved the constraint creation functions and classes from the amplify.constraint
submodule to the amplify
module. In addition, we have removed the penalty function, and the users can now define their own penalty functions by constructing Constraint
classes. See specifying penalty functions for details. All other helper functions are only available by changing modules.
Previous writing style:
from amplify.constraint import equal_to, penalty
c = equal_to(q.sum(), 1)
p = penalty(q[0] * q[1])
New writing style:
from amplify import Constraint, equal_to
c = equal_to(q.sum(), 1)
p = Constraint(q[0] + q[1], le=1, penalty=q[0] * q[1])
Model creation¶
As before, models can be created by explicitly constructing the model class Model
in the Amplify SDK v1 or by summing the objective function and constraints.
In previous versions, BinaryQuadraticModel
and IsingQuadraticModel
were the classes that represented the model and were also responsible for transforming the model into a secondorder model based on the type of variables. In Amplify SDK v1, however, the models are no longer bound to variable types and orders, as they are compatible with solvers that can handle various variable types and orders. Therefore, the Amplify SDK no longer performs the model transformation process when the model is constructed, but rather, the optimal transformation process for the solver is performed within the solve()
function by passing the client corresponding to the solver to be used to the solve()
function.
Previous writing style:
from amplify import BinaryQuadraticModel
model = BinaryQuadraticModel(q.sum() ** 2, c)
New writing style:
from amplify import Model
model = Model(q.sum() ** 2, c)
Previously, the users could obtain the result of the conversion to a quadratic model from the BinaryQuadraticModel
and IsingQuadraticModel
attributes, but in Amplify SDK v1, you can obtain them from the attribute of the Result
class, which is the return value of the solve()
function, or you can explicitly call a model conversion method to check it. See “Variable Conversion and Degree Reduction” for details.
Executing the solver¶
We have moved the solver client from the amplify.client
submodule to the amplify
module. The Solver
class has also been removed, and the solver is now executed by passing the model and solver client to the solve()
function. You can pass all model transformation and graph embedding parameters as parameters to the solve()
function rather than as attributes of the model or solver class.
Previous writing style:
from amplify import Solver, QuadratizationMethod
from amplify.client import FixstarsClient
client = FixstarsClient()
# client.token = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
client.parameters.timeout = 1000
model = BinaryQuadraticModel(q.sum() **2, c, method=QuadratizationMethod.SUBSTITUTION)
solver = Solver(client)
solver.filter_solution = False
result = solver.solve(model)
New writing style:
from amplify import FixstarsClient, solve
client = FixstarsClient()
# client.token = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
client.parameters.timeout = 1000
model = Model(q.sum() **2, c)
result = solve(model, client, quadratization_method="Substitute", filter_solution=False)
Also, the Amplify SDK sets the solution of intermediate models (old logical models) and the result of graph embedding to attributes of the Result
class, which is the return value of the solve()
function. See “Variable Conversion and Degree Reduction” and “Graph Embedding” for details.
Using the backwardcompatible API¶
To ensure that code written in v0 will work with Amplify SDK v1, we provide the legacy API as a backwardcompatible API for v1. The backwardcompatible API is not guaranteed to be 100% compatible, but it maintains compatibility with commonly used features and should work without modification in most cases.
Important
We recommend migrating to the v1 API as soon as possible, as the backwardcompatible API may be removed in future releases.
This will be output as a warning (DeprecationWarning
) when the backwardcompatible API is used.
We provide the backwardcompatible API with the following policy.
Classes¶
Amplify SDK v0 (link to v1 compatible API) 
Backwardcompatible API details 

Subclassed as an alias of 

Subclassed as an alias of 


Not provided 
Function as 


Not provided 
Subclassed as an alias for 


Not provided 
These are not created unless you explicitly call the constructor. They serve as v0compatible models that can be used to obtain quadratic intermediate models (old logical models) of the binary and Ising variables, respectively. However, they cannot be passed to the new 


Not provided 
Provided the same interface as v0 as a wrapper class for the 
Functions¶
Amplify SDK v0 (link to v1 compatible API) 
Backwardcompatible API details 


Not provided 
Alias for 


Not provided 

Not provided 

Not provided 

Not provided 

Not provided 
Alias for 


Not provided 
A function version of 


Not provided 
Namespace¶
Amplify SDK v0 (link to v1 compatible API) 
Backwardcompatible API details 


Provided for compatibility 

Provided for compatibility 