Python SigmoidExpr示例

示例#1

文件： test_f_sharp.py 项目： BayesWitnesses/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
let private sigmoid x =
    let z = exp x
    match x with
        | i when i < 0.0 -> z / (1.0 + z)
        | _ -> 1.0 / (1.0 + exp (-x))
let score (input : double list) =
    sigmoid (2.0)
"""

    interpreter = FSharpInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#2

文件： test_python.py 项目： BayesWitnesses/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
import math
def sigmoid(x):
    if x < 0.0:
        z = math.exp(x)
        return z / (1.0 + z)
    return 1.0 / (1.0 + math.exp(-x))
def score(input):
    return sigmoid(2.0)
"""

    interpreter = PythonInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#3

文件： test_r.py 项目： akashmavle5/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
sigmoid <- function(x) {
    if (x < 0.0) {
        z <- exp(x)
        return(z / (1.0 + z))
    }
    return(1.0 / (1.0 + exp(-x)))
}
score <- function(input) {
    return(sigmoid(2.0))
}
"""

    interpreter = RInterpreter()
    utils.assert_code_equal(interpreter.interpret(expr), expected_code)

示例#4

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
function Score([double[]] $InputVector) {
    return Sigmoid $(2.0)
}
function Sigmoid([double] $x) {
    if ($x -lt 0.0) {
        [double] $z = [math]::Exp($x)
        return $z / (1.0 + $z)
    }
    return 1.0 / (1.0 + [math]::Exp(-$x))
}
"""

    interpreter = PowershellInterpreter()
    utils.assert_code_equal(interpreter.interpret(expr), expected_code)

示例#5

文件： test_dart.py 项目： akashmavle5/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
import 'dart:math';
double score(List<double> input) {
    return sigmoid(2.0);
}
double sigmoid(double x) {
    if (x < 0.0) {
        double z = exp(x);
        return z / (1.0 + z);
    }
    return 1.0 / (1.0 + exp(-x));
}
"""
    interpreter = DartInterpreter()
    utils.assert_code_equal(interpreter.interpret(expr), expected_code)

示例#6

文件： test_haskell.py 项目： akashmavle5/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = r"""
module Model where
score :: [Double] -> Double
score input =
    sigmoid (2.0)
sigmoid :: Double -> Double
sigmoid x
    | x < 0.0 = z / (1.0 + z)
    | otherwise = 1.0 / (1.0 + exp (-x))
  where
    z = exp x
"""

    interpreter = HaskellInterpreter()
    utils.assert_code_equal(interpreter.interpret(expr), expected_code)

示例#7

文件： test_javascript.py 项目： BayesWitnesses/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
function score(input) {
    return sigmoid(2.0);
}
function sigmoid(x) {
    if (x < 0.0) {
        let z = Math.exp(x);
        return z / (1.0 + z);
    }
    return 1.0 / (1.0 + Math.exp(-x));
}
"""

    interpreter = JavascriptInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#8

文件： test_ruby.py 项目： BayesWitnesses/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
def score(input)
    sigmoid(2.0)
end
def sigmoid(x)
    if x < 0.0
        z = Math.exp(x)
        return z / (1.0 + z)
    end
    1.0 / (1.0 + Math.exp(-x))
end
"""

    interpreter = RubyInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#9

文件： test_rust.py 项目： BayesWitnesses/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
fn score(input: Vec<f64>) -> f64 {
    sigmoid(2.0_f64)
}
fn sigmoid(x: f64) -> f64 {
    if x < 0.0_f64 {
        let z: f64 = x.exp();
        return z / (1.0_f64 + z);
    }
    1.0_f64 / (1.0_f64 + (-x).exp())
}
"""

    interpreter = RustInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#10

文件： test_lightgbm.py 项目： BayesWitnesses/m2cgen

def test_multi_class_sigmoid_output_transform():
    estimator = lgb.LGBMClassifier(n_estimators=1,
                                   random_state=1,
                                   max_depth=1,
                                   sigmoid=0.5,
                                   objective="ovr")
    estimator.fit(np.array([[1], [2], [3]]), np.array([1, 2, 3]))

    assembler = LightGBMModelAssembler(estimator)
    actual = assembler.assemble()

    sigmoid = ast.SigmoidExpr(
        ast.BinNumExpr(ast.NumVal(0.5), ast.NumVal(-1.3862943611),
                       ast.BinNumOpType.MUL))

    expected = ast.VectorVal([sigmoid] * 3)

    assert utils.cmp_exprs(actual, expected)

示例#11

def test_sigmoid_fallback_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    class InterpreterWithoutSigmoid(PythonInterpreter):
        sigmoid_function_name = NotImplemented

        def interpret_sigmoid_expr(self, expr, **kwargs):
            return super(PythonInterpreter,
                         self).interpret_sigmoid_expr(expr, **kwargs)

    interpreter = InterpreterWithoutSigmoid()

    expected_code = """
import math
def score(input):
    return (1.0) / ((1.0) + (math.exp((0.0) - (2.0))))
"""

    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#12

文件： test_go.py 项目： BayesWitnesses/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
import "math"
func score(input []float64) float64 {
    return sigmoid(2.0)
}
func sigmoid(x float64) float64 {
    if (x < 0.0) {
        z := math.Exp(x)
        return z / (1.0 + z)
    }
    return 1.0 / (1.0 + math.Exp(-x))
}
"""

    interpreter = GoInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#13

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
<?php
function score(array $input) {
    return sigmoid(2.0);
}
function sigmoid($x) {
    if ($x < 0.0) {
        $z = exp($x);
        return $z / (1.0 + $z);
    }
    return 1.0 / (1.0 + exp(-$x));
}
"""

    interpreter = PhpInterpreter()
    utils.assert_code_equal(interpreter.interpret(expr), expected_code)

示例#14

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
#include <math.h>
double sigmoid(double x) {
    if (x < 0.0) {
        double z = exp(x);
        return z / (1.0 + z);
    }
    return 1.0 / (1.0 + exp(-x));
}
double score(double * input) {
    return sigmoid(2.0);
}
"""

    interpreter = CInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#15

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    interpreter = JavaInterpreter()

    expected_code = """
public class Model {
    public static double score(double[] input) {
        return sigmoid(2.0);
    }
    private static double sigmoid(double x) {
        if (x < 0.0) {
            double z = Math.exp(x);
            return z / (1.0 + z);
        }
        return 1.0 / (1.0 + Math.exp(-x));
    }
}"""

    utils.assert_code_equal(interpreter.interpret(expr), expected_code)

示例#16

文件： test_visual_basic.py 项目： BayesWitnesses/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
Module Model
Function Score(ByRef inputVector() As Double) As Double
    Score = Sigmoid(2.0)
End Function
Function Sigmoid(ByVal number As Double) As Double
    If number < 0.0 Then
        Dim z As Double
        z = Math.Exp(number)
        Sigmoid = z / (1.0 + z)
        Exit Function
    End If
    Sigmoid = 1.0 / (1.0 + Math.Exp(-number))
End Function
End Module
"""

    interpreter = VisualBasicInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#17

def test_statsmodels_glm_logit_link_func():
    estimator = utils.StatsmodelsSklearnLikeWrapper(
        sm.GLM,
        dict(init=dict(
            family=sm.families.Binomial(
                sm.families.links.logit())),
             fit=dict(maxiter=1)))
    estimator = estimator.fit([[1], [2]], [0.1, 0.2])

    assembler = assemblers.StatsmodelsModelAssemblerSelector(estimator)
    actual = assembler.assemble()

    expected = ast.SigmoidExpr(
        ast.BinNumExpr(
            ast.NumVal(0.0),
            ast.BinNumExpr(
                ast.FeatureRef(0),
                ast.NumVal(-0.8567815987),
                ast.BinNumOpType.MUL),
            ast.BinNumOpType.ADD))

    assert utils.cmp_exprs(actual, expected)

示例#18

文件： test_c_sharp.py 项目： BayesWitnesses/m2cgen

def test_sigmoid_expr():
    expr = ast.SigmoidExpr(ast.NumVal(2.0))

    expected_code = """
using static System.Math;
namespace ML {
    public static class Model {
        public static double Score(double[] input) {
            return Sigmoid(2.0);
        }
        private static double Sigmoid(double x) {
            if (x < 0.0) {
                double z = Exp(x);
                return z / (1.0 + z);
            }
            return 1.0 / (1.0 + Exp(-x));
        }
    }
}
"""

    interpreter = CSharpInterpreter()
    assert_code_equal(interpreter.interpret(expr), expected_code)

示例#19

def test_binary_classification():
    estimator = xgb.XGBClassifier(n_estimators=2, random_state=1, max_depth=1)
    utils.get_binary_classification_model_trainer()(estimator)

    assembler = XGBoostModelAssemblerSelector(estimator)
    actual = assembler.assemble()

    sigmoid = ast.SigmoidExpr(ast.BinNumExpr(
        ast.IfExpr(
            ast.CompExpr(ast.FeatureRef(20), ast.NumVal(16.795),
                         ast.CompOpType.GTE), ast.NumVal(-0.5178947448730469),
            ast.NumVal(0.4880000054836273)),
        ast.IfExpr(
            ast.CompExpr(ast.FeatureRef(27), ast.NumVal(0.142349988),
                         ast.CompOpType.GTE), ast.NumVal(-0.4447747468948364),
            ast.NumVal(0.39517202973365784)), ast.BinNumOpType.ADD),
                              to_reuse=True)

    expected = ast.VectorVal([
        ast.BinNumExpr(ast.NumVal(1), sigmoid, ast.BinNumOpType.SUB), sigmoid
    ])

    assert utils.cmp_exprs(actual, expected)

示例#20

文件： test_lightgbm.py 项目： BayesWitnesses/m2cgen

def test_simple_sigmoid_output_transform():
    estimator = lgb.LGBMRegressor(n_estimators=2,
                                  random_state=1,
                                  max_depth=1,
                                  objective="cross_entropy")
    utils.get_bounded_regression_model_trainer()(estimator)

    assembler = LightGBMModelAssembler(estimator)
    actual = assembler.assemble()

    expected = ast.SigmoidExpr(
        ast.BinNumExpr(
            ast.IfExpr(
                ast.CompExpr(ast.FeatureRef(12), ast.NumVal(19.23),
                             ast.CompOpType.GT), ast.NumVal(4.002437528537838),
                ast.NumVal(4.090096709787509)),
            ast.IfExpr(
                ast.CompExpr(ast.FeatureRef(12),
                             ast.NumVal(14.895), ast.CompOpType.GT),
                ast.NumVal(-0.0417499606641773),
                ast.NumVal(0.02069953712454655)), ast.BinNumOpType.ADD))

    assert utils.cmp_exprs(actual, expected)

示例#21

文件： test_lightgbm.py 项目： BayesWitnesses/m2cgen

def test_binary_classification():
    estimator = lgb.LGBMClassifier(n_estimators=2, random_state=1, max_depth=1)
    utils.get_binary_classification_model_trainer()(estimator)

    assembler = LightGBMModelAssembler(estimator)
    actual = assembler.assemble()

    sigmoid = ast.SigmoidExpr(ast.BinNumExpr(
        ast.IfExpr(
            ast.CompExpr(ast.FeatureRef(20), ast.NumVal(16.795),
                         ast.CompOpType.GT), ast.NumVal(0.27502096830384837),
            ast.NumVal(0.6391171126839048)),
        ast.IfExpr(
            ast.CompExpr(ast.FeatureRef(27), ast.NumVal(0.14205),
                         ast.CompOpType.GT), ast.NumVal(-0.21340153096570616),
            ast.NumVal(0.11583109256834748)), ast.BinNumOpType.ADD),
                              to_reuse=True)

    expected = ast.VectorVal([
        ast.BinNumExpr(ast.NumVal(1), sigmoid, ast.BinNumOpType.SUB), sigmoid
    ])

    assert utils.cmp_exprs(actual, expected)

示例#22

文件： test_lightgbm.py 项目： BayesWitnesses/m2cgen

def test_bin_class_sigmoid_output_transform():
    estimator = lgb.LGBMClassifier(n_estimators=1,
                                   random_state=1,
                                   max_depth=1,
                                   sigmoid=0.5)
    utils.get_binary_classification_model_trainer()(estimator)

    assembler = LightGBMModelAssembler(estimator)
    actual = assembler.assemble()

    sigmoid = ast.SigmoidExpr(ast.BinNumExpr(
        ast.NumVal(0.5),
        ast.IfExpr(
            ast.CompExpr(ast.FeatureRef(20), ast.NumVal(16.795),
                         ast.CompOpType.GT), ast.NumVal(0.5500419366076967),
            ast.NumVal(1.2782342253678096)), ast.BinNumOpType.MUL),
                              to_reuse=True)

    expected = ast.VectorVal([
        ast.BinNumExpr(ast.NumVal(1), sigmoid, ast.BinNumOpType.SUB), sigmoid
    ])

    assert utils.cmp_exprs(actual, expected)

示例#23

文件： boosting.py 项目： BayesWitnesses/m2cgen

 def _bin_class_convert_output(self, expr, to_reuse=True):
     return ast.SigmoidExpr(expr, to_reuse=to_reuse)

示例#24

 def _logit_inversed(self, ast_to_transform):
     return ast.SigmoidExpr(ast_to_transform)

示例#25

文件： test_ast.py 项目： BayesWitnesses/m2cgen

    assert ast.count_exprs(
        ast.BinNumExpr(ast.NumVal(1), ast.NumVal(2), ast.BinNumOpType.ADD),
        exclude_list={ast.BinNumExpr}
    ) == 2


EXPR_WITH_ALL_EXPRS = ast.BinVectorNumExpr(
    ast.BinVectorExpr(
        ast.VectorVal([
            ast.AbsExpr(ast.NumVal(-2)),
            ast.AtanExpr(ast.NumVal(2)),
            ast.ExpExpr(ast.NumVal(2)),
            ast.LogExpr(ast.NumVal(2)),
            ast.Log1pExpr(ast.NumVal(2)),
            ast.SigmoidExpr(ast.NumVal(2)),
            ast.SqrtExpr(ast.NumVal(2)),
            ast.PowExpr(ast.NumVal(2), ast.NumVal(3)),
            ast.TanhExpr(ast.NumVal(1)),
            ast.BinNumExpr(
                ast.NumVal(0),
                ast.FeatureRef(0),
                ast.BinNumOpType.ADD)
        ]),
        ast.IdExpr(
            ast.SoftmaxExpr([
                ast.NumVal(1),
                ast.NumVal(2),
                ast.NumVal(3),
                ast.NumVal(4),
                ast.NumVal(5),