Java Code Examples for org.apache.commons.math3.util.FastMath#tanh()

The following examples show how to use org.apache.commons.math3.util.FastMath#tanh() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source File: DerivativeTests.java    From deeplearning4j with Apache License 2.0 6 votes vote down vote up 
@Test
public void testTanhDerivative() {

    //Derivative of sigmoid: ds(x)/dx = s(x)*(1-s(x))
    //s(x) = 1 / (exp(-x) + 1)
    INDArray z = Nd4j.zeros(100);
    double[] expOut = new double[100];
    for (int i = 0; i < 100; i++) {
        double x = 0.1 * (i - 50);
        z.putScalar(i, x);
        double tanh = FastMath.tanh(x);
        expOut[i] = 1.0 - tanh * tanh;
    }

    INDArray zPrime = Nd4j.getExecutioner().exec(new TanhDerivative(z));

    for (int i = 0; i < 100; i++) {
        double relError = Math.abs(expOut[i] - zPrime.getDouble(i))
                        / (Math.abs(expOut[i]) + Math.abs(zPrime.getDouble(i)));
        assertTrue(relError < REL_ERROR_TOLERANCE);
    }
}
Example 2
Source File: Tanh.java    From astor with GNU General Public License v2.0 5 votes vote down vote up 
/** {@inheritDoc} */
public UnivariateFunction derivative() {
    return new UnivariateFunction() {
        /** {@inheritDoc} */
        public double value(double x) {
            final double tanhX = FastMath.tanh(x);
            return 1 - tanhX * tanhX;
        }
    };
}
Example 3
Source File: DSCompiler.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** Compute hyperbolic tangent of a derivative structure.
 * @param operand array holding the operand
 * @param operandOffset offset of the operand in its array
 * @param result array where result must be stored (for
 * hyperbolic tangent the result array <em>cannot</em> be the input
 * array)
 * @param resultOffset offset of the result in its array
 */
public void tanh(final double[] operand, final int operandOffset,
                 final double[] result, final int resultOffset) {

    // create the function value and derivatives
    final double[] function = new double[1 + order];
    final double t = FastMath.tanh(operand[operandOffset]);
    function[0] = t;

    if (order > 0) {

        // the nth order derivative of tanh has the form:
        // dn(tanh(x)/dxn = P_n(tanh(x))
        // where P_n(t) is a degree n+1 polynomial with same parity as n+1
        // P_0(t) = t, P_1(t) = 1 - t^2, P_2(t) = -2 t (1 - t^2) ...
        // the general recurrence relation for P_n is:
        // P_n(x) = (1-t^2) P_(n-1)'(t)
        // as per polynomial parity, we can store coefficients of both P_(n-1) and P_n in the same array
        final double[] p = new double[order + 2];
        p[1] = 1;
        final double t2 = t * t;
        for (int n = 1; n <= order; ++n) {

            // update and evaluate polynomial P_n(t)
            double v = 0;
            p[n + 1] = -n * p[n];
            for (int k = n + 1; k >= 0; k -= 2) {
                v = v * t2 + p[k];
                if (k > 2) {
                    p[k - 2] = (k - 1) * p[k - 1] - (k - 3) * p[k - 3];
                } else if (k == 2) {
                    p[0] = p[1];
                }
            }
            if ((n & 0x1) == 0) {
                v *= t;
            }

            function[n] = v;

        }
    }

    // apply function composition
    compose(operand, operandOffset, function, result, resultOffset);

}
Example 4
Source File: Builtin.java    From systemds with Apache License 2.0 4 votes vote down vote up 
@Override
public double execute (double in) {
	switch(bFunc) {
		case SIN:    return FASTMATH ? FastMath.sin(in) : Math.sin(in);
		case COS:    return FASTMATH ? FastMath.cos(in) : Math.cos(in);
		case TAN:    return FASTMATH ? FastMath.tan(in) : Math.tan(in);
		case ASIN:   return FASTMATH ? FastMath.asin(in) : Math.asin(in);
		case ACOS:   return FASTMATH ? FastMath.acos(in) : Math.acos(in);
		case ATAN:   return Math.atan(in); //faster in Math
		// FastMath.*h is faster 98% of time than Math.*h in initial micro-benchmarks
		case SINH:   return FASTMATH ? FastMath.sinh(in) : Math.sinh(in);
		case COSH:   return FASTMATH ? FastMath.cosh(in) : Math.cosh(in);
		case TANH:   return FASTMATH ? FastMath.tanh(in) : Math.tanh(in);
		case CEIL:   return FASTMATH ? FastMath.ceil(in) : Math.ceil(in);
		case FLOOR:  return FASTMATH ? FastMath.floor(in) : Math.floor(in);
		case LOG:    return Math.log(in); //faster in Math
		case LOG_NZ: return (in==0) ? 0 : Math.log(in); //faster in Math
		case ABS:    return Math.abs(in); //no need for FastMath
		case SIGN:   return FASTMATH ? FastMath.signum(in) : Math.signum(in);
		case SQRT:   return Math.sqrt(in); //faster in Math
		case EXP:    return FASTMATH ? FastMath.exp(in) : Math.exp(in);
		case ROUND: return Math.round(in); //no need for FastMath
		
		case PLOGP:
			if (in == 0.0)
				return 0.0;
			else if (in < 0)
				return Double.NaN;
			else //faster in Math
				return in * Math.log(in);
		
		case SPROP:
			//sample proportion: P*(1-P)
			return in * (1 - in); 

		case SIGMOID:
			//sigmoid: 1/(1+exp(-x))
			return FASTMATH ? 1 / (1 + FastMath.exp(-in))  : 1 / (1 + Math.exp(-in));
		
		case ISNA: return Double.isNaN(in) ? 1 : 0;
		case ISNAN: return Double.isNaN(in) ? 1 : 0;
		case ISINF: return Double.isInfinite(in) ? 1 : 0;
		
		default:
			throw new DMLRuntimeException("Builtin.execute(): Unknown operation: " + bFunc);
	}
}
Example 5
Source File: Tanh.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** {@inheritDoc} */
public double value(double x) {
    return FastMath.tanh(x);
}
Example 6
Source File: Tanh.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** {@inheritDoc} */
public double value(double x) {
    return FastMath.tanh(x);
}
Example 7
Source File: DSCompiler.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** Compute hyperbolic tangent of a derivative structure.
 * @param operand array holding the operand
 * @param operandOffset offset of the operand in its array
 * @param result array where result must be stored (for
 * hyperbolic tangent the result array <em>cannot</em> be the input
 * array)
 * @param resultOffset offset of the result in its array
 */
public void tanh(final double[] operand, final int operandOffset,
                 final double[] result, final int resultOffset) {

    // create the function value and derivatives
    final double[] function = new double[1 + order];
    final double t = FastMath.tanh(operand[operandOffset]);
    function[0] = t;

    if (order > 0) {

        // the nth order derivative of tanh has the form:
        // dn(tanh(x)/dxn = P_n(tanh(x))
        // where P_n(t) is a degree n+1 polynomial with same parity as n+1
        // P_0(t) = t, P_1(t) = 1 - t^2, P_2(t) = -2 t (1 - t^2) ...
        // the general recurrence relation for P_n is:
        // P_n(x) = (1-t^2) P_(n-1)'(t)
        // as per polynomial parity, we can store coefficients of both P_(n-1) and P_n in the same array
        final double[] p = new double[order + 2];
        p[1] = 1;
        final double t2 = t * t;
        for (int n = 1; n <= order; ++n) {

            // update and evaluate polynomial P_n(t)
            double v = 0;
            p[n + 1] = -n * p[n];
            for (int k = n + 1; k >= 0; k -= 2) {
                v = v * t2 + p[k];
                if (k > 2) {
                    p[k - 2] = (k - 1) * p[k - 1] - (k - 3) * p[k - 3];
                } else if (k == 2) {
                    p[0] = p[1];
                }
            }
            if ((n & 0x1) == 0) {
                v *= t;
            }

            function[n] = v;

        }
    }

    // apply function composition
    compose(operand, operandOffset, function, result, resultOffset);

}
Example 8
Source File: SparseGradient.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** {@inheritDoc} */
public SparseGradient tanh() {
    final double t = FastMath.tanh(value);
    return new SparseGradient(t, 1 - t * t, derivatives);
}
Example 9
Source File: DSCompiler.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** Compute hyperbolic tangent of a derivative structure.
 * @param operand array holding the operand
 * @param operandOffset offset of the operand in its array
 * @param result array where result must be stored (for
 * hyperbolic tangent the result array <em>cannot</em> be the input
 * array)
 * @param resultOffset offset of the result in its array
 */
public void tanh(final double[] operand, final int operandOffset,
                 final double[] result, final int resultOffset) {

    // create the function value and derivatives
    final double[] function = new double[1 + order];
    final double t = FastMath.tanh(operand[operandOffset]);
    function[0] = t;

    if (order > 0) {

        // the nth order derivative of tanh has the form:
        // dn(tanh(x)/dxn = P_n(tanh(x))
        // where P_n(t) is a degree n+1 polynomial with same parity as n+1
        // P_0(t) = t, P_1(t) = 1 - t^2, P_2(t) = -2 t (1 - t^2) ...
        // the general recurrence relation for P_n is:
        // P_n(x) = (1-t^2) P_(n-1)'(t)
        // as per polynomial parity, we can store coefficients of both P_(n-1) and P_n in the same array
        final double[] p = new double[order + 2];
        p[1] = 1;
        final double t2 = t * t;
        for (int n = 1; n <= order; ++n) {

            // update and evaluate polynomial P_n(t)
            double v = 0;
            p[n + 1] = -n * p[n];
            for (int k = n + 1; k >= 0; k -= 2) {
                v = v * t2 + p[k];
                if (k > 2) {
                    p[k - 2] = (k - 1) * p[k - 1] - (k - 3) * p[k - 3];
                } else if (k == 2) {
                    p[0] = p[1];
                }
            }
            if ((n & 0x1) == 0) {
                v *= t;
            }

            function[n] = v;

        }
    }

    // apply function composition
    compose(operand, operandOffset, function, result, resultOffset);

}
Example 10
Source File: LibSpoofPrimitives.java    From systemds with Apache License 2.0 4 votes vote down vote up 
public static double[] vectTanhWrite(double[] a, int[] aix, int ai, int alen, int len) {
	double[] c = allocVector(len, true);
	for( int j = ai; j < ai+alen; j++ )
		c[aix[j]] = FastMath.tanh(a[j]);
	return c;
}
Example 11
Source File: Tanh.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** {@inheritDoc} */
public double value(double x) {
    return FastMath.tanh(x);
}
Example 12
Source File: DSCompiler.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** Compute hyperbolic tangent of a derivative structure.
 * @param operand array holding the operand
 * @param operandOffset offset of the operand in its array
 * @param result array where result must be stored (for
 * hyperbolic tangent the result array <em>cannot</em> be the input
 * array)
 * @param resultOffset offset of the result in its array
 */
public void tanh(final double[] operand, final int operandOffset,
                 final double[] result, final int resultOffset) {

    // create the function value and derivatives
    final double[] function = new double[1 + order];
    final double t = FastMath.tanh(operand[operandOffset]);
    function[0] = t;

    if (order > 0) {

        // the nth order derivative of tanh has the form:
        // dn(tanh(x)/dxn = P_n(tanh(x))
        // where P_n(t) is a degree n+1 polynomial with same parity as n+1
        // P_0(t) = t, P_1(t) = 1 - t^2, P_2(t) = -2 t (1 - t^2) ...
        // the general recurrence relation for P_n is:
        // P_n(x) = (1-t^2) P_(n-1)'(t)
        // as per polynomial parity, we can store coefficients of both P_(n-1) and P_n in the same array
        final double[] p = new double[order + 2];
        p[1] = 1;
        final double t2 = t * t;
        for (int n = 1; n <= order; ++n) {

            // update and evaluate polynomial P_n(t)
            double v = 0;
            p[n + 1] = -n * p[n];
            for (int k = n + 1; k >= 0; k -= 2) {
                v = v * t2 + p[k];
                if (k > 2) {
                    p[k - 2] = (k - 1) * p[k - 1] - (k - 3) * p[k - 3];
                } else if (k == 2) {
                    p[0] = p[1];
                }
            }
            if ((n & 0x1) == 0) {
                v *= t;
            }

            function[n] = v;

        }
    }

    // apply function composition
    compose(operand, operandOffset, function, result, resultOffset);

}
Example 13
Source File: Builtin.java    From systemds with Apache License 2.0 4 votes vote down vote up 
@Override
public double execute (double in) {
	switch(bFunc) {
		case SIN:    return FASTMATH ? FastMath.sin(in) : Math.sin(in);
		case COS:    return FASTMATH ? FastMath.cos(in) : Math.cos(in);
		case TAN:    return FASTMATH ? FastMath.tan(in) : Math.tan(in);
		case ASIN:   return FASTMATH ? FastMath.asin(in) : Math.asin(in);
		case ACOS:   return FASTMATH ? FastMath.acos(in) : Math.acos(in);
		case ATAN:   return Math.atan(in); //faster in Math
		// FastMath.*h is faster 98% of time than Math.*h in initial micro-benchmarks
		case SINH:   return FASTMATH ? FastMath.sinh(in) : Math.sinh(in);
		case COSH:   return FASTMATH ? FastMath.cosh(in) : Math.cosh(in);
		case TANH:   return FASTMATH ? FastMath.tanh(in) : Math.tanh(in);
		case CEIL:   return FASTMATH ? FastMath.ceil(in) : Math.ceil(in);
		case FLOOR:  return FASTMATH ? FastMath.floor(in) : Math.floor(in);
		case LOG:    return Math.log(in); //faster in Math
		case LOG_NZ: return (in==0) ? 0 : Math.log(in); //faster in Math
		case ABS:    return Math.abs(in); //no need for FastMath
		case SIGN:   return FASTMATH ? FastMath.signum(in) : Math.signum(in);
		case SQRT:   return Math.sqrt(in); //faster in Math
		case EXP:    return FASTMATH ? FastMath.exp(in) : Math.exp(in);
		case ROUND: return Math.round(in); //no need for FastMath
		
		case PLOGP:
			if (in == 0.0)
				return 0.0;
			else if (in < 0)
				return Double.NaN;
			else //faster in Math
				return in * Math.log(in);
		
		case SPROP:
			//sample proportion: P*(1-P)
			return in * (1 - in); 

		case SIGMOID:
			//sigmoid: 1/(1+exp(-x))
			return FASTMATH ? 1 / (1 + FastMath.exp(-in))  : 1 / (1 + Math.exp(-in));
		
		case ISNA: return Double.isNaN(in) ? 1 : 0;
		case ISNAN: return Double.isNaN(in) ? 1 : 0;
		case ISINF: return Double.isInfinite(in) ? 1 : 0;
		
		default:
			throw new DMLRuntimeException("Builtin.execute(): Unknown operation: " + bFunc);
	}
}
Example 14
Source File: HyperbolicTangentKernel.java    From clust4j with Apache License 2.0 4 votes vote down vote up 
@Override
public double getSimilarity(double[] a, double[] b) {
	return FastMath.tanh(getAlpha() * VecUtils.innerProduct(a, b) + getConstant());
}
Example 15
Source File: Math_10_DSCompiler_s.java    From coming with MIT License 4 votes vote down vote up 
/** Compute hyperbolic tangent of a derivative structure.
 * @param operand array holding the operand
 * @param operandOffset offset of the operand in its array
 * @param result array where result must be stored (for
 * hyperbolic tangent the result array <em>cannot</em> be the input
 * array)
 * @param resultOffset offset of the result in its array
 */
public void tanh(final double[] operand, final int operandOffset,
                 final double[] result, final int resultOffset) {

    // create the function value and derivatives
    final double[] function = new double[1 + order];
    final double t = FastMath.tanh(operand[operandOffset]);
    function[0] = t;

    if (order > 0) {

        // the nth order derivative of tanh has the form:
        // dn(tanh(x)/dxn = P_n(tanh(x))
        // where P_n(t) is a degree n+1 polynomial with same parity as n+1
        // P_0(t) = t, P_1(t) = 1 - t^2, P_2(t) = -2 t (1 - t^2) ...
        // the general recurrence relation for P_n is:
        // P_n(x) = (1-t^2) P_(n-1)'(t)
        // as per polynomial parity, we can store coefficients of both P_(n-1) and P_n in the same array
        final double[] p = new double[order + 2];
        p[1] = 1;
        final double t2 = t * t;
        for (int n = 1; n <= order; ++n) {

            // update and evaluate polynomial P_n(t)
            double v = 0;
            p[n + 1] = -n * p[n];
            for (int k = n + 1; k >= 0; k -= 2) {
                v = v * t2 + p[k];
                if (k > 2) {
                    p[k - 2] = (k - 1) * p[k - 1] - (k - 3) * p[k - 3];
                } else if (k == 2) {
                    p[0] = p[1];
                }
            }
            if ((n & 0x1) == 0) {
                v *= t;
            }

            function[n] = v;

        }
    }

    // apply function composition
    compose(operand, operandOffset, function, result, resultOffset);

}
Example 16
Source File: Tanh.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** {@inheritDoc} */
public double value(double x) {
    return FastMath.tanh(x);
}
Example 17
Source File: LibSpoofPrimitives.java    From systemds with Apache License 2.0 4 votes vote down vote up 
public static double[] vectTanhWrite(double[] a, int[] aix, int ai, int alen, int len) {
	double[] c = allocVector(len, true);
	for( int j = ai; j < ai+alen; j++ )
		c[aix[j]] = FastMath.tanh(a[j]);
	return c;
}
Example 18
Source File: SparseGradient.java    From astor with GNU General Public License v2.0 4 votes vote down vote up 
/** {@inheritDoc} */
public SparseGradient tanh() {
    final double t = FastMath.tanh(value);
    return new SparseGradient(t, 1 - t * t, derivatives);
}
Example 19
Source File: LibSpoofPrimitives.java    From systemds with Apache License 2.0 4 votes vote down vote up 
public static void vectTanhAdd(double[] a, double[] c, int[] aix, int ai, int ci, int alen, int len) {
	for( int j = ai; j < ai+alen; j++ )
		c[ci + aix[j]] += FastMath.tanh(a[j]);
}
Example 20
Source File: LibSpoofPrimitives.java    From systemds with Apache License 2.0 4 votes vote down vote up 
public static void vectTanhAdd(double[] a, double[] c, int ai, int ci, int len) {
	for( int j = ai; j < ai+len; j++, ci++)
		c[ci] +=  FastMath.tanh(a[j]);
}