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vllm/lib/python3.10/site-packages/mpmath/calculus/__init__.py

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+from . import calculus
+# XXX: hack to set methods
+from . import approximation
+from . import differentiation
+from . import extrapolation
+from . import polynomials

vllm/lib/python3.10/site-packages/mpmath/calculus/differentiation.py

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+from ..libmp.backend import xrange
+from .calculus import defun
+
+try:
+    iteritems = dict.iteritems
+except AttributeError:
+    iteritems = dict.items
+
+#----------------------------------------------------------------------------#
+#                                Differentiation                             #
+#----------------------------------------------------------------------------#
+
+@defun
+def difference(ctx, s, n):
+    r"""
+    Given a sequence `(s_k)` containing at least `n+1` items, returns the
+    `n`-th forward difference,
+
+    .. math ::
+
+        \Delta^n = \sum_{k=0}^{\infty} (-1)^{k+n} {n \choose k} s_k.
+    """
+    n = int(n)
+    d = ctx.zero
+    b = (-1) ** (n & 1)
+    for k in xrange(n+1):
+        d += b * s[k]
+        b = (b * (k-n)) // (k+1)
+    return d
+
+def hsteps(ctx, f, x, n, prec, **options):
+    singular = options.get('singular')
+    addprec = options.get('addprec', 10)
+    direction = options.get('direction', 0)
+    workprec = (prec+2*addprec) * (n+1)
+    orig = ctx.prec
+    try:
+        ctx.prec = workprec
+        h = options.get('h')
+        if h is None:
+            if options.get('relative'):
+                hextramag = int(ctx.mag(x))
+            else:
+                hextramag = 0
+            h = ctx.ldexp(1, -prec-addprec-hextramag)
+        else:
+            h = ctx.convert(h)
+        # Directed: steps x, x+h, ... x+n*h
+        direction = options.get('direction', 0)
+        if direction:
+            h *= ctx.sign(direction)
+            steps = xrange(n+1)
+            norm = h
+        # Central: steps x-n*h, x-(n-2)*h ..., x, ..., x+(n-2)*h, x+n*h
+        else:
+            steps = xrange(-n, n+1, 2)
+            norm = (2*h)
+        # Perturb
+        if singular:
+            x += 0.5*h
+        values = [f(x+k*h) for k in steps]
+        return values, norm, workprec
+    finally:
+        ctx.prec = orig
+
+
+@defun
+def diff(ctx, f, x, n=1, **options):
+    r"""
+    Numerically computes the derivative of `f`, `f'(x)`, or generally for
+    an integer `n \ge 0`, the `n`-th derivative `f^{(n)}(x)`.
+    A few basic examples are::
+
+        >>> from mpmath import *
+        >>> mp.dps = 15; mp.pretty = True
+        >>> diff(lambda x: x**2 + x, 1.0)
+        3.0
+        >>> diff(lambda x: x**2 + x, 1.0, 2)
+        2.0
+        >>> diff(lambda x: x**2 + x, 1.0, 3)
+        0.0
+        >>> nprint([diff(exp, 3, n) for n in range(5)])   # exp'(x) = exp(x)
+        [20.0855, 20.0855, 20.0855, 20.0855, 20.0855]
+
+    Even more generally, given a tuple of arguments `(x_1, \ldots, x_k)`
+    and order `(n_1, \ldots, n_k)`, the partial derivative
+    `f^{(n_1,\ldots,n_k)}(x_1,\ldots,x_k)` is evaluated. For example::
+
+        >>> diff(lambda x,y: 3*x*y + 2*y - x, (0.25, 0.5), (0,1))
+        2.75
+        >>> diff(lambda x,y: 3*x*y + 2*y - x, (0.25, 0.5), (1,1))
+        3.0
+
+    **Options**
+
+    The following optional keyword arguments are recognized:
+
+    ``method``
+        Supported methods are ``'step'`` or ``'quad'``: derivatives may be
+        computed using either a finite difference with a small step
+        size `h` (default), or numerical quadrature.
+    ``direction``
+        Direction of finite difference: can be -1 for a left
+        difference, 0 for a central difference (default), or +1
+        for a right difference; more generally can be any complex number.
+    ``addprec``
+        Extra precision for `h` used to account for the function's
+        sensitivity to perturbations (default = 10).
+    ``relative``
+        Choose `h` relative to the magnitude of `x`, rather than an
+        absolute value; useful for large or tiny `x` (default = False).
+    ``h``
+        As an alternative to ``addprec`` and ``relative``, manually
+        select the step size `h`.
+    ``singular``
+        If True, evaluation exactly at the point `x` is avoided; this is
+        useful for differentiating functions with removable singularities.
+        Default = False.
+    ``radius``
+        Radius of integration contour (with ``method = 'quad'``).
+        Default = 0.25. A larger radius typically is faster and more
+        accurate, but it must be chosen so that `f` has no
+        singularities within the radius from the evaluation point.
+
+    A finite difference requires `n+1` function evaluations and must be
+    performed at `(n+1)` times the target precision. Accordingly, `f` must
+    support fast evaluation at high precision.
+
+    With integration, a larger number of function evaluations is
+    required, but not much extra precision is required. For high order
+    derivatives, this method may thus be faster if f is very expensive to
+    evaluate at high precision.
+
+    **Further examples**
+
+    The direction option is useful for computing left- or right-sided
+    derivatives of nonsmooth functions::
+
+        >>> diff(abs, 0, direction=0)
+        0.0
+        >>> diff(abs, 0, direction=1)
+        1.0
+        >>> diff(abs, 0, direction=-1)
+        -1.0
+
+    More generally, if the direction is nonzero, a right difference
+    is computed where the step size is multiplied by sign(direction).
+    For example, with direction=+j, the derivative from the positive
+    imaginary direction will be computed::
+
+        >>> diff(abs, 0, direction=j)
+        (0.0 - 1.0j)
+
+    With integration, the result may have a small imaginary part
+    even even if the result is purely real::
+
+        >>> diff(sqrt, 1, method='quad')    # doctest:+ELLIPSIS
+        (0.5 - 4.59...e-26j)
+        >>> chop(_)
+        0.5
+
+    Adding precision to obtain an accurate value::
+
+        >>> diff(cos, 1e-30)
+        0.0
+        >>> diff(cos, 1e-30, h=0.0001)
+        -9.99999998328279e-31
+        >>> diff(cos, 1e-30, addprec=100)
+        -1.0e-30
+
+    """
+    partial = False
+    try:
+        orders = list(n)
+        x = list(x)
+        partial = True
+    except TypeError:
+        pass
+    if partial:
+        x = [ctx.convert(_) for _ in x]
+        return _partial_diff(ctx, f, x, orders, options)
+    method = options.get('method', 'step')
+    if n == 0 and method != 'quad' and not options.get('singular'):
+        return f(ctx.convert(x))
+    prec = ctx.prec
+    try:
+        if method == 'step':
+            values, norm, workprec = hsteps(ctx, f, x, n, prec, **options)
+            ctx.prec = workprec
+            v = ctx.difference(values, n) / norm**n
+        elif method == 'quad':
+            ctx.prec += 10
+            radius = ctx.convert(options.get('radius', 0.25))
+            def g(t):
+                rei = radius*ctx.expj(t)
+                z = x + rei
+                return f(z) / rei**n
+            d = ctx.quadts(g, [0, 2*ctx.pi])
+            v = d * ctx.factorial(n) / (2*ctx.pi)
+        else:
+            raise ValueError("unknown method: %r" % method)
+    finally:
+        ctx.prec = prec
+    return +v
+
+def _partial_diff(ctx, f, xs, orders, options):
+    if not orders:
+        return f()
+    if not sum(orders):
+        return f(*xs)
+    i = 0
+    for i in range(len(orders)):
+        if orders[i]:
+            break
+    order = orders[i]
+    def fdiff_inner(*f_args):
+        def inner(t):
+            return f(*(f_args[:i] + (t,) + f_args[i+1:]))
+        return ctx.diff(inner, f_args[i], order, **options)
+    orders[i] = 0
+    return _partial_diff(ctx, fdiff_inner, xs, orders, options)
+
+@defun
+def diffs(ctx, f, x, n=None, **options):
+    r"""
+    Returns a generator that yields the sequence of derivatives
+
+    .. math ::
+
+        f(x), f'(x), f''(x), \ldots, f^{(k)}(x), \ldots
+
+    With ``method='step'``, :func:`~mpmath.diffs` uses only `O(k)`
+    function evaluations to generate the first `k` derivatives,
+    rather than the roughly `O(k^2)` evaluations
+    required if one calls :func:`~mpmath.diff` `k` separate times.
+
+    With `n < \infty`, the generator stops as soon as the
+    `n`-th derivative has been generated. If the exact number of
+    needed derivatives is known in advance, this is further
+    slightly more efficient.
+
+    Options are the same as for :func:`~mpmath.diff`.
+
+    **Examples**
+
+        >>> from mpmath import *
+        >>> mp.dps = 15
+        >>> nprint(list(diffs(cos, 1, 5)))
+        [0.540302, -0.841471, -0.540302, 0.841471, 0.540302, -0.841471]
+        >>> for i, d in zip(range(6), diffs(cos, 1)):
+        ...     print("%s %s" % (i, d))
+        ...
+        0 0.54030230586814
+        1 -0.841470984807897
+        2 -0.54030230586814
+        3 0.841470984807897
+        4 0.54030230586814
+        5 -0.841470984807897
+
+    """
+    if n is None:
+        n = ctx.inf
+    else:
+        n = int(n)
+    if options.get('method', 'step') != 'step':
+        k = 0
+        while k < n + 1:
+            yield ctx.diff(f, x, k, **options)
+            k += 1
+        return
+    singular = options.get('singular')
+    if singular:
+        yield ctx.diff(f, x, 0, singular=True)
+    else:
+        yield f(ctx.convert(x))
+    if n < 1:
+        return
+    if n == ctx.inf:
+        A, B = 1, 2
+    else:
+        A, B = 1, n+1
+    while 1:
+        callprec = ctx.prec
+        y, norm, workprec = hsteps(ctx, f, x, B, callprec, **options)
+        for k in xrange(A, B):
+            try:
+                ctx.prec = workprec
+                d = ctx.difference(y, k) / norm**k
+            finally:
+                ctx.prec = callprec
+            yield +d
+            if k >= n:
+                return
+        A, B = B, int(A*1.4+1)
+        B = min(B, n)
+
+def iterable_to_function(gen):
+    gen = iter(gen)
+    data = []
+    def f(k):
+        for i in xrange(len(data), k+1):
+            data.append(next(gen))
+        return data[k]
+    return f
+
+@defun
+def diffs_prod(ctx, factors):
+    r"""
+    Given a list of `N` iterables or generators yielding
+    `f_k(x), f'_k(x), f''_k(x), \ldots` for `k = 1, \ldots, N`,
+    generate `g(x), g'(x), g''(x), \ldots` where
+    `g(x) = f_1(x) f_2(x) \cdots f_N(x)`.
+
+    At high precision and for large orders, this is typically more efficient
+    than numerical differentiation if the derivatives of each `f_k(x)`
+    admit direct computation.
+
+    Note: This function does not increase the working precision internally,
+    so guard digits may have to be added externally for full accuracy.
+
+    **Examples**
+
+        >>> from mpmath import *
+        >>> mp.dps = 15; mp.pretty = True
+        >>> f = lambda x: exp(x)*cos(x)*sin(x)
+        >>> u = diffs(f, 1)
+        >>> v = mp.diffs_prod([diffs(exp,1), diffs(cos,1), diffs(sin,1)])
+        >>> next(u); next(v)
+        1.23586333600241
+        1.23586333600241
+        >>> next(u); next(v)
+        0.104658952245596
+        0.104658952245596
+        >>> next(u); next(v)
+        -5.96999877552086
+        -5.96999877552086
+        >>> next(u); next(v)
+        -12.4632923122697
+        -12.4632923122697
+
+    """
+    N = len(factors)
+    if N == 1:
+        for c in factors[0]:
+            yield c
+    else:
+        u = iterable_to_function(ctx.diffs_prod(factors[:N//2]))
+        v = iterable_to_function(ctx.diffs_prod(factors[N//2:]))
+        n = 0
+        while 1:
+            #yield sum(binomial(n,k)*u(n-k)*v(k) for k in xrange(n+1))
+            s = u(n) * v(0)
+            a = 1
+            for k in xrange(1,n+1):
+                a = a * (n-k+1) // k
+                s += a * u(n-k) * v(k)
+            yield s
+            n += 1
+
+def dpoly(n, _cache={}):
+    """
+    nth differentiation polynomial for exp (Faa di Bruno's formula).
+
+    TODO: most exponents are zero, so maybe a sparse representation
+    would be better.
+    """
+    if n in _cache:
+        return _cache[n]
+    if not _cache:
+        _cache[0] = {(0,):1}
+    R = dpoly(n-1)
+    R = dict((c+(0,),v) for (c,v) in iteritems(R))
+    Ra = {}
+    for powers, count in iteritems(R):
+        powers1 = (powers[0]+1,) + powers[1:]
+        if powers1 in Ra:
+            Ra[powers1] += count
+        else:
+            Ra[powers1] = count
+    for powers, count in iteritems(R):
+        if not sum(powers):
+            continue
+        for k,p in enumerate(powers):
+            if p:
+                powers2 = powers[:k] + (p-1,powers[k+1]+1) + powers[k+2:]
+                if powers2 in Ra:
+                    Ra[powers2] += p*count
+                else:
+                    Ra[powers2] = p*count
+    _cache[n] = Ra
+    return _cache[n]
+
+@defun
+def diffs_exp(ctx, fdiffs):
+    r"""
+    Given an iterable or generator yielding `f(x), f'(x), f''(x), \ldots`
+    generate `g(x), g'(x), g''(x), \ldots` where `g(x) = \exp(f(x))`.
+
+    At high precision and for large orders, this is typically more efficient
+    than numerical differentiation if the derivatives of `f(x)`
+    admit direct computation.
+
+    Note: This function does not increase the working precision internally,
+    so guard digits may have to be added externally for full accuracy.
+
+    **Examples**
+
+    The derivatives of the gamma function can be computed using
+    logarithmic differentiation::
+
+        >>> from mpmath import *
+        >>> mp.dps = 15; mp.pretty = True
+        >>>
+        >>> def diffs_loggamma(x):
+        ...     yield loggamma(x)
+        ...     i = 0
+        ...     while 1:
+        ...         yield psi(i,x)
+        ...         i += 1
+        ...
+        >>> u = diffs_exp(diffs_loggamma(3))
+        >>> v = diffs(gamma, 3)
+        >>> next(u); next(v)
+        2.0
+        2.0
+        >>> next(u); next(v)
+        1.84556867019693
+        1.84556867019693
+        >>> next(u); next(v)
+        2.49292999190269
+        2.49292999190269
+        >>> next(u); next(v)
+        3.44996501352367
+        3.44996501352367
+
+    """
+    fn = iterable_to_function(fdiffs)
+    f0 = ctx.exp(fn(0))
+    yield f0
+    i = 1
+    while 1:
+        s = ctx.mpf(0)
+        for powers, c in iteritems(dpoly(i)):
+            s += c*ctx.fprod(fn(k+1)**p for (k,p) in enumerate(powers) if p)
+        yield s * f0
+        i += 1
+
+@defun
+def differint(ctx, f, x, n=1, x0=0):
+    r"""
+    Calculates the Riemann-Liouville differintegral, or fractional
+    derivative, defined by
+
+    .. math ::
+
+        \,_{x_0}{\mathbb{D}}^n_xf(x) = \frac{1}{\Gamma(m-n)} \frac{d^m}{dx^m}
+        \int_{x_0}^{x}(x-t)^{m-n-1}f(t)dt
+
+    where `f` is a given (presumably well-behaved) function,
+    `x` is the evaluation point, `n` is the order, and `x_0` is
+    the reference point of integration (`m` is an arbitrary
+    parameter selected automatically).
+
+    With `n = 1`, this is just the standard derivative `f'(x)`; with `n = 2`,
+    the second derivative `f''(x)`, etc. With `n = -1`, it gives
+    `\int_{x_0}^x f(t) dt`, with `n = -2`
+    it gives `\int_{x_0}^x \left( \int_{x_0}^t f(u) du \right) dt`, etc.
+
+    As `n` is permitted to be any number, this operator generalizes
+    iterated differentiation and iterated integration to a single
+    operator with a continuous order parameter.
+
+    **Examples**
+
+    There is an exact formula for the fractional derivative of a
+    monomial `x^p`, which may be used as a reference. For example,
+    the following gives a half-derivative (order 0.5)::
+
+        >>> from mpmath import *
+        >>> mp.dps = 15; mp.pretty = True
+        >>> x = mpf(3); p = 2; n = 0.5
+        >>> differint(lambda t: t**p, x, n)
+        7.81764019044672
+        >>> gamma(p+1)/gamma(p-n+1) * x**(p-n)
+        7.81764019044672
+
+    Another useful test function is the exponential function, whose
+    integration / differentiation formula easy generalizes
+    to arbitrary order. Here we first compute a third derivative,
+    and then a triply nested integral. (The reference point `x_0`
+    is set to `-\infty` to avoid nonzero endpoint terms.)::
+
+        >>> differint(lambda x: exp(pi*x), -1.5, 3)
+        0.278538406900792
+        >>> exp(pi*-1.5) * pi**3
+        0.278538406900792
+        >>> differint(lambda x: exp(pi*x), 3.5, -3, -inf)
+        1922.50563031149
+        >>> exp(pi*3.5) / pi**3
+        1922.50563031149
+
+    However, for noninteger `n`, the differentiation formula for the
+    exponential function must be modified to give the same result as the
+    Riemann-Liouville differintegral::
+
+        >>> x = mpf(3.5)
+        >>> c = pi
+        >>> n = 1+2*j
+        >>> differint(lambda x: exp(c*x), x, n)
+        (-123295.005390743 + 140955.117867654j)
+        >>> x**(-n) * exp(c)**x * (x*c)**n * gammainc(-n, 0, x*c) / gamma(-n)
+        (-123295.005390743 + 140955.117867654j)
+
+
+    """
+    m = max(int(ctx.ceil(ctx.re(n)))+1, 1)
+    r = m-n-1
+    g = lambda x: ctx.quad(lambda t: (x-t)**r * f(t), [x0, x])
+    return ctx.diff(g, x, m) / ctx.gamma(m-n)
+
+@defun
+def diffun(ctx, f, n=1, **options):
+    r"""
+    Given a function `f`, returns a function `g(x)` that evaluates the nth
+    derivative `f^{(n)}(x)`::
+
+        >>> from mpmath import *
+        >>> mp.dps = 15; mp.pretty = True
+        >>> cos2 = diffun(sin)
+        >>> sin2 = diffun(sin, 4)
+        >>> cos(1.3), cos2(1.3)
+        (0.267498828624587, 0.267498828624587)
+        >>> sin(1.3), sin2(1.3)
+        (0.963558185417193, 0.963558185417193)
+
+    The function `f` must support arbitrary precision evaluation.
+    See :func:`~mpmath.diff` for additional details and supported
+    keyword options.
+    """
+    if n == 0:
+        return f
+    def g(x):
+        return ctx.diff(f, x, n, **options)
+    return g
+
+@defun
+def taylor(ctx, f, x, n, **options):
+    r"""
+    Produces a degree-`n` Taylor polynomial around the point `x` of the
+    given function `f`. The coefficients are returned as a list.
+
+        >>> from mpmath import *
+        >>> mp.dps = 15; mp.pretty = True
+        >>> nprint(chop(taylor(sin, 0, 5)))
+        [0.0, 1.0, 0.0, -0.166667, 0.0, 0.00833333]
+
+    The coefficients are computed using high-order numerical
+    differentiation. The function must be possible to evaluate
+    to arbitrary precision. See :func:`~mpmath.diff` for additional details
+    and supported keyword options.
+
+    Note that to evaluate the Taylor polynomial as an approximation
+    of `f`, e.g. with :func:`~mpmath.polyval`, the coefficients must be reversed,
+    and the point of the Taylor expansion must be subtracted from
+    the argument:
+
+        >>> p = taylor(exp, 2.0, 10)
+        >>> polyval(p[::-1], 2.5 - 2.0)
+        12.1824939606092
+        >>> exp(2.5)
+        12.1824939607035
+
+    """
+    gen = enumerate(ctx.diffs(f, x, n, **options))
+    if options.get("chop", True):
+        return [ctx.chop(d)/ctx.factorial(i) for i, d in gen]
+    else:
+        return [d/ctx.factorial(i) for i, d in gen]
+
+@defun
+def pade(ctx, a, L, M):
+    r"""
+    Computes a Pade approximation of degree `(L, M)` to a function.
+    Given at least `L+M+1` Taylor coefficients `a` approximating
+    a function `A(x)`, :func:`~mpmath.pade` returns coefficients of
+    polynomials `P, Q` satisfying
+
+    .. math ::
+
+        P = \sum_{k=0}^L p_k x^k
+
+        Q = \sum_{k=0}^M q_k x^k
+
+        Q_0 = 1
+
+        A(x) Q(x) = P(x) + O(x^{L+M+1})
+
+    `P(x)/Q(x)` can provide a good approximation to an analytic function
+    beyond the radius of convergence of its Taylor series (example
+    from G.A. Baker 'Essentials of Pade Approximants' Academic Press,
+    Ch.1A)::
+
+        >>> from mpmath import *
+        >>> mp.dps = 15; mp.pretty = True
+        >>> one = mpf(1)
+        >>> def f(x):
+        ...     return sqrt((one + 2*x)/(one + x))
+        ...
+        >>> a = taylor(f, 0, 6)
+        >>> p, q = pade(a, 3, 3)
+        >>> x = 10
+        >>> polyval(p[::-1], x)/polyval(q[::-1], x)
+        1.38169105566806
+        >>> f(x)
+        1.38169855941551
+
+    """
+    # To determine L+1 coefficients of P and M coefficients of Q
+    # L+M+1 coefficients of A must be provided
+    if len(a) < L+M+1:
+        raise ValueError("L+M+1 Coefficients should be provided")
+
+    if M == 0:
+        if L == 0:
+            return [ctx.one], [ctx.one]
+        else:
+            return a[:L+1], [ctx.one]
+
+    # Solve first
+    # a[L]*q[1] + ... + a[L-M+1]*q[M] = -a[L+1]
+    # ...
+    # a[L+M-1]*q[1] + ... + a[L]*q[M] = -a[L+M]
+    A = ctx.matrix(M)
+    for j in range(M):
+        for i in range(min(M, L+j+1)):
+            A[j, i] = a[L+j-i]
+    v = -ctx.matrix(a[(L+1):(L+M+1)])
+    x = ctx.lu_solve(A, v)
+    q = [ctx.one] + list(x)
+    # compute p
+    p = [0]*(L+1)
+    for i in range(L+1):
+        s = a[i]
+        for j in range(1, min(M,i) + 1):
+            s += q[j]*a[i-j]
+        p[i] = s
+    return p, q

vllm/lib/python3.10/site-packages/mpmath/functions/functions.py

@@ -0,0 +1,645 @@
+from ..libmp.backend import xrange
+
+class SpecialFunctions(object):
+    """
+    This class implements special functions using high-level code.
+
+    Elementary and some other functions (e.g. gamma function, basecase
+    hypergeometric series) are assumed to be predefined by the context as
+    "builtins" or "low-level" functions.
+    """
+    defined_functions = {}
+
+    # The series for the Jacobi theta functions converge for |q| < 1;
+    # in the current implementation they throw a ValueError for
+    # abs(q) > THETA_Q_LIM
+    THETA_Q_LIM = 1 - 10**-7
+
+    def __init__(self):
+        cls = self.__class__
+        for name in cls.defined_functions:
+            f, wrap = cls.defined_functions[name]
+            cls._wrap_specfun(name, f, wrap)
+
+        self.mpq_1 = self._mpq((1,1))
+        self.mpq_0 = self._mpq((0,1))
+        self.mpq_1_2 = self._mpq((1,2))
+        self.mpq_3_2 = self._mpq((3,2))
+        self.mpq_1_4 = self._mpq((1,4))
+        self.mpq_1_16 = self._mpq((1,16))
+        self.mpq_3_16 = self._mpq((3,16))
+        self.mpq_5_2 = self._mpq((5,2))
+        self.mpq_3_4 = self._mpq((3,4))
+        self.mpq_7_4 = self._mpq((7,4))
+        self.mpq_5_4 = self._mpq((5,4))
+        self.mpq_1_3 = self._mpq((1,3))
+        self.mpq_2_3 = self._mpq((2,3))
+        self.mpq_4_3 = self._mpq((4,3))
+        self.mpq_1_6 = self._mpq((1,6))
+        self.mpq_5_6 = self._mpq((5,6))
+        self.mpq_5_3 = self._mpq((5,3))
+
+        self._misc_const_cache = {}
+
+        self._aliases.update({
+            'phase' : 'arg',
+            'conjugate' : 'conj',
+            'nthroot' : 'root',
+            'polygamma' : 'psi',
+            'hurwitz' : 'zeta',
+            #'digamma' : 'psi0',
+            #'trigamma' : 'psi1',
+            #'tetragamma' : 'psi2',
+            #'pentagamma' : 'psi3',
+            'fibonacci' : 'fib',
+            'factorial' : 'fac',
+        })
+
+        self.zetazero_memoized = self.memoize(self.zetazero)
+
+    # Default -- do nothing
+    @classmethod
+    def _wrap_specfun(cls, name, f, wrap):
+        setattr(cls, name, f)
+
+    # Optional fast versions of common functions in common cases.
+    # If not overridden, default (generic hypergeometric series)
+    # implementations will be used
+    def _besselj(ctx, n, z): raise NotImplementedError
+    def _erf(ctx, z): raise NotImplementedError
+    def _erfc(ctx, z): raise NotImplementedError
+    def _gamma_upper_int(ctx, z, a): raise NotImplementedError
+    def _expint_int(ctx, n, z): raise NotImplementedError
+    def _zeta(ctx, s): raise NotImplementedError
+    def _zetasum_fast(ctx, s, a, n, derivatives, reflect): raise NotImplementedError
+    def _ei(ctx, z): raise NotImplementedError
+    def _e1(ctx, z): raise NotImplementedError
+    def _ci(ctx, z): raise NotImplementedError
+    def _si(ctx, z): raise NotImplementedError
+    def _altzeta(ctx, s): raise NotImplementedError
+
+def defun_wrapped(f):
+    SpecialFunctions.defined_functions[f.__name__] = f, True
+    return f
+
+def defun(f):
+    SpecialFunctions.defined_functions[f.__name__] = f, False
+    return f
+
+def defun_static(f):
+    setattr(SpecialFunctions, f.__name__, f)
+    return f
+
+@defun_wrapped
+def cot(ctx, z): return ctx.one / ctx.tan(z)
+
+@defun_wrapped
+def sec(ctx, z): return ctx.one / ctx.cos(z)
+
+@defun_wrapped
+def csc(ctx, z): return ctx.one / ctx.sin(z)
+
+@defun_wrapped
+def coth(ctx, z): return ctx.one / ctx.tanh(z)
+
+@defun_wrapped
+def sech(ctx, z): return ctx.one / ctx.cosh(z)
+
+@defun_wrapped
+def csch(ctx, z): return ctx.one / ctx.sinh(z)
+
+@defun_wrapped
+def acot(ctx, z):
+    if not z:
+        return ctx.pi * 0.5
+    else:
+        return ctx.atan(ctx.one / z)
+
+@defun_wrapped
+def asec(ctx, z): return ctx.acos(ctx.one / z)
+
+@defun_wrapped
+def acsc(ctx, z): return ctx.asin(ctx.one / z)
+
+@defun_wrapped
+def acoth(ctx, z):
+    if not z:
+        return ctx.pi * 0.5j
+    else:
+        return ctx.atanh(ctx.one / z)
+
+
+@defun_wrapped
+def asech(ctx, z): return ctx.acosh(ctx.one / z)
+
+@defun_wrapped
+def acsch(ctx, z): return ctx.asinh(ctx.one / z)
+
+@defun
+def sign(ctx, x):
+    x = ctx.convert(x)
+    if not x or ctx.isnan(x):
+        return x
+    if ctx._is_real_type(x):
+        if x > 0:
+            return ctx.one
+        else:
+            return -ctx.one
+    return x / abs(x)
+
+@defun
+def agm(ctx, a, b=1):
+    if b == 1:
+        return ctx.agm1(a)
+    a = ctx.convert(a)
+    b = ctx.convert(b)
+    return ctx._agm(a, b)
+
+@defun_wrapped
+def sinc(ctx, x):
+    if ctx.isinf(x):
+        return 1/x
+    if not x:
+        return x+1
+    return ctx.sin(x)/x
+
+@defun_wrapped
+def sincpi(ctx, x):
+    if ctx.isinf(x):
+        return 1/x
+    if not x:
+        return x+1
+    return ctx.sinpi(x)/(ctx.pi*x)
+
+# TODO: tests; improve implementation
+@defun_wrapped
+def expm1(ctx, x):
+    if not x:
+        return ctx.zero
+    # exp(x) - 1 ~ x
+    if ctx.mag(x) < -ctx.prec:
+        return x + 0.5*x**2
+    # TODO: accurately eval the smaller of the real/imag parts
+    return ctx.sum_accurately(lambda: iter([ctx.exp(x),-1]),1)
+
+@defun_wrapped
+def log1p(ctx, x):
+    if not x:
+        return ctx.zero
+    if ctx.mag(x) < -ctx.prec:
+        return x - 0.5*x**2
+    return ctx.log(ctx.fadd(1, x, prec=2*ctx.prec))
+
+@defun_wrapped
+def powm1(ctx, x, y):
+    mag = ctx.mag
+    one = ctx.one
+    w = x**y - one
+    M = mag(w)
+    # Only moderate cancellation
+    if M > -8:
+        return w
+    # Check for the only possible exact cases
+    if not w:
+        if (not y) or (x in (1, -1, 1j, -1j) and ctx.isint(y)):
+            return w
+    x1 = x - one
+    magy = mag(y)
+    lnx = ctx.ln(x)
+    # Small y: x^y - 1 ~ log(x)*y + O(log(x)^2 * y^2)
+    if magy + mag(lnx) < -ctx.prec:
+        return lnx*y + (lnx*y)**2/2
+    # TODO: accurately eval the smaller of the real/imag part
+    return ctx.sum_accurately(lambda: iter([x**y, -1]), 1)
+
+@defun
+def _rootof1(ctx, k, n):
+    k = int(k)
+    n = int(n)
+    k %= n
+    if not k:
+        return ctx.one
+    elif 2*k == n:
+        return -ctx.one
+    elif 4*k == n:
+        return ctx.j
+    elif 4*k == 3*n:
+        return -ctx.j
+    return ctx.expjpi(2*ctx.mpf(k)/n)
+
+@defun
+def root(ctx, x, n, k=0):
+    n = int(n)
+    x = ctx.convert(x)
+    if k:
+        # Special case: there is an exact real root
+        if (n & 1 and 2*k == n-1) and (not ctx.im(x)) and (ctx.re(x) < 0):
+            return -ctx.root(-x, n)
+        # Multiply by root of unity
+        prec = ctx.prec
+        try:
+            ctx.prec += 10
+            v = ctx.root(x, n, 0) * ctx._rootof1(k, n)
+        finally:
+            ctx.prec = prec
+        return +v
+    return ctx._nthroot(x, n)
+
+@defun
+def unitroots(ctx, n, primitive=False):
+    gcd = ctx._gcd
+    prec = ctx.prec
+    try:
+        ctx.prec += 10
+        if primitive:
+            v = [ctx._rootof1(k,n) for k in range(n) if gcd(k,n) == 1]
+        else:
+            # TODO: this can be done *much* faster
+            v = [ctx._rootof1(k,n) for k in range(n)]
+    finally:
+        ctx.prec = prec
+    return [+x for x in v]
+
+@defun
+def arg(ctx, x):
+    x = ctx.convert(x)
+    re = ctx._re(x)
+    im = ctx._im(x)
+    return ctx.atan2(im, re)
+
+@defun
+def fabs(ctx, x):
+    return abs(ctx.convert(x))
+
+@defun
+def re(ctx, x):
+    x = ctx.convert(x)
+    if hasattr(x, "real"):    # py2.5 doesn't have .real/.imag for all numbers
+        return x.real
+    return x
+
+@defun
+def im(ctx, x):
+    x = ctx.convert(x)
+    if hasattr(x, "imag"):    # py2.5 doesn't have .real/.imag for all numbers
+        return x.imag
+    return ctx.zero
+
+@defun
+def conj(ctx, x):
+    x = ctx.convert(x)
+    try:
+        return x.conjugate()
+    except AttributeError:
+        return x
+
+@defun
+def polar(ctx, z):
+    return (ctx.fabs(z), ctx.arg(z))
+
+@defun_wrapped
+def rect(ctx, r, phi):
+    return r * ctx.mpc(*ctx.cos_sin(phi))
+
+@defun
+def log(ctx, x, b=None):
+    if b is None:
+        return ctx.ln(x)
+    wp = ctx.prec + 20
+    return ctx.ln(x, prec=wp) / ctx.ln(b, prec=wp)
+
+@defun
+def log10(ctx, x):
+    return ctx.log(x, 10)
+
+@defun
+def fmod(ctx, x, y):
+    return ctx.convert(x) % ctx.convert(y)
+
+@defun
+def degrees(ctx, x):
+    return x / ctx.degree
+
+@defun
+def radians(ctx, x):
+    return x * ctx.degree
+
+def _lambertw_special(ctx, z, k):
+    # W(0,0) = 0; all other branches are singular
+    if not z:
+        if not k:
+            return z
+        return ctx.ninf + z
+    if z == ctx.inf:
+        if k == 0:
+            return z
+        else:
+            return z + 2*k*ctx.pi*ctx.j
+    if z == ctx.ninf:
+        return (-z) + (2*k+1)*ctx.pi*ctx.j
+    # Some kind of nan or complex inf/nan?
+    return ctx.ln(z)
+
+import math
+import cmath
+
+def _lambertw_approx_hybrid(z, k):
+    imag_sign = 0
+    if hasattr(z, "imag"):
+        x = float(z.real)
+        y = z.imag
+        if y:
+            imag_sign = (-1) ** (y < 0)
+        y = float(y)
+    else:
+        x = float(z)
+        y = 0.0
+        imag_sign = 0
+    # hack to work regardless of whether Python supports -0.0
+    if not y:
+        y = 0.0
+    z = complex(x,y)
+    if k == 0:
+        if -4.0 < y < 4.0 and -1.0 < x < 2.5:
+            if imag_sign:
+                # Taylor series in upper/lower half-plane
+                if y > 1.00: return (0.876+0.645j) + (0.118-0.174j)*(z-(0.75+2.5j))
+                if y > 0.25: return (0.505+0.204j) + (0.375-0.132j)*(z-(0.75+0.5j))
+                if y < -1.00: return (0.876-0.645j) + (0.118+0.174j)*(z-(0.75-2.5j))
+                if y < -0.25: return (0.505-0.204j) + (0.375+0.132j)*(z-(0.75-0.5j))
+            # Taylor series near -1
+            if x < -0.5:
+                if imag_sign >= 0:
+                    return (-0.318+1.34j) + (-0.697-0.593j)*(z+1)
+                else:
+                    return (-0.318-1.34j) + (-0.697+0.593j)*(z+1)
+            # return real type
+            r = -0.367879441171442
+            if (not imag_sign) and x > r:
+                z = x
+            # Singularity near -1/e
+            if x < -0.2:
+                return -1 + 2.33164398159712*(z-r)**0.5 - 1.81218788563936*(z-r)
+            # Taylor series near 0
+            if x < 0.5: return z
+            # Simple linear approximation
+            return 0.2 + 0.3*z
+        if (not imag_sign) and x > 0.0:
+            L1 = math.log(x); L2 = math.log(L1)
+        else:
+            L1 = cmath.log(z); L2 = cmath.log(L1)
+    elif k == -1:
+        # return real type
+        r = -0.367879441171442
+        if (not imag_sign) and r < x < 0.0:
+            z = x
+        if (imag_sign >= 0) and y < 0.1 and -0.6 < x < -0.2:
+            return -1 - 2.33164398159712*(z-r)**0.5 - 1.81218788563936*(z-r)
+        if (not imag_sign) and -0.2 <= x < 0.0:
+            L1 = math.log(-x)
+            return L1 - math.log(-L1)
+        else:
+            if imag_sign == -1 and (not y) and x < 0.0:
+                L1 = cmath.log(z) - 3.1415926535897932j
+            else:
+                L1 = cmath.log(z) - 6.2831853071795865j
+            L2 = cmath.log(L1)
+    return L1 - L2 + L2/L1 + L2*(L2-2)/(2*L1**2)
+
+def _lambertw_series(ctx, z, k, tol):
+    """
+    Return rough approximation for W_k(z) from an asymptotic series,
+    sufficiently accurate for the Halley iteration to converge to
+    the correct value.
+    """
+    magz = ctx.mag(z)
+    if (-10 < magz < 900) and (-1000 < k < 1000):
+        # Near the branch point at -1/e
+        if magz < 1 and abs(z+0.36787944117144) < 0.05:
+            if k == 0 or (k == -1 and ctx._im(z) >= 0) or \
+                         (k == 1  and ctx._im(z) < 0):
+                delta = ctx.sum_accurately(lambda: [z, ctx.exp(-1)])
+                cancellation = -ctx.mag(delta)
+                ctx.prec += cancellation
+                # Use series given in Corless et al.
+                p = ctx.sqrt(2*(ctx.e*z+1))
+                ctx.prec -= cancellation
+                u = {0:ctx.mpf(-1), 1:ctx.mpf(1)}
+                a = {0:ctx.mpf(2), 1:ctx.mpf(-1)}
+                if k != 0:
+                    p = -p
+                s = ctx.zero
+                # The series converges, so we could use it directly, but unless
+                # *extremely* close, it is better to just use the first few
+                # terms to get a good approximation for the iteration
+                for l in xrange(max(2,cancellation)):
+                    if l not in u:
+                        a[l] = ctx.fsum(u[j]*u[l+1-j] for j in xrange(2,l))
+                        u[l] = (l-1)*(u[l-2]/2+a[l-2]/4)/(l+1)-a[l]/2-u[l-1]/(l+1)
+                    term = u[l] * p**l
+                    s += term
+                    if ctx.mag(term) < -tol:
+                        return s, True
+                    l += 1
+                ctx.prec += cancellation//2
+                return s, False
+        if k == 0 or k == -1:
+            return _lambertw_approx_hybrid(z, k), False
+    if k == 0:
+        if magz < -1:
+            return z*(1-z), False
+        L1 = ctx.ln(z)
+        L2 = ctx.ln(L1)
+    elif k == -1 and (not ctx._im(z)) and (-0.36787944117144 < ctx._re(z) < 0):
+        L1 = ctx.ln(-z)
+        return L1 - ctx.ln(-L1), False
+    else:
+        # This holds both as z -> 0 and z -> inf.
+        # Relative error is O(1/log(z)).
+        L1 = ctx.ln(z) + 2j*ctx.pi*k
+        L2 = ctx.ln(L1)
+    return L1 - L2 + L2/L1 + L2*(L2-2)/(2*L1**2), False
+
+@defun
+def lambertw(ctx, z, k=0):
+    z = ctx.convert(z)
+    k = int(k)
+    if not ctx.isnormal(z):
+        return _lambertw_special(ctx, z, k)
+    prec = ctx.prec
+    ctx.prec += 20 + ctx.mag(k or 1)
+    wp = ctx.prec
+    tol = wp - 5
+    w, done = _lambertw_series(ctx, z, k, tol)
+    if not done:
+        # Use Halley iteration to solve w*exp(w) = z
+        two = ctx.mpf(2)
+        for i in xrange(100):
+            ew = ctx.exp(w)
+            wew = w*ew
+            wewz = wew-z
+            wn = w - wewz/(wew+ew-(w+two)*wewz/(two*w+two))
+            if ctx.mag(wn-w) <= ctx.mag(wn) - tol:
+                w = wn
+                break
+            else:
+                w = wn
+        if i == 100:
+            ctx.warn("Lambert W iteration failed to converge for z = %s" % z)
+    ctx.prec = prec
+    return +w
+
+@defun_wrapped
+def bell(ctx, n, x=1):
+    x = ctx.convert(x)
+    if not n:
+        if ctx.isnan(x):
+            return x
+        return type(x)(1)
+    if ctx.isinf(x) or ctx.isinf(n) or ctx.isnan(x) or ctx.isnan(n):
+        return x**n
+    if n == 1: return x
+    if n == 2: return x*(x+1)
+    if x == 0: return ctx.sincpi(n)
+    return _polyexp(ctx, n, x, True) / ctx.exp(x)
+
+def _polyexp(ctx, n, x, extra=False):
+    def _terms():
+        if extra:
+            yield ctx.sincpi(n)
+        t = x
+        k = 1
+        while 1:
+            yield k**n * t
+            k += 1
+            t = t*x/k
+    return ctx.sum_accurately(_terms, check_step=4)
+
+@defun_wrapped
+def polyexp(ctx, s, z):
+    if ctx.isinf(z) or ctx.isinf(s) or ctx.isnan(z) or ctx.isnan(s):
+        return z**s
+    if z == 0: return z*s
+    if s == 0: return ctx.expm1(z)
+    if s == 1: return ctx.exp(z)*z
+    if s == 2: return ctx.exp(z)*z*(z+1)
+    return _polyexp(ctx, s, z)
+
+@defun_wrapped
+def cyclotomic(ctx, n, z):
+    n = int(n)
+    if n < 0:
+        raise ValueError("n cannot be negative")
+    p = ctx.one
+    if n == 0:
+        return p
+    if n == 1:
+        return z - p
+    if n == 2:
+        return z + p
+    # Use divisor product representation. Unfortunately, this sometimes
+    # includes singularities for roots of unity, which we have to cancel out.
+    # Matching zeros/poles pairwise, we have (1-z^a)/(1-z^b) ~ a/b + O(z-1).
+    a_prod = 1
+    b_prod = 1
+    num_zeros = 0
+    num_poles = 0
+    for d in range(1,n+1):
+        if not n % d:
+            w = ctx.moebius(n//d)
+            # Use powm1 because it is important that we get 0 only
+            # if it really is exactly 0
+            b = -ctx.powm1(z, d)
+            if b:
+                p *= b**w
+            else:
+                if w == 1:
+                    a_prod *= d
+                    num_zeros += 1
+                elif w == -1:
+                    b_prod *= d
+                    num_poles += 1
+    #print n, num_zeros, num_poles
+    if num_zeros:
+        if num_zeros > num_poles:
+            p *= 0
+        else:
+            p *= a_prod
+            p /= b_prod
+    return p
+
+@defun
+def mangoldt(ctx, n):
+    r"""
+    Evaluates the von Mangoldt function `\Lambda(n) = \log p`
+    if `n = p^k` a power of a prime, and `\Lambda(n) = 0` otherwise.
+
+    **Examples**
+
+        >>> from mpmath import *
+        >>> mp.dps = 25; mp.pretty = True
+        >>> [mangoldt(n) for n in range(-2,3)]
+        [0.0, 0.0, 0.0, 0.0, 0.6931471805599453094172321]
+        >>> mangoldt(6)
+        0.0
+        >>> mangoldt(7)
+        1.945910149055313305105353
+        >>> mangoldt(8)
+        0.6931471805599453094172321
+        >>> fsum(mangoldt(n) for n in range(101))
+        94.04531122935739224600493
+        >>> fsum(mangoldt(n) for n in range(10001))
+        10013.39669326311478372032
+
+    """
+    n = int(n)
+    if n < 2:
+        return ctx.zero
+    if n % 2 == 0:
+        # Must be a power of two
+        if n & (n-1) == 0:
+            return +ctx.ln2
+        else:
+            return ctx.zero
+    # TODO: the following could be generalized into a perfect
+    # power testing function
+    # ---
+    # Look for a small factor
+    for p in (3,5,7,11,13,17,19,23,29,31):
+        if not n % p:
+            q, r = n // p, 0
+            while q > 1:
+                q, r = divmod(q, p)
+                if r:
+                    return ctx.zero
+            return ctx.ln(p)
+    if ctx.isprime(n):
+        return ctx.ln(n)
+    # Obviously, we could use arbitrary-precision arithmetic for this...
+    if n > 10**30:
+        raise NotImplementedError
+    k = 2
+    while 1:
+        p = int(n**(1./k) + 0.5)
+        if p < 2:
+            return ctx.zero
+        if p ** k == n:
+            if ctx.isprime(p):
+                return ctx.ln(p)
+        k += 1
+
+@defun
+def stirling1(ctx, n, k, exact=False):
+    v = ctx._stirling1(int(n), int(k))
+    if exact:
+        return int(v)
+    else:
+        return ctx.mpf(v)
+
+@defun
+def stirling2(ctx, n, k, exact=False):
+    v = ctx._stirling2(int(n), int(k))
+    if exact:
+        return int(v)
+    else:
+        return ctx.mpf(v)

vllm/lib/python3.10/site-packages/mpmath/tests/extratest_gamma.py

@@ -0,0 +1,215 @@
+from mpmath import *
+from mpmath.libmp import ifac
+
+import sys
+if "-dps" in sys.argv:
+    maxdps = int(sys.argv[sys.argv.index("-dps")+1])
+else:
+    maxdps = 1000
+
+raise_ = "-raise" in sys.argv
+
+errcount = 0
+
+def check(name, func, z, y):
+    global errcount
+    try:
+        x = func(z)
+    except:
+        errcount += 1
+        if raise_:
+            raise
+        print()
+        print(name)
+        print("EXCEPTION")
+        import traceback
+        traceback.print_tb(sys.exc_info()[2])
+        print()
+        return
+    xre = x.real
+    xim = x.imag
+    yre = y.real
+    yim = y.imag
+    tol = eps*8
+    err = 0
+    if abs(xre-yre) > abs(yre)*tol:
+        err = 1
+        print()
+        print("Error! %s (re = %s, wanted %s, err=%s)" % (name, nstr(xre,10), nstr(yre,10), nstr(abs(xre-yre))))
+        errcount += 1
+        if raise_:
+            raise SystemExit
+    if abs(xim-yim) > abs(yim)*tol:
+        err = 1
+        print()
+        print("Error! %s (im = %s, wanted %s, err=%s)" % (name, nstr(xim,10), nstr(yim,10), nstr(abs(xim-yim))))
+        errcount += 1
+        if raise_:
+            raise SystemExit
+    if not err:
+        sys.stdout.write("%s ok; " % name)
+
+def testcase(case):
+    z, result = case
+    print("Testing z =", z)
+    mp.dps = 1010
+    z = eval(z)
+    mp.dps = maxdps + 50
+    if result is None:
+        gamma_val = gamma(z)
+        loggamma_val = loggamma(z)
+        factorial_val = factorial(z)
+        rgamma_val = rgamma(z)
+    else:
+        loggamma_val = eval(result)
+        gamma_val = exp(loggamma_val)
+        factorial_val = z * gamma_val
+        rgamma_val = 1/gamma_val
+    for dps in [5, 10, 15, 25, 40, 60, 90, 120, 250, 600, 1000, 1800, 3600]:
+        if dps > maxdps:
+            break
+        mp.dps = dps
+        print("dps = %s" % dps)
+        check("gamma", gamma, z, gamma_val)
+        check("rgamma", rgamma, z, rgamma_val)
+        check("loggamma", loggamma, z, loggamma_val)
+        check("factorial", factorial, z, factorial_val)
+        print()
+        mp.dps = 15
+
+testcases = []
+
+# Basic values
+for n in list(range(1,200)) + list(range(201,2000,17)):
+    testcases.append(["%s" % n, None])
+for n in range(-200,200):
+    testcases.append(["%s+0.5" % n, None])
+    testcases.append(["%s+0.37" % n, None])
+
+testcases += [\
+["(0.1+1j)", None],
+["(-0.1+1j)", None],
+["(0.1-1j)", None],
+["(-0.1-1j)", None],
+["10j", None],
+["-10j", None],
+["100j", None],
+["10000j", None],
+["-10000000j", None],
+["(10**100)*j", None],
+["125+(10**100)*j", None],
+["-125+(10**100)*j", None],
+["(10**10)*(1+j)", None],
+["(10**10)*(-1+j)", None],
+["(10**100)*(1+j)", None],
+["(10**100)*(-1+j)", None],
+["(1.5-1j)", None],
+["(6+4j)", None],
+["(4+1j)", None],
+["(3.5+2j)", None],
+["(1.5-1j)", None],
+["(-6-4j)", None],
+["(-2-3j)", None],
+["(-2.5-2j)", None],
+["(4+1j)", None],
+["(3+3j)", None],
+["(2-2j)", None],
+["1", "0"],
+["2", "0"],
+["3", "log(2)"],
+["4", "log(6)"],
+["5", "log(24)"],
+["0.5", "log(pi)/2"],
+["1.5", "log(sqrt(pi)/2)"],
+["2.5", "log(3*sqrt(pi)/4)"],
+["mpf('0.37')", None],
+["0.25", "log(sqrt(2*sqrt(2*pi**3)/agm(1,sqrt(2))))"],
+["-0.4", None],
+["mpf('-1.9')", None],
+["mpf('12.8')", None],
+["mpf('33.7')", None],
+["mpf('95.2')", None],
+["mpf('160.3')", None],
+["mpf('2057.8')", None],
+["25", "log(ifac(24))"],
+["80", "log(ifac(79))"],
+["500", "log(ifac(500-1))"],
+["8000", "log(ifac(8000-1))"],
+["8000.5", None],
+["mpf('8000.1')", None],
+["mpf('1.37e10')", None],
+["mpf('1.37e10')*(1+j)", None],
+["mpf('1.37e10')*(-1+j)", None],
+["mpf('1.37e10')*(-1-j)", None],
+["mpf('1.37e10')*(-1+j)", None],
+["mpf('1.37e100')", None],
+["mpf('1.37e100')*(1+j)", None],
+["mpf('1.37e100')*(-1+j)", None],
+["mpf('1.37e100')*(-1-j)", None],
+["mpf('1.37e100')*(-1+j)", None],
+["3+4j",
+"mpc('"
+"-1.7566267846037841105306041816232757851567066070613445016197619371316057169"
+"4723618263960834804618463052988607348289672535780644470689771115236512106002"
+"5970873471563240537307638968509556191696167970488390423963867031934333890838"
+"8009531786948197210025029725361069435208930363494971027388382086721660805397"
+"9163230643216054580167976201709951509519218635460317367338612500626714783631"
+"7498317478048447525674016344322545858832610325861086336204591943822302971823"
+"5161814175530618223688296232894588415495615809337292518431903058265147109853"
+"1710568942184987827643886816200452860853873815413367529829631430146227470517"
+"6579967222200868632179482214312673161276976117132204633283806161971389519137"
+"1243359764435612951384238091232760634271570950240717650166551484551654327989"
+"9360285030081716934130446150245110557038117075172576825490035434069388648124"
+"6678152254554001586736120762641422590778766100376515737713938521275749049949"
+"1284143906816424244705094759339932733567910991920631339597278805393743140853"
+"391550313363278558195609260225928','"
+"4.74266443803465792819488940755002274088830335171164611359052405215840070271"
+"5906813009373171139767051863542508136875688550817670379002790304870822775498"
+"2809996675877564504192565392367259119610438951593128982646945990372179860613"
+"4294436498090428077839141927485901735557543641049637962003652638924845391650"
+"9546290137755550107224907606529385248390667634297183361902055842228798984200"
+"9591180450211798341715874477629099687609819466457990642030707080894518168924"
+"6805549314043258530272479246115112769957368212585759640878745385160943755234"
+"9398036774908108204370323896757543121853650025529763655312360354244898913463"
+"7115955702828838923393113618205074162812089732064414530813087483533203244056"
+"0546577484241423134079056537777170351934430586103623577814746004431994179990"
+"5318522939077992613855205801498201930221975721246498720895122345420698451980"
+"0051215797310305885845964334761831751370672996984756815410977750799748813563"
+"8784405288158432214886648743541773208808731479748217023665577802702269468013"
+"673719173759245720489020315779001')"],
+]
+
+for z in [4, 14, 34, 64]:
+    testcases.append(["(2+j)*%s/3" % z, None])
+    testcases.append(["(-2+j)*%s/3" % z, None])
+    testcases.append(["(1+2*j)*%s/3" % z, None])
+    testcases.append(["(2-j)*%s/3" % z, None])
+    testcases.append(["(20+j)*%s/3" % z, None])
+    testcases.append(["(-20+j)*%s/3" % z, None])
+    testcases.append(["(1+20*j)*%s/3" % z, None])
+    testcases.append(["(20-j)*%s/3" % z, None])
+    testcases.append(["(200+j)*%s/3" % z, None])
+    testcases.append(["(-200+j)*%s/3" % z, None])
+    testcases.append(["(1+200*j)*%s/3" % z, None])
+    testcases.append(["(200-j)*%s/3" % z, None])
+
+# Poles
+for n in [0,1,2,3,4,25,-1,-2,-3,-4,-20,-21,-50,-51,-200,-201,-20000,-20001]:
+    for t in ['1e-5', '1e-20', '1e-100', '1e-10000']:
+        testcases.append(["fadd(%s,'%s',exact=True)" % (n, t), None])
+        testcases.append(["fsub(%s,'%s',exact=True)" % (n, t), None])
+        testcases.append(["fadd(%s,'%sj',exact=True)" % (n, t), None])
+        testcases.append(["fsub(%s,'%sj',exact=True)" % (n, t), None])
+
+if __name__ == "__main__":
+    from timeit import default_timer as clock
+    tot_time = 0.0
+    for case in testcases:
+        t1 = clock()
+        testcase(case)
+        t2 = clock()
+        print("Test time:", t2-t1)
+        print()
+        tot_time += (t2-t1)
+    print("Total time:", tot_time)
+    print("Errors:", errcount)

vllm/lib/python3.10/site-packages/mpmath/tests/extratest_zeta.py

@@ -0,0 +1,30 @@
+from mpmath import zetazero
+from timeit import default_timer as clock
+
+def test_zetazero():
+    cases = [\
+    (399999999, 156762524.6750591511),
+    (241389216, 97490234.2276711795),
+    (526196239, 202950727.691229534),
+    (542964976, 209039046.578535272),
+    (1048449112, 388858885.231056486),
+    (1048449113, 388858885.384337406),
+    (1048449114, 388858886.002285122),
+    (1048449115, 388858886.00239369),
+    (1048449116, 388858886.690745053)
+    ]
+    for n, v in cases:
+        print(n, v)
+        t1 = clock()
+        ok = zetazero(n).ae(complex(0.5,v))
+        t2 = clock()
+        print("ok =", ok, ("(time = %s)" % round(t2-t1,3)))
+    print("Now computing two huge zeros (this may take hours)")
+    print("Computing zetazero(8637740722917)")
+    ok = zetazero(8637740722917).ae(complex(0.5,2124447368584.39296466152))
+    print("ok =", ok)
+    ok = zetazero(8637740722918).ae(complex(0.5,2124447368584.39298170604))
+    print("ok =", ok)
+
+if __name__ == "__main__":
+    test_zetazero()

vllm/lib/python3.10/site-packages/mpmath/tests/runtests.py

@@ -0,0 +1,161 @@
+#!/usr/bin/env python
+
+"""
+python runtests.py -py
+  Use py.test to run tests (more useful for debugging)
+
+python runtests.py -coverage
+  Generate test coverage report. Statistics are written to /tmp
+
+python runtests.py -profile
+  Generate profile stats (this is much slower)
+
+python runtests.py -nogmpy
+  Run tests without using GMPY even if it exists
+
+python runtests.py -strict
+  Enforce extra tests in normalize()
+
+python runtests.py -local
+  Insert '../..' at the beginning of sys.path to use local mpmath
+
+python runtests.py -skip ...
+  Skip tests from the listed modules
+
+Additional arguments are used to filter the tests to run. Only files that have
+one of the arguments in their name are executed.
+
+"""
+
+import sys, os, traceback
+
+profile = False
+if "-profile" in sys.argv:
+    sys.argv.remove('-profile')
+    profile = True
+
+coverage = False
+if "-coverage" in sys.argv:
+    sys.argv.remove('-coverage')
+    coverage = True
+
+if "-nogmpy" in sys.argv:
+    sys.argv.remove('-nogmpy')
+    os.environ['MPMATH_NOGMPY'] = 'Y'
+
+if "-strict" in sys.argv:
+    sys.argv.remove('-strict')
+    os.environ['MPMATH_STRICT'] = 'Y'
+
+if "-local" in sys.argv:
+    sys.argv.remove('-local')
+    importdir = os.path.abspath(os.path.join(os.path.dirname(sys.argv[0]),
+                                             '../..'))
+else:
+    importdir = ''
+
+# TODO: add a flag for this
+testdir = ''
+
+def testit(importdir='', testdir='', exit_on_fail=False):
+    """Run all tests in testdir while importing from importdir."""
+    if importdir:
+        sys.path.insert(1, importdir)
+    if testdir:
+        sys.path.insert(1, testdir)
+    import os.path
+    import mpmath
+    print("mpmath imported from %s" % os.path.dirname(mpmath.__file__))
+    print("mpmath backend: %s" % mpmath.libmp.backend.BACKEND)
+    print("mpmath mp class: %s" % repr(mpmath.mp))
+    print("mpmath version: %s" % mpmath.__version__)
+    print("Python version: %s" % sys.version)
+    print("")
+    if "-py" in sys.argv:
+        sys.argv.remove('-py')
+        import py
+        py.test.cmdline.main()
+    else:
+        import glob
+        from timeit import default_timer as clock
+        modules = []
+        args = sys.argv[1:]
+        excluded = []
+        if '-skip' in args:
+            excluded = args[args.index('-skip')+1:]
+            args = args[:args.index('-skip')]
+        # search for tests in directory of this file if not otherwise specified
+        if not testdir:
+            pattern = os.path.dirname(sys.argv[0])
+        else:
+            pattern = testdir
+        if pattern:
+            pattern += '/'
+        pattern += 'test*.py'
+        # look for tests (respecting specified filter)
+        for f in glob.glob(pattern):
+            name = os.path.splitext(os.path.basename(f))[0]
+            # If run as a script, only run tests given as args, if any are given
+            if args and __name__ == "__main__":
+                ok = False
+                for arg in args:
+                    if arg in name:
+                        ok = True
+                        break
+                if not ok:
+                    continue
+            elif name in excluded:
+                continue
+            module = __import__(name)
+            priority = module.__dict__.get('priority', 100)
+            if priority == 666:
+                modules = [[priority, name, module]]
+                break
+            modules.append([priority, name, module])
+        # execute tests
+        modules.sort()
+        tstart = clock()
+        for priority, name, module in modules:
+            print(name)
+            for f in sorted(module.__dict__.keys()):
+                if f.startswith('test_'):
+                    if coverage and ('numpy' in f):
+                        continue
+                    sys.stdout.write("    " + f[5:].ljust(25) + " ")
+                    t1 = clock()
+                    try:
+                        module.__dict__[f]()
+                    except:
+                        etype, evalue, trb = sys.exc_info()
+                        if etype in (KeyboardInterrupt, SystemExit):
+                            raise
+                        print("")
+                        print("TEST FAILED!")
+                        print("")
+                        traceback.print_exc()
+                        if exit_on_fail:
+                            return
+                    t2 = clock()
+                    print("ok " + "       " + ("%.7f" % (t2-t1)) + " s")
+        tend = clock()
+        print("")
+        print("finished tests in " + ("%.2f" % (tend-tstart)) + " seconds")
+        # clean sys.path
+        if importdir:
+            sys.path.remove(importdir)
+        if testdir:
+            sys.path.remove(testdir)
+
+if __name__ == '__main__':
+    if profile:
+        import cProfile
+        cProfile.run("testit('%s', '%s')" % (importdir, testdir), sort=1)
+    elif coverage:
+        import trace
+        tracer = trace.Trace(ignoredirs=[sys.prefix, sys.exec_prefix],
+            trace=0, count=1)
+        tracer.run('testit(importdir, testdir)')
+        r = tracer.results()
+        r.write_results(show_missing=True, summary=True, coverdir="/tmp")
+    else:
+        testit(importdir, testdir)

vllm/lib/python3.10/site-packages/mpmath/tests/test_basic_ops.py

@@ -0,0 +1,451 @@
+import mpmath
+from mpmath import *
+from mpmath.libmp import *
+import random
+import sys
+
+try:
+    long = long
+except NameError:
+    long = int
+
+def test_type_compare():
+    assert mpf(2) == mpc(2,0)
+    assert mpf(0) == mpc(0)
+    assert mpf(2) != mpc(2, 0.00001)
+    assert mpf(2) == 2.0
+    assert mpf(2) != 3.0
+    assert mpf(2) == 2
+    assert mpf(2) != '2.0'
+    assert mpc(2) != '2.0'
+
+def test_add():
+    assert mpf(2.5) + mpf(3) == 5.5
+    assert mpf(2.5) + 3 == 5.5
+    assert mpf(2.5) + 3.0 == 5.5
+    assert 3 + mpf(2.5) == 5.5
+    assert 3.0 + mpf(2.5) == 5.5
+    assert (3+0j) + mpf(2.5) == 5.5
+    assert mpc(2.5) + mpf(3) == 5.5
+    assert mpc(2.5) + 3 == 5.5
+    assert mpc(2.5) + 3.0 == 5.5
+    assert mpc(2.5) + (3+0j) == 5.5
+    assert 3 + mpc(2.5) == 5.5
+    assert 3.0 + mpc(2.5) == 5.5
+    assert (3+0j) + mpc(2.5) == 5.5
+
+def test_sub():
+    assert mpf(2.5) - mpf(3) == -0.5
+    assert mpf(2.5) - 3 == -0.5
+    assert mpf(2.5) - 3.0 == -0.5
+    assert 3 - mpf(2.5) == 0.5
+    assert 3.0 - mpf(2.5) == 0.5
+    assert (3+0j) - mpf(2.5) == 0.5
+    assert mpc(2.5) - mpf(3) == -0.5
+    assert mpc(2.5) - 3 == -0.5
+    assert mpc(2.5) - 3.0 == -0.5
+    assert mpc(2.5) - (3+0j) == -0.5
+    assert 3 - mpc(2.5) == 0.5
+    assert 3.0 - mpc(2.5) == 0.5
+    assert (3+0j) - mpc(2.5) == 0.5
+
+def test_mul():
+    assert mpf(2.5) * mpf(3) == 7.5
+    assert mpf(2.5) * 3 == 7.5
+    assert mpf(2.5) * 3.0 == 7.5
+    assert 3 * mpf(2.5) == 7.5
+    assert 3.0 * mpf(2.5) == 7.5
+    assert (3+0j) * mpf(2.5) == 7.5
+    assert mpc(2.5) * mpf(3) == 7.5
+    assert mpc(2.5) * 3 == 7.5
+    assert mpc(2.5) * 3.0 == 7.5
+    assert mpc(2.5) * (3+0j) == 7.5
+    assert 3 * mpc(2.5) == 7.5
+    assert 3.0 * mpc(2.5) == 7.5
+    assert (3+0j) * mpc(2.5) == 7.5
+
+def test_div():
+    assert mpf(6) / mpf(3) == 2.0
+    assert mpf(6) / 3 == 2.0
+    assert mpf(6) / 3.0 == 2.0
+    assert 6 / mpf(3) == 2.0
+    assert 6.0 / mpf(3) == 2.0
+    assert (6+0j) / mpf(3.0) == 2.0
+    assert mpc(6) / mpf(3) == 2.0
+    assert mpc(6) / 3 == 2.0
+    assert mpc(6) / 3.0 == 2.0
+    assert mpc(6) / (3+0j) == 2.0
+    assert 6 / mpc(3) == 2.0
+    assert 6.0 / mpc(3) == 2.0
+    assert (6+0j) / mpc(3) == 2.0
+
+def test_pow():
+    assert mpf(6) ** mpf(3) == 216.0
+    assert mpf(6) ** 3 == 216.0
+    assert mpf(6) ** 3.0 == 216.0
+    assert 6 ** mpf(3) == 216.0
+    assert 6.0 ** mpf(3) == 216.0
+    assert (6+0j) ** mpf(3.0) == 216.0
+    assert mpc(6) ** mpf(3) == 216.0
+    assert mpc(6) ** 3 == 216.0
+    assert mpc(6) ** 3.0 == 216.0
+    assert mpc(6) ** (3+0j) == 216.0
+    assert 6 ** mpc(3) == 216.0
+    assert 6.0 ** mpc(3) == 216.0
+    assert (6+0j) ** mpc(3) == 216.0
+
+def test_mixed_misc():
+    assert 1 + mpf(3) == mpf(3) + 1 == 4
+    assert 1 - mpf(3) == -(mpf(3) - 1) == -2
+    assert 3 * mpf(2) == mpf(2) * 3 == 6
+    assert 6 / mpf(2) == mpf(6) / 2 == 3
+    assert 1.0 + mpf(3) == mpf(3) + 1.0 == 4
+    assert 1.0 - mpf(3) == -(mpf(3) - 1.0) == -2
+    assert 3.0 * mpf(2) == mpf(2) * 3.0 == 6
+    assert 6.0 / mpf(2) == mpf(6) / 2.0 == 3
+
+def test_add_misc():
+    mp.dps = 15
+    assert mpf(4) + mpf(-70) == -66
+    assert mpf(1) + mpf(1.1)/80 == 1 + 1.1/80
+    assert mpf((1, 10000000000)) + mpf(3) == mpf((1, 10000000000))
+    assert mpf(3) + mpf((1, 10000000000)) == mpf((1, 10000000000))
+    assert mpf((1, -10000000000)) + mpf(3) == mpf(3)
+    assert mpf(3) + mpf((1, -10000000000)) == mpf(3)
+    assert mpf(1) + 1e-15 != 1
+    assert mpf(1) + 1e-20 == 1
+    assert mpf(1.07e-22) + 0 == mpf(1.07e-22)
+    assert mpf(0) + mpf(1.07e-22) == mpf(1.07e-22)
+
+def test_complex_misc():
+    # many more tests needed
+    assert 1 + mpc(2) == 3
+    assert not mpc(2).ae(2 + 1e-13)
+    assert mpc(2+1e-15j).ae(2)
+
+def test_complex_zeros():
+    for a in [0,2]:
+        for b in [0,3]:
+            for c in [0,4]:
+                for d in [0,5]:
+                    assert mpc(a,b)*mpc(c,d) == complex(a,b)*complex(c,d)
+
+def test_hash():
+    for i in range(-256, 256):
+        assert hash(mpf(i)) == hash(i)
+    assert hash(mpf(0.5)) == hash(0.5)
+    assert hash(mpc(2,3)) == hash(2+3j)
+    # Check that this doesn't fail
+    assert hash(inf)
+    # Check that overflow doesn't assign equal hashes to large numbers
+    assert hash(mpf('1e1000')) != hash('1e10000')
+    assert hash(mpc(100,'1e1000')) != hash(mpc(200,'1e1000'))
+    from mpmath.rational import mpq
+    assert hash(mp.mpq(1,3))
+    assert hash(mp.mpq(0,1)) == 0
+    assert hash(mp.mpq(-1,1)) == hash(-1)
+    assert hash(mp.mpq(1,1)) == hash(1)
+    assert hash(mp.mpq(5,1)) == hash(5)
+    assert hash(mp.mpq(1,2)) == hash(0.5)
+    if sys.version_info >= (3, 2):
+        assert hash(mpf(1)*2**2000) == hash(2**2000)
+        assert hash(mpf(1)/2**2000) == hash(mpq(1,2**2000))
+
+# Advanced rounding test
+def test_add_rounding():
+    mp.dps = 15
+    a = from_float(1e-50)
+    assert mpf_sub(mpf_add(fone, a, 53, round_up), fone, 53, round_up) == from_float(2.2204460492503131e-16)
+    assert mpf_sub(fone, a, 53, round_up) == fone
+    assert mpf_sub(fone, mpf_sub(fone, a, 53, round_down), 53, round_down) == from_float(1.1102230246251565e-16)
+    assert mpf_add(fone, a, 53, round_down) == fone
+
+def test_almost_equal():
+    assert mpf(1.2).ae(mpf(1.20000001), 1e-7)
+    assert not mpf(1.2).ae(mpf(1.20000001), 1e-9)
+    assert not mpf(-0.7818314824680298).ae(mpf(-0.774695868667929))
+
+def test_arithmetic_functions():
+    import operator
+    ops = [(operator.add, fadd), (operator.sub, fsub), (operator.mul, fmul),
+        (operator.truediv, fdiv)]
+    a = mpf(0.27)
+    b = mpf(1.13)
+    c = mpc(0.51+2.16j)
+    d = mpc(1.08-0.99j)
+    for x in [a,b,c,d]:
+        for y in [a,b,c,d]:
+            for op, fop in ops:
+                if fop is not fdiv:
+                    mp.prec = 200
+                    z0 = op(x,y)
+                mp.prec = 60
+                z1 = op(x,y)
+                mp.prec = 53
+                z2 = op(x,y)
+                assert fop(x, y, prec=60) == z1
+                assert fop(x, y) == z2
+                if fop is not fdiv:
+                    assert fop(x, y, prec=inf) == z0
+                    assert fop(x, y, dps=inf) == z0
+                    assert fop(x, y, exact=True) == z0
+                assert fneg(fneg(z1, exact=True), prec=inf) == z1
+                assert fneg(z1) == -(+z1)
+    mp.dps = 15
+
+def test_exact_integer_arithmetic():
+    # XXX: re-fix this so that all operations are tested with all rounding modes
+    random.seed(0)
+    for prec in [6, 10, 25, 40, 100, 250, 725]:
+        for rounding in ['d', 'u', 'f', 'c', 'n']:
+            mp.dps = prec
+            M = 10**(prec-2)
+            M2 = 10**(prec//2-2)
+            for i in range(10):
+                a = random.randint(-M, M)
+                b = random.randint(-M, M)
+                assert mpf(a, rounding=rounding) == a
+                assert int(mpf(a, rounding=rounding)) == a
+                assert int(mpf(str(a), rounding=rounding)) == a
+                assert mpf(a) + mpf(b) == a + b
+                assert mpf(a) - mpf(b) == a - b
+                assert -mpf(a) == -a
+                a = random.randint(-M2, M2)
+                b = random.randint(-M2, M2)
+                assert mpf(a) * mpf(b) == a*b
+                assert mpf_mul(from_int(a), from_int(b), mp.prec, rounding) == from_int(a*b)
+    mp.dps = 15
+
+def test_odd_int_bug():
+    assert to_int(from_int(3), round_nearest) == 3
+
+def test_str_1000_digits():
+    mp.dps = 1001
+    # last digit may be wrong
+    assert str(mpf(2)**0.5)[-10:-1] == '9518488472'[:9]
+    assert str(pi)[-10:-1] == '2164201989'[:9]
+    mp.dps = 15
+
+def test_str_10000_digits():
+    mp.dps = 10001
+    # last digit may be wrong
+    assert str(mpf(2)**0.5)[-10:-1] == '5873258351'[:9]
+    assert str(pi)[-10:-1] == '5256375678'[:9]
+    mp.dps = 15
+
+def test_monitor():
+    f = lambda x: x**2
+    a = []
+    b = []
+    g = monitor(f, a.append, b.append)
+    assert g(3) == 9
+    assert g(4) == 16
+    assert a[0] == ((3,), {})
+    assert b[0] == 9
+
+def test_nint_distance():
+    assert nint_distance(mpf(-3)) == (-3, -inf)
+    assert nint_distance(mpc(-3)) == (-3, -inf)
+    assert nint_distance(mpf(-3.1)) == (-3, -3)
+    assert nint_distance(mpf(-3.01)) == (-3, -6)
+    assert nint_distance(mpf(-3.001)) == (-3, -9)
+    assert nint_distance(mpf(-3.0001)) == (-3, -13)
+    assert nint_distance(mpf(-2.9)) == (-3, -3)
+    assert nint_distance(mpf(-2.99)) == (-3, -6)
+    assert nint_distance(mpf(-2.999)) == (-3, -9)
+    assert nint_distance(mpf(-2.9999)) == (-3, -13)
+    assert nint_distance(mpc(-3+0.1j)) == (-3, -3)
+    assert nint_distance(mpc(-3+0.01j)) == (-3, -6)
+    assert nint_distance(mpc(-3.1+0.1j)) == (-3, -3)
+    assert nint_distance(mpc(-3.01+0.01j)) == (-3, -6)
+    assert nint_distance(mpc(-3.001+0.001j)) == (-3, -9)
+    assert nint_distance(mpf(0)) == (0, -inf)
+    assert nint_distance(mpf(0.01)) == (0, -6)
+    assert nint_distance(mpf('1e-100')) == (0, -332)
+
+def test_floor_ceil_nint_frac():
+    mp.dps = 15
+    for n in range(-10,10):
+        assert floor(n) == n
+        assert floor(n+0.5) == n
+        assert ceil(n) == n
+        assert ceil(n+0.5) == n+1
+        assert nint(n) == n
+        # nint rounds to even
+        if n % 2 == 1:
+            assert nint(n+0.5) == n+1
+        else:
+            assert nint(n+0.5) == n
+    assert floor(inf) == inf
+    assert floor(ninf) == ninf
+    assert isnan(floor(nan))
+    assert ceil(inf) == inf
+    assert ceil(ninf) == ninf
+    assert isnan(ceil(nan))
+    assert nint(inf) == inf
+    assert nint(ninf) == ninf
+    assert isnan(nint(nan))
+    assert floor(0.1) == 0
+    assert floor(0.9) == 0
+    assert floor(-0.1) == -1
+    assert floor(-0.9) == -1
+    assert floor(10000000000.1) == 10000000000
+    assert floor(10000000000.9) == 10000000000
+    assert floor(-10000000000.1) == -10000000000-1
+    assert floor(-10000000000.9) == -10000000000-1
+    assert floor(1e-100) == 0
+    assert floor(-1e-100) == -1
+    assert floor(1e100) == 1e100
+    assert floor(-1e100) == -1e100
+    assert ceil(0.1) == 1
+    assert ceil(0.9) == 1
+    assert ceil(-0.1) == 0
+    assert ceil(-0.9) == 0
+    assert ceil(10000000000.1) == 10000000000+1
+    assert ceil(10000000000.9) == 10000000000+1
+    assert ceil(-10000000000.1) == -10000000000
+    assert ceil(-10000000000.9) == -10000000000
+    assert ceil(1e-100) == 1
+    assert ceil(-1e-100) == 0
+    assert ceil(1e100) == 1e100
+    assert ceil(-1e100) == -1e100
+    assert nint(0.1) == 0
+    assert nint(0.9) == 1
+    assert nint(-0.1) == 0
+    assert nint(-0.9) == -1
+    assert nint(10000000000.1) == 10000000000
+    assert nint(10000000000.9) == 10000000000+1
+    assert nint(-10000000000.1) == -10000000000
+    assert nint(-10000000000.9) == -10000000000-1
+    assert nint(1e-100) == 0
+    assert nint(-1e-100) == 0
+    assert nint(1e100) == 1e100
+    assert nint(-1e100) == -1e100
+    assert floor(3.2+4.6j) == 3+4j
+    assert ceil(3.2+4.6j) == 4+5j
+    assert nint(3.2+4.6j) == 3+5j
+    for n in range(-10,10):
+        assert frac(n) == 0
+    assert frac(0.25) == 0.25
+    assert frac(1.25) == 0.25
+    assert frac(2.25) == 0.25
+    assert frac(-0.25) == 0.75
+    assert frac(-1.25) == 0.75
+    assert frac(-2.25) == 0.75
+    assert frac('1e100000000000000') == 0
+    u = mpf('1e-100000000000000')
+    assert frac(u) == u
+    assert frac(-u) == 1  # rounding!
+    u = mpf('1e-400')
+    assert frac(-u, prec=0) == fsub(1, u, exact=True)
+    assert frac(3.25+4.75j) == 0.25+0.75j
+
+def test_isnan_etc():
+    from mpmath.rational import mpq
+    assert isnan(nan) == True
+    assert isnan(3) == False
+    assert isnan(mpf(3)) == False
+    assert isnan(inf) == False
+    assert isnan(mpc(2,nan)) == True
+    assert isnan(mpc(2,nan)) == True
+    assert isnan(mpc(nan,nan)) == True
+    assert isnan(mpc(2,2)) == False
+    assert isnan(mpc(nan,inf)) == True
+    assert isnan(mpc(inf,inf)) == False
+    assert isnan(mpq((3,2))) == False
+    assert isnan(mpq((0,1))) == False
+    assert isinf(inf) == True
+    assert isinf(-inf) == True
+    assert isinf(3) == False
+    assert isinf(nan) == False
+    assert isinf(3+4j) == False
+    assert isinf(mpc(inf)) == True
+    assert isinf(mpc(3,inf)) == True
+    assert isinf(mpc(inf,3)) == True
+    assert isinf(mpc(inf,inf)) == True
+    assert isinf(mpc(nan,inf)) == True
+    assert isinf(mpc(inf,nan)) == True
+    assert isinf(mpc(nan,nan)) == False
+    assert isinf(mpq((3,2))) == False
+    assert isinf(mpq((0,1))) == False
+    assert isnormal(3) == True
+    assert isnormal(3.5) == True
+    assert isnormal(mpf(3.5)) == True
+    assert isnormal(0) == False
+    assert isnormal(mpf(0)) == False
+    assert isnormal(0.0) == False
+    assert isnormal(inf) == False
+    assert isnormal(-inf) == False
+    assert isnormal(nan) == False
+    assert isnormal(float(inf)) == False
+    assert isnormal(mpc(0,0)) == False
+    assert isnormal(mpc(3,0)) == True
+    assert isnormal(mpc(0,3)) == True
+    assert isnormal(mpc(3,3)) == True
+    assert isnormal(mpc(0,nan)) == False
+    assert isnormal(mpc(0,inf)) == False
+    assert isnormal(mpc(3,nan)) == False
+    assert isnormal(mpc(3,inf)) == False
+    assert isnormal(mpc(3,-inf)) == False
+    assert isnormal(mpc(nan,0)) == False
+    assert isnormal(mpc(inf,0)) == False
+    assert isnormal(mpc(nan,3)) == False
+    assert isnormal(mpc(inf,3)) == False
+    assert isnormal(mpc(inf,nan)) == False
+    assert isnormal(mpc(nan,inf)) == False
+    assert isnormal(mpc(nan,nan)) == False
+    assert isnormal(mpc(inf,inf)) == False
+    assert isnormal(mpq((3,2))) == True
+    assert isnormal(mpq((0,1))) == False
+    assert isint(3) == True
+    assert isint(0) == True
+    assert isint(long(3)) == True
+    assert isint(long(0)) == True
+    assert isint(mpf(3)) == True
+    assert isint(mpf(0)) == True
+    assert isint(mpf(-3)) == True
+    assert isint(mpf(3.2)) == False
+    assert isint(3.2) == False
+    assert isint(nan) == False
+    assert isint(inf) == False
+    assert isint(-inf) == False
+    assert isint(mpc(0)) == True
+    assert isint(mpc(3)) == True
+    assert isint(mpc(3.2)) == False
+    assert isint(mpc(3,inf)) == False
+    assert isint(mpc(inf)) == False
+    assert isint(mpc(3,2)) == False
+    assert isint(mpc(0,2)) == False
+    assert isint(mpc(3,2),gaussian=True) == True
+    assert isint(mpc(3,0),gaussian=True) == True
+    assert isint(mpc(0,3),gaussian=True) == True
+    assert isint(3+4j) == False
+    assert isint(3+4j, gaussian=True) == True
+    assert isint(3+0j) == True
+    assert isint(mpq((3,2))) == False
+    assert isint(mpq((3,9))) == False
+    assert isint(mpq((9,3))) == True
+    assert isint(mpq((0,4))) == True
+    assert isint(mpq((1,1))) == True
+    assert isint(mpq((-1,1))) == True
+    assert mp.isnpint(0) == True
+    assert mp.isnpint(1) == False
+    assert mp.isnpint(-1) == True
+    assert mp.isnpint(-1.1) == False
+    assert mp.isnpint(-1.0) == True
+    assert mp.isnpint(mp.mpq(1,2)) == False
+    assert mp.isnpint(mp.mpq(-1,2)) == False
+    assert mp.isnpint(mp.mpq(-3,1)) == True
+    assert mp.isnpint(mp.mpq(0,1)) == True
+    assert mp.isnpint(mp.mpq(1,1)) == False
+    assert mp.isnpint(0+0j) == True
+    assert mp.isnpint(-1+0j) == True
+    assert mp.isnpint(-1.1+0j) == False
+    assert mp.isnpint(-1+0.1j) == False
+    assert mp.isnpint(0+0.1j) == False
+
+
+def test_issue_438():
+    assert mpf(finf) == mpf('inf')
+    assert mpf(fninf) == mpf('-inf')
+    assert mpf(fnan)._mpf_ == mpf('nan')._mpf_

vllm/lib/python3.10/site-packages/mpmath/tests/test_bitwise.py

@@ -0,0 +1,188 @@
+"""
+Test bit-level integer and mpf operations
+"""
+
+from mpmath import *
+from mpmath.libmp import *
+
+def test_bitcount():
+    assert bitcount(0) == 0
+    assert bitcount(1) == 1
+    assert bitcount(7) == 3
+    assert bitcount(8) == 4
+    assert bitcount(2**100) == 101
+    assert bitcount(2**100-1) == 100
+
+def test_trailing():
+    assert trailing(0) == 0
+    assert trailing(1) == 0
+    assert trailing(2) == 1
+    assert trailing(7) == 0
+    assert trailing(8) == 3
+    assert trailing(2**100) == 100
+    assert trailing(2**100-1) == 0
+
+def test_round_down():
+    assert from_man_exp(0, -4, 4, round_down)[:3] == (0, 0, 0)
+    assert from_man_exp(0xf0, -4, 4, round_down)[:3] == (0, 15, 0)
+    assert from_man_exp(0xf1, -4, 4, round_down)[:3] == (0, 15, 0)
+    assert from_man_exp(0xff, -4, 4, round_down)[:3] == (0, 15, 0)
+    assert from_man_exp(-0xf0, -4, 4, round_down)[:3] == (1, 15, 0)
+    assert from_man_exp(-0xf1, -4, 4, round_down)[:3] == (1, 15, 0)
+    assert from_man_exp(-0xff, -4, 4, round_down)[:3] == (1, 15, 0)
+
+def test_round_up():
+    assert from_man_exp(0, -4, 4, round_up)[:3] == (0, 0, 0)
+    assert from_man_exp(0xf0, -4, 4, round_up)[:3] == (0, 15, 0)
+    assert from_man_exp(0xf1, -4, 4, round_up)[:3] == (0, 1, 4)
+    assert from_man_exp(0xff, -4, 4, round_up)[:3] == (0, 1, 4)
+    assert from_man_exp(-0xf0, -4, 4, round_up)[:3] == (1, 15, 0)
+    assert from_man_exp(-0xf1, -4, 4, round_up)[:3] == (1, 1, 4)
+    assert from_man_exp(-0xff, -4, 4, round_up)[:3] == (1, 1, 4)
+
+def test_round_floor():
+    assert from_man_exp(0, -4, 4, round_floor)[:3] == (0, 0, 0)
+    assert from_man_exp(0xf0, -4, 4, round_floor)[:3] == (0, 15, 0)
+    assert from_man_exp(0xf1, -4, 4, round_floor)[:3] == (0, 15, 0)
+    assert from_man_exp(0xff, -4, 4, round_floor)[:3] == (0, 15, 0)
+    assert from_man_exp(-0xf0, -4, 4, round_floor)[:3] == (1, 15, 0)
+    assert from_man_exp(-0xf1, -4, 4, round_floor)[:3] == (1, 1, 4)
+    assert from_man_exp(-0xff, -4, 4, round_floor)[:3] == (1, 1, 4)
+
+def test_round_ceiling():
+    assert from_man_exp(0, -4, 4, round_ceiling)[:3] == (0, 0, 0)
+    assert from_man_exp(0xf0, -4, 4, round_ceiling)[:3] == (0, 15, 0)
+    assert from_man_exp(0xf1, -4, 4, round_ceiling)[:3] == (0, 1, 4)
+    assert from_man_exp(0xff, -4, 4, round_ceiling)[:3] == (0, 1, 4)
+    assert from_man_exp(-0xf0, -4, 4, round_ceiling)[:3] == (1, 15, 0)
+    assert from_man_exp(-0xf1, -4, 4, round_ceiling)[:3] == (1, 15, 0)
+    assert from_man_exp(-0xff, -4, 4, round_ceiling)[:3] == (1, 15, 0)
+
+def test_round_nearest():
+    assert from_man_exp(0, -4, 4, round_nearest)[:3] == (0, 0, 0)
+    assert from_man_exp(0xf0, -4, 4, round_nearest)[:3] == (0, 15, 0)
+    assert from_man_exp(0xf7, -4, 4, round_nearest)[:3] == (0, 15, 0)
+    assert from_man_exp(0xf8, -4, 4, round_nearest)[:3] == (0, 1, 4)    # 1111.1000 -> 10000.0
+    assert from_man_exp(0xf9, -4, 4, round_nearest)[:3] == (0, 1, 4)    # 1111.1001 -> 10000.0
+    assert from_man_exp(0xe8, -4, 4, round_nearest)[:3] == (0, 7, 1)    # 1110.1000 -> 1110.0
+    assert from_man_exp(0xe9, -4, 4, round_nearest)[:3] == (0, 15, 0)     # 1110.1001 -> 1111.0
+    assert from_man_exp(-0xf0, -4, 4, round_nearest)[:3] == (1, 15, 0)
+    assert from_man_exp(-0xf7, -4, 4, round_nearest)[:3] == (1, 15, 0)
+    assert from_man_exp(-0xf8, -4, 4, round_nearest)[:3] == (1, 1, 4)
+    assert from_man_exp(-0xf9, -4, 4, round_nearest)[:3] == (1, 1, 4)
+    assert from_man_exp(-0xe8, -4, 4, round_nearest)[:3] == (1, 7, 1)
+    assert from_man_exp(-0xe9, -4, 4, round_nearest)[:3] == (1, 15, 0)
+
+def test_rounding_bugs():
+    # 1 less than power-of-two cases
+    assert from_man_exp(72057594037927935, -56, 53, round_up) == (0, 1, 0, 1)
+    assert from_man_exp(73786976294838205979, -65, 53, round_nearest) == (0, 1, 1, 1)
+    assert from_man_exp(31, 0, 4, round_up) == (0, 1, 5, 1)
+    assert from_man_exp(-31, 0, 4, round_floor) == (1, 1, 5, 1)
+    assert from_man_exp(255, 0, 7, round_up) == (0, 1, 8, 1)
+    assert from_man_exp(-255, 0, 7, round_floor) == (1, 1, 8, 1)
+
+def test_rounding_issue_200():
+    a = from_man_exp(9867,-100)
+    b = from_man_exp(9867,-200)
+    c = from_man_exp(-1,0)
+    z = (1, 1023, -10, 10)
+    assert mpf_add(a, c, 10, 'd') == z
+    assert mpf_add(b, c, 10, 'd') == z
+    assert mpf_add(c, a, 10, 'd') == z
+    assert mpf_add(c, b, 10, 'd') == z
+
+def test_perturb():
+    a = fone
+    b = from_float(0.99999999999999989)
+    c = from_float(1.0000000000000002)
+    assert mpf_perturb(a, 0, 53, round_nearest) == a
+    assert mpf_perturb(a, 1, 53, round_nearest) == a
+    assert mpf_perturb(a, 0, 53, round_up) == c
+    assert mpf_perturb(a, 0, 53, round_ceiling) == c
+    assert mpf_perturb(a, 0, 53, round_down) == a
+    assert mpf_perturb(a, 0, 53, round_floor) == a
+    assert mpf_perturb(a, 1, 53, round_up) == a
+    assert mpf_perturb(a, 1, 53, round_ceiling) == a
+    assert mpf_perturb(a, 1, 53, round_down) == b
+    assert mpf_perturb(a, 1, 53, round_floor) == b
+    a = mpf_neg(a)
+    b = mpf_neg(b)
+    c = mpf_neg(c)
+    assert mpf_perturb(a, 0, 53, round_nearest) == a
+    assert mpf_perturb(a, 1, 53, round_nearest) == a
+    assert mpf_perturb(a, 0, 53, round_up) == a
+    assert mpf_perturb(a, 0, 53, round_floor) == a
+    assert mpf_perturb(a, 0, 53, round_down) == b
+    assert mpf_perturb(a, 0, 53, round_ceiling) == b
+    assert mpf_perturb(a, 1, 53, round_up) == c
+    assert mpf_perturb(a, 1, 53, round_floor) == c
+    assert mpf_perturb(a, 1, 53, round_down) == a
+    assert mpf_perturb(a, 1, 53, round_ceiling) == a
+
+def test_add_exact():
+    ff = from_float
+    assert mpf_add(ff(3.0), ff(2.5)) == ff(5.5)
+    assert mpf_add(ff(3.0), ff(-2.5)) == ff(0.5)
+    assert mpf_add(ff(-3.0), ff(2.5)) == ff(-0.5)
+    assert mpf_add(ff(-3.0), ff(-2.5)) == ff(-5.5)
+    assert mpf_sub(mpf_add(fone, ff(1e-100)), fone) == ff(1e-100)
+    assert mpf_sub(mpf_add(ff(1e-100), fone), fone) == ff(1e-100)
+    assert mpf_sub(mpf_add(fone, ff(-1e-100)), fone) == ff(-1e-100)
+    assert mpf_sub(mpf_add(ff(-1e-100), fone), fone) == ff(-1e-100)
+    assert mpf_add(fone, fzero) == fone
+    assert mpf_add(fzero, fone) == fone
+    assert mpf_add(fzero, fzero) == fzero
+
+def test_long_exponent_shifts():
+    mp.dps = 15
+    # Check for possible bugs due to exponent arithmetic overflow
+    # in a C implementation
+    x = mpf(1)
+    for p in [32, 64]:
+        a = ldexp(1,2**(p-1))
+        b = ldexp(1,2**p)
+        c = ldexp(1,2**(p+1))
+        d = ldexp(1,-2**(p-1))
+        e = ldexp(1,-2**p)
+        f = ldexp(1,-2**(p+1))
+        assert (x+a) == a
+        assert (x+b) == b
+        assert (x+c) == c
+        assert (x+d) == x
+        assert (x+e) == x
+        assert (x+f) == x
+        assert (a+x) == a
+        assert (b+x) == b
+        assert (c+x) == c
+        assert (d+x) == x
+        assert (e+x) == x
+        assert (f+x) == x
+        assert (x-a) == -a
+        assert (x-b) == -b
+        assert (x-c) == -c
+        assert (x-d) == x
+        assert (x-e) == x
+        assert (x-f) == x
+        assert (a-x) == a
+        assert (b-x) == b
+        assert (c-x) == c
+        assert (d-x) == -x
+        assert (e-x) == -x
+        assert (f-x) == -x
+
+def test_float_rounding():
+    mp.prec = 64
+    for x in [mpf(1), mpf(1)+eps, mpf(1)-eps, -mpf(1)+eps, -mpf(1)-eps]:
+        fa = float(x)
+        fb = float(fadd(x,0,prec=53,rounding='n'))
+        assert fa == fb
+        z = mpc(x,x)
+        ca = complex(z)
+        cb = complex(fadd(z,0,prec=53,rounding='n'))
+        assert ca == cb
+        for rnd in ['n', 'd', 'u', 'f', 'c']:
+            fa = to_float(x._mpf_, rnd=rnd)
+            fb = to_float(fadd(x,0,prec=53,rounding=rnd)._mpf_, rnd=rnd)
+            assert fa == fb
+    mp.prec = 53

vllm/lib/python3.10/site-packages/mpmath/tests/test_calculus.py

@@ -0,0 +1,216 @@
+import pytest
+from mpmath import *
+
+def test_approximation():
+    mp.dps = 15
+    f = lambda x: cos(2-2*x)/x
+    p, err = chebyfit(f, [2, 4], 8, error=True)
+    assert err < 1e-5
+    for i in range(10):
+        x = 2 + i/5.
+        assert abs(polyval(p, x) - f(x)) < err
+
+def test_limits():
+    mp.dps = 15
+    assert limit(lambda x: (x-sin(x))/x**3, 0).ae(mpf(1)/6)
+    assert limit(lambda n: (1+1/n)**n, inf).ae(e)
+
+def test_polyval():
+    assert polyval([], 3) == 0
+    assert polyval([0], 3) == 0
+    assert polyval([5], 3) == 5
+    # 4x^3 - 2x + 5
+    p = [4, 0, -2, 5]
+    assert polyval(p,4) == 253
+    assert polyval(p,4,derivative=True) == (253, 190)
+
+def test_polyroots():
+    p = polyroots([1,-4])
+    assert p[0].ae(4)
+    p, q = polyroots([1,2,3])
+    assert p.ae(-1 - sqrt(2)*j)
+    assert q.ae(-1 + sqrt(2)*j)
+    #this is not a real test, it only tests a specific case
+    assert polyroots([1]) == []
+    pytest.raises(ValueError, lambda: polyroots([0]))
+
+def test_polyroots_legendre():
+    n = 64
+    coeffs = [11975573020964041433067793888190275875, 0,
+        -190100434726484311252477736051902332000, 0,
+        1437919688271127330313741595496589239248, 0,
+        -6897338342113537600691931230430793911840, 0,
+        23556405536185284408974715545252277554280, 0,
+        -60969520211303089058522793175947071316960, 0,
+        124284021969194758465450309166353645376880, 0,
+        -204721258548015217049921875719981284186016, 0,
+        277415422258095841688223780704620656114900, 0,
+        -313237834141273382807123548182995095192800, 0,
+        297432255354328395601259515935229287637200, 0,
+        -239057700565161140389797367947941296605600, 0,
+        163356095386193445933028201431093219347160, 0,
+        -95158890516229191805647495979277603503200, 0,
+        47310254620162038075933656063247634556400, 0,
+        -20071017111583894941305187420771723751200, 0,
+        7255051932731034189479516844750603752850, 0,
+        -2228176940331017311443863996901733412640, 0,
+        579006552594977616773047095969088431600, 0,
+        -126584428502545713788439446082310831200, 0,
+        23112325428835593809686977515028663000, 0,
+        -3491517141958743235617737161547844000, 0,
+        431305058712550634988073414073557200, 0,
+        -42927166660756742088912492757452000, 0,
+        3378527005707706553294038781836500, 0,
+        -205277590220215081719131470288800, 0,
+        9330799555464321896324157740400, 0,
+        -304114948474392713657972548576, 0,
+        6695289961520387531608984680, 0,
+        -91048139350447232095702560, 0,
+        659769125727878493447120, 0,
+        -1905929106580294155360, 0,
+        916312070471295267]
+
+    with mp.workdps(3):
+        with pytest.raises(mp.NoConvergence):
+            polyroots(coeffs, maxsteps=5, cleanup=True, error=False,
+                      extraprec=n*10)
+
+        roots = polyroots(coeffs, maxsteps=50, cleanup=True, error=False,
+                    extraprec=n*10)
+        roots = [str(r) for r in roots]
+        assert roots == \
+            ['-0.999', '-0.996', '-0.991', '-0.983', '-0.973', '-0.961',
+            '-0.946', '-0.93', '-0.911', '-0.889', '-0.866', '-0.841',
+            '-0.813', '-0.784', '-0.753', '-0.72', '-0.685', '-0.649',
+            '-0.611', '-0.572', '-0.531', '-0.489', '-0.446', '-0.402',
+            '-0.357', '-0.311', '-0.265', '-0.217', '-0.17', '-0.121',
+            '-0.073', '-0.0243', '0.0243', '0.073', '0.121', '0.17', '0.217',
+            '0.265', '0.311', '0.357', '0.402', '0.446', '0.489', '0.531',
+            '0.572', '0.611', '0.649', '0.685', '0.72', '0.753', '0.784',
+            '0.813', '0.841', '0.866', '0.889', '0.911', '0.93', '0.946',
+            '0.961', '0.973', '0.983', '0.991', '0.996', '0.999']
+
+def test_polyroots_legendre_init():
+    extra_prec = 100
+    coeffs = [11975573020964041433067793888190275875, 0,
+        -190100434726484311252477736051902332000, 0,
+        1437919688271127330313741595496589239248, 0,
+        -6897338342113537600691931230430793911840, 0,
+        23556405536185284408974715545252277554280, 0,
+        -60969520211303089058522793175947071316960, 0,
+        124284021969194758465450309166353645376880, 0,
+        -204721258548015217049921875719981284186016, 0,
+        277415422258095841688223780704620656114900, 0,
+        -313237834141273382807123548182995095192800, 0,
+        297432255354328395601259515935229287637200, 0,
+        -239057700565161140389797367947941296605600, 0,
+        163356095386193445933028201431093219347160, 0,
+        -95158890516229191805647495979277603503200, 0,
+        47310254620162038075933656063247634556400, 0,
+        -20071017111583894941305187420771723751200, 0,
+        7255051932731034189479516844750603752850, 0,
+        -2228176940331017311443863996901733412640, 0,
+        579006552594977616773047095969088431600, 0,
+        -126584428502545713788439446082310831200, 0,
+        23112325428835593809686977515028663000, 0,
+        -3491517141958743235617737161547844000, 0,
+        431305058712550634988073414073557200, 0,
+        -42927166660756742088912492757452000, 0,
+        3378527005707706553294038781836500, 0,
+        -205277590220215081719131470288800, 0,
+        9330799555464321896324157740400, 0,
+        -304114948474392713657972548576, 0,
+        6695289961520387531608984680, 0,
+        -91048139350447232095702560, 0,
+        659769125727878493447120, 0,
+        -1905929106580294155360, 0,
+        916312070471295267]
+
+    roots_init =  matrix(['-0.999', '-0.996',  '-0.991', '-0.983', '-0.973',
+                          '-0.961', '-0.946',  '-0.93',  '-0.911', '-0.889',
+                          '-0.866', '-0.841',  '-0.813', '-0.784', '-0.753',
+                          '-0.72',  '-0.685',  '-0.649', '-0.611', '-0.572',
+                          '-0.531', '-0.489',  '-0.446', '-0.402', '-0.357',
+                          '-0.311', '-0.265',  '-0.217', '-0.17',  '-0.121',
+                          '-0.073', '-0.0243',  '0.0243', '0.073',  '0.121',
+                          '0.17',    '0.217',   '0.265', ' 0.311',  '0.357',
+                          '0.402',   '0.446',   '0.489',  '0.531',  '0.572',
+                          '0.611',   '0.649',   '0.685',  '0.72',   '0.753',
+                          '0.784',   '0.813',   '0.841',  '0.866',  '0.889',
+                          '0.911',   '0.93',    '0.946',  '0.961',  '0.973',
+                          '0.983',   '0.991',   '0.996',  '0.999',  '1.0'])
+    with mp.workdps(2*mp.dps):
+        roots_exact = polyroots(coeffs, maxsteps=50, cleanup=True, error=False,
+                                extraprec=2*extra_prec)
+    with pytest.raises(mp.NoConvergence):
+        polyroots(coeffs, maxsteps=5, cleanup=True, error=False,
+                  extraprec=extra_prec)
+    roots,err = polyroots(coeffs, maxsteps=5, cleanup=True, error=True,
+                          extraprec=extra_prec,roots_init=roots_init)
+    assert max(matrix(roots_exact)-matrix(roots).apply(abs)) < err
+    roots1,err1 = polyroots(coeffs, maxsteps=25, cleanup=True, error=True,
+                            extraprec=extra_prec,roots_init=roots_init[:60])
+    assert max(matrix(roots_exact)-matrix(roots1).apply(abs)) < err1
+
+def test_pade():
+    one = mpf(1)
+    mp.dps = 20
+    N = 10
+    a = [one]
+    k = 1
+    for i in range(1, N+1):
+        k *= i
+        a.append(one/k)
+    p, q = pade(a, N//2, N//2)
+    for x in arange(0, 1, 0.1):
+        r = polyval(p[::-1], x)/polyval(q[::-1], x)
+        assert(r.ae(exp(x), 1.0e-10))
+    mp.dps = 15
+
+def test_fourier():
+    mp.dps = 15
+    c, s = fourier(lambda x: x+1, [-1, 2], 2)
+    #plot([lambda x: x+1, lambda x: fourierval((c, s), [-1, 2], x)], [-1, 2])
+    assert c[0].ae(1.5)
+    assert c[1].ae(-3*sqrt(3)/(2*pi))
+    assert c[2].ae(3*sqrt(3)/(4*pi))
+    assert s[0] == 0
+    assert s[1].ae(3/(2*pi))
+    assert s[2].ae(3/(4*pi))
+    assert fourierval((c, s), [-1, 2], 1).ae(1.9134966715663442)
+
+def test_differint():
+    mp.dps = 15
+    assert differint(lambda t: t, 2, -0.5).ae(8*sqrt(2/pi)/3)
+
+def test_invlap():
+    mp.dps = 15
+    t = 0.01
+    fp = lambda p: 1/(p+1)**2
+    ft = lambda t: t*exp(-t)
+    ftt = ft(t)
+    assert invertlaplace(fp,t,method='talbot').ae(ftt)
+    assert invertlaplace(fp,t,method='stehfest').ae(ftt)
+    assert invertlaplace(fp,t,method='dehoog').ae(ftt)
+    assert invertlaplace(fp,t,method='cohen').ae(ftt)
+    t = 1.0
+    ftt = ft(t)
+    assert invertlaplace(fp,t,method='talbot').ae(ftt)
+    assert invertlaplace(fp,t,method='stehfest').ae(ftt)
+    assert invertlaplace(fp,t,method='dehoog').ae(ftt)
+    assert invertlaplace(fp,t,method='cohen').ae(ftt)
+
+    t = 0.01
+    fp = lambda p: log(p)/p
+    ft = lambda t: -euler-log(t)
+    ftt = ft(t)
+    assert invertlaplace(fp,t,method='talbot').ae(ftt)
+    assert invertlaplace(fp,t,method='stehfest').ae(ftt)
+    assert invertlaplace(fp,t,method='dehoog').ae(ftt)
+    assert invertlaplace(fp,t,method='cohen').ae(ftt)
+    t = 1.0
+    ftt = ft(t)
+    assert invertlaplace(fp,t,method='talbot').ae(ftt)
+    assert invertlaplace(fp,t,method='stehfest').ae(ftt)
+    assert invertlaplace(fp,t,method='dehoog').ae(ftt)
+    assert invertlaplace(fp,t,method='cohen').ae(ftt)

vllm/lib/python3.10/site-packages/mpmath/tests/test_compatibility.py

@@ -0,0 +1,77 @@
+from mpmath import *
+from random import seed, randint, random
+import math
+
+# Test compatibility with Python floats, which are
+# IEEE doubles (53-bit)
+
+N = 5000
+seed(1)
+
+# Choosing exponents between roughly -140, 140 ensures that
+# the Python floats don't overflow or underflow
+xs = [(random()-1) * 10**randint(-140, 140) for x in range(N)]
+ys = [(random()-1) * 10**randint(-140, 140) for x in range(N)]
+
+# include some equal values
+ys[int(N*0.8):] = xs[int(N*0.8):]
+
+# Detect whether Python is compiled to use 80-bit floating-point
+# instructions, in which case the double compatibility test breaks
+uses_x87 = -4.1974624032366689e+117 / -8.4657370748010221e-47 \
+    == 4.9581771393902231e+163
+
+def test_double_compatibility():
+    mp.prec = 53
+    for x, y in zip(xs, ys):
+        mpx = mpf(x)
+        mpy = mpf(y)
+        assert mpf(x) == x
+        assert (mpx < mpy) == (x < y)
+        assert (mpx > mpy) == (x > y)
+        assert (mpx == mpy) == (x == y)
+        assert (mpx != mpy) == (x != y)
+        assert (mpx <= mpy) == (x <= y)
+        assert (mpx >= mpy) == (x >= y)
+        assert mpx == mpx
+        if uses_x87:
+            mp.prec = 64
+            a = mpx + mpy
+            b = mpx * mpy
+            c = mpx / mpy
+            d = mpx % mpy
+            mp.prec = 53
+            assert +a == x + y
+            assert +b == x * y
+            assert +c == x / y
+            assert +d == x % y
+        else:
+            assert mpx + mpy == x + y
+            assert mpx * mpy == x * y
+            assert mpx / mpy == x / y
+            assert mpx % mpy == x % y
+        assert abs(mpx) == abs(x)
+        assert mpf(repr(x)) == x
+        assert ceil(mpx) == math.ceil(x)
+        assert floor(mpx) == math.floor(x)
+
+def test_sqrt():
+    # this fails quite often. it appers to be float
+    # that rounds the wrong way, not mpf
+    fail = 0
+    mp.prec = 53
+    for x in xs:
+        x = abs(x)
+        mp.prec = 100
+        mp_high = mpf(x)**0.5
+        mp.prec = 53
+        mp_low = mpf(x)**0.5
+        fp = x**0.5
+        assert abs(mp_low-mp_high) <= abs(fp-mp_high)
+        fail += mp_low != fp
+    assert fail < N/10
+
+def test_bugs():
+    # particular bugs
+    assert mpf(4.4408920985006262E-16) < mpf(1.7763568394002505E-15)
+    assert mpf(-4.4408920985006262E-16) > mpf(-1.7763568394002505E-15)

vllm/lib/python3.10/site-packages/mpmath/tests/test_convert.py

@@ -0,0 +1,233 @@
+import random
+from mpmath import *
+from mpmath.libmp import *
+
+
+def test_basic_string():
+    """
+    Test basic string conversion
+    """
+    mp.dps = 15
+    assert mpf('3') == mpf('3.0') == mpf('0003.') == mpf('0.03e2') == mpf(3.0)
+    assert mpf('30') == mpf('30.0') == mpf('00030.') == mpf(30.0)
+    for i in range(10):
+        for j in range(10):
+            assert mpf('%ie%i' % (i,j)) == i * 10**j
+    assert str(mpf('25000.0')) == '25000.0'
+    assert str(mpf('2500.0')) == '2500.0'
+    assert str(mpf('250.0')) == '250.0'
+    assert str(mpf('25.0')) == '25.0'
+    assert str(mpf('2.5')) == '2.5'
+    assert str(mpf('0.25')) == '0.25'
+    assert str(mpf('0.025')) == '0.025'
+    assert str(mpf('0.0025')) == '0.0025'
+    assert str(mpf('0.00025')) == '0.00025'
+    assert str(mpf('0.000025')) == '2.5e-5'
+    assert str(mpf(0)) == '0.0'
+    assert str(mpf('2.5e1000000000000000000000')) == '2.5e+1000000000000000000000'
+    assert str(mpf('2.6e-1000000000000000000000')) == '2.6e-1000000000000000000000'
+    assert str(mpf(1.23402834e-15)) == '1.23402834e-15'
+    assert str(mpf(-1.23402834e-15)) == '-1.23402834e-15'
+    assert str(mpf(-1.2344e-15)) == '-1.2344e-15'
+    assert repr(mpf(-1.2344e-15)) == "mpf('-1.2343999999999999e-15')"
+    assert str(mpf("2163048125L")) == '2163048125.0'
+    assert str(mpf("-2163048125l")) == '-2163048125.0'
+    assert str(mpf("-2163048125L/1088391168")) == '-1.98738118113799'
+    assert str(mpf("2163048125/1088391168l")) == '1.98738118113799'
+
+def test_pretty():
+    mp.pretty = True
+    assert repr(mpf(2.5)) == '2.5'
+    assert repr(mpc(2.5,3.5)) == '(2.5 + 3.5j)'
+    mp.pretty = False
+    iv.pretty = True
+    assert repr(mpi(2.5,3.5)) == '[2.5, 3.5]'
+    iv.pretty = False
+
+def test_str_whitespace():
+    assert mpf('1.26 ') == 1.26
+
+def test_unicode():
+    mp.dps = 15
+    try:
+        unicode = unicode
+    except NameError:
+        unicode = str
+    assert mpf(unicode('2.76')) == 2.76
+    assert mpf(unicode('inf')) == inf
+
+def test_str_format():
+    assert to_str(from_float(0.1),15,strip_zeros=False) == '0.100000000000000'
+    assert to_str(from_float(0.0),15,show_zero_exponent=True) == '0.0e+0'
+    assert to_str(from_float(0.0),0,show_zero_exponent=True) == '.0e+0'
+    assert to_str(from_float(0.0),0,show_zero_exponent=False) == '.0'
+    assert to_str(from_float(0.0),1,show_zero_exponent=True) == '0.0e+0'
+    assert to_str(from_float(0.0),1,show_zero_exponent=False) == '0.0'
+    assert to_str(from_float(1.23),3,show_zero_exponent=True) == '1.23e+0'
+    assert to_str(from_float(1.23456789000000e-2),15,strip_zeros=False,min_fixed=0,max_fixed=0) == '1.23456789000000e-2'
+    assert to_str(from_float(1.23456789000000e+2),15,strip_zeros=False,min_fixed=0,max_fixed=0) == '1.23456789000000e+2'
+    assert to_str(from_float(2.1287e14), 15, max_fixed=1000) == '212870000000000.0'
+    assert to_str(from_float(2.1287e15), 15, max_fixed=1000) == '2128700000000000.0'
+    assert to_str(from_float(2.1287e16), 15, max_fixed=1000) == '21287000000000000.0'
+    assert to_str(from_float(2.1287e30), 15, max_fixed=1000) == '2128700000000000000000000000000.0'
+
+def test_tight_string_conversion():
+    mp.dps = 15
+    # In an old version, '0.5' wasn't recognized as representing
+    # an exact binary number and was erroneously rounded up or down
+    assert from_str('0.5', 10, round_floor) == fhalf
+    assert from_str('0.5', 10, round_ceiling) == fhalf
+
+def test_eval_repr_invariant():
+    """Test that eval(repr(x)) == x"""
+    random.seed(123)
+    for dps in [10, 15, 20, 50, 100]:
+        mp.dps = dps
+        for i in range(1000):
+            a = mpf(random.random())**0.5 * 10**random.randint(-100, 100)
+            assert eval(repr(a)) == a
+    mp.dps = 15
+
+def test_str_bugs():
+    mp.dps = 15
+    # Decimal rounding used to give the wrong exponent in some cases
+    assert str(mpf('1e600')) == '1.0e+600'
+    assert str(mpf('1e10000')) == '1.0e+10000'
+
+def test_str_prec0():
+    assert to_str(from_float(1.234), 0) == '.0e+0'
+    assert to_str(from_float(1e-15), 0) == '.0e-15'
+    assert to_str(from_float(1e+15), 0) == '.0e+15'
+    assert to_str(from_float(-1e-15), 0) == '-.0e-15'
+    assert to_str(from_float(-1e+15), 0) == '-.0e+15'
+
+def test_convert_rational():
+    mp.dps = 15
+    assert from_rational(30, 5, 53, round_nearest) == (0, 3, 1, 2)
+    assert from_rational(-7, 4, 53, round_nearest) == (1, 7, -2, 3)
+    assert to_rational((0, 1, -1, 1)) == (1, 2)
+
+def test_custom_class():
+    class mympf:
+        @property
+        def _mpf_(self):
+            return mpf(3.5)._mpf_
+    class mympc:
+        @property
+        def _mpc_(self):
+            return mpf(3.5)._mpf_, mpf(2.5)._mpf_
+    assert mpf(2) + mympf() == 5.5
+    assert mympf() + mpf(2) == 5.5
+    assert mpf(mympf()) == 3.5
+    assert mympc() + mpc(2) == mpc(5.5, 2.5)
+    assert mpc(2) + mympc() == mpc(5.5, 2.5)
+    assert mpc(mympc()) == (3.5+2.5j)
+
+def test_conversion_methods():
+    class SomethingRandom:
+        pass
+    class SomethingReal:
+        def _mpmath_(self, prec, rounding):
+            return mp.make_mpf(from_str('1.3', prec, rounding))
+    class SomethingComplex:
+        def _mpmath_(self, prec, rounding):
+            return mp.make_mpc((from_str('1.3', prec, rounding), \
+                from_str('1.7', prec, rounding)))
+    x = mpf(3)
+    z = mpc(3)
+    a = SomethingRandom()
+    y = SomethingReal()
+    w = SomethingComplex()
+    for d in [15, 45]:
+        mp.dps = d
+        assert (x+y).ae(mpf('4.3'))
+        assert (y+x).ae(mpf('4.3'))
+        assert (x+w).ae(mpc('4.3', '1.7'))
+        assert (w+x).ae(mpc('4.3', '1.7'))
+        assert (z+y).ae(mpc('4.3'))
+        assert (y+z).ae(mpc('4.3'))
+        assert (z+w).ae(mpc('4.3', '1.7'))
+        assert (w+z).ae(mpc('4.3', '1.7'))
+        x-y; y-x; x-w; w-x; z-y; y-z; z-w; w-z
+        x*y; y*x; x*w; w*x; z*y; y*z; z*w; w*z
+        x/y; y/x; x/w; w/x; z/y; y/z; z/w; w/z
+        x**y; y**x; x**w; w**x; z**y; y**z; z**w; w**z
+        x==y; y==x; x==w; w==x; z==y; y==z; z==w; w==z
+    mp.dps = 15
+    assert x.__add__(a) is NotImplemented
+    assert x.__radd__(a) is NotImplemented
+    assert x.__lt__(a) is NotImplemented
+    assert x.__gt__(a) is NotImplemented
+    assert x.__le__(a) is NotImplemented
+    assert x.__ge__(a) is NotImplemented
+    assert x.__eq__(a) is NotImplemented
+    assert x.__ne__(a) is NotImplemented
+    # implementation detail
+    if hasattr(x, "__cmp__"):
+        assert x.__cmp__(a) is NotImplemented
+    assert x.__sub__(a) is NotImplemented
+    assert x.__rsub__(a) is NotImplemented
+    assert x.__mul__(a) is NotImplemented
+    assert x.__rmul__(a) is NotImplemented
+    assert x.__div__(a) is NotImplemented
+    assert x.__rdiv__(a) is NotImplemented
+    assert x.__mod__(a) is NotImplemented
+    assert x.__rmod__(a) is NotImplemented
+    assert x.__pow__(a) is NotImplemented
+    assert x.__rpow__(a) is NotImplemented
+    assert z.__add__(a) is NotImplemented
+    assert z.__radd__(a) is NotImplemented
+    assert z.__eq__(a) is NotImplemented
+    assert z.__ne__(a) is NotImplemented
+    assert z.__sub__(a) is NotImplemented
+    assert z.__rsub__(a) is NotImplemented
+    assert z.__mul__(a) is NotImplemented
+    assert z.__rmul__(a) is NotImplemented
+    assert z.__div__(a) is NotImplemented
+    assert z.__rdiv__(a) is NotImplemented
+    assert z.__pow__(a) is NotImplemented
+    assert z.__rpow__(a) is NotImplemented
+
+def test_mpmathify():
+    assert mpmathify('1/2') == 0.5
+    assert mpmathify('(1.0+1.0j)') == mpc(1, 1)
+    assert mpmathify('(1.2e-10 - 3.4e5j)') == mpc('1.2e-10', '-3.4e5')
+    assert mpmathify('1j') == mpc(1j)
+
+def test_issue548():
+    try:
+        # This expression is invalid, but may trigger the ReDOS vulnerability
+        # in the regular expression for parsing complex numbers.
+        mpmathify('(' + '1' * 5000 + '!j')
+    except:
+        return
+    # The expression is invalid and should raise an exception.
+    assert False
+
+def test_compatibility():
+    try:
+        import numpy as np
+        from fractions import Fraction
+        from decimal import Decimal
+        import decimal
+    except ImportError:
+        return
+    # numpy types
+    for nptype in np.core.numerictypes.typeDict.values():
+        if issubclass(nptype, np.complexfloating):
+            x = nptype(complex(0.5, -0.5))
+        elif issubclass(nptype, np.floating):
+            x = nptype(0.5)
+        elif issubclass(nptype, np.integer):
+            x = nptype(2)
+        # Handle the weird types
+        try: diff = np.abs(type(np.sqrt(x))(sqrt(x)) - np.sqrt(x))
+        except: continue
+        assert diff < 2.0**-53
+    #Fraction and Decimal
+    oldprec = mp.prec
+    mp.prec = 1000
+    decimal.getcontext().prec = mp.dps
+    assert sqrt(Fraction(2, 3)).ae(sqrt(mpf('2/3')))
+    assert sqrt(Decimal(2)/Decimal(3)).ae(sqrt(mpf('2/3')))
+    mp.prec = oldprec

vllm/lib/python3.10/site-packages/mpmath/tests/test_diff.py

@@ -0,0 +1,61 @@
+from mpmath import *
+
+def test_diff():
+    mp.dps = 15
+    assert diff(log, 2.0, n=0).ae(log(2))
+    assert diff(cos, 1.0).ae(-sin(1))
+    assert diff(abs, 0.0) == 0
+    assert diff(abs, 0.0, direction=1) == 1
+    assert diff(abs, 0.0, direction=-1) == -1
+    assert diff(exp, 1.0).ae(e)
+    assert diff(exp, 1.0, n=5).ae(e)
+    assert diff(exp, 2.0, n=5, direction=3*j).ae(e**2)
+    assert diff(lambda x: x**2, 3.0, method='quad').ae(6)
+    assert diff(lambda x: 3+x**5, 3.0, n=2, method='quad').ae(540)
+    assert diff(lambda x: 3+x**5, 3.0, n=2, method='step').ae(540)
+    assert diffun(sin)(2).ae(cos(2))
+    assert diffun(sin, n=2)(2).ae(-sin(2))
+
+def test_diffs():
+    mp.dps = 15
+    assert [chop(d) for d in diffs(sin, 0, 1)] == [0, 1]
+    assert [chop(d) for d in diffs(sin, 0, 1, method='quad')] == [0, 1]
+    assert [chop(d) for d in diffs(sin, 0, 2)] == [0, 1, 0]
+    assert [chop(d) for d in diffs(sin, 0, 2, method='quad')] == [0, 1, 0]
+
+def test_taylor():
+    mp.dps = 15
+    # Easy to test since the coefficients are exact in floating-point
+    assert taylor(sqrt, 1, 4) == [1, 0.5, -0.125, 0.0625, -0.0390625]
+
+def test_diff_partial():
+    mp.dps = 15
+    x,y,z = xyz = 2,3,7
+    f = lambda x,y,z: 3*x**2 * (y+2)**3 * z**5
+    assert diff(f, xyz, (0,0,0)).ae(25210500)
+    assert diff(f, xyz, (0,0,1)).ae(18007500)
+    assert diff(f, xyz, (0,0,2)).ae(10290000)
+    assert diff(f, xyz, (0,1,0)).ae(15126300)
+    assert diff(f, xyz, (0,1,1)).ae(10804500)
+    assert diff(f, xyz, (0,1,2)).ae(6174000)
+    assert diff(f, xyz, (0,2,0)).ae(6050520)
+    assert diff(f, xyz, (0,2,1)).ae(4321800)
+    assert diff(f, xyz, (0,2,2)).ae(2469600)
+    assert diff(f, xyz, (1,0,0)).ae(25210500)
+    assert diff(f, xyz, (1,0,1)).ae(18007500)
+    assert diff(f, xyz, (1,0,2)).ae(10290000)
+    assert diff(f, xyz, (1,1,0)).ae(15126300)
+    assert diff(f, xyz, (1,1,1)).ae(10804500)
+    assert diff(f, xyz, (1,1,2)).ae(6174000)
+    assert diff(f, xyz, (1,2,0)).ae(6050520)
+    assert diff(f, xyz, (1,2,1)).ae(4321800)
+    assert diff(f, xyz, (1,2,2)).ae(2469600)
+    assert diff(f, xyz, (2,0,0)).ae(12605250)
+    assert diff(f, xyz, (2,0,1)).ae(9003750)
+    assert diff(f, xyz, (2,0,2)).ae(5145000)
+    assert diff(f, xyz, (2,1,0)).ae(7563150)
+    assert diff(f, xyz, (2,1,1)).ae(5402250)
+    assert diff(f, xyz, (2,1,2)).ae(3087000)
+    assert diff(f, xyz, (2,2,0)).ae(3025260)
+    assert diff(f, xyz, (2,2,1)).ae(2160900)
+    assert diff(f, xyz, (2,2,2)).ae(1234800)

vllm/lib/python3.10/site-packages/mpmath/tests/test_division.py

@@ -0,0 +1,143 @@
+from mpmath.libmp import *
+from mpmath import mpf, mp
+
+from random import randint, choice, seed
+
+all_modes = [round_floor, round_ceiling, round_down, round_up, round_nearest]
+
+fb = from_bstr
+fi = from_int
+ff = from_float
+
+
+def test_div_1_3():
+    a = fi(1)
+    b = fi(3)
+    c = fi(-1)
+
+    # floor rounds down, ceiling rounds up
+    assert mpf_div(a, b, 7, round_floor)   == fb('0.01010101')
+    assert mpf_div(a, b, 7, round_ceiling) == fb('0.01010110')
+    assert mpf_div(a, b, 7, round_down)    == fb('0.01010101')
+    assert mpf_div(a, b, 7, round_up)      == fb('0.01010110')
+    assert mpf_div(a, b, 7, round_nearest) == fb('0.01010101')
+
+    # floor rounds up, ceiling rounds down
+    assert mpf_div(c, b, 7, round_floor)   == fb('-0.01010110')
+    assert mpf_div(c, b, 7, round_ceiling) == fb('-0.01010101')
+    assert mpf_div(c, b, 7, round_down)    == fb('-0.01010101')
+    assert mpf_div(c, b, 7, round_up)      == fb('-0.01010110')
+    assert mpf_div(c, b, 7, round_nearest) == fb('-0.01010101')
+
+def test_mpf_divi_1_3():
+    a = 1
+    b = fi(3)
+    c = -1
+    assert mpf_rdiv_int(a, b, 7, round_floor)   == fb('0.01010101')
+    assert mpf_rdiv_int(a, b, 7, round_ceiling) == fb('0.01010110')
+    assert mpf_rdiv_int(a, b, 7, round_down)    == fb('0.01010101')
+    assert mpf_rdiv_int(a, b, 7, round_up)      == fb('0.01010110')
+    assert mpf_rdiv_int(a, b, 7, round_nearest) == fb('0.01010101')
+    assert mpf_rdiv_int(c, b, 7, round_floor)   == fb('-0.01010110')
+    assert mpf_rdiv_int(c, b, 7, round_ceiling) == fb('-0.01010101')
+    assert mpf_rdiv_int(c, b, 7, round_down)    == fb('-0.01010101')
+    assert mpf_rdiv_int(c, b, 7, round_up)      == fb('-0.01010110')
+    assert mpf_rdiv_int(c, b, 7, round_nearest) == fb('-0.01010101')
+
+
+def test_div_300():
+
+    q = fi(1000000)
+    a = fi(300499999)    # a/q is a little less than a half-integer
+    b = fi(300500000)    # b/q exactly a half-integer
+    c = fi(300500001)    # c/q is a little more than a half-integer
+
+    # Check nearest integer rounding (prec=9 as 2**8 < 300 < 2**9)
+
+    assert mpf_div(a, q, 9, round_down) == fi(300)
+    assert mpf_div(b, q, 9, round_down) == fi(300)
+    assert mpf_div(c, q, 9, round_down) == fi(300)
+    assert mpf_div(a, q, 9, round_up) == fi(301)
+    assert mpf_div(b, q, 9, round_up) == fi(301)
+    assert mpf_div(c, q, 9, round_up) == fi(301)
+
+    # Nearest even integer is down
+    assert mpf_div(a, q, 9, round_nearest) == fi(300)
+    assert mpf_div(b, q, 9, round_nearest) == fi(300)
+    assert mpf_div(c, q, 9, round_nearest) == fi(301)
+
+    # Nearest even integer is up
+    a = fi(301499999)
+    b = fi(301500000)
+    c = fi(301500001)
+    assert mpf_div(a, q, 9, round_nearest) == fi(301)
+    assert mpf_div(b, q, 9, round_nearest) == fi(302)
+    assert mpf_div(c, q, 9, round_nearest) == fi(302)
+
+
+def test_tight_integer_division():
+    # Test that integer division at tightest possible precision is exact
+    N = 100
+    seed(1)
+    for i in range(N):
+        a = choice([1, -1]) * randint(1, 1<<randint(10, 100))
+        b = choice([1, -1]) * randint(1, 1<<randint(10, 100))
+        p = a * b
+        width = bitcount(abs(b)) - trailing(b)
+        a = fi(a); b = fi(b); p = fi(p)
+        for mode in all_modes:
+            assert mpf_div(p, a, width, mode) == b
+
+
+def test_epsilon_rounding():
+    # Verify that mpf_div uses infinite precision; this result will
+    # appear to be exactly 0.101 to a near-sighted algorithm
+
+    a = fb('0.101' + ('0'*200) + '1')
+    b = fb('1.10101')
+    c = mpf_mul(a, b, 250, round_floor) # exact
+    assert mpf_div(c, b, bitcount(a[1]), round_floor) == a # exact
+
+    assert mpf_div(c, b, 2, round_down) == fb('0.10')
+    assert mpf_div(c, b, 3, round_down) == fb('0.101')
+    assert mpf_div(c, b, 2, round_up) == fb('0.11')
+    assert mpf_div(c, b, 3, round_up) == fb('0.110')
+    assert mpf_div(c, b, 2, round_floor) == fb('0.10')
+    assert mpf_div(c, b, 3, round_floor) == fb('0.101')
+    assert mpf_div(c, b, 2, round_ceiling) == fb('0.11')
+    assert mpf_div(c, b, 3, round_ceiling) == fb('0.110')
+
+    # The same for negative numbers
+    a = fb('-0.101' + ('0'*200) + '1')
+    b = fb('1.10101')
+    c = mpf_mul(a, b, 250, round_floor)
+    assert mpf_div(c, b, bitcount(a[1]), round_floor) == a
+
+    assert mpf_div(c, b, 2, round_down) == fb('-0.10')
+    assert mpf_div(c, b, 3, round_up) == fb('-0.110')
+
+    # Floor goes up, ceiling goes down
+    assert mpf_div(c, b, 2, round_floor) == fb('-0.11')
+    assert mpf_div(c, b, 3, round_floor) == fb('-0.110')
+    assert mpf_div(c, b, 2, round_ceiling) == fb('-0.10')
+    assert mpf_div(c, b, 3, round_ceiling) == fb('-0.101')
+
+
+def test_mod():
+    mp.dps = 15
+    assert mpf(234) % 1 == 0
+    assert mpf(-3) % 256 == 253
+    assert mpf(0.25) % 23490.5 == 0.25
+    assert mpf(0.25) % -23490.5 == -23490.25
+    assert mpf(-0.25) % 23490.5 == 23490.25
+    assert mpf(-0.25) % -23490.5 == -0.25
+    # Check that these cases are handled efficiently
+    assert mpf('1e10000000000') % 1 == 0
+    assert mpf('1.23e-1000000000') % 1 == mpf('1.23e-1000000000')
+    # test __rmod__
+    assert 3 % mpf('1.75') == 1.25
+
+def test_div_negative_rnd_bug():
+    mp.dps = 15
+    assert (-3) / mpf('0.1531879017645047') == mpf('-19.583791966887116')
+    assert mpf('-2.6342475750861301') / mpf('0.35126216427941814') == mpf('-7.4993775104985909')