From 449f4a21a9119372922a053e10c482f9b203a856 Mon Sep 17 00:00:00 2001 From: Vesa Karvonen Date: Sat, 18 May 2024 22:56:53 +0300 Subject: [PATCH] Update multicore-bench doc for main --- .../Multicore_bench/Cmd/index.html | 2 +- .../Multicore_bench/Metric/index.html | 12 +- .../Multicore_bench/Suite/index.html | 2 +- .../Multicore_bench/Times/index.html | 4 +- .../Multicore_bench/Trend/index.html | 4 + .../Multicore_bench/Unit_of_rate/index.html | 2 +- .../Multicore_bench/Unit_of_time/index.html | 2 +- .../Multicore_bench/Util/Bits/index.html | 2 +- .../Multicore_bench/Util/index.html | 2 +- .../Multicore_bench/index.html | 4 +- doc/multicore-bench/db.js | 2 +- doc/multicore-bench/index.html | 2 +- doc/odoc.support/odoc.css | 2 +- doc/sherlodoc.js | 3600 +++++++++++------ 14 files changed, 2344 insertions(+), 1298 deletions(-) create mode 100644 doc/multicore-bench/Multicore_bench/Trend/index.html diff --git a/doc/multicore-bench/Multicore_bench/Cmd/index.html b/doc/multicore-bench/Multicore_bench/Cmd/index.html index 8d37f90..8e89a2e 100644 --- a/doc/multicore-bench/Multicore_bench/Cmd/index.html +++ b/doc/multicore-bench/Multicore_bench/Cmd/index.html @@ -1,5 +1,5 @@ -Cmd (multicore-bench.Multicore_bench.Cmd)

Module Multicore_bench.Cmd

Command line interface for a benchmark executable.

type output = [
  1. | `JSON
    (*

    `JSON gives the JSON output for current-bench.

    *)
  2. | `Brief
    (*

    `Brief gives concise human readable output.

    *)
  3. | `Diff of string
    (*

    `Diff "path.json" gives concise human readable diff against results stored in specified path.json file.

    *)
]

Specifies the output format.

val run : benchmarks:(string * Suite.t) list -> diff --git a/doc/multicore-bench/Multicore_bench/Metric/index.html b/doc/multicore-bench/Multicore_bench/Metric/index.html index 8ecb2da..35b79a1 100644 --- a/doc/multicore-bench/Multicore_bench/Metric/index.html +++ b/doc/multicore-bench/Multicore_bench/Metric/index.html @@ -1,4 +1,12 @@ -Metric (multicore-bench.Multicore_bench.Metric)

Module Multicore_bench.Metric

Dealing with benchmark metrics.

type t

Represents a metric.

+

Module Multicore_bench.Metric

Dealing with benchmark metrics.

type t

Represents a metric.

val make : + metric:string -> + config:string -> + value:float -> + ?units:string -> + ?trend:Trend.t -> + ?description:string -> + unit -> + t

make ~metric ~config ~value ... () constructs a metric with given specification.

diff --git a/doc/multicore-bench/Multicore_bench/Suite/index.html b/doc/multicore-bench/Multicore_bench/Suite/index.html index 3f18d0c..a2ec74e 100644 --- a/doc/multicore-bench/Multicore_bench/Suite/index.html +++ b/doc/multicore-bench/Multicore_bench/Suite/index.html @@ -1,4 +1,4 @@ -Suite (multicore-bench.Multicore_bench.Suite)

Module Multicore_bench.Suite

Dealing with benchmark suites.

type t = budgetf:float -> Metric.t list

Represents a benchmark suite, i.e. a function that produces a list of metric outputs for current-bench.

diff --git a/doc/multicore-bench/Multicore_bench/Times/index.html b/doc/multicore-bench/Multicore_bench/Times/index.html index b1cf31d..03750c5 100644 --- a/doc/multicore-bench/Multicore_bench/Times/index.html +++ b/doc/multicore-bench/Multicore_bench/Times/index.html @@ -1,5 +1,5 @@ -Times (multicore-bench.Multicore_bench.Times)

Module Multicore_bench.Times

Recording timings of benchmarks running on multiple domains in parallel and producing metrics from the recorded timings.

type t

Represents a record of elapsed times of multiple runs of a benchmark running on multiple domains.

val record : budgetf:float -> @@ -23,4 +23,4 @@ ?unit_of_time:Unit_of_time.t -> ?unit_of_rate:Unit_of_rate.t -> t -> - Metric.t list

to_thruput_metrics ~n ~singular ~config times produces a pair of metrics from the recorded times where one metric is for the time a single operation takes and the other is the thruput of operations over all domains.

Optional arguments:

  • ~plural: Plural for the operation. Defaults to singular + "s".
  • ~unit_of_time: Unit of time for the duration of a single operation. Defaults to `ns.
  • ~unit_of_rate: Unit of rate for the number of operations per second. Defaults to `M.
+ Metric.t list

to_thruput_metrics ~n ~singular ~config times produces a pair of metrics from the recorded times where one metric is for the time a single operation takes and the other is the thruput of operations over all domains.

Optional arguments:

  • ~plural: Plural for the operation. Defaults to singular ^ "s".
  • ~unit_of_time: Unit of time for the duration of a single operation. Defaults to `ns.
  • ~unit_of_rate: Unit of rate for the number of operations per second. Defaults to `M.
diff --git a/doc/multicore-bench/Multicore_bench/Trend/index.html b/doc/multicore-bench/Multicore_bench/Trend/index.html new file mode 100644 index 0000000..334034d --- /dev/null +++ b/doc/multicore-bench/Multicore_bench/Trend/index.html @@ -0,0 +1,4 @@ + +Trend (multicore-bench.Multicore_bench.Trend)

Module Multicore_bench.Trend

Dealing with trends.

type t = [
  1. | `Lower_is_better
  2. | `Higher_is_better
]

Whether a lower or higher value is better.

diff --git a/doc/multicore-bench/Multicore_bench/Unit_of_rate/index.html b/doc/multicore-bench/Multicore_bench/Unit_of_rate/index.html index 46a3fb8..651f014 100644 --- a/doc/multicore-bench/Multicore_bench/Unit_of_rate/index.html +++ b/doc/multicore-bench/Multicore_bench/Unit_of_rate/index.html @@ -1,4 +1,4 @@ -Unit_of_rate (multicore-bench.Multicore_bench.Unit_of_rate)

Module Multicore_bench.Unit_of_rate

Dealing with units of rate.

type t = [
  1. | `_1
    (*

    1/s

    *)
  2. | `k
    (*

    103/s or k/s

    *)
  3. | `M
    (*

    106/s or M/s

    *)
  4. | `G
    (*

    109/s or G/s

    *)
]

Represents a unit of rate, i.e. how many per second.

val to_divisor : t -> float

to_divisor t converts the unit of rate t to a divisor.

val to_mnemonic : t -> string

to_mnemonic t returns a human readable mnemonic for the unit of rate t.

diff --git a/doc/multicore-bench/Multicore_bench/Unit_of_time/index.html b/doc/multicore-bench/Multicore_bench/Unit_of_time/index.html index 994849d..d97f9cb 100644 --- a/doc/multicore-bench/Multicore_bench/Unit_of_time/index.html +++ b/doc/multicore-bench/Multicore_bench/Unit_of_time/index.html @@ -1,4 +1,4 @@ -Unit_of_time (multicore-bench.Multicore_bench.Unit_of_time)

Module Multicore_bench.Unit_of_time

Dealing with units of time.

type t = [
  1. | `s
    (*

    seconds

    *)
  2. | `ms
    (*

    milliseconds

    *)
  3. | `mus
    (*

    microseconds

    *)
  4. | `ns
    (*

    nanoseconds

    *)
]

Represents a unit of time.

val to_multiplier : t -> float

to_multiplier t converts the unit of time t to a multiplier.

val to_mnemonic : t -> string

to_mnemonic t returns a human readable mnemonic for the unit of time t.

diff --git a/doc/multicore-bench/Multicore_bench/Util/Bits/index.html b/doc/multicore-bench/Multicore_bench/Util/Bits/index.html index 8f9f042..3c82367 100644 --- a/doc/multicore-bench/Multicore_bench/Util/Bits/index.html +++ b/doc/multicore-bench/Multicore_bench/Util/Bits/index.html @@ -1,4 +1,4 @@ -Bits (multicore-bench.Multicore_bench.Util.Bits)

Module Util.Bits

A minimalistic bitset data structure.

type t

Represents a bitset.

val create : unit -> t

create () returns a new zero length bitset.

val push : t -> bool -> unit

push bs b adds the bit b to the end of the bitset bs.

val iter : (bool -> unit) -> t -> unit

iter action bs calls the action for each bit in the bitset bs.

diff --git a/doc/multicore-bench/Multicore_bench/Util/index.html b/doc/multicore-bench/Multicore_bench/Util/index.html index 6d89df7..b908420 100644 --- a/doc/multicore-bench/Multicore_bench/Util/index.html +++ b/doc/multicore-bench/Multicore_bench/Util/index.html @@ -1,5 +1,5 @@ -Util (multicore-bench.Multicore_bench.Util)

Module Multicore_bench.Util

Utilities for creating benchmarks.

⚠️ In the future we expect to regroup these utilities under different modules and deprecate them in this module.

val iter_factor : int

A multiplier depending various factors such as whether we are running on a 32- or 64-bit machine (1x/10x), bytecode or native (1x/10x), and whether we are running on single-core or multicore OCaml (1x/10x).

val alloc : ?batch:int -> int Stdlib.Atomic.t -> int

alloc ~batch n tries to decrement the specified atomic variable n by at most the optional amount ~batch and not beyond n having value 0. Returns the amount by which n was decremented, which is 0 only in case n is 0.

val cross : 'a list -> 'b list -> ('a * 'b) list

cross xs ys returns a list formed by pairing each element of xs with each element of ys.

For example:

# Util.cross [1; 2; 3] ["a"; "b"]
 - : (int * string) list =
diff --git a/doc/multicore-bench/Multicore_bench/index.html b/doc/multicore-bench/Multicore_bench/index.html
index e57c10d..7f2cc60 100644
--- a/doc/multicore-bench/Multicore_bench/index.html
+++ b/doc/multicore-bench/Multicore_bench/index.html
@@ -1,4 +1,4 @@
 
-Multicore_bench (multicore-bench.Multicore_bench)
Module Multicore_bench
Multicore bench is a framework for writing multicore benchmark executables to run on current-bench.
To use the framework one typically opens it
open Multicore_bench
which brings a number of submodules into scope.
module Metric : sig ... end
Dealing with benchmark metrics.
module Unit_of_rate : sig ... end
Dealing with units of rate.
module Unit_of_time : sig ... end
Dealing with units of time.
module Times : sig ... end
Recording timings of benchmarks running on multiple domains in parallel and producing metrics from the recorded timings.
module Suite : sig ... end
Dealing with benchmark suites.
module Cmd : sig ... end
Command line interface for a benchmark executable.
module Util : sig ... end
Utilities for creating benchmarks.

+
Module Multicore_bench
Multicore bench is a framework for writing multicore benchmark executables to run on current-bench.
To use the framework one typically opens it
open Multicore_bench
which brings a number of submodules into scope.
module Trend : sig ... end
Dealing with trends.
module Metric : sig ... end
Dealing with benchmark metrics.
module Unit_of_rate : sig ... end
Dealing with units of rate.
module Unit_of_time : sig ... end
Dealing with units of time.
module Times : sig ... end
Recording timings of benchmarks running on multiple domains in parallel and producing metrics from the recorded timings.
module Suite : sig ... end
Dealing with benchmark suites.
module Cmd : sig ... end
Command line interface for a benchmark executable.
module Util : sig ... end
Utilities for creating benchmarks.

diff --git a/doc/multicore-bench/db.js b/doc/multicore-bench/db.js
index 58c6224..031090f 100644
--- a/doc/multicore-bench/db.js
+++ b/doc/multicore-bench/db.js
@@ -1 +1 @@
-function sherlodoc_db () { return 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"; }
+function sherlodoc_db () { return 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"; 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diff --git a/doc/multicore-bench/index.html b/doc/multicore-bench/index.html
index 21550e6..65d9e4a 100644
--- a/doc/multicore-bench/index.html
+++ b/doc/multicore-bench/index.html
@@ -1,4 +1,4 @@
 
-index (multicore-bench.index)
multicore-bench index
Library multicore-bench
The entry point of this library is the module: Multicore_bench.

diff --git a/doc/odoc.support/odoc.css b/doc/odoc.support/odoc.css
index c23517b..71148de 100644
--- a/doc/odoc.support/odoc.css
+++ b/doc/odoc.support/odoc.css
@@ -1,7 +1,7 @@
 @charset "UTF-8";
 /* Copyright (c) 2016 The odoc contributors. All rights reserved.
    Distributed under the ISC license, see terms at the end of the file.
-   odoc 2.4.1 */
+   odoc 2.4.2 */
 
 /* Fonts */
 /* noticia-text-regular - latin */
diff --git a/doc/sherlodoc.js b/doc/sherlodoc.js
index fca2733..2e545c4 100644
--- a/doc/sherlodoc.js
+++ b/doc/sherlodoc.js
@@ -1,39 +1,39 @@
 // Generated by js_of_ocaml
-//# buildInfo:effects=false, kind=exe, use-js-string=true, version=5.7.1
+//# buildInfo:effects=false, kind=exe, use-js-string=true, version=5.8.1
 (function(a){typeof
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-hv(a,b,c,d,e){if(d<=b)for(var
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+lw(a,b,c,d,e){if(d<=b)for(var
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 for(var
 f=e;f>=1;f--)c[d+f]=a[b+f];return 0}function
-hw(a,b,c){if(a[1]===b){a[1]=c;return 1}return 0}function
-hx(a,b){var
+gk(a,b,c){if(a[1]===b){a[1]=c;return 1}return 0}function
+lx(a,b){var
 c=a[1];a[1]+=b;return c}function
-cs(a){return a[1]}function
-fm(a){var
-b=k.process;if(b&&b.env&&b.env[a]!=undefined)return b.env[a];if(k.jsoo_static_env&&k.jsoo_static_env[a])return k.jsoo_static_env[a]}var
-cH=0;(function(){var
-c=fm(et);if(c!==undefined){var
+bA(a){return a[1]}function
+gV(a){var
+b=f.process;if(b&&b.env&&b.env[a]!=undefined)return b.env[a];if(f.jsoo_static_env&&f.jsoo_static_env[a])return f.jsoo_static_env[a]}var
+dU=0;(function(){var
+c=gV(fZ);if(c!==undefined){var
 b=c.split(",");for(var
-a=0;aa.hi)return 1;if(this.hia.mi)return 1;if(this.mia.lo)return 1;if(this.loc)return 1;if(ba.mi)return 1;if(this.mia.lo)return 1;if(this.lo>24),c=-this.hi+(b>>24);return new
@@ -65,7 +65,7 @@ b=this.lo+a.lo,c=this.mi+a.mi+(b>>24),e=this.hi+a.hi+(c>>24);return new
 d(b,c,e)};d.prototype.sub=function(a){var
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-b=this.lo*a.lo,c=(b*e5|0)+this.mi*a.lo+this.lo*a.mi,e=(c*e5|0)+this.hi*a.lo+this.mi*a.mi+this.lo*a.hi;return new
+b=this.lo*a.lo,c=(b*gD|0)+this.mi*a.lo+this.lo*a.mi,e=(c*gD|0)+this.hi*a.lo+this.mi*a.mi+this.lo*a.hi;return new
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+Error(b||e[a]);d.code=a;if(!c)throw d;return d}function
+m(a,b,c){var
+d=0,e=0;for(;d>>0}function
+n(a,b){var
+q=a[0]|a[1]<<8|a[2]<<16;if(q==0x2FB528&&a[3]==fY){var
+e=a[4],l=e>>5&1,s=e>>2&1,o=e&3,j=e>>6;if(e&8)i(0);var
+h=6-l,n=o==3?4:o,t=m(a,h,n);h+=n;var
+p=j?1<>3);c=r+(r>>3)*(a[5]&7)}if(c>2145386496)i(1);var
+d=new
+g((b==1?k||c:b?0:c)+12);d[0]=1,d[4]=4,d[8]=8;return{b:h+p,y:0,l:0,d:t,w:b&&b!=1?b:d.subarray(12),e:c,o:new
+f(d.buffer,0,3),u:k,c:s,m:Math.min(131072,c)}}else if((q>>4|a[3]<<20)==0x184D2A5)return u(a,4)+8;i(0)}function
+o(a){var
+b=0;for(;1<c)i(3);var
+d=1<0){var
+q=o(j+1),s=h>>3,z=(1<>(h&7)&z,A=(1<A)f-=B}x[++k]=--f;if(f==-1){j+=f;r[--y]=k}else
+j-=f;if(!f)do{var
+G=h>>3;t=(a[G]|a[G+1]<<8)>>(h&7)&3;h+=2;k+=t}while(t==3)}if(k>aZ||j)i(0);var
+n=0,M=(d>>1)+(d>>3)+3,L=d-1;for(var
+m=0;m<=k;++m){var
+u=x[m];if(u<1){w[m]=-u;continue}for(e=0;e=y)}}if(n)i(0);for(e=0;e>3,{b:p,s:r,n:D,t:F}]}function
+al(a,b){var
+c=0,e=-1,w=new
+g(292),x=a[b],d=w.subarray(0,ae),J=w.subarray(ae,fe),k=new
+C(w.buffer,fe);if(x>3;n+=(a[m]|a[m+1]<<8)>>(f&7)&(1<>3;p+=(a[m]|a[m+1]<<8)>>(f&7)&(1<aZ)i(0)}else{e=x-bw;for(;c>4;d[c+1]=B&15}++b}var
+z=0;for(c=0;c11)i(0);z+=l&&1<0;--c){var
+I=k[c];s(H,c,I,k[c-1]=I+J[c]*(1<j&&h>3,p=(a[g]|a[g+1]<<8|a[g+2]<<16)>>(d&7);e=(e<>2,f=e<<1,g=e+f;r(a.subarray(d,d+=a[0]|a[1]<<8),b.subarray(0,e),c);r(a.subarray(d,d+=a[2]|a[3]<<8),b.subarray(e,f),c);r(a.subarray(d,d+=a[4]|a[5]<<8),b.subarray(f,g),c);r(a.subarray(d),b.subarray(g),c)}function
+l(a,b,c){var
+P,d=b.b,R=a[d],S=R>>1&3;b.l=R&1;var
+L=R>>3|a[d+1]<<5|a[d+2]<<13,p=(d+=3)+L;if(S==1){if(d>=a.length)return;b.b=d+1;if(c){s(c,a[d],b.y,b.y+=L);return c}return s(new
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+D=a[d],G=D&3,A=D>>2&3,m=D>>4,u=0,ad=0;if(G<2)if(A&1)m|=a[++d]<<4|(A&2&&a[++d]<<12);else
+m=D>>3;else{ad=A;if(A<2)m|=(a[++d]&63)<<4,u=a[d]>>6|a[++d]<<2;else if(A==2)m|=a[++d]<<4|(a[++d]&3)<<12,u=a[d]>>2|a[++d]<<6;else
+m|=a[++d]<<4|(a[++d]&63)<<12,u=a[d]>>6|a[++d]<<2|a[++d]<<10}++d;var
+h=c?c.subarray(b.y,b.y+b.m):new
+g(b.m),l=h.length-m;if(G==0)h.set(a.subarray(d,d+=m),l);else if(G==1)s(h,a[d++],l);else{var
+T=b.h;if(G==2){var
+Y=al(a,d);u+=d-(d=Y[0]);b.h=T=Y[1]}else if(!T)i(0);(ad?af:r)(a.subarray(d,d+=u),h.subarray(l),T)}var
+n=a[d++];if(n){if(n==aZ)n=(a[d++]|a[d++]<<8)+0x7F00;else if(n>bw)n=n-aL<<8|a[d++];var
+ae=a[d++];if(ae&3)i(0);var
+E=[ah,ai,ag];for(var
+f=2;f>-1;--f){var
+V=ae>>(f<<1)+2&3;if(V==1){var
+X=new
+g([0,0,a[d++]]);E[f]={s:X.subarray(2,3),n:X.subarray(0,1),t:new
+C(X.buffer,0,1),b:0}}else if(V==2)P=t(a,d,9-(f&1)),d=P[0],E[f]=P[1];else if(V==3){if(!b.t)i(0);E[f]=b.t[f]}}var
+Q=b.t=E,y=Q[0],z=Q[1],w=Q[2],Z=a[p-1];if(!Z)i(0);var
+j=(p<<3)-8+o(Z)-w.b,e=j>>3,k=0,I=(a[e]|a[e+1]<<8)>>(j&7)&(1<>3;var
+K=(a[e]|a[e+1]<<8)>>(j&7)&(1<>3;var
+J=(a[e]|a[e+1]<<8)>>(j&7)&(1<>3;var
+ac=1<>>(j&7)&ac-1);e=(j-=N[W])>>3;var
+x=ak[W]+((a[e]|a[e+1]<<8|a[e+2]<<16)>>(j&7)&(1<>3;var
+H=aj[U]+((a[e]|a[e+1]<<8|a[e+2]<<16)>>(j&7)&(1<>3;I=w.t[I]+((a[e]|a[e+1]<<8)>>(j&7)&(1<<_)-1);e=(j-=$)>>3;J=y.t[J]+((a[e]|a[e+1]<<8)>>(j&7)&(1<<$)-1);e=(j-=aa)>>3;K=z.t[K]+((a[e]|a[e+1]<<8)>>(j&7)&(1<3){b.o[2]=b.o[1];b.o[1]=b.o[0];b.o[0]=q-=3}else{var
+F=q-(H!=0);if(F){q=F==3?b.o[0]-1:b.o[F];if(F>1)b.o[2]=b.o[1];b.o[1]=b.o[0];b.o[0]=q}else
+q=b.o[0]}for(var
+f=0;fx)v=x;for(var
+f=0;f>24},read16u:function(){var
 b=this.s,a=this.i;this.i=a+2;return b[a]<<8|b[a+1]},read16s:function(){var
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-b=this.i;this.i=b+a;return cJ(this.s.subarray(b,b+a))},readuint8array:function(a){var
+b=this.i;this.i=b+a;return dX(this.s.subarray(b,b+a))},readuint8array:function(a){var
 b=this.i;this.i=b+a;return this.s.subarray(b,b+a)}};function
-aD(a){return bu(ao(a))}function
-hT(d,b){function
+be(a){return cm(a1(a))}function
+lX(d,b){function
 f(a){var
-b=d.read8u(),c=b&bl;while((b&w)!=0){b=d.read8u();var
-e=c<<7;if(c!=e>>7)a[0]=true;c=e|b&bl}return c}var
-x=d.read32u();switch(x){case
+b=d.read8u(),c=b&ca;while((b&M)!=0){b=d.read8u();var
+e=c<<7;if(c!=e>>7)a[0]=true;c=e|b&ca}return c}var
+w=d.read32u();switch(w){case
 0x8495A6BE:var
-v=20,o=0,h=d.read32u(),r=h,p=d.read32u(),s=d.read32u(),t=d.read32u();break;case
+v=20,n=0,h=d.read32u(),q=h,o=d.read32u(),r=d.read32u(),t=d.read32u();break;case
 0x8495A6BD:var
-v=d.read8u()&ci,o=1,a=[false],h=f(a),r=f(a),p=f(a),s=f(a),t=f(a);if(a[0])m("caml_input_value_from_reader: object too large to be read back on this platform");break;case
-0x8495A6BF:m("caml_input_value_from_reader: object too large to be read back on a 32-bit platform");break;default:m("caml_input_value_from_reader: bad object");break}var
-n=[],c=p>0?[]:null,i=0;function
+v=d.read8u()&dr,n=1,a=[false],h=f(a),q=f(a),o=f(a),r=f(a),t=f(a);if(a[0])s("caml_input_value_from_reader: object too large to be read back on this platform");break;case
+0x8495A6BF:s("caml_input_value_from_reader: object too large to be read back on a 32-bit platform");break;default:s("caml_input_value_from_reader: bad object");break}var
+m=[],c=o>0?[]:null,i=0;function
 l(a){var
-k=a.read8u();if(k>=0x40)if(k>=w){var
-r=k&0xF,l=k>>4&0x7,b=[r];if(l==0)return b;if(c)c[i++]=b;n.push(b,l);return b}else
-return k&ci;else if(k>=0x20){var
+k=a.read8u();if(k>=0x40)if(k>=M){var
+q=k&0xF,l=k>>4&0x7,b=[q];if(l==0)return b;if(c)c[i++]=b;m.push(b,l);return b}else
+return k&dr;else if(k>=0x20){var
 f=k&0x1F,b=a.readstr(f);if(c)c[i++]=b;return b}else
 switch(k){case
 0x00:return a.read8s();case
 0x01:return a.read16s();case
 0x02:return a.read32s();case
-0x03:m("input_value: integer too large");break;case
+0x03:s("input_value: integer too large");break;case
 0x04:var
-j=a.read8u();if(o==0)j=i-j;return c[j];case
+j=a.read8u();if(n==0)j=i-j;return c[j];case
 0x05:var
-j=a.read16u();if(o==0)j=i-j;return c[j];case
+j=a.read16u();if(n==0)j=i-j;return c[j];case
 0x06:var
-j=a.read32u();if(o==0)j=i-j;return c[j];case
+j=a.read32u();if(n==0)j=i-j;return c[j];case
 0x08:var
-t=a.read32u(),r=t&eo,l=t>>10,b=[r];if(l==0)return b;if(c)c[i++]=b;n.push(b,l);return b;case
-0x13:m("input_value: data block too large");break;case
+t=a.read32u(),q=t&fR,l=t>>10,b=[q];if(l==0)return b;if(c)c[i++]=b;m.push(b,l);return b;case
+0x13:s("input_value: data block too large");break;case
 0x09:var
 f=a.read8u(),b=a.readstr(f);if(c)c[i++]=b;return b;case
 0x0A:var
@@ -682,68 +854,76 @@ f=a.read32u(),b=a.readstr(f);if(c)c[i++]=b;return b;case
 g=new
 Array(8);for(var
 d=0;d<8;d++)g[7-d]=a.read8u();var
-b=aD(g);if(c)c[i++]=b;return b;case
+b=be(g);if(c)c[i++]=b;return b;case
 0x0B:var
 g=new
 Array(8);for(var
 d=0;d<8;d++)g[d]=a.read8u();var
-b=aD(g);if(c)c[i++]=b;return b;case
+b=be(g);if(c)c[i++]=b;return b;case
 0x0E:var
 f=a.read8u(),b=new
-Array(f+1);b[0]=ad;var
+Array(f+1);b[0]=aK;var
 g=new
 Array(8);if(c)c[i++]=b;for(var
 d=1;d<=f;d++){for(var
-h=0;h<8;h++)g[7-h]=a.read8u();b[d]=aD(g)}return b;case
+h=0;h<8;h++)g[7-h]=a.read8u();b[d]=be(g)}return b;case
 0x0D:var
 f=a.read8u(),b=new
-Array(f+1);b[0]=ad;var
+Array(f+1);b[0]=aK;var
 g=new
 Array(8);if(c)c[i++]=b;for(var
 d=1;d<=f;d++){for(var
-h=0;h<8;h++)g[h]=a.read8u();b[d]=aD(g)}return b;case
+h=0;h<8;h++)g[h]=a.read8u();b[d]=be(g)}return b;case
 0x07:var
 f=a.read32u(),b=new
-Array(f+1);b[0]=ad;if(c)c[i++]=b;var
+Array(f+1);b[0]=aK;if(c)c[i++]=b;var
 g=new
 Array(8);for(var
 d=1;d<=f;d++){for(var
-h=0;h<8;h++)g[7-h]=a.read8u();b[d]=aD(g)}return b;case
+h=0;h<8;h++)g[7-h]=a.read8u();b[d]=be(g)}return b;case
 0x0F:var
 f=a.read32u(),b=new
-Array(f+1);b[0]=ad;var
+Array(f+1);b[0]=aK;var
 g=new
 Array(8);for(var
 d=1;d<=f;d++){for(var
-h=0;h<8;h++)g[h]=a.read8u();b[d]=aD(g)}return b;case
+h=0;h<8;h++)g[h]=a.read8u();b[d]=be(g)}return b;case
 0x10:case
-0x11:m("input_value: code pointer");break;case
+0x11:s("input_value: code pointer");break;case
 0x12:case
 0x18:case
 0x19:var
-s,u=e;while((s=a.read8u())!=0)u+=String.fromCharCode(s);var
-q=aC[u],p;if(!q)m("input_value: unknown custom block identifier");switch(k){case
+r,u=e;while((r=a.read8u())!=0)u+=String.fromCharCode(r);var
+p=bd[u],o;if(!p)s("input_value: unknown custom block identifier");switch(k){case
 0x12:break;case
-0x19:if(!q.fixed_length)m("input_value: expected a fixed-size custom block");p=q.fixed_length;break;case
-0x18:p=a.read32u();a.read32s();a.read32s();break}var
-v=a.i,l=[0],b=q.deserialize(a,l);if(p!=undefined)if(p!=l[0])m("input_value: incorrect length of serialized custom block");if(c)c[i++]=b;return b;default:m("input_value: ill-formed message")}}if(o)if(eX)var
+0x19:if(!p.fixed_length)s("input_value: expected a fixed-size custom block");o=p.fixed_length;break;case
+0x18:o=a.read32u();a.read32s();a.read32s();break}var
+v=a.i,l=[0],b=p.deserialize(a,l);if(o!=undefined)if(o!=l[0])s("input_value: incorrect length of serialized custom block");if(c)c[i++]=b;return b;default:s("input_value: ill-formed message")}}if(n)if(gu)var
 u=d.readuint8array(h),g=new
-Uint8Array(r),g=eX(u,g),d=new
-cr(g,0);else
-m("input_value: compressed object, cannot decompress");var
-g=l(d);while(n.length>0){var
-q=n.pop(),j=n.pop(),k=j.length;if(k0){var
+p=m.pop(),j=m.pop(),k=j.length;if(k>24&L,a>>31&E)}function
-e6(a,b){return a.or(b)}function
-h2(a){return a.toInt()}function
-h6(a,b){switch(b.length){case
+gj(G(a),typeof
+b=="number"?b:b[0]);return lX(c,b)}function
+l4(a){return+a.isZero()}function
+bF(a){return new
+d(a&am,a>>24&am,a>>31&ad)}function
+gF(a){return a.toInt()}function
+l3(a){return+a.isNeg()}function
+gB(a){return a.neg()}function
+l1(a,b){var
+c=dS(a);if(c.signedconv&&l3(b)){c.sign=-1;b=gB(b)}var
+d=e,i=bF(c.base),h="0123456789abcdef";do{var
+g=b.udivmod(i);b=g.quotient;d=h.charAt(gF(g.modulus))+d}while(!l4(b));if(c.prec>=0){c.filler=Q;var
+f=c.prec-d.length;if(f>0)d=bh(f,R)+d}return dI(c,d)}function
+gE(a,b){return a.or(b)}function
+l$(a,b){switch(b.length){case
 1:return new
 a;case
 2:return new
@@ -760,36 +940,35 @@ a(b[1],b[2],b[3],b[4],b[5]);case
 a(b[1],b[2],b[3],b[4],b[5],b[6]);case
 8:return new
 a(b[1],b[2],b[3],b[4],b[5],b[6],b[7])}function
-c(){return a.apply(this,e8(b))}c.prototype=a.prototype;return new
+c(){return a.apply(this,gH(b))}c.prototype=a.prototype;return new
 c}var
-bq=aB;function
-aF(a,b){return function(){var
+cg=aQ;function
+bg(a,b){return function(){var
 f=arguments.length,d=new
 Array(a),e=Math.min(arguments.length,a);for(var
-c=0;c>16;return c}function
-h8(a,b,c){var
-p=2,q=3,t=5,e=6,i=7,h=8,k=9,o=1,n=2,s=3,u=4,r=5;if(!a.lex_default){a.lex_base=a2(a[o]);a.lex_backtrk=a2(a[n]);a.lex_check=a2(a[r]);a.lex_trans=a2(a[u]);a.lex_default=a2(a[s])}var
-f,d=b,l=a5(c[p]);if(d>=0){c[i]=c[t]=c[e];c[h]=-1}else
+mb(a,b,c){var
+o=2,p=3,t=5,e=6,i=7,h=8,k=9,n=1,m=2,r=3,u=4,q=5;if(!a.lex_default){a.lex_base=bI(a[n]);a.lex_backtrk=bI(a[m]);a.lex_check=bI(a[q]);a.lex_trans=bI(a[u]);a.lex_default=bI(a[r])}var
+f,d=b,l=bL(c[o]);if(d>=0){c[i]=c[t]=c[e];c[h]=-1}else
 d=-d-1;for(;;){var
 g=a.lex_base[d];if(g<0)return-g-1;var
-j=a.lex_backtrk[d];if(j>=0){c[i]=c[e];c[h]=j}if(c[e]>=c[q])if(c[k]==0)return-d-1;else
-f=az;else{f=l[c[e]];c[e]++}if(a.lex_check[g+f]==d)d=a.lex_trans[g+f];else
-d=a.lex_default[d];if(d<0){c[e]=c[i];if(c[h]==-1)m("lexing: empty token");else
-return c[h]}else if(f==az)c[k]=0}}function
-fa(a){return z(a)}function
-e2(a,b){return a.add(b)}function
-e3(a,b){return a.mul(b)}function
-hZ(a){return a.neg()}function
-cF(a,b){return a.ucompare(b)<0}function
-im(a){var
-b=0,e=f(a),c=10,d=1;if(e>0)switch(P(a,b)){case
+j=a.lex_backtrk[d];if(j>=0){c[i]=c[e];c[h]=j}if(c[e]>=c[p])if(c[k]==0)return-d-1;else
+f=ae;else{f=l[c[e]];c[e]++}if(a.lex_check[g+f]==d)d=a.lex_trans[g+f];else
+d=a.lex_default[d];if(d<0){c[e]=c[i];if(c[h]==-1)s("lexing: empty token");else
+return c[h]}else if(f==ae)c[k]=0}}function
+gM(a){return N(a)}function
+gz(a,b){return a.add(b)}function
+gA(a,b){return a.mul(b)}function
+dQ(a,b){return a.ucompare(b)<0}function
+mp(a){var
+b=0,e=k(a),c=10,d=1;if(e>0)switch($(a,b)){case
 45:b++;d=-1;break;case
-43:b++;d=1;break}if(b+10)switch(P(a,b)){case
 66:c=2;b+=2;break;case
 117:case
 85:b+=2;break}return[b,d,c]}function
-fb(a){if(a>=48&&a<=57)return a-48;if(a>=65&&a<=90)return a-55;if(a>=97&&a<=122)return a-87;return-1}function
-e4(a){var
-i=im(a),h=i[0],k=i[1],e=i[2],j=bv(e),l=new
-d(L,0xfffffff,E).udivmod(j).quotient,g=P(a,h),b=fb(g);if(b<0||b>=e)m(aU);var
-c=bv(b);for(;;){h++;g=P(a,h);if(g==95)continue;b=fb(g);if(b<0||b>=e)break;if(cF(l,c))m(aU);b=bv(b);c=e2(e3(j,c),b);if(cF(c,b))m(aU)}if(h!=f(a))m(aU);if(e==10&&cF(new
-d(0,0,D),c))m(aU);if(k<0)c=hZ(c);return c}function
-hA(a,b){return a.get(a.offset(b))}function
-h4(a,b){return a.xor(b)}function
-h1(a,b){return a.shift_right_unsigned(b)}function
-h0(a,b){return a.shift_left(b)}function
-a3(a){function
-o(a,b){return h0(a,b)}function
-h(a,b){return h1(a,b)}function
-s(a,b){return e6(a,b)}function
-f(a,b){return h4(a,b)}function
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