From f9df7ce57d7b54ff54a33d32d6866e9d73e98eba Mon Sep 17 00:00:00 2001 From: Aryan Sharma Date: Wed, 21 Oct 2026 22:21:24 +0530 Subject: [PATCH] feat: add `ml/base/loss/float32/squared-error-gradient` Signed-off-by: Aryan Sharma --- .../float32/squared-error-gradient/README.md | 225 ++++++++++++++++++ .../benchmark/benchmark.js | 64 +++++ .../benchmark/benchmark.native.js | 74 ++++++ .../benchmark/c/native/Makefile | 146 ++++++++++++ .../benchmark/c/native/benchmark.c | 148 ++++++++++++ .../squared-error-gradient/binding.gyp | 170 +++++++++++++ .../squared-error-gradient/docs/repl.txt | 39 +++ .../docs/types/index.d.ts | 62 +++++ .../squared-error-gradient/docs/types/test.ts | 72 ++++++ .../examples/c/Makefile | 146 ++++++++++++ .../examples/c/example.c | 33 +++ .../squared-error-gradient/examples/index.js | 34 +++ .../squared-error-gradient/include.gypi | 53 +++++ .../loss/float32/squared_error_gradient.h | 38 +++ .../squared-error-gradient/lib/index.js | 55 +++++ .../squared-error-gradient/lib/main.js | 75 ++++++ .../squared-error-gradient/lib/native.js | 68 ++++++ .../squared-error-gradient/manifest.json | 75 ++++++ .../squared-error-gradient/package.json | 69 ++++++ .../squared-error-gradient/src/Makefile | 70 ++++++ .../squared-error-gradient/src/addon.c | 22 ++ .../float32/squared-error-gradient/src/main.c | 40 ++++ .../test/fixtures/julia/REQUIRE | 2 + .../test/fixtures/julia/runner.jl | 95 ++++++++ .../test/fixtures/julia/small_negative.json | 1 + .../test/fixtures/julia/small_positive.json | 1 + .../test/fixtures/julia/tiny_negative.json | 1 + .../test/fixtures/julia/tiny_positive.json | 1 + .../squared-error-gradient/test/test.js | 136 +++++++++++ .../test/test.native.js | 145 +++++++++++ 30 files changed, 2160 insertions(+) create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/README.md create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/benchmark.native.js create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/c/native/Makefile create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/c/native/benchmark.c create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/binding.gyp create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/c/Makefile create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/c/example.c create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/index.js create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/include.gypi create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/include/stdlib/ml/base/loss/float32/squared_error_gradient.h create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/lib/index.js create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/lib/main.js create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/lib/native.js create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/manifest.json create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/package.json create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/Makefile create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/addon.c create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/main.c create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/REQUIRE create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/runner.jl create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/small_negative.json create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/small_positive.json create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/tiny_negative.json create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/tiny_positive.json create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/test.js create mode 100644 lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/test.native.js diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/README.md b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/README.md new file mode 100644 index 000000000000..c09234cb1c44 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/README.md @@ -0,0 +1,225 @@ + + +# squaredErrorGradient + +> Compute the [squared error loss gradient][squared-error-loss-gradient] with respect to a model parameter for a single-precision floating-point number. + +
+ +The [squared error loss gradient][squared-error-loss-gradient] is defined as + + + +```math +\frac{\partial \ell}{\partial w} = -(y-p)x +``` + + + +
+ + + +
+ +## Usage + +```javascript +var squaredErrorGradient = require( '@stdlib/ml/base/loss/float32/squared-error-gradient' ); +``` + +#### squaredErrorGradient( x, y, p ) + +Computes the [squared error loss gradient][squared-error-loss-gradient] with respect to a model parameter for a single-precision floating-point number. + +```javascript +var v = squaredErrorGradient( 5.0, -2.0, -1.782 ); +// returns ~1.09 + +v = squaredErrorGradient( -4.0, 1.0, -0.999 ); +// returns ~7.996 +``` + +The function accepts the following arguments: + +- **x**: input value. +- **y**: true target value. +- **p**: predicted value. + +If any argument is `NaN`, the function returns `NaN`. + +```javascript +var v = squaredErrorGradient( NaN, 2.0, 0.782 ); +// returns NaN + +v = squaredErrorGradient( 1.0, NaN, 0.782 ); +// returns NaN + +v = squaredErrorGradient( 1.0, 2.0, NaN ); +// returns NaN + +v = squaredErrorGradient( NaN, NaN, NaN ); +// returns NaN +``` + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var squaredErrorGradient = require( '@stdlib/ml/base/loss/float32/squared-error-gradient' ); + +var x = uniform( 100, -100.0, 100.0, { + 'dtype': 'float32' +}); +var y = uniform( 100, -100.0, 100.0, { + 'dtype': 'float32' +}); +var p = uniform( 100, -100.0, 100.0, { + 'dtype': 'float32' +}); +logEachMap( 'squaredErrorGradient(%0.4f, %0.4f, %0.4f) = %0.4f', x, y, p, squaredErrorGradient ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/ml/base/loss/float32/squared_error_gradient.h" +``` + +#### stdlib_base_float32_squared_error_gradient( x, y, p ) + +Computes the [squared error loss gradient][squared-error-loss-gradient] with respect to a model parameter for a single-precision floating-point number. + +```c +float out = stdlib_base_float32_squared_error_gradient( 5.0f, -2.0f, -1.782f ); +// returns ~1.09 +``` + +The function accepts the following arguments: + +- **x**: `[in] float` input value. +- **y**: `[in] float` true target value. +- **p**: `[in] float` predicted value. + +```c +float stdlib_base_float32_squared_error_gradient( const float x, const float y, const float p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/ml/base/loss/float32/squared_error_gradient.h" +#include + +int main( void ) { + const float x[] = { -10.0f, -9.56f, -8.67f, -7.78f, -6.89f, 6.89f, 7.78f, 8.67f, 9.56f, 10.0f }; + const float y[] = { -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f }; + const float p[] = { -5.0f, -3.89f, -2.78f, -1.67f, -0.56f, 0.56f, 1.67f, 2.78f, 3.89f, 5.0f }; + + float v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_float32_squared_error_gradient( x[ i ], y[ i ], p[ i ] ); + printf( "squaredErrorGradient(%f, %f, %f) = %f\n", x[ i ], y[ i ], p[ i ], v ); + } +} +``` + +
+ + + +
+ + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[squared-error-loss-gradient]: https://en.wikipedia.org/wiki/Mean_squared_error#Loss_function + +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/benchmark.js new file mode 100644 index 000000000000..44fc0bccc9cd --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/benchmark.js @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pkg = require( './../package.json' ).name; +var squaredErrorGradient = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var len; + var x; + var y; + var p; + var v; + var i; + + len = 100; + x = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + y = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + p = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = squaredErrorGradient( x[ i%x.length ], y[ i%y.length ], p[ i%p.length ] ); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/benchmark.native.js new file mode 100644 index 000000000000..04fae5a7ebd2 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var squaredErrorGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( squaredErrorGradient instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var len; + var x; + var y; + var p; + var v; + var i; + + len = 100; + x = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + y = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + p = uniform( len, -100.0, 100.0, { + 'dtype': 'float32' + }); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = squaredErrorGradient( x[ i%x.length ], y[ i%y.length ], p[ i%p.length ] ); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/c/native/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..e771a0938d1f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/benchmark/c/native/benchmark.c @@ -0,0 +1,148 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float32/squared_error_gradient.h" +#include +#include +#include +#include +#include + +#define NAME "squared_error_gradient" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static float random_uniform( const float min, const float max ) { + float v = (float)rand() / ( (float)RAND_MAX + 1.0f ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + float *x; + float *y; + float *p; + double t; + float v; + int i; + + x = (float *) malloc( 100 * sizeof( float ) ); + y = (float *) malloc( 100 * sizeof( float ) ); + p = (float *) malloc( 100 * sizeof( float ) ); + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -100.0f, 100.0f ); + y[ i ] = random_uniform( -100.0f, 100.0f ); + p[ i ] = random_uniform( -100.0f, 100.0f ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + v = stdlib_base_float32_squared_error_gradient( x[ i % 100 ], y[ i % 100 ], p[ i % 100 ] ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + free( p ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/binding.gyp b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/repl.txt new file mode 100644 index 000000000000..04b83cbbd373 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/repl.txt @@ -0,0 +1,39 @@ + +{{alias}}( x, y, p ) + Computes the squared error loss gradient with respect to a model parameter + for a single-precision floating-point number. + + If any argument is `NaN`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + y: number + True target value. + + p: number + Predicted value. + + Returns + ------- + v: number + Squared error loss gradient. + + Examples + -------- + > var v = {{alias}}( 5.0, -2.0, -1.782 ) + ~1.09 + > v = {{alias}}( 1.0, 0.202, 0.202 ) + 0.0 + > v = {{alias}}( -4.0, 1.0, -0.999 ) + ~7.996 + > v = {{alias}}( 4.723, 0.2, 0.532 ) + ~1.568 + > v = {{alias}}( 1.0, NaN, 0.987 ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/types/index.d.ts new file mode 100644 index 000000000000..72803e2c397c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/types/index.d.ts @@ -0,0 +1,62 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Computes the squared error loss gradient with respect to a model parameter for a single-precision floating-point number. +* +* ## Notes +* +* - The squared error loss is defined as the squared difference of the observed and fitted value. +* +* @param x - input value +* @param y - true target value +* @param p - predicted value +* @returns squared error loss gradient +* +* @example +* var v = squaredErrorGradient( 5.0, -2.0, -1.782 ); +* // returns ~1.09 +* +* @example +* var v = squaredErrorGradient( 1.0, 0.202, 0.202 ); +* // returns 0.0 +* +* @example +* var v = squaredErrorGradient( -4.0, 1.0, -0.999 ); +* // returns ~7.996 +* +* @example +* var v = squaredErrorGradient( -10.33, -2.4, 0.234 ); +* // returns ~-27.209 +* +* @example +* var v = squaredErrorGradient( 4.723, 0.2, 0.532 ); +* // returns ~1.568 +* +* @example +* var v = squaredErrorGradient( 11.928, -1.811, -0.9 ); +* // returns ~10.866 +*/ +declare function squaredErrorGradient( x: number, y: number, p: number ): number; + + +// EXPORTS // + +export = squaredErrorGradient; diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/types/test.ts new file mode 100644 index 000000000000..c8a4df3d6932 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/docs/types/test.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import squaredErrorGradient = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + squaredErrorGradient( 5.0, -2.0, -1.782 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + squaredErrorGradient( true, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( false, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( null, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( undefined, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( '5', -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( [], -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( {}, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( ( x: number ): number => x, -2.0, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + squaredErrorGradient( 1.0, true, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, false, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, null, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, undefined, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, '5', 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, [], 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, {}, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, ( x: number ): number => x, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + squaredErrorGradient( 1.0, -2.0, true ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, false ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, null ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, undefined ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, '5' ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, [] ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, {} ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, ( x: number ): number => x ); // $ExpectError +} + + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + squaredErrorGradient(); // $ExpectError + squaredErrorGradient( 1.0 ); // $ExpectError + squaredErrorGradient( 1.0, 0.7873 ); // $ExpectError + squaredErrorGradient( 1.0, 0.900, 0.7873, 0.546 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/c/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/c/example.c b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/c/example.c new file mode 100644 index 000000000000..ed2c92bea71b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/c/example.c @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float32/squared_error_gradient.h" +#include + +int main( void ) { + const float x[] = { -10.0f, -9.56f, -8.67f, -7.78f, -6.89f, 6.89f, 7.78f, 8.67f, 9.56f, 10.0f }; + const float y[] = { -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f }; + const float p[] = { -5.0f, -3.89f, -2.78f, -1.67f, -0.56f, 0.56f, 1.67f, 2.78f, 3.89f, 5.0f }; + + float v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_float32_squared_error_gradient( x[ i ], y[ i ], p[ i ] ); + printf( "squaredErrorGradient(%f, %f, %f) = %f\n", x[ i ], y[ i ], p[ i ], v ); + } +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/index.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/index.js new file mode 100644 index 000000000000..4ff91f5085c4 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var squaredErrorGradient = require( './../lib' ); + +var x = uniform( 100, -100.0, 100.0, { + 'dtype': 'float32' +}); +var y = uniform( 100, -100.0, 100.0, { + 'dtype': 'float32' +}); +var p = uniform( 100, -100.0, 100.0, { + 'dtype': 'float32' +}); +logEachMap( 'squaredErrorGradient(%0.4f, %0.4f, %0.4f) = %0.4f', x, y, p, squaredErrorGradient ); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/include.gypi b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "machine learning", + "ml", + "loss", + "float32", + "squared error", + "squared error loss", + "squared error loss gradient", + "gradient", + "single-precision", + "single", + "float" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/addon.c b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/addon.c new file mode 100644 index 000000000000..5a34f954038d --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float32/squared_error_gradient.h" +#include "stdlib/math/base/napi/ternary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_FFF_F( stdlib_base_float32_squared_error_gradient ) diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/main.c b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/main.c new file mode 100644 index 000000000000..60af2ae4ae7c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/src/main.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float32/squared_error_gradient.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/constants/float32/nan.h" + +/** +* Computes the squared error loss gradient with respect to a model parameter for a single-precision floating-point number. +* +* @param x input value +* @param y true target value +* @param p predicted value +* @return squared error loss gradient +* +* @example +* float out = stdlib_base_float32_squared_error_gradient( 1.0f, 0.202f, 0.202f ); +* // returns 0.0f +*/ +float stdlib_base_float32_squared_error_gradient( const float x, const float y, const float p ) { + if ( stdlib_base_is_nanf( x ) || stdlib_base_is_nanf( y ) || stdlib_base_is_nanf( p ) ) { + return STDLIB_CONSTANT_FLOAT32_NAN; + } + return ( p-y ) * x; +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/REQUIRE b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/REQUIRE new file mode 100644 index 000000000000..7c8193c06e65 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/REQUIRE @@ -0,0 +1,2 @@ +julia 1.4.2 +JSON 0.21.0 diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/runner.jl new file mode 100644 index 000000000000..2dd7789d025c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/runner.jl @@ -0,0 +1,95 @@ +#!/usr/bin/env julia +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import JSON + +""" + gen( x, y, p, name ) + +Generate fixture data and write to file. + +# Arguments + +* `x`: input domain +* `y`: response domain +* `p`: prediction domain +* `name::AbstractString`: output filename + +# Examples + +``` julia +julia> x = Float32.( range( -1000.0, 1000.0, 2001 ) ); +julia> y = Float32.( range( -1000.0, 1000.0, 2001 ) ); +julia> p = Float32.( range( -1000.0, 1000.0, 2001 ) ); +julia> gen( x, y, p, "data.json" ); +``` +""" +function gen( x, y, p, name ) + x = Float32.( x ); + y = Float32.( y ); + p = Float32.( p ); + + v = -( y .- p ) .* x; + + # Store data to be written to file as a collection: + data = Dict([ + ("x", x), + ("y", y), + ("p", p), + ("expected", v) + ]); + + # Based on the script directory, create an output filepath: + filepath = joinpath( dir, name ); + + # Write the data to the output filepath as JSON: + outfile = open( filepath, "w" ); + write( outfile, JSON.json(data) ); + write( outfile, "\n" ); + close( outfile ); +end + +# Get the filename: +file = @__FILE__; + +# Extract the directory in which this file resides: +dir = dirname(file); + +# Positive tiny values: +x = Float32.( range( 0.0, stop=20e-20, length=503 ) ); +y = Float32.( range( 0.0, stop=10e-20, length=503 ) ); +p = Float32.( range( 10e-20, stop=0.0, length=503 ) ); +gen( x, y, p, "tiny_positive.json" ); + +# Small positive values: +x = Float32.( range( 0.0, stop=50.0, length=503 ) ); +y = Float32.( range( 0.0, stop=10.0, length=503 ) ); +p = Float32.( range( 10.0, stop=0.0, length=503 ) ); +gen( x, y, p, "small_positive.json" ); + +# Negative tiny values: +x = Float32.( range( 0.0, stop=-20e-20, length=503 ) ); +y = Float32.( range( -10e-20, stop=0.0, length=503 ) ); +p = Float32.( range( 0.0, stop=-10e-20, length=503 ) ); +gen( x, y, p, "tiny_negative.json" ); + +# Small negative values: +x = Float32.( range( 0.0, stop=-50.0, length=503 ) ); +y = Float32.( range( -10.0, stop=0.0, length=503 ) ); +p = Float32.( range( 0.0, stop=-10.0, length=503 ) ); +gen( x, y, p, "small_negative.json" ); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/small_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/small_negative.json new file mode 100644 index 000000000000..0cbc0c2693a0 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/small_negative.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/small_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/small_positive.json new file mode 100644 index 000000000000..030cfa20c28a --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/small_positive.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/tiny_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/tiny_negative.json new file mode 100644 index 000000000000..cc78057a0f36 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/tiny_negative.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/tiny_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/tiny_positive.json new file mode 100644 index 000000000000..68cd6961e470 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/fixtures/julia/tiny_positive.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/test.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/test.js new file mode 100644 index 000000000000..7a4da4e95eea --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/test.js @@ -0,0 +1,136 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isAlmostSameValue = require( '@stdlib/number/float32/base/assert/is-almost-same-value' ); +var squaredErrorGradient = require( './../lib' ); + + +// FIXTURES // + +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof squaredErrorGradient, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for tiny positive values', function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = tinyPositive.x; + y = tinyPositive.y; + p = tinyPositive.p; + expected = tinyPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for small positive values', function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = smallPositive.x; + y = smallPositive.y; + p = smallPositive.p; + expected = smallPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for tiny negative values', function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = tinyNegative.x; + y = tinyNegative.y; + p = tinyNegative.p; + expected = tinyNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for small negative values', function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = smallNegative.x; + y = smallNegative.y; + p = smallNegative.p; + expected = smallNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', function test( t ) { + var v; + + v = squaredErrorGradient( NaN, 2.0, 0.782 ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( 1.0, NaN, 0.782 ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( 1.0, 2.0, NaN ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( NaN, NaN, NaN ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/test.native.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/test.native.js new file mode 100644 index 000000000000..ae6d9c828117 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-error-gradient/test/test.native.js @@ -0,0 +1,145 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isAlmostSameValue = require( '@stdlib/number/float32/base/assert/is-almost-same-value' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); + + +// VARIABLES // + +var squaredErrorGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( squaredErrorGradient instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof squaredErrorGradient, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for tiny positive values', opts, function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = tinyPositive.x; + y = tinyPositive.y; + p = tinyPositive.p; + expected = tinyPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for small positive values', opts, function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = smallPositive.x; + y = smallPositive.y; + p = smallPositive.p; + expected = smallPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for tiny negative values', opts, function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = tinyNegative.x; + y = tinyNegative.y; + p = tinyNegative.p; + expected = tinyNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for small negative values', opts, function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = smallNegative.x; + y = smallNegative.y; + p = smallNegative.p; + expected = smallNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', opts, function test( t ) { + var v; + + v = squaredErrorGradient( NaN, 2.0, 0.782 ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( 1.0, NaN, 0.782 ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( 1.0, 2.0, NaN ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( NaN, NaN, NaN ); + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + t.end(); +});