diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/README.md b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/README.md
new file mode 100644
index 000000000000..5cccd346a289
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/README.md
@@ -0,0 +1,238 @@
+
+
+# squaredHingeGradient
+
+> Compute the [squared hinge loss gradient][squared-hinge-loss-gradient] with respect to a model parameter.
+
+
+
+The [squared hinge loss gradient][squared-hinge-loss-gradient] is defined as
+
+
+
+```math
+\frac{\partial \ell}{\partial w} = \begin{cases} -2y(t - yp)x & \text{if } yp \leq t \\ 0 & \text{otherwise} \end{cases}
+```
+
+
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var squaredHingeGradient = require( '@stdlib/ml/base/loss/float32/squared-hinge-gradient' );
+```
+
+#### squaredHingeGradient( x, t, y, p )
+
+Computes the [squared hinge loss gradient][squared-hinge-loss-gradient] with respect to a model parameter.
+
+```javascript
+var v = squaredHingeGradient( 3.0, 1.0, 1.0, 0.782 );
+// returns ~-1.308
+
+v = squaredHingeGradient( -1.3, 1.0, 1.0, -0.999 );
+// returns ~5.197
+```
+
+The function accepts the following arguments:
+
+- **x**: input value.
+- **t**: margin threshold.
+- **y**: true target value.
+- **p**: predicted value.
+
+If any argument is `NaN`, the function returns `NaN`.
+
+```javascript
+var v = squaredHingeGradient( NaN, 1.0, 1.0, 0.782 );
+// returns NaN
+
+v = squaredHingeGradient( 1.0, 1.0, NaN, 0.782 );
+// returns NaN
+
+v = squaredHingeGradient( NaN, NaN, 1.0, 0.782 );
+// returns NaN
+
+v = squaredHingeGradient( NaN, NaN, NaN, NaN );
+// returns NaN
+```
+
+If `y` is not +1 or -1, the function returns `NaN`.
+
+```javascript
+var v = squaredHingeGradient( 3.0, 1.0, -0.9, 1.0 );
+// returns NaN
+
+v = squaredHingeGradient( 2.4, 1.0, 0.453, 0.76 );
+// returns NaN
+```
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var uniform = require( '@stdlib/random/array/uniform' );
+var sample = require( '@stdlib/random/sample' );
+var logEachMap = require( '@stdlib/console/log-each-map' );
+var squaredHingeGradient = require( '@stdlib/ml/base/loss/float32/squared-hinge-gradient' );
+
+var y = sample( [ -1.0, 1.0 ], {
+ 'size': 100
+});
+var opts = {
+ 'dtype': 'float32'
+};
+var x = uniform( 100, -100.0, 100.0, opts );
+var t = uniform( 100, 0.0, 5.0, opts );
+var p = uniform( 100, -5.0, 5.0, opts );
+
+logEachMap( 'squaredHingeGradient(%0.4f, %0.4f, %0.4f, %0.4f) = %0.4f', x, t, y, p, squaredHingeGradient );
+```
+
+
+
+
+
+
+
+* * *
+
+
+
+## C APIs
+
+
+
+
+
+
+
+
+
+
+
+### Usage
+
+```c
+#include "stdlib/ml/base/loss/float32/squared_hinge_gradient.h"
+```
+
+#### stdlib_base_float32_squared_hinge_gradient( x, t, y, p )
+
+Computes the [squared hinge loss gradient][squared-hinge-loss-gradient] with respect to a model parameter.
+
+```c
+float out = stdlib_base_float32_squared_hinge_gradient( 3.0f, 1.0f, 1.0f, 0.782f );
+// returns ~-1.308f
+```
+
+The function accepts the following arguments:
+
+- **x**: `[in] float` input value.
+- **t**: `[in] float` margin threshold.
+- **y**: `[in] float` true target value.
+- **p**: `[in] float` predicted value.
+
+```c
+float stdlib_base_float32_squared_hinge_gradient( const float x, const float t, const float y, const float p );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+### Examples
+
+```c
+#include "stdlib/ml/base/loss/float32/squared_hinge_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 t[] = { 0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f };
+ 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_hinge_gradient( x[ i ], t[ i ], y[ i ], p[ i ] );
+ printf( "squaredHingeGradient(%f, %f, %f, %f) = %f\n", x[ i ], t[ i ], y[ i ], p[ i ], v );
+ }
+}
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[squared-hinge-loss-gradient]: https://en.wikipedia.org/wiki/Hinge_loss#Optimization
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/benchmark/benchmark.js
new file mode 100644
index 000000000000..5886232df7d0
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/benchmark/benchmark.js
@@ -0,0 +1,65 @@
+/**
+* @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 sample = require( '@stdlib/random/sample' );
+var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var pkg = require( './../package.json' ).name;
+var squaredHingeGradient = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+ var len;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ len = 100;
+ y = sample( [ -1.0, 1.0 ], {
+ 'size': len
+ });
+ x = uniform( len, -100.0, 100.0, {
+ 'dtype': 'float32'
+ });
+ p = uniform( len, -2.0, 2.0, {
+ 'dtype': 'float32'
+ });
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = squaredHingeGradient( x[ i%x.length ], 1.0, 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-hinge-gradient/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..08b5b2d0591e
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/benchmark/benchmark.native.js
@@ -0,0 +1,75 @@
+/**
+* @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 sample = require( '@stdlib/random/sample' );
+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 squaredHingeGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+ 'skip': ( squaredHingeGradient 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;
+ y = sample( [ -1.0, 1.0 ], {
+ 'size': len
+ });
+ x = uniform( len, -100.0, 100.0, {
+ 'dtype': 'float32'
+ });
+ p = uniform( len, -2.0, 2.0, {
+ 'dtype': 'float32'
+ });
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = squaredHingeGradient( x[ i%x.length ], 1.0, 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-hinge-gradient/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/benchmark/c/native/Makefile
new file mode 100644
index 000000000000..979768abbcec
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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-hinge-gradient/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/benchmark/c/native/benchmark.c
new file mode 100644
index 000000000000..4378453d5ceb
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/benchmark/c/native/benchmark.c
@@ -0,0 +1,161 @@
+/**
+* @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_hinge_gradient.h"
+#include
+#include
+#include
+#include
+#include
+
+#define NAME "squared_hinge_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) );
+}
+
+/**
+* Randomly samples either +1 or -1.
+*
+* @return randomly sampled value (+1 or -1)
+*/
+static float random_sample( void ) {
+ float v = (float)rand() / ( (float)RAND_MAX );
+ if ( v >= 0.5f ) {
+ return 1.0f;
+ }
+ return -1.0f;
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+ double elapsed;
+ float *x;
+ float *p;
+ float *y;
+ float v;
+ double t;
+ int i;
+
+ x = (float *) malloc( 100 * sizeof( float ) );
+ p = (float *) malloc( 100 * sizeof( float ) );
+ y = (float *) malloc( 100 * sizeof( float ) );
+ for ( i = 0; i < 100; i++ ) {
+ y[ i ] = random_sample();
+ x[ i ] = random_uniform( -100.0f, 100.0f );
+ p[ i ] = random_uniform( -2.0f, 2.0f );
+ }
+
+ t = tic();
+ for ( i = 0; i < ITERATIONS; i++ ) {
+ v = stdlib_base_float32_squared_hinge_gradient( x[ i%100 ], 1.0f, 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-hinge-gradient/binding.gyp b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/binding.gyp
new file mode 100644
index 000000000000..0d6508a12e99
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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-hinge-gradient/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/docs/repl.txt
new file mode 100644
index 000000000000..2e0416519fb0
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/docs/repl.txt
@@ -0,0 +1,46 @@
+
+{{alias}}( x, t, y, p )
+ Computes the squared hinge loss gradient with respect to a model parameter
+ for a single-precision floating-point number.
+
+ If any argument is `NaN`, the function returns `NaN`.
+
+ If `y` is not +1 or -1, the function returns `NaN`.
+
+ When `t = 1.0`, we get the loss used by SVM.
+
+ Parameters
+ ----------
+ x: number
+ Input value.
+
+ t: number
+ Margin threshold.
+
+ y: number
+ True target value.
+
+ p: number
+ Predicted value.
+
+ Returns
+ -------
+ v: number
+ Squared hinge loss gradient.
+
+ Examples
+ --------
+ > var v = {{alias}}( 3.0, 1.0, 1.0, 0.782 )
+ ~-1.308
+ > v = {{alias}}( 2.5, 1.0, 1.0, 0.202 )
+ ~-3.99
+ > v = {{alias}}( -1.3, 1.0, 1.0, -0.999 )
+ ~5.197
+ > v = {{alias}}( -2.0, 1.0, -1.0, 0.2 )
+ ~-4.8
+ > v = {{alias}}( NaN, 1.0, 1.0, 0.987 )
+ NaN
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/docs/types/index.d.ts
new file mode 100644
index 000000000000..62dbd96f7523
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/docs/types/index.d.ts
@@ -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.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Computes the squared hinge loss gradient with respect to a model parameter for a single-precision floating-point number.
+*
+* ## Notes
+*
+* - If `y` is not +1 or -1, the function returns `NaN`.
+* - When `t = 1.0`, we get the loss used by SVM.
+*
+* @param x - input value
+* @param t - margin threshold
+* @param y - true target value
+* @param p - predicted value
+* @returns squared hinge loss gradient
+*
+* @example
+* var v = squaredHingeGradient( 3.0, 1.0, 1.0, 0.782 );
+* // returns ~-1.308
+*
+* @example
+* var v = squaredHingeGradient( 2.5, 1.0, 1.0, 0.202 );
+* // returns ~-3.99
+*
+* @example
+* var v = squaredHingeGradient( -1.3, 1.0, 1.0, -0.999 );
+* // returns ~5.197
+*
+* @example
+* var v = squaredHingeGradient( -2.0, 1.0, -1.0, 0.234 );
+* // returns ~-4.936
+*
+* @example
+* var v = squaredHingeGradient( -2.0, 1.0, -1.0, 0.2 );
+* // returns ~-4.8
+*
+* @example
+* var v = squaredHingeGradient( -1.3, 1.0, 1.0, -0.9 );
+* // returns ~4.94
+*/
+declare function squaredHingeGradient( x: number, t: number, y: number, p: number ): number;
+
+
+// EXPORTS //
+
+export = squaredHingeGradient;
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/docs/types/test.ts
new file mode 100644
index 000000000000..7395e7372333
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/docs/types/test.ts
@@ -0,0 +1,84 @@
+/*
+* @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 squaredHingeGradient = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+ squaredHingeGradient( 0.5869, 1.0, 1.0, 0.782 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+ squaredHingeGradient( true, 1.0, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( false, 1.0, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( null, 1.0, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( undefined, 1.0, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( '5', 1.0, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( [], 1.0, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( {}, 1.0, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( ( x: number ): number => x, 1.0, 1.0, 0.782 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a number...
+{
+ squaredHingeGradient( 0.5869, true, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, false, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, null, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, undefined, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, '5', 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, [], 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, {}, 1.0, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, ( x: number ): number => x, 1.0, 0.782 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a number...
+{
+ squaredHingeGradient( 0.5869, 1.0, true, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, false, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, null, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, undefined, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, '5', 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, [], 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, {}, 0.782 ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, ( x: number ): number => x, 0.782 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourth argument which is not a number...
+{
+ squaredHingeGradient( 0.5869, 1.0, 1.0, true ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, 1.0, false ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, 1.0, null ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, 1.0, undefined ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, 1.0, '5' ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, 1.0, [] ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, 1.0, {} ); // $ExpectError
+ squaredHingeGradient( 0.5869, 1.0, 1.0, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ squaredHingeGradient(); // $ExpectError
+ squaredHingeGradient( 1.0 ); // $ExpectError
+ squaredHingeGradient( 1.0, 0.900 ); // $ExpectError
+ squaredHingeGradient( 1.0, 0.900, 0.7873 ); // $ExpectError
+ squaredHingeGradient( 1.0, 0.900, 1.0, 0.787, 0.7873 ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/examples/c/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/examples/c/Makefile
new file mode 100644
index 000000000000..c8f8e9a1517b
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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-hinge-gradient/examples/c/example.c b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/examples/c/example.c
new file mode 100644
index 000000000000..05a5a13cb896
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/examples/c/example.c
@@ -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.
+*/
+
+#include "stdlib/ml/base/loss/float32/squared_hinge_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 t[] = { 0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f };
+ 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_hinge_gradient( x[ i ], t[ i ], y[ i ], p[ i ] );
+ printf( "squaredHingeGradient(%f, %f, %f, %f) = %f\n", x[ i ], t[ i ], y[ i ], p[ i ], v );
+ }
+}
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/examples/index.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/examples/index.js
new file mode 100644
index 000000000000..dcf8ac16170b
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/examples/index.js
@@ -0,0 +1,36 @@
+/**
+* @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 sample = require( '@stdlib/random/sample' );
+var logEachMap = require( '@stdlib/console/log-each-map' );
+var squaredHingeGradient = require( './../lib' );
+
+var y = sample( [ -1.0, 1.0 ], {
+ 'size': 100
+});
+var opts = {
+ 'dtype': 'float32'
+};
+var x = uniform( 100, -100.0, 100.0, opts );
+var t = uniform( 100, 0.0, 5.0, opts );
+var p = uniform( 100, -5.0, 5.0, opts );
+
+logEachMap( 'squaredHingeGradient(%0.4f, %0.4f, %0.4f, %0.4f) = %0.4f', x, t, y, p, squaredHingeGradient );
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/include.gypi b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/include.gypi
new file mode 100644
index 000000000000..bee8d41a2caf
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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': [
+ ' 0.0 ) {
+ return f32( f32( -2.0 * x * y ) * z );
+ }
+ return 0.0;
+}
+
+
+// EXPORTS //
+
+module.exports = squaredHingeGradient;
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/lib/native.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/lib/native.js
new file mode 100644
index 000000000000..beb843f684e7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/lib/native.js
@@ -0,0 +1,69 @@
+/**
+* @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 addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Computes the squared hinge loss gradient with respect to a model parameter.
+*
+* @private
+* @param {number} x - input value
+* @param {number} t - margin threshold
+* @param {number} y - true target value
+* @param {number} p - predicted value
+* @returns {number} squared hinge loss gradient
+*
+* @example
+* var v = squaredHingeGradient( 3.0, 1.0, 1.0, 0.782 );
+* // returns ~-1.308
+*
+* @example
+* var v = squaredHingeGradient( 2.5, 1.0, 1.0, 0.202 );
+* // returns ~-3.99
+*
+* @example
+* var v = squaredHingeGradient( -1.3, 1.0, 1.0, -0.999 );
+* // returns ~5.197
+*
+* @example
+* var v = squaredHingeGradient( -2.0, 1.0, -1.0, 0.234 );
+* // returns ~-4.936
+*
+* @example
+* var v = squaredHingeGradient( -2.0, 1.0, -1.0, 0.2 );
+* // returns ~-4.8
+*
+* @example
+* var v = squaredHingeGradient( -1.3, 1.0, 1.0, -0.9 );
+* // returns ~4.94
+*/
+function squaredHingeGradient( x, t, y, p ) {
+ return addon( x, t, y, p );
+}
+
+
+// EXPORTS //
+
+module.exports = squaredHingeGradient;
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/manifest.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/manifest.json
new file mode 100644
index 000000000000..84305927be56
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/manifest.json
@@ -0,0 +1,75 @@
+{
+ "options": {
+ "task": "build"
+ },
+ "fields": [
+ {
+ "field": "src",
+ "resolve": true,
+ "relative": true
+ },
+ {
+ "field": "include",
+ "resolve": true,
+ "relative": true
+ },
+ {
+ "field": "libraries",
+ "resolve": false,
+ "relative": false
+ },
+ {
+ "field": "libpath",
+ "resolve": true,
+ "relative": false
+ }
+ ],
+ "confs": [
+ {
+ "task": "build",
+ "src": [
+ "./src/main.c"
+ ],
+ "include": [
+ "./include"
+ ],
+ "libraries": [],
+ "libpath": [],
+ "dependencies": [
+ "@stdlib/math/base/napi/quaternary",
+ "@stdlib/math/base/assert/is-nanf",
+ "@stdlib/constants/float32/nan"
+ ]
+ },
+ {
+ "task": "benchmark",
+ "src": [
+ "./src/main.c"
+ ],
+ "include": [
+ "./include"
+ ],
+ "libraries": [],
+ "libpath": [],
+ "dependencies": [
+ "@stdlib/math/base/assert/is-nanf",
+ "@stdlib/constants/float32/nan"
+ ]
+ },
+ {
+ "task": "examples",
+ "src": [
+ "./src/main.c"
+ ],
+ "include": [
+ "./include"
+ ],
+ "libraries": [],
+ "libpath": [],
+ "dependencies": [
+ "@stdlib/math/base/assert/is-nanf",
+ "@stdlib/constants/float32/nan"
+ ]
+ }
+ ]
+}
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/package.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/package.json
new file mode 100644
index 000000000000..5aab6961fcee
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/package.json
@@ -0,0 +1,69 @@
+{
+ "name": "@stdlib/ml/base/loss/float32/squared-hinge-gradient",
+ "version": "0.0.0",
+ "description": "Compute the squared hinge loss gradient with respect to a model parameter.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "gypfile": true,
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "include": "./include",
+ "lib": "./lib",
+ "src": "./src",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "machine learning",
+ "ml",
+ "loss",
+ "float32",
+ "hinge",
+ "squared hinge loss",
+ "squared hinge loss gradient",
+ "gradient",
+ "single-precision",
+ "single",
+ "float"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/src/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/src/Makefile
new file mode 100644
index 000000000000..2caf905cedbe
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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-hinge-gradient/src/addon.c b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/src/addon.c
new file mode 100644
index 000000000000..1ab044df6484
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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_hinge_gradient.h"
+#include "stdlib/math/base/napi/quaternary.h"
+
+STDLIB_MATH_BASE_NAPI_MODULE_FFFF_F( stdlib_base_float32_squared_hinge_gradient )
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/src/main.c b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/src/main.c
new file mode 100644
index 000000000000..a081f5be2aae
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/src/main.c
@@ -0,0 +1,49 @@
+/**
+* @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_hinge_gradient.h"
+#include "stdlib/math/base/assert/is_nanf.h"
+#include "stdlib/constants/float32/nan.h"
+
+/**
+* Computes the squared hinge loss gradient with respect to a model parameter.
+*
+* @param x input value
+* @param t margin threshold
+* @param y true target value
+* @param p predicted value
+* @return squared hinge loss gradient
+*
+* @example
+* float out = stdlib_base_float32_squared_hinge_gradient( 2.5f, 1.0f, 1.0f, 0.202f );
+* // returns ~-3.99f
+*/
+float stdlib_base_float32_squared_hinge_gradient( const float x, const float t, const float y, const float p ) {
+ float z;
+ if (
+ stdlib_base_is_nanf( x ) || stdlib_base_is_nanf( t ) || stdlib_base_is_nanf( y ) || stdlib_base_is_nanf( p ) ||
+ ( y != -1.0f && y != 1.0f )
+ ) {
+ return STDLIB_CONSTANT_FLOAT32_NAN;
+ }
+ z = t - ( y*p );
+ if ( z > 0.0f ) {
+ return -2.0f * x * y * z;
+ }
+ return 0.0f;
+}
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/REQUIRE b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/REQUIRE
new file mode 100644
index 000000000000..7c8193c06e65
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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-hinge-gradient/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/runner.jl
new file mode 100644
index 000000000000..efcd33efc1e8
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/runner.jl
@@ -0,0 +1,102 @@
+#!/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, t, y, p, name )
+
+Generate fixture data and write to file.
+
+# Arguments
+
+* `x`: input domain
+* `t`: margin threshold
+* `y`: response domain
+* `p`: prediction domain
+* `name::AbstractString`: output filename
+
+# Examples
+
+``` julia
+julia> x = Float32.( range( -1000.0, 1000.0, 2001 ) );
+julia> t = Float32.( range( 0.0, stop=5.0, length=2001 ) );
+julia> y = Float32.( rand( [ -1.0, 1.0 ], 2001 ) );
+julia> p = Float32.( range( -1000.0, 1000.0, 2001 ) );
+julia> gen( x, t, y, p, "data.json" );
+```
+"""
+function gen( x, t, y, p, name )
+ x = Float32.( x );
+ t = Float32.( t );
+ y = Float32.( y );
+ p = Float32.( p );
+
+ z = t .- p .* y;
+ v = ifelse.( z .> 0.0f0, -2.0f0 .* x .* y .* z, 0.0f0 );
+
+ # Store data to be written to file as a collection:
+ data = Dict([
+ ("x", x),
+ ("t", t),
+ ("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);
+
+t = Float32.( range( 0.0, stop=5.0, length=503 ) );
+
+# Positive tiny values:
+y = Float32.( rand( [ -1.0, 1.0 ], 503 ) );
+x = Float32.( range( 0.0, stop=20e-20, length=503 ) );
+p = Float32.( range( 0.0, stop=1e-20, length=503 ) );
+gen( x, t, y, p, "tiny_positive.json" );
+
+# Small positive values:
+y = Float32.( rand( [ -1.0, 1.0 ], 503 ) );
+x = Float32.( range( 0.0, stop=50, length=503 ) );
+p = Float32.( range( 0.0, stop=2.0, length=503 ) );
+gen( x, t, y, p, "small_positive.json" );
+
+# Negative tiny values:
+y = Float32.( rand( [ -1.0, 1.0 ], 503 ) );
+x = Float32.( range( 0.0, stop=-20e-20, length=503 ) );
+p = Float32.( range( -1e-20, stop=0.0, length=503 ) );
+gen( x, t, y, p, "tiny_negative.json" );
+
+# Small negative values:
+y = Float32.( rand( [ -1.0, 1.0 ], 503 ) );
+x = Float32.( range( 0.0, stop=-50, length=503 ) );
+p = Float32.( range( -2.0, stop=0.0, length=503 ) );
+gen( x, t, y, p, "small_negative.json" );
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/small_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/small_negative.json
new file mode 100644
index 000000000000..59b4675b86f0
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/small_negative.json
@@ -0,0 +1 @@
+{"expected":[-0.0,0,0.8015745878219604,1.2059333324432373,1.6126728057861328,0,0,2.847177028656006,3.2634401321411133,3.682084321975708,0,0,4.9523024559021,5.380469799041748,5.811018943786621,6.243948936462402,0,7.116950035095215,0,7.999476432800293,8.444310188293457,0,9.3411226272583,0,10.247457504272461,0,11.163314819335938,11.624815940856934,12.08869743347168,12.554959297180176,13.023603439331055,0,13.968032836914062,14.443817138671875,0,15.402534484863281,15.885461807250977,0,0,17.348533630371094,17.840986251831055,18.335819244384766,0,0,0,20.33896255493164,0,21.354820251464844,21.86631965637207,22.380197525024414,22.896461486816406,23.41510581970215,23.936126708984375,24.459529876708984,24.98531723022461,25.51348304748535,0,26.57695960998535,0,27.64995765686035,0,28.732481002807617,0,29.824525833129883,30.374122619628906,0,0,32.037193298339844,0,33.157806396484375,0,34.28794860839844,0,35.4276123046875,0,0,37.15496826171875,37.735511779785156,38.31843948364258,38.903751373291016,0,0,40.67395782470703,41.26879119873047,0,0,43.06756591796875,43.67192459106445,44.278663635253906,44.887779235839844,45.49928283691406,46.113155364990234,0,47.34805679321289,47.96908187866211,0,0,49.846431732177734,50.47697448730469,0,51.745208740234375,52.38290023803711,0,53.66542053222656,54.310245513916016,0,55.6070556640625,0,56.91337966918945,0,58.22923278808594,0,0,0,0,0,0,0,0,64.26842498779297,0,0,0,67.01441192626953,0,68.40168762207031,69.09890747070312,69.79849243164062,0,0,71.91155242919922,0,73.33216857910156,74.04605102539062,74.76231384277344,75.48094177246094,0,0,0,78.37931060791016,79.10985565185547,79.84278106689453,0,0,-0.22856952250003815,82.79828643798828,83.54312133789062,-1.4583089351654053,85.0399169921875,-2.3059170246124268,-2.738050937652588,87.302978515625,88.06210327148438,-4.0677924156188965,-4.5221476554870605,-4.982062339782715,-5.447532653808594,-5.918558597564697,-6.395135879516602,93.44256591796875,94.22073364257812,-7.858208179473877,-8.357007026672363,-8.861366271972656,97.35718536376953,98.14725494384766,98.93970489501953,-10.934351921081543,100.53173828125,101.33133697509766,102.13330078125,-13.096219062805176,103.74437713623047,-14.210490226745605,105.36499786376953,106.17887878417969,106.99512481689453,107.81375885009766,-17.0933780670166,-17.686622619628906,110.28396606445312,-18.889781951904297,-19.49968910217285,-20.115158081054688,-20.736181259155273,-21.362754821777344,115.28864288330078,-22.63257598876953,116.97592163085938,-23.924623489379883,-24.578975677490234,119.52468872070312,120.37904357910156,-26.57537269592285,-27.2519474029541,-27.934078216552734,-28.621767044067383,-29.315011978149414,125.5551528930664,-30.718164443969727,127.299560546875,-32.14353942871094,129.0535125732422,129.93405151367188,-34.323265075683594,-35.06095504760742,-35.804195404052734,133.48004150390625,134.37246704101562,-38.067256927490234,136.1645050048828,-39.60374069213867,-40.380306243896484,-41.16244125366211,139.7771453857422,140.68626403808594,-43.54216384887695,-44.346519470214844,-45.15642547607422,-45.97188949584961,-46.79290771484375,146.19093322753906,-48.45161056518555,-49.28929901123047,-50.13254165649414,149.90834045410156,-51.835689544677734,151.7813262939453,152.7213897705078,153.66383361816406,-55.30864334106445,155.5558624267578,-57.078460693359375,-57.97169876098633,158.41177368164062,-59.77484130859375,160.32760620117188,161.2891082763672,162.2529754638672,163.21923828125,164.1878662109375,-65.31761932373047,-66.26085662841797,-67.20965576171875,168.08621215820312,-69.1239013671875,170.04966735839844,171.0349884033203,-72.03694915771484,173.01271057128906,174.0051727294922,-75,-75.99878692626953,-77.0031509399414,-78.01304626464844,179.00311279296875,180.0098419189453,-81.07609558105469,182.03045654296875,-83.1458969116211,184.06056213378906,185.07919311523438,-86.29227447509766,187.1236114501953,188.14938354492188,-89.48865509033203,-90.56523132324219,-91.64735412597656,192.2763214111328,-93.82827758789062,-94.92706298828125,195.39649963378906,196.4413299560547,-98.25677490234375,198.53811645507812,-100.50434875488281,-101.636474609375,201.70115661621094,-103.91739654541016,-105.0661849975586,-106.22053527832031,-107.38043975830078,-108.5458984375,208.09153747558594,209.16493225097656,-112.07560729980469,211.31886291503906,-114.45652770996094,-115.65531158447266,214.56764221191406,215.6553192138672,-119.28500366210938,217.8378143310547,-121.73259735107422,220.02984619140625,221.12940979003906,-125.44562530517578,-126.69441223144531,224.44247436523438,-129.2086639404297,-130.47412109375,227.7769317626953,-133.02169799804688,-134.30381774902344,-135.5915069580078,232.25624084472656,233.38201904296875,234.51016235351562,-140.79774475097656,236.7736053466797,237.90892028808594,239.04660034179688,240.18666076660156,-147.4305877685547,242.4739227294922,-150.12261962890625,-151.47695922851562,-152.8368682861328,-154.2023162841797,-155.57333374023438,-156.9499053955078,-158.33201599121094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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/small_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/small_positive.json
new file mode 100644
index 000000000000..797d03476794
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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-hinge-gradient/test/fixtures/julia/tiny_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/tiny_negative.json
new file mode 100644
index 000000000000..196df4582a06
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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-hinge-gradient/test/fixtures/julia/tiny_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/fixtures/julia/tiny_positive.json
new file mode 100644
index 000000000000..fee848c235f8
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-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-hinge-gradient/test/test.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/test.js
new file mode 100644
index 000000000000..7599c048c72e
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/test.js
@@ -0,0 +1,158 @@
+/**
+* @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 squaredHingeGradient = 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 squaredHingeGradient, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function computes the squared hinge loss gradient for tiny positive values', function test( t ) {
+ var expected;
+ var th;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ x = tinyPositive.x;
+ th = tinyPositive.t;
+ y = tinyPositive.y;
+ p = tinyPositive.p;
+ expected = tinyPositive.expected;
+ for ( i = 0; i < y.length; i++ ) {
+ v = squaredHingeGradient( x[ i ], th[ i ], y[ i ], p[ i ] );
+ t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the function computes the squared hinge loss gradient for small positive values', function test( t ) {
+ var expected;
+ var th;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ x = smallPositive.x;
+ th = smallPositive.t;
+ y = smallPositive.y;
+ p = smallPositive.p;
+ expected = smallPositive.expected;
+ for ( i = 0; i < y.length; i++ ) {
+ v = squaredHingeGradient( x[ i ], th[ i ], y[ i ], p[ i ] );
+ t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the function computes the squared hinge loss gradient for tiny negative values', function test( t ) {
+ var expected;
+ var th;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ x = tinyNegative.x;
+ th = tinyNegative.t;
+ y = tinyNegative.y;
+ p = tinyNegative.p;
+ expected = tinyNegative.expected;
+ for ( i = 0; i < y.length; i++ ) {
+ v = squaredHingeGradient( x[ i ], th[ i ], y[ i ], p[ i ] );
+ t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the function computes the squared hinge loss gradient for small negative values', function test( t ) {
+ var expected;
+ var th;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ x = smallNegative.x;
+ th = smallNegative.t;
+ y = smallNegative.y;
+ p = smallNegative.p;
+ expected = smallNegative.expected;
+ for ( i = 0; i < y.length; i++ ) {
+ v = squaredHingeGradient( x[ i ], th[ i ], y[ i ], p[ i ] );
+ t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the function returns `NaN` if provided `NaN`', function test( t ) {
+ var v;
+
+ v = squaredHingeGradient( NaN, 1.0, 1.0, 0.782 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( 1.0, NaN, 1.0, 0.782 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( NaN, NaN, 1.0, 0.782 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( NaN, NaN, NaN, 0.782 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( NaN, NaN, NaN, NaN );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function returns `NaN` if y is not +1 or -1', function test( t ) {
+ var v;
+
+ v = squaredHingeGradient( 3.0, 1.0, -0.9, 1.0 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( 2.4, 1.0, 0.453, 0.76 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/test.native.js b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/test.native.js
new file mode 100644
index 000000000000..a7d02499541a
--- /dev/null
+++ b/lib/node_modules/@stdlib/ml/base/loss/float32/squared-hinge-gradient/test/test.native.js
@@ -0,0 +1,167 @@
+/**
+* @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 squaredHingeGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+ 'skip': ( squaredHingeGradient instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof squaredHingeGradient, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function computes the squared hinge loss gradient for tiny positive values', opts, function test( t ) {
+ var expected;
+ var th;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ x = tinyPositive.x;
+ th = tinyPositive.t;
+ y = tinyPositive.y;
+ p = tinyPositive.p;
+ expected = tinyPositive.expected;
+ for ( i = 0; i < y.length; i++ ) {
+ v = squaredHingeGradient( x[ i ], th[ i ], y[ i ], p[ i ] );
+ t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the function computes the squared hinge loss gradient for small positive values', opts, function test( t ) {
+ var expected;
+ var th;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ x = smallPositive.x;
+ th = smallPositive.t;
+ y = smallPositive.y;
+ p = smallPositive.p;
+ expected = smallPositive.expected;
+ for ( i = 0; i < y.length; i++ ) {
+ v = squaredHingeGradient( x[ i ], th[ i ], y[ i ], p[ i ] );
+ t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the function computes the squared hinge loss gradient for tiny negative values', opts, function test( t ) {
+ var expected;
+ var th;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ x = tinyNegative.x;
+ th = tinyNegative.t;
+ y = tinyNegative.y;
+ p = tinyNegative.p;
+ expected = tinyNegative.expected;
+ for ( i = 0; i < y.length; i++ ) {
+ v = squaredHingeGradient( x[ i ], th[ i ], y[ i ], p[ i ] );
+ t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the function computes the squared hinge loss gradient for small negative values', opts, function test( t ) {
+ var expected;
+ var th;
+ var x;
+ var y;
+ var p;
+ var v;
+ var i;
+
+ x = smallNegative.x;
+ th = smallNegative.t;
+ y = smallNegative.y;
+ p = smallNegative.p;
+ expected = smallNegative.expected;
+ for ( i = 0; i < y.length; i++ ) {
+ v = squaredHingeGradient( x[ i ], th[ i ], y[ i ], p[ i ] );
+ t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' );
+ }
+ t.end();
+});
+
+tape( 'the function returns `NaN` if provided `NaN`', opts, function test( t ) {
+ var v;
+
+ v = squaredHingeGradient( NaN, 1.0, 1.0, 0.782 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( 1.0, NaN, 1.0, 0.782 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( NaN, NaN, 1.0, 0.782 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( NaN, NaN, NaN, 0.782 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( NaN, NaN, NaN, NaN );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function returns `NaN` if y is not +1 or -1', opts, function test( t ) {
+ var v;
+
+ v = squaredHingeGradient( 3.0, 1.0, -0.9, 1.0 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+
+ v = squaredHingeGradient( 2.4, 1.0, 0.453, 0.76 );
+ t.strictEqual( isnanf( v ), true, 'returns expected value' );
+ t.end();
+});