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feat: add support for stack for sasum
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‎lib/node_modules/@stdlib/blas/sasum/README.md‎

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<!--
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@license Apache-2.0
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Copyright (c) 2024 The Stdlib Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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# sasum
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> Compute the sum of [absolute values][@stdlib/math/base/special/abs] ([_L1_ norm][l1norm]).
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<section class="intro">
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The [_L1_ norm][l1norm] is defined as
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<!-- <equation class="equation" label="eq:l1norm" align="center" raw="\|\mathbf{x}\|_1 = \sum_{i=0}^{n-1} \vert x_i \vert" alt="L1 norm definition."> -->
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```math
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\|\mathbf{x}\|_1 = \sum_{i=0}^{n-1} \vert x_i \vert
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```
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<!-- <div class="equation" align="center" data-raw-text="\|\mathbf{x}\|_1 = \sum_{i=0}^{n-1} \vert x_i \vert" data-equation="eq:l1norm">
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<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@c403cb0cbb15d9b7b453e3cea34ca2379500ddd4/lib/node_modules/@stdlib/blas/base/sasum/docs/img/equation_l1norm.svg" alt="L1 norm definition.">
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<br>
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</div> -->
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<!-- </equation> -->
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</section>
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<!-- /.intro -->
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<section class="usage">
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## Usage
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```javascript
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var sasum = require( '@stdlib/blas/sasum' );
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```
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#### sasum( x\[, dim] )
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Computes the sum of [absolute values][@stdlib/math/base/special/abs].
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```javascript
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var Float32Array = require( '@stdlib/array/float32' );
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var array = require( '@stdlib/ndarray/array' );
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var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );
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var z = sasum( x );
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// returns <ndarray>
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var v = z.get();
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// returns 15.0
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```
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The function has the following parameters:
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- **x**: a non-zero-dimensional [`ndarray`][@stdlib/ndarray/ctor] whose underlying data type is `float32`.
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- **dim**: dimension for which to compute the sum. Must be a negative integer. Negative indices are resolved relative to the last array dimension, with the last dimension corresponding to `-1`. Default: `-1`.
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For multi-dimensional input [`ndarrays`][@stdlib/ndarray/ctor], the function performs batched computation, such that the function computes the sum for each pair of vectors in `x` according to the specified dimension index.
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```javascript
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var Float32Array = require( '@stdlib/array/float32' );
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var array = require( '@stdlib/ndarray/array' );
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var opts = {
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'shape': [ 2, 3 ]
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};
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var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 3.0 ] ), opts );
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var z = sasum( x );
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// returns <ndarray>
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var v1 = z.get( 0 );
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// returns 9.0
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var v2 = z.get( 1 );
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// returns 9.0
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```
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</section>
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<!-- /.usage -->
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<section class="notes">
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## Notes
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- Negative indices are resolved relative to the last [`ndarray`][@stdlib/ndarray/ctor] dimension, with the last dimension corresponding to `-1`.
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- The output [`ndarray`][@stdlib/ndarray/ctor] has the same data type as the input [`ndarray`][@stdlib/ndarray/ctor] and has a shape which is determined by broadcasting and excludes the contracted dimension.
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- If provided an empty vector, the sum is `0`.
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- `sasum()` provides a higher-level interface to the [BLAS][blas] level 1 function [`sasum`][@stdlib/blas/base/sasum].
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</section>
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<!-- /.notes -->
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<section class="examples">
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## Examples
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<!-- eslint no-undef: "error" -->
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```javascript
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var array = require( '@stdlib/ndarray/array' );
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var sasum = require( '@stdlib/blas/sasum' );
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var opts = {
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'dtype': 'float32'
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};
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var x = array( discreteUniform( 10, 0, 100, opts ), {
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'shape': [ 5, 2 ]
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});
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console.log( ndarray2array( x ) );
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var z = sasum( x, -1 );
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console.log( ndarray2array( z ) );
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```
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</section>
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<!-- /.examples -->
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<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
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<section class="related">
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</section>
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<!-- /.related -->
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<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="links">
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[l1norm]: https://en.wikipedia.org/wiki/Norm_%28mathematics%29
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[@stdlib/math/base/special/abs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/abs
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[blas]: http://www.netlib.org/blas
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[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
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[@stdlib/blas/base/sasum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/sasum
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/blas/sasum/benchmark/benchmark.js‎

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2024 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var bench = require( '@stdlib/bench' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var array = require( '@stdlib/ndarray/array' );
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var pkg = require( './../package.json' ).name;
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var sasum = require( './../lib/main.js' );
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// VARIABLES //
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var opts = {
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'dtype': 'float32'
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};
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// FUNCTIONS //
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/**
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* Creates a benchmark function.
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*
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* @private
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* @param {PositiveInteger} len - array length
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var x = array( uniform( len, -100.0, 100.0, opts ) );
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return benchmark;
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/**
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* Benchmark function.
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*
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* @private
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* @param {Benchmark} b - benchmark instance
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*/
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function benchmark( b ) {
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var d;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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d = sasum( x );
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if ( isnan( d.get() ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( d.get() ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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}
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}
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// MAIN //
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/**
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* Main execution sequence.
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*
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* @private
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*/
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function main() {
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var len;
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var min;
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var max;
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var f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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len = pow( 10, i );
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f = createBenchmark( len );
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bench( pkg+'::vectors:len='+len, f );
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}
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}
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main();

‎lib/node_modules/@stdlib/blas/sasum/benchmark/benchmark.stack.js‎

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2024 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var bench = require( '@stdlib/bench' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var numel = require( '@stdlib/ndarray/base/numel' );
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var array = require( '@stdlib/ndarray/array' );
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var pkg = require( './../package.json' ).name;
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var sasum = require( './../lib/main.js' );
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// VARIABLES //
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var OPTS = {
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'dtype': 'float32'
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};
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// FUNCTIONS //
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/**
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* Creates a benchmark function.
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*
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* @private
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* @param {PositiveIntegerArray} shape - array shape
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* @returns {Function} benchmark function
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*/
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function createBenchmark( shape ) {
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var x;
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var N;
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var o;
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N = numel( shape );
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o = {
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'shape': shape
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};
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x = array( uniform( N, -100.0, 100.0, OPTS ), o );
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return benchmark;
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/**
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* Benchmark function.
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*
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* @private
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* @param {Benchmark} b - benchmark instance
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*/
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function benchmark( b ) {
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var d;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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d = sasum( x );
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if ( isnan( d.iget( 0 ) ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( d.iget( 0 ) ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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}
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}
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// MAIN //
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/**
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* Main execution sequence.
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*
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* @private
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*/
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function main() {
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var shape;
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var min;
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var max;
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var N;
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var f;
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var i;
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min = 1; // 10^min
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max = 6; // 10^max
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for ( i = min; i <= max; i++ ) {
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N = pow( 10, i );
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shape = [ 2, N/2 ];
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f = createBenchmark( shape );
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bench( pkg+'::stacks:size='+N+',ndims='+shape.length+',shape=('+shape.join( ',' )+')', f );
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shape = [ N/2, 2 ];
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f = createBenchmark( shape );
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bench( pkg+'::stacks:size='+N+',ndims='+shape.length+',shape=('+shape.join( ',' )+')', f );
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}
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}
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main();

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