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* @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.
*/
/* eslint-disable max-len */
'use strict';
// MODULES //
var isNonNegativeIntegerArray = require( '@stdlib/assert/is-nonnegative-integer-array' ).primitives;
var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive;
var isIterableLike = require( '@stdlib/assert/is-iterable-like' );
var isCollection = require( '@stdlib/assert/is-collection' );
var isArrayBuffer = require( '@stdlib/assert/is-arraybuffer' );
var isPlainObject = require( '@stdlib/assert/is-plain-object' );
var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
var isComplexDataType = require( '@stdlib/ndarray/base/assert/is-complex-floating-point-data-type' );
var isGenericDataType = require( '@stdlib/ndarray/base/assert/is-generic-data-type' );
var isBinaryDataType = require( '@stdlib/ndarray/base/assert/is-binary-data-type' );
var isDataType = require( '@stdlib/ndarray/base/assert/is-data-type' );
var hasOwnProp = require( '@stdlib/assert/has-own-property' );
var flatten3d = require( '@stdlib/array/base/flatten3d' );
var slice = require( '@stdlib/array/base/slice' );
var arrayShape = require( '@stdlib/array/shape' );
var typedarray = require( '@stdlib/array/typed' );
var iterator2array = require( '@stdlib/array/from-iterator' );
var buffer = require( '@stdlib/ndarray/base/buffer' );
var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' );
var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
var numel = require( '@stdlib/ndarray/base/numel' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var defaults = require( '@stdlib/ndarray/defaults' );
var array2buffer = require( '@stdlib/buffer/from-array' );
var ITERATOR_SYMBOL = require( '@stdlib/symbol/iterator' );
var format = require( '@stdlib/string/format' );
var arraybuffer2tensor3d = require( './from_arraybuffer.js' );
// VARIABLES //
var DEFAULT_DTYPE = defaults.get( 'dtypes.default' );
var DEFAULT_ORDER = defaults.get( 'order' );
// FUNCTIONS //
/**
* Resolves the order of the output ndarray.
*
* @private
* @param {*} options - options argument
* @returns {string} order
*/
function resolveOrder( options ) {
if ( hasOwnProp( options, 'order' ) ) {
return options.order;
}
return DEFAULT_ORDER;
}
/**
* Returns a three-dimensional ndarray having a specified data type.
*
* @private
* @param {(NonNegativeIntegerArray|Collection|ArrayBuffer|Iterable|Options)} arg - shape, array-like object, ArrayBuffer, iterable, or options object
* @param {*} dtype - data type
* @param {(Options|null)} options - function options
* @param {boolean} [options.readonly=false] - boolean indicating whether to return a read-only ndarray
* @param {string} [options.mode='throw'] - specifies how to handle indices which exceed ndarray dimensions
* @param {StringArray} [options.submode=[options.mode]] - specifies how to handle subscripts which exceed array dimensions on a per dimension basis
* @returns {(ndarray|null)} three-dimensional ndarray
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
*
* var v = tensor3dWithDType( [ 2, 2, 5 ], 'float64', {} );
* // returns <ndarray>
*
* var sh = getShape( v );
* // returns [ 2, 2, 5 ]
*
* var dt = String( getDType( v ) );
* // returns 'float64'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
*
* var v = tensor3dWithDType( [ [ [ 1, 2 ], [ 3, 4 ] ] ], 'generic', {} );
* // returns <ndarray>
*
* var sh = getShape( v );
* // returns [ 1, 2, 2 ]
*
* var dt = String( getDType( v ) );
* // returns 'generic'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
* var ArrayBuffer = require( '@stdlib/array/buffer' );
*
* var buf = new ArrayBuffer( 32 );
* var v = tensor3dWithDType( buf, 'float64', {} );
* // returns <ndarray>
*
* var sh = getShape( v );
* // returns [ 1, 1, 4 ]
*
* var dt = String( getDType( v ) );
* // returns 'float64'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
*
* var v = tensor3dWithDType( {}, 'float64', null );
* // returns <ndarray>
*
* var sh = getShape( v );
* // returns [ 0, 0, 0 ]
*
* var dt = String( getDType( v ) );
* // returns 'float64'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
* var array2iterator = require( '@stdlib/array/to-iterator' );
*
* var v = tensor3dWithDType( array2iterator( [ [ [ 1, 2 ], [ 3, 4 ] ] ] ), 'generic', {} );
* // returns <ndarray>
*
* var sh = getShape( v );
* // returns [ 1, 2, 2 ]
*
* var dt = String( getDType( v ) );
* // returns 'generic'
*/
function tensor3dWithDType( arg, dtype, options ) {
var opts;
var buf;
var ord;
var sh;
// Note: in all of the following, we delegate option validation to the ndarray constructor...
if ( options === null ) {
opts = {};
} else {
opts = options;
}
// Case: tensor3d( shape )
if ( isNonNegativeIntegerArray( arg ) && arg.length === 3 ) {
buf = buffer( dtype, numel( arg ) );
ord = resolveOrder( opts );
return new ndarray( dtype, buf, arg, shape2strides( arg, ord ), 0, ord, opts );
}
// Case: tensor3d( collection )
if ( isCollection( arg ) ) {
sh = arrayShape( arg );
if ( sh.length < 3 ) {
return null;
}
sh = slice( sh, 0, 3 );
buf = flatten3d( arg, sh, false );
if ( isBinaryDataType( dtype ) ) {
buf = array2buffer( buf ); // note: we assume that `buf` is an array of octets
} else if ( isComplexDataType( dtype ) ) {
// Sniff the first value in order to determine if we've been provided a nested array containing interleaved real and imaginary components...
if ( isNumber( buf[ 0 ] ) ) {
// As each real and imaginary component pair corresponds to a single complex number, we need to update the ndarray shape:
sh[ sh.length-1 ] /= 2;
}
buf = typedarray( buf, dtype );
} else if ( !isGenericDataType( dtype ) ) {
buf = typedarray( buf, dtype );
}
ord = resolveOrder( opts );
return new ndarray( dtype, buf, sh, shape2strides( sh, ord ), 0, ord, opts );
}
// Case: tensor3d( ArrayBuffer )
if ( isArrayBuffer( arg ) ) {
sh = [ 1, 1, arg.byteLength/bytesPerElement( dtype ) ];
ord = resolveOrder( opts );
return arraybuffer2tensor3d( dtype, arg, sh, shape2strides( sh, ord ), 0, ord, opts );
}
// Case: tensor3d( Iterable )
if ( isIterableLike( arg ) ) {
buf = arg[ ITERATOR_SYMBOL ]();
buf = iterator2array( buf );
sh = arrayShape( buf );
if ( sh.length < 3 ) {
return null;
}
sh = slice( sh, 0, 3 );
buf = flatten3d( buf, sh, false );
if ( isBinaryDataType( dtype ) ) {
buf = array2buffer( buf ); // note: we assume that `buf` is an array of octets
} else if ( isComplexDataType( dtype ) ) {
// Sniff the first value in order to determine if we've materialized a nested array containing interleaved real and imaginary components...
if ( isNumber( buf[ 0 ] ) ) {
// As each real and imaginary component pair corresponds to a single complex number, we need to update the ndarray shape:
sh[ sh.length-1 ] /= 2;
}
buf = typedarray( buf, dtype );
} else if ( !isGenericDataType( dtype ) ) {
buf = typedarray( buf, dtype );
}
ord = resolveOrder( opts );
return new ndarray( dtype, buf, sh, shape2strides( sh, ord ), 0, ord, opts );
}
// Case: tensor3d( options )
if ( options === null && isPlainObject( arg ) ) {
buf = buffer( dtype, 0 );
return new ndarray( dtype, buf, [ 0, 0, 0 ], [ 0, 0, 0 ], 0, resolveOrder( arg ), arg );
}
return null;
}
// MAIN //
/**
* Creates a three-dimensional ndarray.
*
* ## Notes
*
* - This API is intended to match the conventions of `@stdlib/array/typed`, which has a similar signature.
*
* @param {(NonNegativeInteger|NonNegativeIntegerArray|ArrayLikeObject<Collection>|ArrayBuffer|Iterable)} [arg0] - number of elements in the first dimension, shape, nested array, ArrayBuffer, or iterable
* @param {NonNegativeInteger} [arg1] - number of elements in the second dimension or byte offset
* @param {(NonNegativeInteger|NonNegativeIntegerArray)} [arg2] - number of elements in the last dimension, number of elements in the first dimension, or shape
* @param {NonNegativeInteger} [arg3] - number of elements in the second dimension
* @param {NonNegativeInteger} [arg4] - number of elements in the last dimension
* @param {*} [dtype='float64'] - data type
* @param {Options} [options] - function options
* @param {boolean} [options.readonly=false] - boolean indicating whether to return a read-only three-dimensional ndarray
* @param {string} [options.mode='throw'] - specifies how to handle indices which exceed ndarray dimensions
* @param {StringArray} [options.submode=[options.mode]] - specifies how to handle subscripts which exceed array dimensions on a per dimension basis
* @param {string} [options.order='row-major'] - memory layout (either row-major or column-major)
* @throws {TypeError} first argument must be either a shape, array-like object, ArrayBuffer, iterable, data type, or options object
* @throws {TypeError} must provide valid options
* @returns {ndarray} three-dimensional ndarray
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
*
* var arr = tensor3d();
* // returns <ndarray>
*
* var sh = getShape( arr );
* // returns [ 0, 0, 0 ]
*
* var dt = String( getDType( arr ) );
* // returns 'float64'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
*
* var arr = tensor3d( 2, 2, 2 );
* // returns <ndarray>
*
* var sh = getShape( arr );
* // returns [ 2, 2, 2 ]
*
* var dt = String( getDType( arr ) );
* // returns 'float64'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
*
* var arr = tensor3d( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ] ] );
* // returns <ndarray>
*
* var sh = getShape( arr );
* // returns [ 2, 2, 2 ]
*
* var dt = String( getDType( arr ) );
* // returns 'float64'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
*
* var arr = tensor3d( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ], 'float32' );
* // returns <ndarray>
*
* var sh = getShape( arr );
* // returns [ 1, 2, 2 ]
*
* var dt = String( getDType( arr ) );
* // returns 'float32'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
* var ArrayBuffer = require( '@stdlib/array/buffer' );
*
* var buf = new ArrayBuffer( 32 );
* var arr = tensor3d( buf );
* // returns <ndarray>
*
* var sh = getShape( arr );
* // returns [ 1, 1, 4 ]
*
* var dt = String( getDType( arr ) );
* // returns 'float64'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
* var ArrayBuffer = require( '@stdlib/array/buffer' );
*
* var buf = new ArrayBuffer( 32 );
* var arr = tensor3d( buf, 16 );
* // returns <ndarray>
*
* var sh = getShape( arr );
* // returns [ 1, 1, 2 ]
*
* var dt = String( getDType( arr ) );
* // returns 'float64'
*
* @example
* var getDType = require( '@stdlib/ndarray/dtype' );
* var getShape = require( '@stdlib/ndarray/shape' );
* var ArrayBuffer = require( '@stdlib/array/buffer' );
*
* var buf = new ArrayBuffer( 64 );
* var arr = tensor3d( buf, 16, 2, 1, 1 );
* // returns <ndarray>
*
* var sh = getShape( arr );
* // returns [ 2, 1, 1 ]
*
* var dt = String( getDType( arr ) );
* // returns 'float64'
*/
function tensor3d() { // eslint-disable-line max-statements
var nargs;
var arg0;
var arg1;
var arg2;
var arg3;
var arg4;
var arg5;
var arg6;
var buf;
var ord;
var out;
var sh;
nargs = arguments.length;
// Case: tensor3d()
if ( nargs === 0 ) {
buf = buffer( DEFAULT_DTYPE, 0 );
return new ndarray( DEFAULT_DTYPE, buf, [ 0, 0, 0 ], [ 0, 0, 0 ], 0, DEFAULT_ORDER );
}
arg0 = arguments[ 0 ];
// Case: tensor3d( arg0 );
if ( nargs === 1 ) {
if ( isDataType( arg0 ) ) {
return tensor3dWithDType( [ 0, 0, 0 ], arg0, null );
}
out = tensor3dWithDType( arg0, DEFAULT_DTYPE, null );
if ( out === null ) {
throw new TypeError( format( 'invalid argument. Must provide a shape, ArrayBuffer, array-like object, iterable, data type, or options object. Value: `%s`.', arg0 ) );
}
return out;
}
arg1 = arguments[ 1 ];
// Case: tensor3d( arg0, arg1 )
if ( nargs === 2 ) {
// Case: tensor3d( dtype, options )
if ( isDataType( arg0 ) ) {
if ( arg1 === null ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg1 ) );
}
return tensor3dWithDType( [ 0, 0, 0 ], arg0, arg1 );
}
// Case: tensor3d( arg0, dtype )
if ( isDataType( arg1 ) ) {
out = tensor3dWithDType( arg0, arg1, null );
if ( out === null ) {
throw new TypeError( format( 'invalid argument. First argument must be a shape, ArrayBuffer, array-like object, or iterable. Value: `%s`.', arg0 ) );
}
return out;
}
// Case: tensor3d( ArrayBuffer, byteOffset )
// Note: unlike a matrix, a three-dimensional ndarray shape cannot be fully specified by two arguments, and thus, in contrast to `@stdlib/ndarray/matrix/ctor`, two nonnegative integers is not a supported signature.
if ( isNonNegativeInteger( arg1 ) ) {
if ( !isArrayBuffer( arg0 ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ArrayBuffer. Value: `%s`.', arg0 ) );
}
sh = [ 1, 1, (arg0.byteLength-arg1)/bytesPerElement( DEFAULT_DTYPE ) ];
return arraybuffer2tensor3d( DEFAULT_DTYPE, arg0, sh, shape2strides( sh, DEFAULT_ORDER ), arg1, DEFAULT_ORDER );
}
// Case: tensor3d( arg0, options )
if ( arg1 === null ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg1 ) );
}
out = tensor3dWithDType( arg0, DEFAULT_DTYPE, arg1 );
if ( out === null ) {
throw new TypeError( format( 'invalid argument. First argument must be a shape, ArrayBuffer, array-like object, or iterable. Value: `%s`.', arg0 ) );
}
return out;
}
arg2 = arguments[ 2 ];
// Case: tensor3d( arg0, arg1, arg2 )
if ( nargs === 3 ) {
// Case: tensor3d( K, M, N )
if ( isNonNegativeInteger( arg0 ) ) {
if ( !isNonNegativeInteger( arg1 ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a nonnegative integer. Value: `%s`.', arg1 ) );
}
if ( !isNonNegativeInteger( arg2 ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be a nonnegative integer. Value: `%s`.', arg2 ) );
}
return tensor3dWithDType( [ arg0, arg1, arg2 ], DEFAULT_DTYPE, null );
}
// Case: tensor3d( arg0, dtype, options )
if ( isDataType( arg1 ) ) {
if ( arg2 === null ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg2 ) );
}
out = tensor3dWithDType( arg0, arg1, arg2 );
if ( out === null ) {
throw new TypeError( format( 'invalid argument. First argument must be a shape, ArrayBuffer, array-like object, or iterable. Value: `%s`.', arg0 ) );
}
return out;
}
// Case: tensor3d( ArrayBuffer, byteOffset, arg2 )
if ( !isArrayBuffer( arg0 ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ArrayBuffer. Value: `%s`.', arg0 ) );
}
if ( !isNonNegativeInteger( arg1 ) ) {
throw new TypeError( format( 'invalid argument. Byte offset must be a nonnegative integer. Value: `%s`.', arg1 ) );
}
// Case: tensor3d( ArrayBuffer, byteOffset, dtype )
if ( isDataType( arg2 ) ) {
sh = [ 1, 1, (arg0.byteLength-arg1)/bytesPerElement( arg2 ) ];
return arraybuffer2tensor3d( arg2, arg0, sh, shape2strides( sh, DEFAULT_ORDER ), arg1, DEFAULT_ORDER );
}
// Case: tensor3d( ArrayBuffer, byteOffset, shape )
if ( isNonNegativeIntegerArray( arg2 ) && arg2.length === 3 ) {
return arraybuffer2tensor3d( DEFAULT_DTYPE, arg0, arg2, shape2strides( arg2, DEFAULT_ORDER ), arg1, DEFAULT_ORDER );
}
// Case: tensor3d( ArrayBuffer, byteOffset, options )
if ( arg2 === null ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg2 ) );
}
sh = [ 1, 1, (arg0.byteLength-arg1)/bytesPerElement( DEFAULT_DTYPE ) ];
ord = resolveOrder( arg2 );
return arraybuffer2tensor3d( DEFAULT_DTYPE, arg0, sh, shape2strides( sh, ord ), arg1, ord, arg2 );
}
arg3 = arguments[ 3 ];
// Case: tensor3d( arg0, arg1, arg2, arg3 )
if ( nargs === 4 ) {
// Case: tensor3d( K, M, N, arg3 )
if ( isNonNegativeInteger( arg0 ) ) {
if ( !isNonNegativeInteger( arg1 ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a nonnegative integer. Value: `%s`.', arg1 ) );
}
if ( !isNonNegativeInteger( arg2 ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be a nonnegative integer. Value: `%s`.', arg2 ) );
}
// Case: tensor3d( K, M, N, dtype )
if ( isDataType( arg3 ) ) {
return tensor3dWithDType( [ arg0, arg1, arg2 ], arg3, null );
}
// Case: tensor3d( K, M, N, options )
if ( arg3 === null ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg3 ) );
}
return tensor3dWithDType( [ arg0, arg1, arg2 ], DEFAULT_DTYPE, arg3 );
}
// Case: tensor3d( ArrayBuffer, byteOffset, arg2, arg3 )
if ( !isArrayBuffer( arg0 ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ArrayBuffer. Value: `%s`.', arg0 ) );
}
if ( !isNonNegativeInteger( arg1 ) ) {
throw new TypeError( format( 'invalid argument. Byte offset must be a nonnegative integer. Value: `%s`.', arg1 ) );
}
// Case: tensor3d( ArrayBuffer, byteOffset, shape, arg3 )
if ( isNonNegativeIntegerArray( arg2 ) && arg2.length === 3 ) {
// Case: tensor3d( ArrayBuffer, byteOffset, shape, dtype )
if ( isDataType( arg3 ) ) {
return arraybuffer2tensor3d( arg3, arg0, arg2, shape2strides( arg2, DEFAULT_ORDER ), arg1, DEFAULT_ORDER );
}
// Case: tensor3d( ArrayBuffer, byteOffset, shape, options )
if ( !isPlainObject( arg3 ) ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg3 ) );
}
ord = resolveOrder( arg3 );
return arraybuffer2tensor3d( DEFAULT_DTYPE, arg0, arg2, shape2strides( arg2, ord ), arg1, ord, arg3 );
}
// Case: tensor3d( ArrayBuffer, byteOffset, dtype, options )
if ( !isDataType( arg2 ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be a recognized/supported data type. Value: `%s`.', arg2 ) );
}
if ( !isPlainObject( arg3 ) ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg3 ) );
}
sh = [ 1, 1, (arg0.byteLength-arg1)/bytesPerElement( arg2 ) ];
ord = resolveOrder( arg3 );
return arraybuffer2tensor3d( arg2, arg0, sh, shape2strides( sh, ord ), arg1, ord, arg3 );
}
arg4 = arguments[ 4 ];
// Case: tensor3d( arg0, arg1, arg2, arg3, arg4 )
if ( nargs === 5 ) {
// Case: tensor3d( K, M, N, dtype, options )
if ( isNonNegativeInteger( arg0 ) ) {
if ( !isNonNegativeInteger( arg1 ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a nonnegative integer. Value: `%s`.', arg1 ) );
}
if ( !isNonNegativeInteger( arg2 ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be a nonnegative integer. Value: `%s`.', arg2 ) );
}
if ( !isDataType( arg3 ) ) {
throw new TypeError( format( 'invalid argument. Fourth argument must be a recognized/supported data type. Value: `%s`.', arg3 ) );
}
if ( !isPlainObject( arg4 ) ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg4 ) );
}
return tensor3dWithDType( [ arg0, arg1, arg2 ], arg3, arg4 );
}
// Case: tensor3d( ArrayBuffer, byteOffset, arg2, arg3, arg4 )
if ( !isArrayBuffer( arg0 ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ArrayBuffer. Value: `%s`.', arg0 ) );
}
if ( !isNonNegativeInteger( arg1 ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a nonnegative integer. Value: `%s`.', arg1 ) );
}
// Case: tensor3d( ArrayBuffer, byteOffset, K, M, N )
if ( isNonNegativeInteger( arg2 ) ) {
if ( !isNonNegativeInteger( arg3 ) ) {
throw new TypeError( format( 'invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.', arg3 ) );
}
if ( !isNonNegativeInteger( arg4 ) ) {
throw new TypeError( format( 'invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.', arg4 ) );
}
sh = [ arg2, arg3, arg4 ];
return arraybuffer2tensor3d( DEFAULT_DTYPE, arg0, sh, shape2strides( sh, DEFAULT_ORDER ), arg1, DEFAULT_ORDER );
}
// Case: tensor3d( ArrayBuffer, byteOffset, shape, dtype, options )
if ( !isNonNegativeIntegerArray( arg2 ) || arg2.length !== 3 ) {
throw new TypeError( format( 'invalid argument. Third argument must be a valid shape. Value: `%s`.', arg2 ) );
}
if ( !isDataType( arg3 ) ) {
throw new TypeError( format( 'invalid argument. Fourth argument must be a recognized/supported data type. Value: `%s`.', arg3 ) );
}
if ( !isPlainObject( arg4 ) ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg4 ) );
}
ord = resolveOrder( arg4 );
return arraybuffer2tensor3d( arg3, arg0, arg2, shape2strides( arg2, ord ), arg1, ord, arg4 );
}
arg5 = arguments[ 5 ];
// Case: tensor3d( ArrayBuffer, byteOffset, K, M, N, arg5 )
if ( nargs === 6 ) {
if ( !isArrayBuffer( arg0 ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ArrayBuffer. Value: `%s`.', arg0 ) );
}
if ( !isNonNegativeInteger( arg1 ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a nonnegative integer. Value: `%s`.', arg1 ) );
}
if ( !isNonNegativeInteger( arg2 ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be a nonnegative integer. Value: `%s`.', arg2 ) );
}
if ( !isNonNegativeInteger( arg3 ) ) {
throw new TypeError( format( 'invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.', arg3 ) );
}
if ( !isNonNegativeInteger( arg4 ) ) {
throw new TypeError( format( 'invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.', arg4 ) );
}
sh = [ arg2, arg3, arg4 ];
// Case: tensor3d( ArrayBuffer, byteOffset, K, M, N, dtype )
if ( isDataType( arg5 ) ) {
return arraybuffer2tensor3d( arg5, arg0, sh, shape2strides( sh, DEFAULT_ORDER ), arg1, DEFAULT_ORDER );
}
// Case: tensor3d( ArrayBuffer, byteOffset, K, M, N, options )
if ( !isPlainObject( arg5 ) ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg5 ) );
}
ord = resolveOrder( arg5 );
return arraybuffer2tensor3d( DEFAULT_DTYPE, arg0, sh, shape2strides( sh, ord ), arg1, ord, arg5 );
}
arg6 = arguments[ 6 ];
// Case: tensor3d( ArrayBuffer, byteOffset, K, M, N, dtype, options )
if ( !isArrayBuffer( arg0 ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ArrayBuffer. Value: `%s`.', arg0 ) );
}
if ( !isNonNegativeInteger( arg1 ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a nonnegative integer. Value: `%s`.', arg1 ) );
}
if ( !isNonNegativeInteger( arg2 ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be a nonnegative integer. Value: `%s`.', arg2 ) );
}
if ( !isNonNegativeInteger( arg3 ) ) {
throw new TypeError( format( 'invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.', arg3 ) );
}
if ( !isNonNegativeInteger( arg4 ) ) {
throw new TypeError( format( 'invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.', arg4 ) );
}
if ( !isDataType( arg5 ) ) {
throw new TypeError( format( 'invalid argument. Sixth argument must be a recognized/supported data type. Value: `%s`.', arg5 ) );
}
if ( !isPlainObject( arg6 ) ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', arg6 ) );
}
sh = [ arg2, arg3, arg4 ];
ord = resolveOrder( arg6 );
return arraybuffer2tensor3d( arg5, arg0, sh, shape2strides( sh, ord ), arg1, ord, arg6 );
}
// EXPORTS //
module.exports = tensor3d;
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