@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* 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 { inferShape } from '../tensor_util_env';
import { assertNonNull } from '../util';
import { makeTensor } from './tensor_ops_util';
/**
* Creates rank-4 `tf.Tensor` with the provided values, shape and dtype.
*
* The same functionality can be achieved with `tf.tensor`, but in general
* we recommend using `tf.tensor4d` as it makes the code more readable.
*
* ```js
* // Pass a nested array.
* tf.tensor4d([[[[1], [2]], [[3], [4]]]]).print();
* ```
* ```js
* // Pass a flat array and specify a shape.
* tf.tensor4d([1, 2, 3, 4], [1, 2, 2, 1]).print();
* ```
*
* @param values The values of the tensor. Can be nested array of numbers,
* or a flat array, or a `TypedArray`.
* @param shape The shape of the tensor. Optional. If not provided,
* it is inferred from `values`.
* @param dtype The data type.
*
* @doc {heading: 'Tensors', subheading: 'Creation'}
*/
export function tensor4d(values, shape, dtype) {
assertNonNull(values);
if (shape != null && shape.length !== 4) {
throw new Error('tensor4d() requires shape to have four numbers');
}
const inferredShape = inferShape(values, dtype);
if (inferredShape.length !== 4 && inferredShape.length !== 1) {
throw new Error('tensor4d() requires values to be number[][][][] or flat/TypedArray');
}
if (inferredShape.length === 1 && shape == null) {
throw new Error('tensor4d() requires shape to be provided when `values` ' +
'are a flat array');
}
return makeTensor(values, shape, inferredShape, dtype);
}
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