| 1 | /**
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| 2 | * @license
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| 3 | * Copyright 2018 Google LLC. All Rights Reserved.
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| 4 | * Licensed under the Apache License, Version 2.0 (the "License");
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| 5 | * you may not use this file except in compliance with the License.
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| 6 | * You may obtain a copy of the License at
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| 7 | *
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| 8 | * http://www.apache.org/licenses/LICENSE-2.0
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| 9 | *
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| 10 | * Unless required by applicable law or agreed to in writing, software
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| 11 | * distributed under the License is distributed on an "AS IS" BASIS,
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| 12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 13 | * See the License for the specific language governing permissions and
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| 14 | * limitations under the License.
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| 15 | * =============================================================================
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| 16 | */
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| 17 | import { isTypedArray } from '../util';
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| 18 | import { makeTensor } from './tensor_ops_util';
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| 19 | /**
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| 20 | * Creates rank-0 `tf.Tensor` (scalar) with the provided value and dtype.
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| 21 | *
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| 22 | * The same functionality can be achieved with `tf.tensor`, but in general
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| 23 | * we recommend using `tf.scalar` as it makes the code more readable.
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| 24 | *
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| 25 | * ```js
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| 26 | * tf.scalar(3.14).print();
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| 27 | * ```
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| 28 | *
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| 29 | * @param value The value of the scalar.
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| 30 | * @param dtype The data type.
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| 31 | *
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| 32 | * @doc {heading: 'Tensors', subheading: 'Creation'}
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| 33 | */
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| 34 | export function scalar(value, dtype) {
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| 35 | if (((isTypedArray(value) && dtype !== 'string') || Array.isArray(value)) &&
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| 36 | dtype !== 'complex64') {
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| 37 | throw new Error('Error creating a new Scalar: value must be a primitive ' +
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| 38 | '(number|boolean|string)');
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| 39 | }
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| 40 | if (dtype === 'string' && isTypedArray(value) &&
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| 41 | !(value instanceof Uint8Array)) {
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| 42 | throw new Error('When making a scalar from encoded string, ' +
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| 43 | 'the value must be `Uint8Array`.');
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| 44 | }
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| 45 | const shape = [];
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| 46 | const inferredShape = [];
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| 47 | return makeTensor(value, shape, inferredShape, dtype);
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| 48 | }
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