/**
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* @license
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* Copyright 2020 Google LLC. All Rights Reserved.
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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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*/
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/// <amd-module name="@tensorflow/tfjs-core/dist/ops/mod" />
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import { Tensor } from '../tensor';
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import { TensorLike } from '../types';
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/**
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* Returns the mod of a and b element-wise.
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* `floor(x / y) * y + mod(x, y) = x`
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* Supports broadcasting.
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*
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* We also expose `tf.modStrict` which has the same signature as this op and
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* asserts that `a` and `b` are the same shape (does not broadcast).
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*
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* ```js
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* const a = tf.tensor1d([1, 4, 3, 16]);
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* const b = tf.tensor1d([1, 2, 9, 4]);
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*
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* a.mod(b).print(); // or tf.mod(a, b)
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* ```
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*
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* ```js
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* // Broadcast a mod b.
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* const a = tf.tensor1d([2, 4, 6, 8]);
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* const b = tf.scalar(5);
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*
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* a.mod(b).print(); // or tf.mod(a, b)
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* ```
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*
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* @param a The first tensor.
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* @param b The second tensor. Must have the same type as `a`.
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*
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* @doc {heading: 'Operations', subheading: 'Arithmetic'}
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*/
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declare function mod_<T extends Tensor>(a: Tensor | TensorLike, b: Tensor | TensorLike): T;
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export declare const mod: typeof mod_;
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export {};
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