/**

* @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 * as tf from './index';

import {ALL_ENVS, describeWithFlags} from './jasmine_util';

import {expectArraysClose, expectArraysEqual} from './test_util';

describeWithFlags('tf.buffer', ALL_ENVS, () => {

it('float32', async () => {

const buff = tf.buffer([1, 2, 3], 'float32');

buff.set(1.3, 0, 0, 0);

buff.set(2.9, 0, 1, 0);

expect(buff.get(0, 0, 0)).toBeCloseTo(1.3);

expect(buff.get(0, 0, 1)).toBeCloseTo(0);

expect(buff.get(0, 0, 2)).toBeCloseTo(0);

expect(buff.get(0, 1, 0)).toBeCloseTo(2.9);

expect(buff.get(0, 1, 1)).toBeCloseTo(0);

expect(buff.get(0, 1, 2)).toBeCloseTo(0);

expectArraysClose(await buff.toTensor().data(), [1.3, 0, 0, 2.9, 0, 0]);

expectArraysClose(buff.values, new Float32Array([1.3, 0, 0, 2.9, 0, 0]));

});

it('get() out of range throws', async () => {

const t = tf.tensor([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2]);

const buff = await t.buffer();

expect(buff.get(0, 0, 0)).toBeCloseTo(1);

expect(buff.get(0, 0, 1)).toBeCloseTo(2);

expect(() => buff.get(0, 0, 2))

.toThrowError(/Requested out of range element/);

});

it('int32', async () => {

const buff = tf.buffer([2, 3], 'int32');

buff.set(1.3, 0, 0);

buff.set(2.1, 1, 1);

expect(buff.get(0, 0)).toEqual(1);

expect(buff.get(0, 1)).toEqual(0);

expect(buff.get(0, 2)).toEqual(0);

expect(buff.get(1, 0)).toEqual(0);

expect(buff.get(1, 1)).toEqual(2);

expect(buff.get(1, 2)).toEqual(0);

expectArraysClose(await buff.toTensor().data(), [1, 0, 0, 0, 2, 0]);

expectArraysClose(buff.values, new Int32Array([1, 0, 0, 0, 2, 0]));

});

it('bool', async () => {

const buff = tf.buffer([4], 'bool');

buff.set(true, 1);

buff.set(true, 2);

expect(buff.get(0)).toBeFalsy();

expect(buff.get(1)).toBeTruthy();

expect(buff.get(2)).toBeTruthy();

expect(buff.get(3)).toBeFalsy();

expectArraysClose(await buff.toTensor().data(), [0, 1, 1, 0]);

expectArraysClose(buff.values, new Uint8Array([0, 1, 1, 0]));

});

it('string', async () => {

const buff = tf.buffer([2, 2], 'string');

buff.set('first', 0, 0);

buff.set('third', 1, 0);

expect(buff.get(0, 0)).toEqual('first');

expect(buff.get(0, 1)).toBeFalsy();

expect(buff.get(1, 0)).toEqual('third');

expect(buff.get(1, 1)).toBeFalsy();

expectArraysEqual(

await buff.toTensor().data(), ['first', null, 'third', null]);

});

it('throws when passed non-integer shape', () => {

const msg = 'Tensor must have a shape comprised of positive ' +

'integers but got shape [2,2.2].';

expect(() => tf.buffer([2, 2.2])).toThrowError(msg);

});

it('throws when passed negative shape', () => {

const msg = 'Tensor must have a shape comprised of positive ' +

'integers but got shape [2,-2].';

expect(() => tf.buffer([2, -2])).toThrowError(msg);

});

});