mirror of https://github.com/tensorflow/tfjs.git
54 lines
1.9 KiB
TypeScript
54 lines
1.9 KiB
TypeScript
/**
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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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import '@tensorflow/tfjs-backend-cpu';
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import '@tensorflow/tfjs-backend-webgl';
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import '@tensorflow/tfjs-backend-webgpu';
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import * as tfc from '@tensorflow/tfjs-core';
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// tslint:disable-next-line: no-imports-from-dist
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import {Constraints, describeWithFlags} from '@tensorflow/tfjs-core/dist/jasmine_util';
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import * as tfl from '@tensorflow/tfjs-layers';
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import {SMOKE} from './constants';
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// TODO(#6518): Test against wasm as well.
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const NOT_WASM: Constraints = {
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predicate: testEnv => testEnv.backendName !== 'wasm',
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};
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/**
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* Tests that tf.grad works for layers models.
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* Regression test for https://github.com/tensorflow/tfjs/issues/4130
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*/
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describe(`${SMOKE} tf.grad for layers models`, () => {
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describeWithFlags(`layers_model`, NOT_WASM, (env) => {
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it(`can compute grad of prediction`, async () => {
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await tfc.setBackend(env.name);
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const model = tfl.sequential();
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model.add(tfl.layers.dense({inputShape: [1], units: 1}));
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const forward = (x: tfc.Tensor) => model.predict(x) as tfc.Tensor;
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const grad = tfc.grad(forward);
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const input = tfc.tensor([1], [1, 1]);
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const dy = tfc.onesLike(input);
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expect(() => {
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grad(input, dy);
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}).not.toThrow();
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});
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});
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});
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