本文整理汇总了TypeScript中deeplearn.CheckpointLoader.getAllVariables方法的典型用法代码示例。如果您正苦于以下问题：TypeScript CheckpointLoader.getAllVariables方法的具体用法？TypeScript CheckpointLoader.getAllVariables怎么用？TypeScript CheckpointLoader.getAllVariables使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类deeplearn.CheckpointLoader的用法示例。
在下文中一共展示了CheckpointLoader.getAllVariables方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的TypeScript代码示例。
示例1: load
/**
* Loads necessary variables for SqueezeNet. Resolves the promise when the
* variables have all been loaded.
*/
async load(): Promise<void> {
if (this.variableDictionary[this.style] == null) {
const checkpointLoader =
new dl.CheckpointLoader(GOOGLE_CLOUD_STORAGE_DIR + this.style + '/');
this.variableDictionary[this.style] =
await checkpointLoader.getAllVariables();
}
this.variables = this.variableDictionary[this.style];
}示例2:
.then(() => {
const reader = new dl.CheckpointLoader(CHECKPOINT_URL);
return reader.getAllVariables();
})示例3:
* 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 dl from 'deeplearn';
// manifest.json lives in the same directory.
const reader = new dl.CheckpointLoader('.');
reader.getAllVariables().then(async vars => {
const primerData = 3;
const expected = [1, 4, 1, 5, 9, 2, 6, 5, 3, 5, 8, 9, 7, 9, 3, 2, 3, 8, 4];
const lstmKernel1 =
vars['rnn/multi_rnn_cell/cell_0/basic_lstm_cell/kernel'] as dl.Tensor2D;
const lstmBias1 =
vars['rnn/multi_rnn_cell/cell_0/basic_lstm_cell/bias'] as dl.Tensor1D;
const lstmKernel2 =
vars['rnn/multi_rnn_cell/cell_1/basic_lstm_cell/kernel'] as dl.Tensor2D;
const lstmBias2 =
vars['rnn/multi_rnn_cell/cell_1/basic_lstm_cell/bias'] as dl.Tensor1D;
const fullyConnectedBiases = vars['fully_connected/biases'] as dl.Tensor1D;
const fullyConnectedWeights = vars['fully_connected/weights'] as dl.Tensor2D;示例4: XMLHttpRequest
*
* 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 dl from 'deeplearn';
// manifest.json lives in the same directory as the mnist demo.
const reader = new dl.CheckpointLoader('.');
reader.getAllVariables().then(vars => {
// Get sample data.
const xhr = new XMLHttpRequest();
xhr.open('GET', 'sample_data.json');
xhr.onload = async () => {
const data = JSON.parse(xhr.responseText) as SampleData;
// Wrap everything in a dl.tidy so we clean up intermediate Tensors.
dl.tidy(async () => {
console.log(`Evaluation set: n=${data.images.length}.`);
let numCorrect = 0;
for (let i = 0; i < data.images.length; i++) {
const x = dl.tensor1d(data.images[i]);
// Infer through the model to get a prediction.