/**
  * 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];
 }

 .then(() => {
   const reader = new dl.CheckpointLoader(CHECKPOINT_URL);
   return reader.getAllVariables();
 })

 * 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 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;

 * 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 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]);