text: /**
   * @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.
   * =============================================================================
   */
  // tslint:disable-next-line: no-imports-from-dist
  import * as tfOps from '@tensorflow/tfjs-core/dist/ops/ops_for_converter';
  import { getParamValue } from './utils';
  export const executeOp = (node, tensorMap, context) => {
      switch (node.op) {
          case 'ResizeBilinear': {
              const images = getParamValue('images', node, tensorMap, context);
              const size = getParamValue('size', node, tensorMap, context);
              const alignCorners = getParamValue('alignCorners', node, tensorMap, context);
              return [tfOps.image.resizeBilinear(images, [size[0], size[1]], alignCorners)];
          }
          case 'ResizeNearestNeighbor': {
              const images = getParamValue('images', node, tensorMap, context);
              const size = getParamValue('size', node, tensorMap, context);
              const alignCorners = getParamValue('alignCorners', node, tensorMap, context);
              return [tfOps.image.resizeNearestNeighbor(images, [size[0], size[1]], alignCorners)];
          }
          case 'CropAndResize': {
              const image = getParamValue('image', node, tensorMap, context);
              const boxes = getParamValue('boxes', node, tensorMap, context);
              const boxInd = getParamValue('boxInd', node, tensorMap, context);
              const cropSize = getParamValue('cropSize', node, tensorMap, context);
              const method = getParamValue('method', node, tensorMap, context);
              const extrapolationValue = getParamValue('extrapolationValue', node, tensorMap, context);
              return [tfOps.image.cropAndResize(image, boxes, boxInd, cropSize, method, extrapolationValue)];
          }
          default:
              throw TypeError(`Node type ${node.op} is not implemented`);
      }
  };
  export const CATEGORY = 'image';
  //# sourceMappingURL=image_executor.js.map