chore: update node_modules with new binary files and dependencies

- Add new binary files for nodemon, onnxruntime-web, and xenova/transformers
- Update various JavaScript and TypeScript files in node_modules
- Remove unused files and dependencies
- Add new test fixtures and documentation files

node_modules/onnxruntime-web/lib/onnxjs/backends/webgl/ops/slice.ts

@@ -0,0 +1,142 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+import {AttributeWithCacheKey, createAttributeWithCacheKey} from '../../../attribute-with-cache-key';
+import {Graph} from '../../../graph';
+import {NUMBER_TYPES, OperatorImplementation, OperatorInitialization} from '../../../operators';
+import {Tensor} from '../../../tensor';
+import {ShapeUtil} from '../../../util';
+import {WebGLInferenceHandler} from '../inference-handler';
+import {ProgramInfo, TextureType} from '../types';
+
+export interface SliceAttributes extends AttributeWithCacheKey {
+  readonly axes: number[];
+  readonly ends: number[];
+  readonly starts: number[];
+}
+
+const sliceProgramMetadata = {
+  name: 'Slice',
+  inputNames: ['A'],
+  inputTypes: [TextureType.unpacked]
+};
+
+export const slice: OperatorImplementation<SliceAttributes> =
+    (inferenceHandler: WebGLInferenceHandler, inputs: Tensor[], attributes: SliceAttributes): Tensor[] => {
+      validateInputs(inputs);
+      const output = inferenceHandler.run(
+          {
+            ...sliceProgramMetadata,
+            cacheHint: attributes.cacheKey,
+            get: () => createSliceProgramInfo(inferenceHandler, inputs[0], attributes)
+          },
+          inputs);
+      return [output];
+    };
+
+export const parseSliceAttributes: OperatorInitialization<SliceAttributes> = (node: Graph.Node): SliceAttributes => {
+  const starts = node.attributes.getInts('starts');
+  const ends = node.attributes.getInts('ends');
+  const axes = node.attributes.getInts('axes', []);
+  return createAttributeWithCacheKey({starts, ends, axes});
+};
+
+const createSliceProgramInfo =
+    (inferenceHandler: WebGLInferenceHandler, input: Tensor, attributes: SliceAttributes): ProgramInfo => {
+      const axes = (attributes.axes.length === 0) ? input.dims.slice(0).map((val, i) => i) : attributes.axes;
+      const normalizedAxes = ShapeUtil.normalizeAxes(axes, input.dims.length);
+      const starts = attributes.starts.map((start, i) => {
+        if (start > input.dims[normalizedAxes[i]] - 1) {
+          return input.dims[normalizedAxes[i]];
+        }
+        return ShapeUtil.normalizeAxis(start, input.dims[normalizedAxes[i]]);
+      });
+      const ends = attributes.ends.map((end, i) => {
+        if (end > input.dims[normalizedAxes[i]] - 1) {
+          return input.dims[normalizedAxes[i]];
+        }
+        return ShapeUtil.normalizeAxis(end, input.dims[normalizedAxes[i]]);
+      });
+
+      const outputShape = input.dims.slice();
+
+      const sliceOps: string[] = [];
+      for (let i = 0; i < normalizedAxes.length; i++) {
+        outputShape[normalizedAxes[i]] = ends[i] - starts[i];
+        if (starts[i] > 0) {
+          sliceOps.push(`outputIdx[${normalizedAxes[i]}] += ${starts[i]};`);
+        }  // else { sliceOps.push(`outputIdx[${normalizedAxes[i]}] += 0;`); }
+      }
+
+      const rank = outputShape.length;
+      const shaderSource = `
+      float process(int outputIdx[${rank}]) {
+        ${sliceOps.join('\n      ')}
+        return _A(outputIdx);
+      }`;
+      return {
+        ...sliceProgramMetadata,
+        output: {dims: outputShape, type: input.type, textureType: TextureType.unpacked},
+        shaderSource
+      };
+    };
+
+const validateInputs = (inputs: Tensor[]): void => {
+  if (!inputs || inputs.length !== 1) {
+    throw new Error('Slice requires 1 input.');
+  }
+  if (NUMBER_TYPES.indexOf(inputs[0].type) === -1) {
+    throw new Error('Invalid input type.');
+  }
+};
+
+export const sliceV10 = (inferenceHandler: WebGLInferenceHandler, inputs: Tensor[]): Tensor[] => {
+  validateInputsV10(inputs);
+  const attributes = generateSliceAttributesFromInputs(inferenceHandler, inputs);
+  const output = inferenceHandler.run(
+      {
+        ...sliceProgramMetadata,
+        cacheHint: attributes.cacheKey,
+        get: () => createSliceProgramInfo(inferenceHandler, inputs[0], attributes)
+      },
+      [inputs[0]]);
+  return [output];
+};
+
+const generateSliceAttributesFromInputs =
+    (inferenceHandler: WebGLInferenceHandler, inputs: Tensor[]): SliceAttributes => {
+      if (!inferenceHandler.session.isInitializer(inputs[1].dataId) ||
+          !inferenceHandler.session.isInitializer(inputs[2].dataId) ||
+          (inputs.length >= 4 && !inferenceHandler.session.isInitializer(inputs[3].dataId)) ||
+          (inputs.length >= 5 && !inferenceHandler.session.isInitializer(inputs[4].dataId))) {
+        throw new Error('dynamic slice attributes are not allowed');
+      }
+
+      if (inputs.length >= 5 && inputs[4].integerData.some((i: number) => i !== 1)) {
+        throw new Error('currently non-1 steps is not supported for Slice');
+      }
+
+      const starts = Array.from(inputs[1].integerData);
+      const ends = Array.from(inputs[2].integerData);
+      const axes = inputs.length >= 4 ? Array.from(inputs[3].integerData) : [];
+      const cacheKey = `${axes};${starts};${ends}`;
+      return {starts, ends, axes, cacheKey};
+    };
+
+const validateInputsV10 = (inputs: Tensor[]): void => {
+  if (!inputs || inputs.length < 3 || inputs.length > 5) {
+    throw new Error('Invalid input number.');
+  }
+  if (inputs[1].type !== 'int32' || inputs[1].dims.length !== 1) {
+    throw new Error('Invalid input type.');
+  }
+  if (inputs[2].type !== 'int32' || inputs[2].dims.length !== 1) {
+    throw new Error('Invalid input type.');
+  }
+  if (inputs.length >= 4 && (inputs[3].type !== 'int32' || inputs[3].dims.length !== 1)) {
+    throw new Error('Invalid input type.');
+  }
+  if (inputs.length >= 5 && (inputs[4].type !== 'int32' || inputs[4].dims.length !== 1)) {
+    throw new Error('Invalid input type.');
+  }
+};