Remove dist importing

.tslint/noImportsFromDistRule.js

@@ -0,0 +1,44 @@
+"use strict";
+var __extends = (this && this.__extends) || (function () {
+    var extendStatics = function (d, b) {
+        extendStatics = Object.setPrototypeOf ||
+            ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||
+            function (d, b) { for (var p in b) if (b.hasOwnProperty(p)) d[p] = b[p]; };
+        return extendStatics(d, b);
+    };
+    return function (d, b) {
+        extendStatics(d, b);
+        function __() { this.constructor = d; }
+        d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());
+    };
+})();
+exports.__esModule = true;
+var Lint = require("tslint");
+var Rule = /** @class */ (function (_super) {
+    __extends(Rule, _super);
+    function Rule() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    Rule.prototype.apply = function (sourceFile) {
+        return this.applyWithWalker(new NoImportsFromDistWalker(sourceFile, this.getOptions()));
+    };
+    Rule.FAILURE_STRING = "importing from dist/ is prohibited. Please use public API";
+    return Rule;
+}(Lint.Rules.AbstractRule));
+exports.Rule = Rule;
+var NoImportsFromDistWalker = /** @class */ (function (_super) {
+    __extends(NoImportsFromDistWalker, _super);
+    function NoImportsFromDistWalker() {
+        return _super !== null && _super.apply(this, arguments) || this;
+    }
+    NoImportsFromDistWalker.prototype.visitImportDeclaration = function (node) {
+        var importFrom = node.moduleSpecifier.getText();
+        var reg = /@tensorflow\/tfjs[-a-z]*\/dist/;
+        if (importFrom.match(reg)) {
+            var fix = new Lint.Replacement(node.moduleSpecifier.getStart(), node.moduleSpecifier.getWidth(), importFrom.replace(/\/dist[\/]*/, ''));
+            this.addFailure(this.createFailure(node.moduleSpecifier.getStart(), node.moduleSpecifier.getWidth(), Rule.FAILURE_STRING, fix));
+        }
+        _super.prototype.visitImportDeclaration.call(this, node);
+    };
+    return NoImportsFromDistWalker;
+}(Lint.RuleWalker));

.tslint/noImportsFromDistRule.ts

@@ -0,0 +1,30 @@
+import * as Lint from "tslint";
+import * as ts from "typescript";
+
+export class Rule extends Lint.Rules.AbstractRule {
+  public static FAILURE_STRING = "importing from dist/ is prohibited. Please use public API";
+
+  public apply(sourceFile: ts.SourceFile): Lint.RuleFailure[] {
+    return this.applyWithWalker(
+      new NoImportsFromDistWalker(sourceFile, this.getOptions()));
+  }
+}
+
+class NoImportsFromDistWalker extends Lint.RuleWalker {
+  public visitImportDeclaration(node: ts.ImportDeclaration) {
+    const importFrom = node.moduleSpecifier.getText();
+    const reg = /@tensorflow\/tfjs[-a-z]*\/dist/;
+    if (importFrom.match(reg)) {
+      const fix = new Lint.Replacement(node.moduleSpecifier.getStart(),
+        node.moduleSpecifier.getWidth(),
+        importFrom.replace(/\/dist[\/]*/, ''));
+
+      this.addFailure(this.createFailure(node.moduleSpecifier.getStart(),
+        node.moduleSpecifier.getWidth(),
+        Rule.FAILURE_STRING, fix));
+    }
+
+    super.visitImportDeclaration(node);
+  }
+
+}

src/io/file_system_test.ts

@@ -16,7 +16,7 @@
  */
 
 import * as tfc from '@tensorflow/tfjs-core';
-import {expectArraysClose} from '@tensorflow/tfjs-core/dist/test_util';
+import {test_util} from '@tensorflow/tfjs-core/';
 import * as fs from 'fs';
 import * as path from 'path';
 import * as rimraf from 'rimraf';
@@ -223,7 +223,7 @@ describe('File system IOHandler', () => {
                 dtype: 'float32',
               }
             ]);
-            expectArraysClose(
+            test_util.expectArraysClose(
                 new Float32Array(modelArtifacts.weightData),
                 new Float32Array([-1.1, -3.3, -3.3, -7.7]));
             done();
@@ -346,7 +346,7 @@ describe('File system IOHandler', () => {
           new NodeFileSystem([`${modelPath}`, `${modelManifestJSONPath}`]);
       handler.load()
           .then(modelArtifacts => {
-            expectArraysClose(
+            test_util.expectArraysClose(
                 new Uint8Array(modelArtifacts.modelTopology as ArrayBuffer),
                 new Uint8Array(modelData));
             expect(modelArtifacts.weightSpecs).toEqual([
@@ -361,7 +361,7 @@ describe('File system IOHandler', () => {
                 dtype: 'float32',
               }
             ]);
-            expectArraysClose(
+            test_util.expectArraysClose(
                 new Float32Array(modelArtifacts.weightData),
                 new Float32Array([-1.1, -3.3, -3.3, -7.7]));
             done();

src/nodejs_kernel_backend.ts

@@ -17,17 +17,17 @@
 
 // tslint:disable-next-line:max-line-length
 import {BackendTimingInfo, DataMover, DataType, fill, KernelBackend, ones, Rank, rsqrt, Scalar, scalar, ShapeMap, Tensor, Tensor1D, tensor1d, Tensor2D, tensor2d, Tensor3D, tensor3d, Tensor4D, tidy, util} from '@tensorflow/tfjs-core';
-import {EPSILON_FLOAT32} from '@tensorflow/tfjs-core/dist/backends/backend';
-import {Conv2DInfo, Conv3DInfo} from '@tensorflow/tfjs-core/dist/ops/conv_util';
-import {Activation} from '@tensorflow/tfjs-core/dist/ops/fused_util';
-import {Tensor5D} from '@tensorflow/tfjs-core/dist/tensor';
-import {BackendValues, upcastType} from '@tensorflow/tfjs-core/dist/types';
+import {backend_util} from '@tensorflow/tfjs-core';
+import {Tensor5D} from '@tensorflow/tfjs-core';
 import {isNullOrUndefined} from 'util';
 import {Int64Scalar} from './int64_tensors';
 // tslint:disable-next-line:max-line-length
 import {createTensorsTypeOpAttr, createTypeOpAttr, getTFDType} from './ops/op_utils';
 import {TensorMetadata, TFEOpAttr, TFJSBinding} from './tfjs_binding';
 
+type Conv2DInfo = backend_util.Conv2DInfo;
+type BackendValues = backend_util.BackendValues;
+
 type TensorInfo = {
   shape: number[],
   dtype: number,
@@ -37,6 +37,9 @@ type TensorInfo = {
 
 interface DataId {}
 
+const {upcastType} = backend_util;
+const EPSILON_FLOAT32 = 1e-7;
+
 export class NodeJSKernelBackend extends KernelBackend {
   binding: TFJSBinding;
   isGPUPackage: boolean;
@@ -370,7 +373,7 @@ export class NodeJSKernelBackend extends KernelBackend {
 
   fusedBatchMatMul(
       a: Tensor3D, b: Tensor3D, transposeA: boolean, transposeB: boolean,
-      bias?: Tensor, activation?: Activation,
+      bias?: Tensor, activation?: backend_util.Activation,
       preluActivationWeights?: Tensor): Tensor3D {
     // Core TensorFlow does not have a fused BatchMatMul op. Combine calls to
     // achieve the same results:

src/nodejs_kernel_backend_test.ts

@@ -16,18 +16,17 @@
  */
 
 import * as tf from '@tensorflow/tfjs-core';
-import {Tensor5D} from '@tensorflow/tfjs-core/dist/tensor';
-// tslint:disable-next-line:max-line-length
-import {expectArraysClose} from '@tensorflow/tfjs-core/dist/test_util';
+import {Tensor5D} from '@tensorflow/tfjs-core';
+import {test_util} from '@tensorflow/tfjs-core';
 import {NodeJSKernelBackend} from './nodejs_kernel_backend';
 
 describe('delayed upload', () => {
   it('should handle data before op execution', async () => {
     const t = tf.tensor1d([1, 2, 3]);
-    expectArraysClose(await t.data(), [1, 2, 3]);
+    test_util.expectArraysClose(await t.data(), [1, 2, 3]);
 
     const r = t.add(tf.tensor1d([4, 5, 6]));
-    expectArraysClose(await r.data(), [5, 7, 9]);
+    test_util.expectArraysClose(await r.data(), [5, 7, 9]);
   });
 
   it('Should not cache tensors in the tensor map for device support. ', () => {

src/run_tests.ts

@@ -17,6 +17,7 @@
 
 // We import index.ts so that the Node backend gets registered.
 import './index';
+// tslint:disable-next-line:no-imports-from-dist
 import * as jasmine_util from '@tensorflow/tfjs-core/dist/jasmine_util';
 
 Error.stackTraceLimit = Infinity;

src/tfjs_binding.ts

@@ -15,7 +15,8 @@
  * =============================================================================
  */
 
-import {BackendValues} from '@tensorflow/tfjs-core/dist/types';
+import {backend_util} from '@tensorflow/tfjs-core';
+type BackendValues = backend_util.BackendValues;
 
 export declare class TensorMetadata {
   id: number;

tslint.json

@@ -1,4 +1,5 @@
 {
+  "rulesDirectory": ".tslint",
   "rules": {
     "array-type": [true, "array-simple"],
     "arrow-return-shorthand": true,
@@ -36,6 +37,7 @@
     "no-reference": true,
     "no-require-imports": true,
     "no-string-throw": true,
+    "no-imports-from-dist": true,
     "no-unused-expression": true,
     "no-unused-variable": true,
     "no-var-keyword": true,