@tensorflow/tfjs-layers - npm Package Compare versions

Comparing version 0.2.0 to 0.3.0

dist/backend/tfjs_backend.d.ts

@@ -25,2 +25,4 @@ import { Scalar, Tensor, Tensor1D, Tensor2D } from '@tensorflow/tfjs-core';
 export declare function squeeze(x: Tensor, axis: number): Tensor;
+export declare function temporalPadding(x: Tensor, padding?: [number, number]): Tensor;
+export declare function spatial2dPadding(x: Tensor, padding?: [[number, number], [number, number]], dataFormat?: DataFormat): Tensor;
 export declare function repeat(x: Tensor, n: number): Tensor;
@@ -27,0 +29,0 @@ export declare function flatten(x: Tensor): Tensor;

dist/backend/tfjs_backend.js

@@ -125,2 +125,48 @@ "use strict";
 exports.squeeze = squeeze;
+function temporalPadding(x, padding) {
+    if (ndim(x) !== 3) {
+        throw new errors_1.ValueError("temporalPadding expects input tensor to be 3-D, but received a " +
+            (ndim(x) + "-D tensor."));
+    }
+    if (padding == null) {
+        padding = [1, 1];
+    }
+    if (padding.length !== 2) {
+        throw new errors_1.ValueError("temporalPadding expects input padding pattern to be a length-2 " +
+            ("array, but received a length-" + padding.length + " array."));
+    }
+    var pattern = [[0, 0], padding, [0, 0]];
+    return tfc.pad(x, pattern);
+}
+exports.temporalPadding = temporalPadding;
+function spatial2dPadding(x, padding, dataFormat) {
+    if (ndim(x) !== 4) {
+        throw new errors_1.ValueError("temporalPadding expects input tensor to be 4-D, but received a " +
+            (ndim(x) + "-D tensor."));
+    }
+    if (padding == null) {
+        padding = [[1, 1], [1, 1]];
+    }
+    if (padding.length !== 2 || padding[0].length !== 2 ||
+        padding[1].length !== 2) {
+        throw new errors_1.ValueError('spatial2dPadding expects `padding` to be an Array of two Arrays, ' +
+            'each of which is an Array of two integers.');
+    }
+    if (dataFormat == null) {
+        dataFormat = common_3.imageDataFormat();
+    }
+    if (dataFormat !== 'channelsLast' && dataFormat !== 'channelsFirst') {
+        throw new errors_1.ValueError("Unknown data format: " + dataFormat + ". " +
+            "Supported data formats are 'channelsLast' and 'channelsFirst.");
+    }
+    var pattern;
+    if (dataFormat === 'channelsFirst') {
+        pattern = [[0, 0], [0, 0], padding[0], padding[1]];
+    }
+    else {
+        pattern = [[0, 0], padding[0], padding[1], [0, 0]];
+    }
+    return tfc.pad(x, pattern);
+}
+exports.spatial2dPadding = spatial2dPadding;
 function repeat(x, n) {
@@ -127,0 +173,0 @@ if (x.shape.length !== 2) {

dist/engine/topology.d.ts

@@ -87,2 +87,3 @@ import { Scalar, Tensor } from '@tensorflow/tfjs-core';
     private _callHook;
+    private _addedWeightNames;
     readonly id: number;
@@ -89,0 +90,0 @@ protected _stateful: boolean;

dist/exports.d.ts

@@ -12,2 +12,3 @@ import { Constraint, MaxNormConfig, MinMaxNormConfig, UnitNormConfig } from './constraints';
 import { BatchNormalizationLayerConfig } from './layers/normalization';
+import { ZeroPadding2DLayerConfig } from './layers/padding';
 import { GlobalPooling2DLayerConfig, Pooling1DLayerConfig, Pooling2DLayerConfig } from './layers/pooling';
@@ -51,2 +52,3 @@ import { GRUCellLayerConfig, GRULayerConfig, LSTMCellLayerConfig, LSTMLayerConfig, RNNCell, RNNLayerConfig, SimpleRNNCellLayerConfig, SimpleRNNLayerConfig, StackedRNNCellsConfig } from './layers/recurrent';
     static batchNormalization(config: BatchNormalizationLayerConfig): Layer;
+    static zeroPadding2d(config: ZeroPadding2DLayerConfig): Layer;
     static avgPooling1d(config: Pooling1DLayerConfig): Layer;
@@ -53,0 +55,0 @@ static avgPooling2d(config: Pooling2DLayerConfig): Layer;

dist/exports.js

@@ -21,2 +21,3 @@ "use strict";
 var normalization_1 = require("./layers/normalization");
+var padding_1 = require("./layers/padding");
 var pooling_1 = require("./layers/pooling");
@@ -135,2 +136,5 @@ var recurrent_1 = require("./layers/recurrent");
     };
+    LayerExports.zeroPadding2d = function (config) {
+        return new padding_1.ZeroPadding2D(config);
+    };
     LayerExports.avgPooling1d = function (config) {
@@ -394,2 +398,11 @@ return new pooling_1.AvgPooling1D(config);
             heading: 'Layers',
+            subheading: 'Padding',
+            namespace: 'layers',
+            useDocsFrom: 'ZeroPadding2D',
+            configParamIndices: [0]
+        })
+    ], LayerExports, "zeroPadding2d", null);
+    __decorate([
+        tfjs_core_1.doc({
+            heading: 'Layers',
             subheading: 'Pooling',
@@ -396,0 +409,0 @@ namespace: 'layers',

dist/layers/convolutional.js

@@ -189,3 +189,3 @@ "use strict";
         if (this.useBias) {
-            this.bias = this.addWeight('kernel', [this.filters], types_1.DType.float32, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);
+            this.bias = this.addWeight('bias', [this.filters], types_1.DType.float32, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);
         }
@@ -192,0 +192,0 @@ this.inputSpec =

dist/utils/serialization_utils.js

@@ -45,3 +45,4 @@ "use strict";
                 var tsKey = generic_utils.toCamelCase(pythonicKey);
-                if (generic_utils.SerializableEnumRegistry.contains(pythonicKey)) {
+                if (generic_utils.SerializableEnumRegistry.contains(pythonicKey) &&
+                    (typeof pythonicValue === 'string' || pythonicValue == null)) {
                     var enumValue = generic_utils.SerializableEnumRegistry.lookup(pythonicKey, pythonicValue);
@@ -99,3 +100,4 @@ if (enumValue != null) {
             else {
-                if (generic_utils.SerializableEnumRegistry.contains(pyKey)) {
+                if (generic_utils.SerializableEnumRegistry.contains(pyKey) &&
+                    (typeof tsValue === 'string' || tsValue == null)) {
                     var enumString = generic_utils.SerializableEnumRegistry.reverseLookup(pyKey, tsValue);
@@ -102,0 +104,0 @@ pyDict[pyKey] = enumString;

dist/version.d.ts

@@ -1,2 +0,2 @@
-declare const version = "0.2.0";
+declare const version = "0.3.0";
 export { version };

dist/version.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-var version = '0.2.0';
+var version = '0.3.0';
 exports.version = version;

package.json

 {
   "name": "@tensorflow/tfjs-layers",
-  "version": "0.2.0",
+  "version": "0.3.0",
   "description": "TensorFlow layers API in JavaScript",
@@ -9,3 +9,3 @@ "private": false,
   "devDependencies": {
-    "@tensorflow/tfjs-core": "0.6.0",
+    "@tensorflow/tfjs-core": "0.6.1",
     "@types/jasmine": "~2.5.53",
@@ -47,4 +47,4 @@ "@types/underscore": "^1.8.7",
   "peerDependencies": {
-    "@tensorflow/tfjs-core": "0.6.0"
+    "@tensorflow/tfjs-core": "0.6.1"
   }
 }

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Improved metrics

Total package byte prevSize

2172262

increased by1.35%

Number of package files

81

increased by2.53%

Lines of code

37479

increased by1.38%

No dependency changes