@tensorflow/tfjs-core - npm Package Compare versions

Comparing version 0.6.0 to 0.6.1

dist/kernels/backend_cpu.d.ts

@@ -52,5 +52,7 @@ import { Conv2DInfo } from '../ops/conv_util';
     maximum(a: Tensor, b: Tensor): Tensor;
+    squaredDifference(a: Tensor, b: Tensor): Tensor;
     ceil<T extends Tensor>(x: T): T;
     floor<T extends Tensor>(x: T): T;
     exp<T extends Tensor>(x: T): T;
+    expm1<T extends Tensor>(x: T): T;
     log<T extends Tensor>(x: T): T;
@@ -77,2 +79,3 @@ log1p<T extends Tensor>(x: T): T;
     atan<T extends Tensor>(x: T): T;
+    atan2<T extends Tensor>(a: T, b: T): T;
     sinh<T extends Tensor>(x: T): T;
@@ -79,0 +82,0 @@ cosh<T extends Tensor>(x: T): T;

dist/kernels/backend_cpu.js

@@ -516,2 +516,8 @@ "use strict";
     };
+    MathBackendCPU.prototype.squaredDifference = function (a, b) {
+        return this.broadcastedBinaryOp(a, b, a.dtype, function (aVal, bVal) {
+            var diff = aVal - bVal;
+            return diff * diff;
+        });
+    };
     MathBackendCPU.prototype.ceil = function (x) {
@@ -541,2 +547,10 @@ var values = x.dataSync();
     };
+    MathBackendCPU.prototype.expm1 = function (x) {
+        var values = x.dataSync();
+        var newValues = new Float32Array(values.length);
+        for (var i = 0; i < values.length; ++i) {
+            newValues[i] = Math.expm1(values[i]);
+        }
+        return tensor_1.Tensor.make(x.shape, { values: newValues });
+    };
     MathBackendCPU.prototype.log = function (x) {
@@ -764,2 +778,5 @@ var values = x.dataSync();
     };
+    MathBackendCPU.prototype.atan2 = function (a, b) {
+        return this.broadcastedBinaryOp(a, b, a.dtype, function (aValue, bValue) { return Math.atan2(aValue, bValue); });
+    };
     MathBackendCPU.prototype.sinh = function (x) {
@@ -766,0 +783,0 @@ var resultValues = new Float32Array(x.size);

dist/kernels/backend_webgl.d.ts

@@ -81,2 +81,3 @@ import { TimingInfo } from '../engine';
     maximum(a: Tensor, b: Tensor): Tensor;
+    squaredDifference(a: Tensor, b: Tensor): Tensor;
     divide(a: Tensor, b: Tensor): Tensor;
@@ -89,2 +90,3 @@ add(a: Tensor, b: Tensor): Tensor;
     exp<T extends Tensor>(x: T): T;
+    expm1<T extends Tensor>(x: T): T;
     log<T extends Tensor>(x: T): T;
@@ -111,2 +113,3 @@ log1p<T extends Tensor>(x: T): T;
     atan<T extends Tensor>(x: T): T;
+    atan2<T extends Tensor>(a: T, b: T): T;
     sinh<T extends Tensor>(x: T): T;
@@ -113,0 +116,0 @@ cosh<T extends Tensor>(x: T): T;

dist/kernels/backend_webgl.js

@@ -502,2 +502,6 @@ "use strict";
     };
+    MathBackendWebGL.prototype.squaredDifference = function (a, b) {
+        var program = new binaryop_gpu_1.BinaryOpProgram(binaryop_gpu.SQUARED_DIFFERENCE, a.shape, b.shape);
+        return this.compileAndRun(program, [a, b]);
+    };
     MathBackendWebGL.prototype.divide = function (a, b) {
@@ -535,2 +539,6 @@ var program = new binaryop_gpu_1.BinaryOpProgram(binaryop_gpu.DIV, a.shape, b.shape);
     };
+    MathBackendWebGL.prototype.expm1 = function (x) {
+        var program = new unaryop_gpu_1.UnaryOpProgram(x.shape, unary_op.EXPM1);
+        return this.compileAndRun(program, [x]);
+    };
     MathBackendWebGL.prototype.log = function (x) {
@@ -621,2 +629,6 @@ var program = new unaryop_gpu_1.UnaryOpProgram(x.shape, unary_op.LOG);
     };
+    MathBackendWebGL.prototype.atan2 = function (a, b) {
+        var program = new binaryop_gpu_1.BinaryOpProgram(binaryop_gpu.ATAN2, a.shape, b.shape);
+        return this.compileAndRun(program, [a, b]);
+    };
     MathBackendWebGL.prototype.sinh = function (x) {
@@ -623,0 +635,0 @@ var program = new unaryop_gpu_1.UnaryOpProgram(x.shape, unary_op.SINH);

dist/kernels/backend.d.ts

@@ -51,2 +51,3 @@ import { Conv2DInfo } from '../ops/conv_util';
     maximum(a: Tensor, b: Tensor): Tensor;
+    squaredDifference(a: Tensor, b: Tensor): Tensor;
     ceil<T extends Tensor>(x: T): T;
@@ -56,2 +57,3 @@ floor<T extends Tensor>(x: T): T;
     exp<T extends Tensor>(x: T): T;
+    expm1<T extends Tensor>(x: T): T;
     log<T extends Tensor>(x: T): T;
@@ -78,2 +80,3 @@ log1p<T extends Tensor>(x: T): T;
     atan<T extends Tensor>(x: T): T;
+    atan2<T extends Tensor>(a: T, b: T): T;
     sinh<T extends Tensor>(x: T): T;
@@ -80,0 +83,0 @@ cosh<T extends Tensor>(x: T): T;

dist/kernels/webgl/binaryop_gpu.d.ts

@@ -7,2 +7,3 @@ import { GPGPUProgram } from './gpgpu_math';
 export declare const POW = "\n  return (round(mod(b, 2.0)) == 0 || round(mod(b, 2.0)) == 2) ?\n      pow(abs(a), b) : sign(a) * pow(abs(a), b);\n";
+export declare const SQUARED_DIFFERENCE = "return (a - b) * (a - b);";
 export declare const EQUAL: string;
@@ -21,2 +22,3 @@ export declare const NOT_EQUAL: string;
 export declare const MIN: string;
+export declare const ATAN2: string;
 export declare class BinaryOpProgram implements GPGPUProgram {
@@ -23,0 +25,0 @@ variableNames: string[];

dist/kernels/webgl/binaryop_gpu.js

@@ -10,2 +10,3 @@ "use strict";
 exports.POW = "\n  return (round(mod(b, 2.0)) == 0 || round(mod(b, 2.0)) == 2) ?\n      pow(abs(a), b) : sign(a) * pow(abs(a), b);\n";
+exports.SQUARED_DIFFERENCE = 'return (a - b) * (a - b);';
 exports.EQUAL = CHECK_NAN_SNIPPET + "\n  return float(a == b);\n";
@@ -24,2 +25,3 @@ exports.NOT_EQUAL = CHECK_NAN_SNIPPET + "\n  return float(a != b);\n";
 exports.MIN = CHECK_NAN_SNIPPET + "\n  return min(a, b);\n";
+exports.ATAN2 = CHECK_NAN_SNIPPET + "\n  return atan(a, b);\n";
 var BinaryOpProgram = (function () {
@@ -26,0 +28,0 @@ function BinaryOpProgram(op, aShape, bShape) {

dist/kernels/webgl/shader_compiler.js

@@ -79,5 +79,5 @@ "use strict";
 var SAMPLE_4D_SNIPPET = "\nvec2 UVfrom4D(int texNumR, int texNumC, int stride0,\n    int stride1, int stride2, int row, int col, int depth,\n    int depth2) {\n  // Explicitly use integer operations as dot() only works on floats.\n  int index = row * stride0 + col * stride1 + depth * stride2 + depth2;\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n";
-var UNSIGNED_BYTE_TEXTURE_SAMPLE_SNIPPET = "\n  uniform float NaN;\n\n  const vec4 floatDeltas = vec4(\n      1.0,\n      1.0 / 255.0,\n      1.0 / (255.0 * 255.0),\n      1.0 / (255.0 * 255.0 * 255.0)\n  );\n  const float minValue = " + tex_util.FLOAT_MIN + ".0;\n  const float maxValue = " + tex_util.FLOAT_MAX + ".0;\n  const float range = (maxValue - minValue) / 255.0;\n  const vec2 dotRange = vec2(1.0, range);\n\n  float sample(sampler2D texture, vec2 uv) {\n    vec4 sampleValue = texture2D(texture, uv);\n    if (all(equal(sampleValue, vec4(" + tex_util.BYTE_NAN_VALUE + ")))) {\n      return NaN;\n    }\n\n    vec4 encValue = floor(sampleValue * 255.0 + 0.5);\n    float decodedValue = dot(encValue, floatDeltas);\n    return dot(vec2(minValue, decodedValue), dotRange);\n  }\n";
+var UNSIGNED_BYTE_TEXTURE_SAMPLE_SNIPPET = "\n  uniform float NaN;\n\n  const vec4 floatDeltas = vec4(\n      1.0,\n      1.0 / 255.0,\n      1.0 / (255.0 * 255.0),\n      1.0 / (255.0 * 255.0 * 255.0)\n  );\n  const float minValue = " + tex_util.FLOAT_MIN + ".0;\n  const float maxValue = " + tex_util.FLOAT_MAX + ".0;\n  const float range = (maxValue - minValue) / 255.0;\n  const vec2 dotRange = vec2(1.0, range);\n\n  float sampleTexture(sampler2D textureSampler, vec2 uv) {\n    vec4 sampleValue = texture2D(textureSampler, uv);\n    if (all(equal(sampleValue, vec4(" + tex_util.BYTE_NAN_VALUE + ")))) {\n      return NaN;\n    }\n\n    vec4 encValue = floor(sampleValue * 255.0 + 0.5);\n    float decodedValue = dot(encValue, floatDeltas);\n    return dot(vec2(minValue, decodedValue), dotRange);\n  }\n";
 var UNSIGNED_BYTE_TEXTURE_SETOUTPUT_SNIPPET = "\n  const vec4 floatPowers = vec4(\n    1.0,\n    255.0,\n    255.0 * 255.0,\n    255.0 * 255.0 * 255.0\n  );\n  const vec2 recipRange = vec2(1.0/range);\n  const vec2 recipRange255 = vec2(1.0/(maxValue - minValue));\n\n  void setOutput(float decodedValue) {\n    if (isNaN(decodedValue)) {\n      gl_FragColor = vec4(" + tex_util.BYTE_NAN_VALUE + ");\n      return;\n    }\n\n    float a = dot(vec2(decodedValue, -minValue), recipRange);\n    float b = fract(a) * 255.0;\n    float c = fract(b) * 255.0;\n    float d = fract(c) * 255.0;\n    gl_FragColor = floor(vec4(a, b, c, d)) / 255.0;\n\n    // TODO(dsmilkov): Version above gets better accuracy but probably slower\n    // than the version below. Benchmark to determine if the accuracy is worth\n    // the cost.\n\n    // float normValue = dot(vec2(decodedValue, -minValue), recipRange255);\n    // vec4 f = normValue * floatPowers;\n    // gl_FragColor = floor(fract(f) * 255.0) / 255.0;\n  }\n";
-var FLOAT_TEXTURE_SAMPLE_SNIPPET = "\n  float sample(sampler2D texture, vec2 uv) {\n    return texture2D(texture, uv).r;\n  }\n";
+var FLOAT_TEXTURE_SAMPLE_SNIPPET = "\n  float sampleTexture(sampler2D textureSampler, vec2 uv) {\n    return texture2D(textureSampler, uv).r;\n  }\n";
 var FLOAT_TEXTURE_SETOUTPUT_SNIPPET = "\n  void setOutput(float val) {\n    gl_FragColor = vec4(val, 0, 0, 0);\n  }\n";
@@ -123,3 +123,3 @@ var SHADER_PREFIX = "\n  precision highp float;\n  precision highp int;\n  varying vec2 resultUV;\n  const vec2 halfCR = vec2(0.5, 0.5);\n\n  bool isNaN(float val) {\n    float v1 = val * val;\n    float v2 = val * val;\n    return v1 == v2 ? false : true;\n  }\n\n  bool hasNaN(vec4 values) {\n    vec4 v1 = values * values;\n    vec4 v2 = values * values;\n    return any(notEqual(v1, v2));\n  }\n\n  float getNaN(vec4 values) {\n    return dot(vec4(1), values);\n  }\n\n  int round(float value) {\n    return int(floor(value + 0.5));\n  }\n\n  int imod(int x, int y) {\n    return x - y * (x / y);\n  }\n\n  const vec2 randomConst = vec2(\n    23.14069263277926, // e^pi (Gelfond's constant)\n     2.665144142690225 // 2^sqrt(2) (Gelfond\u2013Schneider constant)\n  );\n\n  float random(float seed) {\n      return fract(cos(dot(resultUV * seed, randomConst)) * 12345.6789);\n  }\n\n  " + SAMPLE_1D_SNIPPET + "\n  " + SAMPLE_2D_SNIPPET + "\n  " + SAMPLE_3D_SNIPPET + "\n  " + SAMPLE_4D_SNIPPET + "\n";
     var funcName = 'get' + texName.charAt(0).toUpperCase() + texName.slice(1);
-    return "\n    float " + funcName + "() {\n      return sample(" + texName + ", halfCR);\n    }\n  ";
+    return "\n    float " + funcName + "() {\n      return sampleTexture(" + texName + ", halfCR);\n    }\n  ";
 }
@@ -139,3 +139,3 @@ function getSampler1D(inputInfo) {
     if (util.arraysEqual(shape, texShape)) {
-        return "\n    float " + funcName + "(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2(" + texNumC + ".0, " + texNumR + ".0);\n      return sample(" + texName + ", uv);\n    }\n  ";
+        return "\n    float " + funcName + "(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2(" + texNumC + ".0, " + texNumR + ".0);\n      return sampleTexture(" + texName + ", uv);\n    }\n  ";
     }
@@ -150,8 +150,8 @@ var _a = util.squeezeShape(shape), newShape = _a.newShape, keptDims = _a.keptDims;
     if (texNumC === 1) {
-        return "\n    float " + funcName + "(int row, int col) {\n      int index = row * " + shape[1] + " + col;\n      vec2 uv = vec2(0.5, (float(index) + 0.5) / " + texNumR + ".0);\n      return sample(" + texName + ", uv);\n    }\n  ";
+        return "\n    float " + funcName + "(int row, int col) {\n      int index = row * " + shape[1] + " + col;\n      vec2 uv = vec2(0.5, (float(index) + 0.5) / " + texNumR + ".0);\n      return sampleTexture(" + texName + ", uv);\n    }\n  ";
     }
     if (texNumR === 1) {
-        return "\n    float " + funcName + "(int row, int col) {\n      int index = row * " + shape[1] + " + col;\n      vec2 uv = vec2((float(index) + 0.5) / " + texNumC + ".0, 0.5);\n      return sample(" + texName + ", uv);\n    }\n  ";
+        return "\n    float " + funcName + "(int row, int col) {\n      int index = row * " + shape[1] + " + col;\n      vec2 uv = vec2((float(index) + 0.5) / " + texNumC + ".0, 0.5);\n      return sampleTexture(" + texName + ", uv);\n    }\n  ";
     }
-    return "\n  float " + funcName + "(int row, int col) {\n    vec2 uv = UVfrom2D(" + texNumR + ", " + texNumC + ", " + shape[1] + ", row, col);\n    return sample(" + texName + ", uv);\n  }\n";
+    return "\n  float " + funcName + "(int row, int col) {\n    vec2 uv = UVfrom2D(" + texNumR + ", " + texNumC + ", " + shape[1] + ", row, col);\n    return sampleTexture(" + texName + ", uv);\n  }\n";
 }
@@ -175,8 +175,8 @@ function getSampler3D(inputInfo) {
     if (texNumC === stride0) {
-        return "\n        float " + funcName + "(int row, int col, int depth) {\n          int texR = row;\n          int texC = col * " + stride1 + " + depth;\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2(" + texNumC + ".0, " + texNumR + ".0);\n          return sample(" + texName + ", uv);\n        }\n      ";
+        return "\n        float " + funcName + "(int row, int col, int depth) {\n          int texR = row;\n          int texC = col * " + stride1 + " + depth;\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2(" + texNumC + ".0, " + texNumR + ".0);\n          return sampleTexture(" + texName + ", uv);\n        }\n      ";
     }
     if (texNumC === stride1) {
-        return "\n    float " + funcName + "(int row, int col, int depth) {\n      int texR = row * " + shape[1] + " + col;\n      int texC = depth;\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(" + texNumC + ".0, " + texNumR + ".0);\n      return sample(" + texName + ", uv);\n    }\n  ";
+        return "\n    float " + funcName + "(int row, int col, int depth) {\n      int texR = row * " + shape[1] + " + col;\n      int texC = depth;\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(" + texNumC + ".0, " + texNumR + ".0);\n      return sampleTexture(" + texName + ", uv);\n    }\n  ";
     }
-    return "\n      float " + funcName + "(int row, int col, int depth) {\n        vec2 uv = UVfrom3D(\n            " + texNumR + ", " + texNumC + ", " + stride0 + ", " + stride1 + ", row, col, depth);\n        return sample(" + texName + ", uv);\n      }\n  ";
+    return "\n      float " + funcName + "(int row, int col, int depth) {\n        vec2 uv = UVfrom3D(\n            " + texNumR + ", " + texNumC + ", " + stride0 + ", " + stride1 + ", row, col, depth);\n        return sampleTexture(" + texName + ", uv);\n      }\n  ";
 }
@@ -200,8 +200,8 @@ function getSampler4D(inputInfo) {
     if (texNumC === stride0) {
-        return "\n      float " + funcName + "(int row, int col, int depth, int depth2) {\n        int texR = row;\n        int texC = col * " + stride1 + " + depth * " + stride2 + " + depth2;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(" + texNumC + ".0, " + texNumR + ".0);\n        return sample(" + texName + ", uv);\n      }\n    ";
+        return "\n      float " + funcName + "(int row, int col, int depth, int depth2) {\n        int texR = row;\n        int texC = col * " + stride1 + " + depth * " + stride2 + " + depth2;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(" + texNumC + ".0, " + texNumR + ".0);\n        return sampleTexture(" + texName + ", uv);\n      }\n    ";
     }
     if (texNumC === stride2) {
-        return "\n      float " + funcName + "(int row, int col, int depth, int depth2) {\n        int texR = row * " + shape[1] * shape[2] + " + col * " + shape[2] + " + depth;\n        int texC = depth2;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(" + texNumC + ".0, " + texNumR + ".0);\n        return sample(" + texName + ", uv);\n      }\n    ";
+        return "\n      float " + funcName + "(int row, int col, int depth, int depth2) {\n        int texR = row * " + shape[1] * shape[2] + " + col * " + shape[2] + " + depth;\n        int texC = depth2;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(" + texNumC + ".0, " + texNumR + ".0);\n        return sampleTexture(" + texName + ", uv);\n      }\n    ";
     }
-    return "\n    float " + funcName + "(int row, int col, int depth, int depth2) {\n      vec2 uv = UVfrom4D(" + texNumR + ", " + texNumC + ", " + stride0 + ", " + stride1 + ",\n          " + stride2 + ", row, col, depth, depth2);\n      return sample(" + texName + ", uv);\n    }\n  ";
+    return "\n    float " + funcName + "(int row, int col, int depth, int depth2) {\n      vec2 uv = UVfrom4D(" + texNumR + ", " + texNumC + ", " + stride0 + ", " + stride1 + ",\n          " + stride2 + ", row, col, depth, depth2);\n      return sampleTexture(" + texName + ", uv);\n    }\n  ";
 }
@@ -215,11 +215,11 @@ function getSamplerFlat(inputInfo) {
     if (tNumC === 1 && tNumR === 1) {
-        return "\n      float " + funcName + "(int index) {\n        return sample(" + texName + ", halfCR);\n      }\n    ";
+        return "\n      float " + funcName + "(int index) {\n        return sampleTexture(" + texName + ", halfCR);\n      }\n    ";
     }
     if (tNumC === 1) {
-        return "\n      float " + funcName + "(int index) {\n        vec2 uv = vec2(0.5, (float(index) + 0.5) / " + tNumR + ".0);\n        return sample(" + texName + ", uv);\n      }\n    ";
+        return "\n      float " + funcName + "(int index) {\n        vec2 uv = vec2(0.5, (float(index) + 0.5) / " + tNumR + ".0);\n        return sampleTexture(" + texName + ", uv);\n      }\n    ";
     }
     if (tNumR === 1) {
-        return "\n      float " + funcName + "(int index) {\n        vec2 uv = vec2((float(index) + 0.5) / " + tNumC + ".0, 0.5);\n        return sample(" + texName + ", uv);\n      }\n    ";
+        return "\n      float " + funcName + "(int index) {\n        vec2 uv = vec2((float(index) + 0.5) / " + tNumC + ".0, 0.5);\n        return sampleTexture(" + texName + ", uv);\n      }\n    ";
     }
-    return "\n    float " + funcName + "(int index) {\n      vec2 uv = UVfrom1D(" + tNumR + ", " + tNumC + ", index);\n      return sample(" + texName + ", uv);\n    }\n  ";
+    return "\n    float " + funcName + "(int index) {\n      vec2 uv = UVfrom1D(" + tNumR + ", " + tNumC + ", index);\n      return sampleTexture(" + texName + ", uv);\n    }\n  ";
 }
@@ -278,3 +278,3 @@ function getBroadcastOutputCoordsSampler(inputInfo, outShapeInfo, texFuncSnippet, funcName) {
     if (util.arraysEqual(inTexShape, outTexShape)) {
-        return "\n      float " + funcName + "() {\n        return sample(" + texName + ", resultUV);\n      }\n    ";
+        return "\n      float " + funcName + "() {\n        return sampleTexture(" + texName + ", resultUV);\n      }\n    ";
     }
@@ -286,3 +286,3 @@ var inSize = util.sizeFromShape(inTexShape);
     }
-    return "\n    float " + funcName + "() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + outTexShape[0] + ", " + outTexShape[1] + "));\n      int index = resTexRC.x * " + outTexShape[1] + " + resTexRC.y;\n      " + broadcastSnippet + "\n      int texR = index / " + inTexShape[1] + ";\n      int texC = index - texR * " + inTexShape[1] + ";\n      vec2 uv = (vec2(texC, texR) + halfCR) /\n                 vec2(" + inTexShape[1] + ".0, " + inTexShape[0] + ".0);\n\n      return sample(" + texName + ", uv);\n    }\n  ";
+    return "\n    float " + funcName + "() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(" + outTexShape[0] + ", " + outTexShape[1] + "));\n      int index = resTexRC.x * " + outTexShape[1] + " + resTexRC.y;\n      " + broadcastSnippet + "\n      int texR = index / " + inTexShape[1] + ";\n      int texC = index - texR * " + inTexShape[1] + ";\n      vec2 uv = (vec2(texC, texR) + halfCR) /\n                 vec2(" + inTexShape[1] + ".0, " + inTexShape[0] + ".0);\n\n      return sampleTexture(" + texName + ", uv);\n    }\n  ";
 }
@@ -289,0 +289,0 @@ function getCoordsDataType(rank) {

dist/kernels/webgl/unaryop_gpu.d.ts

@@ -19,2 +19,3 @@ import { GPGPUProgram } from './gpgpu_math';
 export declare const EXP = "\n  return exp(x);\n";
+export declare const EXPM1 = "\n  return exp(x) - 1.0;\n";
 export declare const LOG = "\n  return log(x);\n";
@@ -21,0 +22,0 @@ export declare const LOG1P = "\n  return log(1.0 + x);\n";

dist/kernels/webgl/unaryop_gpu.js

@@ -32,2 +32,3 @@ "use strict";
 exports.EXP = "\n  return exp(x);\n";
+exports.EXPM1 = "\n  return exp(x) - 1.0;\n";
 exports.LOG = "\n  return log(x);\n";
@@ -34,0 +35,0 @@ exports.LOG1P = "\n  return log(1.0 + x);\n";

dist/ops/binary_ops.d.ts

@@ -17,2 +17,5 @@ import { Tensor } from '../tensor';
     static maximumStrict<T extends Tensor>(a: T, b: T): T;
+    static squaredDifference<T extends Tensor>(a: Tensor, b: Tensor): T;
+    static squaredDifferenceStrict<T extends Tensor>(a: T, b: T): T;
+    static atan2<T extends Tensor>(a: Tensor, b: Tensor): T;
 }

dist/ops/binary_ops.js

@@ -123,2 +123,3 @@ "use strict";
     BinaryOps.div = function (a, b) {
+        util.assertTypesMatch(a, b);
         var outShape = broadcast_util.assertAndGetBroadcastShape(a.shape, b.shape);
@@ -179,2 +180,43 @@ var der = function (dy) {
     };
+    BinaryOps.squaredDifference = function (a, b) {
+        util.assertTypesMatch(a, b);
+        broadcast_util.assertAndGetBroadcastShape(a.shape, b.shape);
+        var der = function (dy) {
+            var two = ops_1.scalar(2);
+            var derA = function () { return dy.mul(a.sub(b).mul(two)); };
+            var derB = function () { return dy.mul(b.sub(a).mul(two)); };
+            return { a: derA, b: derB };
+        };
+        return environment_1.ENV.engine.runKernel(function (backend) { return backend.squaredDifference(a, b); }, { a: a, b: b }, der);
+    };
+    BinaryOps.squaredDifferenceStrict = function (a, b) {
+        util.assertShapesMatch(a.shape, b.shape, 'Error in squaredDifferenceStrict: ');
+        return a.squaredDifference(b);
+    };
+    BinaryOps.atan2 = function (a, b) {
+        util.assertTypesMatch(a, b);
+        var outShape = broadcast_util.assertAndGetBroadcastShape(a.shape, b.shape);
+        var der = function (dy) {
+            var derA = function () {
+                var d = BinaryOps.add(ops_1.square(a), ops_1.square(b));
+                var res = dy.mul(b.div(d));
+                var reduceAxes = broadcast_util.getReductionAxes(a.shape, outShape);
+                if (reduceAxes.length > 0) {
+                    res = res.sum(reduceAxes);
+                }
+                return res.reshape(a.shape);
+            };
+            var derB = function () {
+                var d = BinaryOps.add(ops_1.square(a), ops_1.square(b));
+                var res = ops_1.neg(dy.mul(a.div(d)));
+                var reduceAxes = broadcast_util.getReductionAxes(b.shape, outShape);
+                if (reduceAxes.length > 0) {
+                    res = res.sum(reduceAxes);
+                }
+                return res.reshape(b.shape);
+            };
+            return { a: derA, b: derB };
+        };
+        return environment_1.ENV.engine.runKernel(function (backend) { return backend.atan2(a, b); }, { a: a, b: b }, der);
+    };
     __decorate([
@@ -229,4 +271,14 @@ doc_1.doc({ heading: 'Operations', subheading: 'Arithmetic' }),
     ], BinaryOps, "maximumStrict", null);
+    __decorate([
+        doc_1.doc({ heading: 'Operations', subheading: 'Arithmetic' }),
+        operation_1.operation
+    ], BinaryOps, "squaredDifference", null);
+    __decorate([
+        operation_1.operation
+    ], BinaryOps, "squaredDifferenceStrict", null);
+    __decorate([
+        operation_1.operation
+    ], BinaryOps, "atan2", null);
     return BinaryOps;
 }());
 exports.BinaryOps = BinaryOps;

dist/ops/ops.d.ts

@@ -86,2 +86,3 @@ import { ArrayOps } from './array_ops';
 export declare const exp: typeof UnaryOps.exp;
+export declare const expm1: typeof UnaryOps.expm1;
 export declare const floor: typeof UnaryOps.floor;
@@ -104,2 +105,3 @@ export declare const leakyRelu: typeof UnaryOps.leakyRelu;
 export declare const add: typeof BinaryOps.add;
+export declare const atan2: typeof BinaryOps.atan2;
 export declare const addStrict: typeof BinaryOps.addStrict;
@@ -118,2 +120,4 @@ export declare const div: typeof BinaryOps.div;
 export declare const subStrict: typeof BinaryOps.subStrict;
+export declare const squaredDifference: typeof BinaryOps.squaredDifference;
+export declare const squaredDifferenceStrict: typeof BinaryOps.squaredDifferenceStrict;
 export declare const norm: typeof NormOps.norm;
@@ -120,0 +124,0 @@ export declare const cast: typeof ArrayOps.cast;

dist/ops/ops.js

@@ -88,2 +88,3 @@ "use strict";
 exports.exp = unary_ops_1.UnaryOps.exp;
+exports.expm1 = unary_ops_1.UnaryOps.expm1;
 exports.floor = unary_ops_1.UnaryOps.floor;
@@ -106,2 +107,3 @@ exports.leakyRelu = unary_ops_1.UnaryOps.leakyRelu;
 exports.add = binary_ops_1.BinaryOps.add;
+exports.atan2 = binary_ops_1.BinaryOps.atan2;
 exports.addStrict = binary_ops_1.BinaryOps.addStrict;
@@ -120,2 +122,4 @@ exports.div = binary_ops_1.BinaryOps.div;
 exports.subStrict = binary_ops_1.BinaryOps.subStrict;
+exports.squaredDifference = binary_ops_1.BinaryOps.squaredDifference;
+exports.squaredDifferenceStrict = binary_ops_1.BinaryOps.squaredDifferenceStrict;
 exports.norm = norm_1.NormOps.norm;
@@ -122,0 +126,0 @@ exports.cast = array_ops_1.ArrayOps.cast;

dist/ops/reduction_ops.js

@@ -75,3 +75,6 @@ "use strict";
             var reduceSizeScalar = ops.scalar(reduceSize);
-            var res = x.div(reduceSizeScalar);
+            var xReduce = reduceSizeScalar.dtype === x.dtype ?
+                x :
+                x.cast(reduceSizeScalar.dtype);
+            var res = xReduce.div(reduceSizeScalar);
             var value = res.sum(axis, keepDims);
@@ -78,0 +81,0 @@ var gradFunc = function (dy) {

dist/ops/unary_ops.d.ts

@@ -7,2 +7,3 @@ import { Tensor } from '../tensor';
     static exp<T extends Tensor>(x: T): T;
+    static expm1<T extends Tensor>(x: T): T;
     static log<T extends Tensor>(x: T): T;
@@ -9,0 +10,0 @@ static log1p<T extends Tensor>(x: T): T;

dist/ops/unary_ops.js

@@ -44,2 +44,8 @@ "use strict";
     };
+    UnaryOps.expm1 = function (x) {
+        var grad = function (dy) {
+            return { x: function () { return dy.mulStrict(x.exp()); } };
+        };
+        return environment_1.ENV.engine.runKernel(function (backend) { return backend.expm1(x); }, { x: x }, grad);
+    };
     UnaryOps.log = function (x) {
@@ -224,2 +230,6 @@ var grad = function (dy) {
         operation_1.operation
+    ], UnaryOps, "expm1", null);
+    __decorate([
+        doc_1.doc({ heading: 'Operations', subheading: 'Basic math' }),
+        operation_1.operation
     ], UnaryOps, "log", null);
@@ -226,0 +236,0 @@ __decorate([

dist/tensor.d.ts

@@ -74,2 +74,3 @@ import { DataType, Rank, ShapeMap, TypedArray } from './types';
     argMax<T extends Tensor>(axis?: number): T;
+    cast<T extends this>(dtype: DataType): T;
     add<T extends Tensor>(x: Tensor): T;
@@ -89,2 +90,4 @@ addStrict<T extends this>(this: T, x: T): T;
     maximumStrict<T extends this>(this: T, x: T): T;
+    squaredDifference<T extends Tensor>(x: Tensor): T;
+    squaredDifferenceStrict<T extends this>(this: T, x: T): T;
     transpose<T extends Tensor>(this: T, perm?: number[]): T;
@@ -111,2 +114,3 @@ notEqual<T extends Tensor>(x: Tensor): T;
     exp<T extends Tensor>(this: T): T;
+    expm1<T extends Tensor>(this: T): T;
     log<T extends Tensor>(this: T): T;
@@ -113,0 +117,0 @@ log1p<T extends Tensor>(this: T): T;

dist/tensor.js

@@ -380,2 +380,6 @@ "use strict";
     };
+    Tensor.prototype.cast = function (dtype) {
+        this.throwIfDisposed();
+        return ops.cast(this, dtype);
+    };
     Tensor.prototype.add = function (x) {
@@ -437,2 +441,10 @@ this.throwIfDisposed();
     };
+    Tensor.prototype.squaredDifference = function (x) {
+        this.throwIfDisposed();
+        return ops.squaredDifference(this, x);
+    };
+    Tensor.prototype.squaredDifferenceStrict = function (x) {
+        this.throwIfDisposed();
+        return ops.squaredDifferenceStrict(this, x);
+    };
     Tensor.prototype.transpose = function (perm) {
@@ -522,2 +534,6 @@ this.throwIfDisposed();
     };
+    Tensor.prototype.expm1 = function () {
+        this.throwIfDisposed();
+        return ops.expm1(this);
+    };
     Tensor.prototype.log = function () {
@@ -524,0 +540,0 @@ this.throwIfDisposed();

dist/test_util.js

@@ -110,6 +110,8 @@ "use strict";
     describe(testName, function () {
-        beforeEach(function () {
+        beforeAll(function () {
             environment_1.ENV.setFeatures(features || {});
             environment_1.ENV.addCustomBackend('webgl', function () { return new backend_webgl_1.MathBackendWebGL(); });
             environment_1.ENV.addCustomBackend('cpu', function () { return new backend_cpu_1.MathBackendCPU(); });
+        });
+        beforeEach(function () {
             if (features && features.BACKEND != null) {
@@ -122,2 +124,4 @@ environment_1.Environment.setBackend(features.BACKEND);
             environment_1.ENV.engine.endScope(null);
+        });
+        afterAll(function () {
             environment_1.ENV.reset();
@@ -124,0 +128,0 @@ });

dist/version.d.ts

@@ -1,2 +0,2 @@
-declare const version = "0.6.0";
+declare const version = "0.6.1";
 export { version };

dist/version.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-var version = '0.6.0';
+var version = '0.6.1';
 exports.version = version;

dist/weights_loader.d.ts

@@ -12,2 +12,2 @@ import { NamedTensorMap } from './types';
 }
-export declare function loadWeights(manifest: WeightsManifestConfig, filePathPrefix?: string, weightNames?: string[]): Promise<NamedTensorMap>;
+export declare function loadWeights(manifest: WeightsManifestConfig, filePathPrefix?: string, weightNames?: string[], requestOptions?: RequestInit): Promise<NamedTensorMap>;

dist/weights_loader.js

@@ -44,3 +44,3 @@ "use strict";
 };
-function loadWeights(manifest, filePathPrefix, weightNames) {
+function loadWeights(manifest, filePathPrefix, weightNames, requestOptions) {
     if (filePathPrefix === void 0) { filePathPrefix = ''; }
@@ -105,3 +105,3 @@ return __awaiter(this, void 0, void 0, function () {
                                 (!filePathPrefix.endsWith('/') ? '/' : '') + filepath;
-                            requests.push(fetch(fetchUrl));
+                            requests.push(fetch(fetchUrl, requestOptions));
                         });
@@ -108,0 +108,0 @@ });

package.json

 {
   "name": "@tensorflow/tfjs-core",
-  "version": "0.6.0",
+  "version": "0.6.1",
   "description": "Hardware-accelerated JavaScript library for machine intelligence",
@@ -12,3 +12,3 @@ "private": false,
     "type": "git",
-    "url": "https://github.com/PAIR-code/deeplearnjs.git"
+    "url": "https://github.com/tensorflow/tfjs-core.git"
   },
@@ -15,0 +15,0 @@ "license": "Apache-2.0",

README.md

@@ -1,173 +0,50 @@
-<a id="travis-badge" href="https://travis-ci.org/PAIR-code/deeplearnjs" alt="Build Status">
-  <img src="https://travis-ci.org/PAIR-code/deeplearnjs.svg?branch=master" />
+<a id="travis-badge" href="https://travis-ci.org/tensorflow/tfjs-core" alt="Build Status">
+  <img src="https://travis-ci.org/tensorflow/tfjs-core.svg?branch=master" />
 </a>
 
-# Getting started
+# TensorFlow.js Core API
 
-**deeplearn.js** is an open source hardware-accelerated JavaScript library for
-machine intelligence. **deeplearn.js** brings performant machine learning
-building blocks to the web, allowing you to train neural networks in a browser
-or run pre-trained models in inference mode.
+> NOTE: Building on the momentum of deeplearn.js, we have joined the TensorFlow
+family and we are starting a new ecosystem of libraries and tools for Machine
+Learning in Javascript, called [TensorFlow.js](https://js.tensorflow.org).
+This repo moved from `PAIR-code/deeplearnjs` to `tensorflow/tfjs-core`.
 
-We provide an API that closely mirrors the TensorFlow eager API.
-**deeplearn.js** was originally developed by the Google Brain PAIR team to build
-powerful interactive machine learning tools for the browser, but it can be used
-for everything from education, to model understanding, to art projects.
+A part of the TensorFlow.js ecosystem, this repo hosts `@tensorflow/tfjs-core`,
+the TensorFlow.js Core API, which provides low-level, hardware-accelerated
+linear algebra operations and an eager API for automatic differentiation.
 
-## Usage
+Check out [js.tensorflow.org](https://js.tensorflow.org) for more
+information about the library, tutorials and API docs.
 
-You can install this library via yarn/npm: `yarn add deeplearn`
-or `npm install deeplearn`
+To keep track of issues, we use the [tensorflow/tfjs](https://github.com/tensorflow/tfjs) Github repo.
 
-Alternatively you can use a script tag. Here we load it from a CDN.
-In this case it will be available as a global variable named `dl`.
+## Importing
 
-You can replace also specify which version to load replacing `@latest` with a specific
-version string (e.g. `0.5.0`).
+You can install TensorFlow.js via yarn or npm. We recommend using the
+[@tensorflow/tfjs](https://www.npmjs.com/package/@tensorflow/tfjs) npm package,
+which gives you both this Core API and the higher-level
+[Layers API](https://github.com/tensorflow/tfjs-layers):
 
-```html
-<script src="https://cdn.jsdelivr.net/npm/deeplearn@latest"></script>
-<!-- or -->
-<script src="https://unpkg.com/deeplearn@latest"></script>
-```
-
-#### TypeScript / ES6 JavaScript
-
-Let's add a scalar value to a 1D Tensor. Deeplearn js supports _broadcasting_
-the value of scalar over all the elements in the tensor.
-
 ```js
-import * as dl from 'deeplearn'; // If not loading the script as a global
-
-const a = dl.tensor1d([1, 2, 3]);
-const b = dl.scalar(2);
-
-const result = a.add(b); // a is not modified, result is a new tensor
-result.data().then(data => console.log(data)); // Float32Array([3, 4, 5]
-
-// Alternatively you can use a blocking call to get the data.
-// However this might slow your program down if called repeatedly.
-console.log(result.dataSync()); // Float32Array([3, 4, 5]
+import * as tf from '@tensorflow/tfjs';
+// You have the Core API: tf.matMul(), tf.softmax(), ...
+// You also have Layers API: tf.model(), tf.layers.dense(), ...
 ```
 
-See the [TypeScript starter project](https://github.com/PAIR-code/deeplearnjs/tree/master/starter/typescript/) and the
-[ES6 starter project](https://github.com/PAIR-code/deeplearnjs/tree/master/starter/es6/) to get you quickly started.
+On the other hand, if you care about the bundle size and you do not use the
+Layers API, you can import only the Core API:
 
-#### ES5 JavaScript
-
-Let's do the same thing in ES5 Javascript. Remember to include the script tag to
-load deeplearn.js
-
 ```js
-var a = dl.tensor1d([1, 2, 3]);
-var b = dl.scalar(2);
-
-var result = a.add(b); // a is not modified, result is a new tensor
-
-// Option 1: With a Promise.
-result.data().then(data => console.log(data)); // Float32Array([3, 4, 5])
-
-// Option 2: Synchronous download of data. Blocks the UI.
-console.log(result.dataSync());
+import * as tfc from '@tensorflow/tfjs-core';
+// You have the Core API: tfc.matMul(), tfc.softmax(), ...
+// No Layers API.
 ```
 
-## Development
+For info about development, check out [DEVELOPMENT.md](./DEVELOPMENT.md).
 
-To build **deeplearn.js** from source, we need to clone the project and prepare
-the dev environment:
+## For more information
 
-```bash
-$ git clone https://github.com/PAIR-code/deeplearnjs.git
-$ cd deeplearnjs
-$ yarn # Installs dependencies.
-```
+- [TensorFlow.js API documentation](https://js.tensorflow.org/api/latest/)
+- [TensorFlow.js Tutorials](https://js.tensorflow.org/tutorials/)
 
-#### Yarn vs NPM
-Generally speaking it's up to you. Yarn is fully interoperable with npm. You can either do `yarn` or `npm install`. However we use yarn, and if you are adding or removing dependencies you should use yarn to keep the `yarn.lock` file up to date.
-
-#### Code editor
-We recommend using [Visual Studio Code](https://code.visualstudio.com/) for
-development. Make sure to install
-[TSLint VSCode extension](https://marketplace.visualstudio.com/items?itemName=eg2.tslint)
-and the npm [clang-format](https://github.com/angular/clang-format) `1.2.2` or later
-with the
-[Clang-Format VSCode extension](https://marketplace.visualstudio.com/items?itemName=xaver.clang-format)
-for auto-formatting.
-
-#### Interactive development
-To interactively develop any of the demos (e.g. `demos/nn-art/`):
-
-```bash
-$ ./scripts/watch-demo demos/nn-art
->> Starting up http-server, serving ./
->> Available on:
->>   http://127.0.0.1:8080
->> Hit CTRL-C to stop the server
->> 1357589 bytes written to dist/demos/nn-art/bundle.js (0.85 seconds) at 10:34:45 AM
-```
-
-Then visit `http://localhost:8080/demos/nn-art/`. The
-`watch-demo` script monitors for changes of typescript code and does
-incremental compilation (~200-400ms), so users can have a fast edit-refresh
-cycle when developing apps.
-
-#### Testing
-Before submitting a pull request, make sure the code passes all the tests and is clean of lint errors:
-
-```bash
-$ yarn test
-$ yarn lint
-```
-
-To run a subset of tests and/or on a specific browser:
-
-```bash
-$ yarn test --browsers=Chrome --grep='multinomial'
- 
-> ...
-> Chrome 62.0.3202 (Mac OS X 10.12.6): Executed 28 of 1891 (skipped 1863) SUCCESS (6.914 secs / 0.634 secs)
-```
-
-To run the tests once and exit the karma process (helpful on Windows):
-
-```bash
-$ yarn test --single-run
-```
-
-#### Packaging (browser and npm)
-
-```bash
-$ yarn build-npm
-> Stored standalone library at dist/deeplearn(.min).js
-> deeplearn-VERSION.tgz
-```
-
-To install it locally, run `npm install ./deeplearn-VERSION.tgz`.
-
-> On Windows, use bash (available through git) to use the scripts above.
-
-Looking to contribute, and don't know where to start? Check out our "help wanted"
-[issues](https://github.com/PAIR-code/deeplearnjs/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22).
-
-## Supported environments
-
-**deeplearn.js** targets environments with WebGL 1.0 or WebGL 2.0. For devices
-without the `OES_texture_float` extension, we fall back to fixed precision
-floats backed by a `gl.UNSIGNED_BYTE` texture. For platforms without WebGL,
-we provide CPU fallbacks.
-
-## Resources
-
-* [Tutorials](https://deeplearnjs.org/docs/tutorials/index.html)
-* [API Reference](https://deeplearnjs.org/docs/api/index.html)
-* [Demos](https://deeplearnjs.org/index.html#demos)
-* [Roadmap](https://deeplearnjs.org/docs/roadmap.html)
-
-## Thanks
-
-<p style="display:flex; align-items:center;">
-  <a href="https://www.browserstack.com/">
-    <img src="https://www.browserstack.com/images/layout/browserstack-logo-600x315.png" height="70" style="height:70px;">
-  </a>
-  <span>&nbsp; for providing testing support.</span>
-</p>
+Thanks <a href="https://www.browserstack.com/">BrowserStack</a> for providing testing support.

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