Add conv_util.checkPadOnDimRoundingMode() function with tests.

tfjs-core/src/gradients/DepthwiseConv2dNative_grad.ts

@@ -58,13 +58,8 @@ export const depthwiseConv2dNativeGradConfig: GradConfig = {
             `dilations must be  1. Got strides ${strides} and dilations ` +
             `'${$dilations}'.`);
 
-    if (dimRoundingMode != null) {
-      util.assert(
-          util.isInt(pad as number),
-          () =>
-              `Error in depthwiseConv2d: pad must be an integer when using, ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-    }
+    conv_util.checkPadOnDimRoundingMode(
+        'depthwiseConv2d', pad, dimRoundingMode);
 
     return {
       x: () => depthwiseConv2dNativeBackpropInput(

tfjs-core/src/ops/avg_pool.ts

@@ -72,32 +72,8 @@ function avgPool_<T extends Tensor3D|Tensor4D>(
   util.assert(
       x4D.rank === 4,
       () => `Error in avgPool: x must be rank 4 but got rank ${x4D.rank}.`);
-
-  if (dimRoundingMode != null) {
-    if (typeof pad === 'string') {
-      throw Error(
-          `Error in avgPool: pad must be an integer when using `  +
-          `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-    } else if (typeof pad === 'number') {
-      util.assert(
-          util.isInt(pad),
-          () => `Error in avgPool: pad must be an integer when using ` +
-              `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-    } else if (typeof pad === 'object') {
-      (pad as conv_util.ExplicitPadding).forEach(p => {p.forEach(v =>{
-        util.assert(
-            util.isInt(v),
-            () => `Error in avgPool: pad must be an integer when using ` +
-                `dimRoundingMode ${dimRoundingMode} but got pad ${v}.`);
-        });
-      });
-    } else {
-      throw Error(`Unknown padding parameter: ${pad}`);
-    }
-  }
-
+  conv_util.checkPadOnDimRoundingMode('avgPool', pad, dimRoundingMode);
   const inputs: AvgPoolInputs = {x: x4D};
-
   const attrs: AvgPoolAttrs = {filterSize, strides, pad, dimRoundingMode};
 
   // tslint:disable-next-line: no-unnecessary-type-assertion

tfjs-core/src/ops/avg_pool_3d.ts

@@ -24,6 +24,7 @@ import {convertToTensor} from '../tensor_util_env';
 import {TensorLike} from '../types';
 import * as util from '../util';
 
+import {checkPadOnDimRoundingMode} from './conv_util';
 import {cast} from './cast';
 import {op} from './operation';
 import {reshape} from './reshape';
@@ -85,16 +86,8 @@ function avgPool3d_<T extends Tensor4D|Tensor5D>(
       dataFormat === 'NDHWC',
       () => `Error in avgPool3d: Only NDHWC is currently supported, ` +
           `but got dataFormat of ${dataFormat}`);
-
-  if (dimRoundingMode != null) {
-    util.assert(
-        util.isInt(pad as number),
-        () => `Error in avgPool3d: pad must be an integer when using, ` +
-            `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-  }
-
+  checkPadOnDimRoundingMode('avgPool3d', pad, dimRoundingMode);
   const inputs: AvgPool3DInputs = {x: x5D};
-
   const attrs:
       AvgPool3DAttrs = {filterSize, strides, pad, dimRoundingMode, dataFormat};
 

tfjs-core/src/ops/avg_pool_3d_grad.ts

@@ -25,6 +25,7 @@ import {convertToTensor} from '../tensor_util_env';
 import {TensorLike} from '../types';
 import * as util from '../util';
 
+import {checkPadOnDimRoundingMode} from './conv_util';
 import {op} from './operation';
 import {reshape} from './reshape';
 
@@ -77,16 +78,8 @@ function avgPool3dGrad_<T extends Tensor4D|Tensor5D>(
       input5D.rank === 5,
       () => `Error in avgPool3dGrad: input must be rank 5 but got rank ` +
           `${input5D.rank}.`);
-
-  if (dimRoundingMode != null) {
-    util.assert(
-        util.isInt(pad as number),
-        () => `Error in avgPool3dGrad: pad must be an integer when ` +
-            `using, dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-  }
-
+  checkPadOnDimRoundingMode('avgPool3dGrad', pad, dimRoundingMode);
   const inputs: AvgPool3DGradInputs = {dy: dy5D, input: input5D};
-
   const attrs: AvgPool3DGradAttrs = {filterSize, strides, pad, dimRoundingMode};
 
   // tslint:disable-next-line: no-unnecessary-type-assertion

tfjs-core/src/ops/avg_pool_3d_test.ts

@@ -157,14 +157,31 @@ describeWithFlags('avgPool3d', ALL_ENVS, () => {
     expect(() => tf.avgPool3d(x as tf.Tensor5D, 2, 1, 'valid')).toThrowError();
   });
 
-  it('throws when dimRoundingMode is set and pad is not a number', async () => {
+  it('throws when dimRoundingMode is set and pad is same', async () => {
+    const x = tf.tensor5d([1], [1, 1, 1, 1, 1]);
+    const pad = 'same';
+    const dimRoundingMode = 'round';
+
+    expect(() => tf.avgPool3d(x, 2, 1, pad, dimRoundingMode)).toThrowError();
+  });
+
+  it('throws when dimRoundingMode is set and pad is valid', async () => {
     const x = tf.tensor5d([1], [1, 1, 1, 1, 1]);
     const pad = 'valid';
     const dimRoundingMode = 'round';
 
     expect(() => tf.avgPool3d(x, 2, 1, pad, dimRoundingMode)).toThrowError();
   });
 
+  it('throws when dimRoundingMode is set and pad is a non-integer number',
+     async () => {
+       const x = tf.tensor5d([1], [1, 1, 1, 1, 1]);
+       const pad = 1.2;
+       const dimRoundingMode = 'round';
+
+       expect(() => tf.avgPool3d(x, 2, 1, pad, dimRoundingMode)).toThrowError();
+     });
+
   it('throws when passed a non-tensor', () => {
     expect(() => tf.avgPool3d({} as tf.Tensor5D, 2, 1, 'valid')).toThrowError();
   });

tfjs-core/src/ops/avg_pool_test.ts

@@ -210,7 +210,16 @@ describeWithFlags('avgPool', ALL_ENVS, () => {
     ]);
   });
 
-  it('throws when dimRoundingMode is set and pad is not a number', () => {
+  it('throws when dimRoundingMode is set and pad is same', () => {
+    const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
+
+    const pad = 'same';
+    const dimRoundingMode = 'round';
+
+    expect(() => tf.avgPool(x, 2, 1, pad, dimRoundingMode)).toThrowError();
+  });
+
+  it('throws when dimRoundingMode is set and pad is valid', () => {
     const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
 
     const pad = 'valid';
@@ -219,6 +228,28 @@ describeWithFlags('avgPool', ALL_ENVS, () => {
     expect(() => tf.avgPool(x, 2, 1, pad, dimRoundingMode)).toThrowError();
   });
 
+  it('throws when dimRoundingMode is set and pad is a non-integer number',
+     () => {
+       const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
+
+       const pad = 1.2;
+       const dimRoundingMode = 'round';
+
+       expect(() => tf.avgPool(x, 2, 1, pad, dimRoundingMode)).toThrowError();
+     });
+
+  it('throws when dimRoundingMode is set and pad is explicit by non-integer ' +
+         'number',
+     () => {
+       const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
+
+       const pad = [[0, 0], [0, 2.1], [1, 1], [0, 0]] as
+           tf.backend_util.ExplicitPadding;
+       const dimRoundingMode = 'round';
+
+       expect(() => tf.avgPool(x, 2, 1, pad, dimRoundingMode)).toThrowError();
+     });
+
   it('throws when passed a non-tensor', () => {
     expect(() => tf.avgPool({} as tf.Tensor3D, 2, 1, 'valid'))
         .toThrowError(/Argument 'x' passed to 'avgPool' must be a Tensor/);

tfjs-core/src/ops/conv1d.ts

@@ -74,13 +74,7 @@ function conv1d_<T extends Tensor2D|Tensor3D>(
       $filter.rank === 3,
       () => `Error in conv1d: filter must be rank 3, but got rank ` +
           `${$filter.rank}.`);
-  if (dimRoundingMode != null) {
-    util.assert(
-        util.isInt(pad as number),
-        () => `Error in conv1d: pad must be an integer when using, ` +
-            `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-  }
-
+  conv_util.checkPadOnDimRoundingMode('conv1d', pad, dimRoundingMode);
   util.assert(
       x3D.shape[2] === $filter.shape[1],
       () => `Error in conv1d: depth of input (${x3D.shape[2]}) must match ` +

tfjs-core/src/ops/conv1d_test.ts

@@ -134,6 +134,90 @@ describeWithFlags('conv1d', ALL_ENVS, () => {
     expectArraysClose(await result.data(), await expectedResult.data());
   });
 
+  it('throws when dimRoundingMode is set and pad is same', () => {
+    const inputDepth = 1;
+    const inputShape: [number, number, number] = [2, 2, inputDepth];
+    const outputDepth = 1;
+    const fSize = 1;
+    const pad = 'same';
+    const stride = 1;
+    const dataFormat = 'NWC';
+    const dilation = 1;
+    const dimRoundingMode = 'round';
+
+    const x = tf.tensor3d([1, 2, 3, 4], inputShape);
+    const w = tf.tensor3d([3], [fSize, inputDepth, outputDepth]);
+
+    expect(
+        () => tf.conv1d(
+            x, w, stride, pad, dataFormat, dilation, dimRoundingMode))
+        .toThrowError();
+  });
+
+  it('throws when dimRoundingMode is set and pad is valid', () => {
+    const inputDepth = 1;
+    const inputShape: [number, number, number] = [2, 2, inputDepth];
+    const outputDepth = 1;
+    const fSize = 1;
+    const pad = 'valid';
+    const stride = 1;
+    const dataFormat = 'NWC';
+    const dilation = 1;
+    const dimRoundingMode = 'round';
+
+    const x = tf.tensor3d([1, 2, 3, 4], inputShape);
+    const w = tf.tensor3d([3], [fSize, inputDepth, outputDepth]);
+
+    expect(
+        () => tf.conv1d(
+            x, w, stride, pad, dataFormat, dilation, dimRoundingMode))
+        .toThrowError();
+  });
+
+  it('throws when dimRoundingMode is set and pad is a non-integer number',
+     () => {
+       const inputDepth = 1;
+       const inputShape: [number, number, number] = [2, 2, inputDepth];
+       const outputDepth = 1;
+       const fSize = 1;
+       const pad = 1.2;
+       const stride = 1;
+       const dataFormat = 'NWC';
+       const dilation = 1;
+       const dimRoundingMode = 'round';
+
+       const x = tf.tensor3d([1, 2, 3, 4], inputShape);
+       const w = tf.tensor3d([3], [fSize, inputDepth, outputDepth]);
+
+       expect(
+           () => tf.conv1d(
+               x, w, stride, pad, dataFormat, dilation, dimRoundingMode))
+           .toThrowError();
+     });
+
+  it('throws when dimRoundingMode is set and pad is explicit by non-integer ' +
+         'number',
+     () => {
+       const inputDepth = 1;
+       const inputShape: [number, number, number] = [2, 2, inputDepth];
+       const outputDepth = 1;
+       const fSize = 1;
+       const pad = [[0, 0], [0, 2.1], [1, 1], [0, 0]] as
+          tf.backend_util.ExplicitPadding;
+       const stride = 1;
+       const dataFormat = 'NWC';
+       const dilation = 1;
+       const dimRoundingMode = 'round';
+
+       const x = tf.tensor3d([1, 2, 3, 4], inputShape);
+       const w = tf.tensor3d([3], [fSize, inputDepth, outputDepth]);
+
+       expect(
+           () => tf.conv1d(
+               x, w, stride, pad, dataFormat, dilation, dimRoundingMode))
+           .toThrowError();
+     });
+
   it('TensorLike', async () => {
     const pad = 'same';
     const stride = 1;

tfjs-core/src/ops/conv2d.ts

@@ -84,13 +84,7 @@ function conv2d_<T extends Tensor3D|Tensor4D>(
       $filter.rank === 4,
       () => `Error in conv2d: filter must be rank 4, but got rank ` +
           `${$filter.rank}.`);
-  if (dimRoundingMode != null) {
-    util.assert(
-        util.isInt(pad as number),
-        () => `Error in conv2d: pad must be an integer when using, ` +
-            `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-  }
-
+  conv_util.checkPadOnDimRoundingMode('conv2d', pad, dimRoundingMode);
   const inDepth = dataFormat === 'NHWC' ? x4D.shape[3] : x4D.shape[1];
   util.assert(
       inDepth === $filter.shape[2],

tfjs-core/src/ops/conv2d_backprop_filter.ts

@@ -81,13 +81,7 @@ function conv2DBackpropFilter_<T extends Tensor3D|Tensor4D>(
       outDepth === filterShape[3],
       () => `Error in conv2dDerFilter: depth of dy (${outDepth}) must ` +
           `match output depth for filter (${filterShape[3]}).`);
-  if (dimRoundingMode != null) {
-    util.assert(
-        util.isInt(pad as number),
-        () => `Error in conv2dDerFilter: pad must be an integer when using, ` +
-            `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-  }
-
+  conv_util.checkPadOnDimRoundingMode('conv2dDerFilter', pad, dimRoundingMode);
   const inputs: Conv2DBackpropFilterInputs = {x: x4D, dy: dy4D};
   const attrs: Conv2DBackpropFilterAttrs =
       {strides, pad, dataFormat, dimRoundingMode, filterShape};

tfjs-core/src/ops/conv2d_backprop_input.ts

@@ -92,15 +92,8 @@ function conv2DBackpropInput_<T extends Tensor3D|Tensor4D>(
       outDepth === filter.shape[3],
       () => `Error in conv2dDerInput: depth of output (${outDepth}) must ` +
           `match output depth for filter ${filter.shape[3]}.`);
-  if (dimRoundingMode != null) {
-    util.assert(
-        util.isInt(pad as number),
-        () => `Error in conv2dDerInput: pad must be an integer when using, ` +
-            `dimRoundingMode ${dimRoundingMode} but got pad ${pad}.`);
-  }
-
+  conv_util.checkPadOnDimRoundingMode('conv2dDerInput', pad, dimRoundingMode);
   const inputs: Conv2DBackpropInputInputs = {dy: dy4D, filter};
-
   const attrs: Conv2DBackpropInputAttrs =
       {strides, pad, dataFormat, dimRoundingMode, inputShape: xShape4D};