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add clipByValue int32 test and fix the node impl #3822

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Merged
merged 4 commits into from
Aug 18, 2020
Merged

add clipByValue int32 test and fix the node impl #3822

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491c24a
add clipByValue int32 test and fix the node impl
pyu10055 Aug 18, 2020
a689ac6
Merge branch 'master' into node_clip_by_value
pyu10055 Aug 18, 2020
58179f5
fix cpu backend failed test for clip
pyu10055 Aug 18, 2020
cde2a8e
fix wasm backend
pyu10055 Aug 18, 2020
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2 changes: 1 addition & 1 deletion tfjs-backend-cpu/src/backend_cpu.ts
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Expand Up @@ -1152,7 +1152,7 @@ export class MathBackendCPU extends KernelBackend {
const v = values[i];
resultValues[i] = v > max ? max : (v < min ? min : v);
}
return this.makeOutput(resultValues, x.shape, 'float32');
return this.makeOutput(resultValues, x.shape, x.dtype);
}

abs<T extends Tensor>(x: T): T {
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2 changes: 1 addition & 1 deletion tfjs-backend-wasm/src/kernels/ClipByValue.ts
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Expand Up @@ -39,7 +39,7 @@ function clip(args: {
const {x} = inputs;
const {clipValueMin, clipValueMax} = attrs;
const xId = backend.dataIdMap.get(x.dataId).id;
const out = backend.makeOutput(x.shape, 'float32');
const out = backend.makeOutput(x.shape, x.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
wasmClip(xId, clipValueMin, clipValueMax, outId);
return out;
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9 changes: 9 additions & 0 deletions tfjs-core/src/ops/clip_by_value_test.ts
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Expand Up @@ -135,4 +135,13 @@ describeWithFlags('clipByValue', ALL_ENVS, () => {
expect(() => tf.clipByValue('q', 0, 1))
.toThrowError(/Argument 'x' passed to 'clipByValue' must be numeric/);
});

it('clip int32 tensor', async () => {
const min = -1;
const max = 50;
const tensor = tf.tensor([2, 3, 4], [3], 'int32');
const result = tf.clipByValue(tensor, min, max);
expectArraysClose(await result.data(), [2, 3, 4]);
expect(result.dtype).toEqual('int32');
});
});
4 changes: 2 additions & 2 deletions tfjs-node/src/nodejs_kernel_backend.ts
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Expand Up @@ -722,8 +722,8 @@ export class NodeJSKernelBackend extends KernelBackend {
}

clip<T extends Tensor>(x: T, min: number, max: number): T {
const xMin = this.minimum(x, scalar(max));
return this.maximum(xMin, scalar(min)) as T;
const xMin = this.minimum(x, scalar(max, x.dtype));
return this.maximum(xMin, scalar(min, x.dtype)) as T;
}

abs<T extends Tensor>(x: T): T {
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