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[WebGPU] Don't release the uniform buffer under delayed mode #1968

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Merged
merged 1 commit into from
Sep 5, 2019
Merged

[WebGPU] Don't release the uniform buffer under delayed mode #1968

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9 changes: 6 additions & 3 deletions tfjs-backend-webgpu/src/backend_webgpu.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -459,12 +459,15 @@ export class WebGPUBackend extends KernelBackend {
});
this.commandQueueOwnedIds.add(output.dataId);

const uniformInfo = {
byteSize: uniformData.byteLength,
usage: GPUBufferUsage.COPY_DST | GPUBufferUsage.UNIFORM,
buffer: uniforms.resource.buffer};
this.disposalQueue.push(uniformInfo);

if (ENV.get('WEBGPU_IMMEDIATE_EXECUTION_ENABLED')) {
this.submitQueue();
}
this.releaseBuffer(
uniforms.resource.buffer, uniformData.byteLength,
GPUBufferUsage.COPY_DST | GPUBufferUsage.UNIFORM);

if (shouldTimeProgram) {
query = this.endTimer(query);
Expand Down
16 changes: 8 additions & 8 deletions tfjs-backend-webgpu/src/backend_webgpu_test.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ describeWebGPU('backend webgpu', () => {

expect(endNumBytes - startNumBytes).toEqual(48);
expect(endNumTensors - startNumTensors).toEqual(2);
expect(endNumBytesInGPU - startNumBytesInGPU).toEqual(48);
expect(endNumBytesInGPU - startNumBytesInGPU).toEqual(24);

tf.test_util.expectArraysClose(
dData, new Float32Array([9, 12, 15, 19, 26, 33]));
Expand Down Expand Up @@ -120,7 +120,7 @@ describeWebGPU('backend webgpu', () => {
tf.ENV.set('WEBGPU_IMMEDIATE_EXECUTION_ENABLED', savedFlag);
});

it('should recycle buffers in delayed mode', () => {
it('should not recycle buffers in delayed mode', () => {
const savedFlag = tf.ENV.get('WEBGPU_IMMEDIATE_EXECUTION_ENABLED');
tf.ENV.set('WEBGPU_IMMEDIATE_EXECUTION_ENABLED', false);
const backend = tf.backend() as WebGPUBackend;
Expand All @@ -139,8 +139,8 @@ describeWebGPU('backend webgpu', () => {
const freeBuffersAfterFirstMatMul = bufferManager.getNumFreeBuffers();
const usedBuffersAfterFirstMatMul = bufferManager.getNumUsedBuffers();
expect(freeBuffersAfterFirstMatMul - freeBuffersAfterFirstMul)
.toEqual(1); // from released uniform
expect(usedBuffersAfterFirstMatMul - usedBuffersAfterFirstMul).toEqual(2);
.toEqual(0);
expect(usedBuffersAfterFirstMatMul - usedBuffersAfterFirstMul).toEqual(3);

const a2 = tf.tensor2d([2, 4, 6, 8], [2, 2]);
const b2 = tf.tensor2d([0.5, 0.5, 0.5, 0.5], [2, 2]);
Expand All @@ -149,15 +149,15 @@ describeWebGPU('backend webgpu', () => {
const freeBuffersAfterSecondMul = bufferManager.getNumFreeBuffers();
const usedBuffersAfterSecondMul = bufferManager.getNumUsedBuffers();
expect(freeBuffersAfterSecondMul - freeBuffersAfterFirstMatMul)
.toEqual(0); // released a uniform buffer and reused a buffer
expect(usedBuffersAfterSecondMul - usedBuffersAfterFirstMatMul).toEqual(3);
.toEqual(0);
expect(usedBuffersAfterSecondMul - usedBuffersAfterFirstMatMul).toEqual(4);

const f2 = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
tf.matMul(c2, f2);
const freeBuffersAfterSecondMatMul = bufferManager.getNumFreeBuffers();
const usedBuffersAfterSecondMatMul = bufferManager.getNumUsedBuffers();
expect(freeBuffersAfterSecondMatMul - freeBuffersAfterSecondMul).toEqual(0);
expect(usedBuffersAfterSecondMatMul - usedBuffersAfterSecondMul).toEqual(2);
expect(usedBuffersAfterSecondMatMul - usedBuffersAfterSecondMul).toEqual(3);
tf.ENV.set('WEBGPU_IMMEDIATE_EXECUTION_ENABLED', savedFlag);
});

Expand All @@ -174,4 +174,4 @@ describeWebGPU('backend webgpu', () => {
// Now that data has been downloaded to the CPU, dataSync should work.
expect(() => c.dataSync()).not.toThrow();
});
});
});