Method readToGPU

tfjs-backend-webgpu/src/backend_webgpu.ts:596–630

* Read tensor to a new GPUBuffer. * @param dataId The source tensor.

(dataId: DataId)

   * @param dataId The source tensor.
   */
  override readToGPU(dataId: DataId): GPUData {
    const srcTensorData = this.tensorMap.get(dataId);
    const {values, dtype, shape, resource} = srcTensorData;

    if (dtype === 'complex64') {
      throw new Error('Does not support reading buffer for complex64 dtype.');
    }

    if (resource == null) {
      if (values != null) {
        throw new Error('Data is not on GPU but on CPU.');
      } else {
        throw new Error('There is no data on GPU or CPU.');
      }
    }

    const srcBuffer = resource as GPUBuffer;
    const size = srcBuffer.size;
    const usage = srcBuffer.usage;
    const buffer = this.bufferManager.acquireBuffer(size, usage);
    this.ensureCommandEncoderReady();
    this.endComputePassEncoder();
    this.commandEncoder.copyBufferToBuffer(
        resource as GPUBuffer, 0, buffer, 0, size);
    this.submitQueue();

    const tensorInfo = this.makeTensorInfo(shape, dtype);
    // Make engine track this tensor, so that we can dispose it later.
    const tensorRef = engine().makeTensorFromTensorInfo(tensorInfo);

    const tensorData = this.tensorMap.get(tensorInfo.dataId);
    tensorData.resource = buffer;

    return {tensorRef, buffer};
  }

  bufferSync<R extends Rank, D extends DataType>(t: TensorInfo):
      TensorBuffer<R, D> {