course8的linear算子问题

[IsUpsAndDowns]

linear.cpp中的output = std::make_shared<Tensor<float>>(1, out_features_, feature_dims); 这段代码的out_features和feature_dims的位置是否写反了

    std::shared_ptr<Tensor<float>> output = outputs.at(i);
    if (output == nullptr || output->empty()) {
      output = std::make_shared<Tensor<float>>(1, out_features_, feature_dims);
      outputs.at(i) = output;
    }

    CHECK(output->channels() == 1 && output->rows() == feature_dims &&
          output->cols() == out_features_)
        << "The row of output tensor should be same to feature_dims_ and the "
           "col of output tensor should be same to output_features_ "
        << i << " th";
    const auto& output_raw_shapes = output->raw_shapes();
    if (output_raw_shapes.size() == 2) {
      CHECK(output_raw_shapes.at(0) == feature_dims &&
            output_raw_shapes.at(1) == out_features_);
    }
    if (output_raw_shapes.size() == 1) {
      CHECK(output_raw_shapes.at(0) == out_features_);
    }

测试linear算子的单元测试

TEST(test_register, test_linear1) {
    std::shared_ptr<RuntimeOperator> op = std::make_shared<RuntimeOperator>();
    op->type = "nn.Linear";

    // bias parameter
    bool bias = true;
    std::shared_ptr<RuntimeParameter> bias_param = std::make_shared<RuntimeParameterBool>(bias);
    op->params.insert({"bias", bias_param});

    const uint32_t batch_size = 1;
    std::vector<sftensor> inputs(batch_size);
    std::vector<sftensor> outputs(batch_size);

    const uint32_t in_channel = 1;
    std::shared_ptr<Tensor<float>> input = std::make_shared<Tensor<float>>(in_channel, 2, 4);
    input->data().slice(0) = "1,1,1,1;"
                             "1,1,1,1;";
    inputs.at(0) = input;

    const uint32_t kernel_h = 3;
    const uint32_t kernel_w = 4;

    std::vector<sftensor> weights;
    std::shared_ptr<Tensor<float>> kernel = std::make_shared<Tensor<float>>(in_channel, kernel_h, kernel_w);
    kernel->slice(0) = arma::fmat("2,2,2,2;"
                                          "2,2,2,2;"
                                          "2,2,2,2;");

    weights.push_back(kernel);

    std::vector<sftensor> Bias;
    std::shared_ptr<Tensor<float>> b = std::make_shared<Tensor<float>>(in_channel, 1, 3);
    b->slice(0) = arma::fmat("1, 1, 1;");

    Bias.push_back(b);

    const uint32_t in_features = 4;
    const uint32_t out_features = 3;
    LinearLayer linear_layer(in_features, out_features, true);
    linear_layer.set_weights(weights);
    linear_layer.set_bias(Bias);

    linear_layer.Forward(inputs, outputs);
    ASSERT_EQ(outputs.size(), 1);

    outputs.at(0)->Show();

    std::shared_ptr<Tensor<float>> output1 = outputs.front();
    const arma::fmat output2 = arma::fmat("9,9,9;"
                                          "9,9,9;");
    ASSERT_TRUE(arma::approx_equal(output1->data().slice(0), output2, "absdiff", 1e-5));
}