Method run

src/framework/audio/zipenhancer.cpp:1001–1019

    }

    ZipEnhancerGraphOutput run(const Tensor4 & input) const {
        if (input.b != 1 || input.c != 2 || input.t != frames_ || input.f != kFreqBins) {
            throw std::runtime_error("ZipEnhancer forward graph input shape changed without rebuild");
        }
        ggml_backend_tensor_set(input_, input.v.data(), 0, input.v.size() * sizeof(float));
        const auto status = core::compute_backend_graph(backend_, graph_, plan_, "ZipEnhancer forward");
        ggml_backend_synchronize(backend_);
        if (status != GGML_STATUS_SUCCESS) {
            throw std::runtime_error("ZipEnhancer forward graph compute failed");
        }
        ZipEnhancerGraphOutput output;
        output.magnitude = Tensor4(magnitude_shape_.dims[0], magnitude_shape_.dims[1], magnitude_shape_.dims[2], magnitude_shape_.dims[3]);
        output.phase_real = Tensor4(phase_shape_.dims[0], phase_shape_.dims[1], phase_shape_.dims[2], phase_shape_.dims[3]);
        output.phase_imag = Tensor4(phase_shape_.dims[0], phase_shape_.dims[1], phase_shape_.dims[2], phase_shape_.dims[3]);
        ggml_backend_tensor_get(magnitude_, output.magnitude.v.data(), 0, output.magnitude.v.size() * sizeof(float));
        ggml_backend_tensor_get(phase_real_, output.phase_real.v.data(), 0, output.phase_real.v.size() * sizeof(float));
        ggml_backend_tensor_get(phase_imag_, output.phase_imag.v.data(), 0, output.phase_imag.v.size() * sizeof(float));
        return output;
    }

private:
    ggml_backend_t backend_ = nullptr;