Function Decode

tensorflow/contrib/ffmpeg/decode_audio_op.cc:44–91

* Decoding implementation, shared across V1 and V2 ops. Creates a new * output in the context. */

 * output in the context.
 */
void Decode(OpKernelContext* context,
            const tensorflow::StringPiece& file_contents,
            const string& file_format, const int32 samples_per_second,
            const int32 channel_count, const string& stream) {
  // Write the input data to a temp file.
  const string temp_filename = io::GetTempFilename(file_format);
  OP_REQUIRES_OK(context, WriteFile(temp_filename, file_contents));
  FileDeleter deleter(temp_filename);

  // Run FFmpeg on the data and verify results.
  std::vector<float> output_samples;
  Status result =
      ffmpeg::ReadAudioFile(temp_filename, file_format, samples_per_second,
                            channel_count, stream, &output_samples);
  if (result.code() == error::Code::NOT_FOUND) {
    OP_REQUIRES(
        context, result.ok(),
        errors::Unavailable("FFmpeg must be installed to run this op. FFmpeg "
                            "can be found at http://www.ffmpeg.org."));
  } else if (result.code() == error::UNKNOWN) {
    LOG(ERROR) << "Ffmpeg failed with error '" << result.error_message()
               << "'. Returning empty tensor.";
    Tensor* output = nullptr;
    OP_REQUIRES_OK(context,
                   context->allocate_output(0, TensorShape({0, 0}), &output));
    return;
  } else {
    OP_REQUIRES_OK(context, result);
  }
  OP_REQUIRES(context, !output_samples.empty(),
              errors::Unknown("No output created by FFmpeg."));
  OP_REQUIRES(
      context, output_samples.size() % channel_count == 0,
      errors::Unknown("FFmpeg created non-integer number of audio frames."));

  // Copy the output data to the output Tensor.
  Tensor* output = nullptr;
  const int64 frame_count = output_samples.size() / channel_count;
  OP_REQUIRES_OK(context,
                 context->allocate_output(
                     0, TensorShape({frame_count, channel_count}), &output));
  auto matrix = output->tensor<float, 2>();
  for (int32 frame = 0; frame < frame_count; ++frame) {
    for (int32 channel = 0; channel < channel_count; ++channel) {
      matrix(frame, channel) = output_samples[frame * channel_count + channel];
    }
  }
}

}  // namespace