Address other todos

Author: NicolasHug

src/torchcodec/_core/Encoder.cpp

@@ -14,6 +14,18 @@ torch::Tensor validateWf(torch::Tensor wf) {
       "waveform must have float32 dtype, got ",
       wf.dtype());
   TORCH_CHECK(wf.dim() == 2, "waveform must have 2 dimensions, got ", wf.dim());
+
+  // We enforce this, but if we get user reports we should investigate whether
+  // that's actually needed.
+  int numChannels = static_cast<int>(wf.sizes()[0]);
+  TORCH_CHECK(
+      numChannels <= AV_NUM_DATA_POINTERS,
+      "Trying to encode ",
+      numChannels,
+      " channels, but FFmpeg only supports ",
+      AV_NUM_DATA_POINTERS,
+      " channels per frame.");
+
   return wf.contiguous();
 }
 
@@ -164,18 +176,7 @@ void AudioEncoder::initializeEncoder(
   // what the `.sample_fmt` defines.
   avCodecContext_->sample_fmt = findBestOutputSampleFormat(*avCodec);
 
-  int numChannels = static_cast<int>(wf_.sizes()[0]);
-  TORCH_CHECK(
-      // TODO-ENCODING is this even true / needed? We can probably support more
-      // with non-planar data?
-      numChannels <= AV_NUM_DATA_POINTERS,
-      "Trying to encode ",
-      numChannels,
-      " channels, but FFmpeg only supports ",
-      AV_NUM_DATA_POINTERS,
-      " channels per frame.");
-
-  setDefaultChannelLayout(avCodecContext_, numChannels);
+  setDefaultChannelLayout(avCodecContext_, static_cast<int>(wf_.sizes()[0]));
 
   int status = avcodec_open2(avCodecContext_.get(), avCodec, nullptr);
   TORCH_CHECK(
@@ -325,14 +326,17 @@ void AudioEncoder::encodeInnerLoop(
     ReferenceAVPacket packet(autoAVPacket);
     status = avcodec_receive_packet(avCodecContext_.get(), packet.get());
     if (status == AVERROR(EAGAIN) || status == AVERROR_EOF) {
-      // TODO-ENCODING this is from TorchAudio, probably needed, but not sure.
-      //   if (status == AVERROR_EOF) {
-      //     status = av_interleaved_write_frame(avFormatContext_.get(),
-      //     nullptr); TORCH_CHECK(
-      //         status == AVSUCCESS,
-      //         "Failed to flush packet ",
-      //         getFFMPEGErrorStringFromErrorCode(status));
-      //   }
+      if (status == AVERROR_EOF) {
+        // Flush the packets that were potentially buffered by
+        // av_interleaved_write_frame(). See corresponding block in
+        // TorchAudio:
+        // https://github.com/pytorch/audio/blob/d60ce09e2c532d5bf2e05619e700ab520543465e/src/libtorio/ffmpeg/stream_writer/encoder.cpp#L21
+        status = av_interleaved_write_frame(avFormatContext_.get(), nullptr);
+        TORCH_CHECK(
+            status == AVSUCCESS,
+            "Failed to flush packet: ",
+            getFFMPEGErrorStringFromErrorCode(status));
+      }
       return;
     }
     TORCH_CHECK(

src/torchcodec/_core/custom_ops.cpp

@@ -394,8 +394,6 @@ void encode_audio_to_file(
       .encode();
 }
 
-// TODO-ENCODING is "format" a good parameter name?? It kinda conflicts with
-// "sample_format" which we may eventually want to expose.
 at::Tensor encode_audio_to_tensor(
     const at::Tensor wf,
     int64_t sample_rate,

test/test_ops.py

@@ -1132,11 +1132,11 @@ def test_bad_input(self, tmp_path):
 
         with pytest.raises(RuntimeError, match="No such file or directory"):
             encode_audio_to_file(
-                wf=torch.rand(10, 10), sample_rate=10, filename="./bad/path.mp3"
+                wf=torch.rand(2, 10), sample_rate=10, filename="./bad/path.mp3"
             )
         with pytest.raises(RuntimeError, match="Check the desired extension"):
             encode_audio_to_file(
-                wf=torch.rand(10, 10), sample_rate=10, filename="./file.bad_extension"
+                wf=torch.rand(2, 10), sample_rate=10, filename="./file.bad_extension"
             )
 
         with pytest.raises(RuntimeError, match="invalid sample rate=10"):
@@ -1153,6 +1153,11 @@ def test_bad_input(self, tmp_path):
                 bit_rate=-1,  # bad
             )
 
+        with pytest.raises(RuntimeError, match="Trying to encode 10 channels"):
+            encode_audio_to_file(
+                wf=torch.rand(10, 20), sample_rate=10, filename="doesnt_matter"
+            )
+
     @pytest.mark.parametrize(
         "encode_method", (encode_audio_to_file, encode_audio_to_tensor)
     )