Commit b9956a6a authored by Myle Ott's avatar Myle Ott
Browse files

Fix FP16 version comparison

parent 753935ef

fairseq/models/fconv.py

+1 −1
Original line number Diff line number Diff line
@@ -497,7 +497,7 @@ class FConvDecoder(FairseqIncrementalDecoder): 
        return self.embed_positions.max_positions() if self.embed_positions is not None else float('inf')



    def upgrade_state_dict(self, state_dict):

        if state_dict.get('decoder.version', torch.Tensor([1]))[0] < 2:

        if utils.item(state_dict.get('decoder.version', torch.Tensor([1]))[0]) < 2:

            # old models use incorrect weight norm dimension

            for i, conv in enumerate(self.convolutions):

                # reconfigure weight norm

fairseq/models/transformer.py

+2 −2
Original line number Diff line number Diff line
@@ -277,7 +277,7 @@ class TransformerEncoder(FairseqEncoder): 
            if 'encoder.embed_positions.weights' in state_dict:

                del state_dict['encoder.embed_positions.weights']

            state_dict['encoder.embed_positions._float_tensor'] = torch.FloatTensor(1)

        if state_dict.get('encoder.version', torch.Tensor([1]))[0] < 2:

        if utils.item(state_dict.get('encoder.version', torch.Tensor([1]))[0]) < 2:

            # earlier checkpoints did not normalize after the stack of layers

            self.layer_norm = None

            self.normalize = False
@@ -415,7 +415,7 @@ class TransformerDecoder(FairseqIncrementalDecoder): 
                    if k in state_dict:

                        state_dict['decoder.layers.{}.{}.{}'.format(i, new, m)] = state_dict[k]

                        del state_dict[k]

        if state_dict.get('decoder.version', torch.Tensor([1]))[0] < 2:

        if utils.item(state_dict.get('decoder.version', torch.Tensor([1]))[0]) < 2:

            # earlier checkpoints did not normalize after the stack of layers

            self.layer_norm = None

            self.normalize = False