diff --git a/examples/tacotron2/config.py b/examples/tacotron2/config.py index 77e1f9c..dacf42a 100644 --- a/examples/tacotron2/config.py +++ b/examples/tacotron2/config.py @@ -32,6 +32,7 @@ _C.data = CN( _C.model = CN( dict( vocab_size=37, # set this according to the frontend's vocab size + n_tones=None, reduction_factor=1, # reduction factor d_encoder=512, # embedding & encoder's internal size encoder_conv_layers=3, # number of conv layer in tacotron2 encoder @@ -54,6 +55,7 @@ _C.model = CN( p_decoder_dropout= 0.1, # droput probability of second rnn layer in decoder p_postnet_dropout=0.5, # droput probability in decoder postnet + d_global_condition=None, use_stop_token= True, # wherther to use binary classifier to predict when to stop use_guided_attention_loss=False, # whether to use guided attention loss diff --git a/examples/tacotron2/synthesize.ipynb b/examples/tacotron2/synthesize.ipynb index 6fe0edd..2ede277 100644 --- a/examples/tacotron2/synthesize.ipynb +++ b/examples/tacotron2/synthesize.ipynb @@ -60,11 +60,11 @@ "text": [ "data:\n", " batch_size: 32\n", - " d_mels: 80\n", " fmax: 8000\n", " fmin: 0\n", " hop_length: 256\n", " n_fft: 1024\n", + " n_mels: 80\n", " padding_idx: 0\n", " sample_rate: 22050\n", " valid_size: 64\n", @@ -76,11 +76,13 @@ " d_attention_rnn: 1024\n", " d_decoder_rnn: 1024\n", " d_encoder: 512\n", + " d_global_condition: None\n", " d_postnet: 512\n", " d_prenet: 256\n", " encoder_conv_layers: 3\n", " encoder_kernel_size: 5\n", " guided_attention_loss_sigma: 0.2\n", + " n_tones: None\n", " p_attention_dropout: 0.1\n", " p_decoder_dropout: 0.1\n", " p_encoder_dropout: 0.5\n", @@ -119,14 +121,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "[checkpoint] Rank 0: loaded model from runs/refactor/checkpoints/step-21000.pdparams\n" + "[checkpoint] Rank 0: loaded model from runs/refactor/checkpoints/step-50000.pdparams\n" ] } ], "source": [ "frontend = EnglishCharacter()\n", "model = Tacotron2.from_pretrained(\n", - " synthesizer_config, \"runs/refactor/checkpoints/step-21000\")\n", + " synthesizer_config, \"runs/refactor/checkpoints/step-50000\")\n", "model.eval()" ] }, @@ -139,7 +141,7 @@ "name": "stderr", "output_type": "stream", "text": [ - " 36%|███▌ | 355/1000 [00:01<00:02, 267.97it/s]" + " 36%|███▋ | 363/1000 [00:01<00:02, 266.51it/s]" ] }, { @@ -174,18 +176,19 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ - "display.plot_alignment(alignment)" + "fig = display.plot_alignment(alignment)" ] }, { @@ -277,7 +280,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "time: 9.308465242385864s\n" + "time: 9.420342922210693s\n" ] } ], @@ -296,7 +299,7 @@ "text/html": [ "\n", " \n", " "