mode `setup_model()` to `models/__init__.py`

TTS/tts/models/__init__.py

@@ -0,0 +1,108 @@
+from TTS.utils.generic_utils import find_module
+
+
+def setup_model(num_chars, num_speakers, c, speaker_embedding_dim=None):
+    print(" > Using model: {}".format(c.model))
+    MyModel = find_module("TTS.tts.models", c.model.lower())
+    if c.model.lower() in "tacotron":
+        model = MyModel(
+            num_chars=num_chars + getattr(c, "add_blank", False),
+            num_speakers=num_speakers,
+            r=c.r,
+            postnet_output_dim=int(c.audio["fft_size"] / 2 + 1),
+            decoder_output_dim=c.audio["num_mels"],
+            use_gst=c.use_gst,
+            gst=c.gst,
+            memory_size=c.memory_size,
+            attn_type=c.attention_type,
+            attn_win=c.windowing,
+            attn_norm=c.attention_norm,
+            prenet_type=c.prenet_type,
+            prenet_dropout=c.prenet_dropout,
+            prenet_dropout_at_inference=c.prenet_dropout_at_inference,
+            forward_attn=c.use_forward_attn,
+            trans_agent=c.transition_agent,
+            forward_attn_mask=c.forward_attn_mask,
+            location_attn=c.location_attn,
+            attn_K=c.attention_heads,
+            separate_stopnet=c.separate_stopnet,
+            bidirectional_decoder=c.bidirectional_decoder,
+            double_decoder_consistency=c.double_decoder_consistency,
+            ddc_r=c.ddc_r,
+            speaker_embedding_dim=speaker_embedding_dim,
+        )
+    elif c.model.lower() == "tacotron2":
+        model = MyModel(
+            num_chars=num_chars + getattr(c, "add_blank", False),
+            num_speakers=num_speakers,
+            r=c.r,
+            postnet_output_dim=c.audio["num_mels"],
+            decoder_output_dim=c.audio["num_mels"],
+            use_gst=c.use_gst,
+            gst=c.gst,
+            attn_type=c.attention_type,
+            attn_win=c.windowing,
+            attn_norm=c.attention_norm,
+            prenet_type=c.prenet_type,
+            prenet_dropout=c.prenet_dropout,
+            prenet_dropout_at_inference=c.prenet_dropout_at_inference,
+            forward_attn=c.use_forward_attn,
+            trans_agent=c.transition_agent,
+            forward_attn_mask=c.forward_attn_mask,
+            location_attn=c.location_attn,
+            attn_K=c.attention_heads,
+            separate_stopnet=c.separate_stopnet,
+            bidirectional_decoder=c.bidirectional_decoder,
+            double_decoder_consistency=c.double_decoder_consistency,
+            ddc_r=c.ddc_r,
+            speaker_embedding_dim=speaker_embedding_dim,
+        )
+    elif c.model.lower() == "glow_tts":
+        model = MyModel(
+            num_chars=num_chars + getattr(c, "add_blank", False),
+            hidden_channels_enc=c["hidden_channels_encoder"],
+            hidden_channels_dec=c["hidden_channels_decoder"],
+            hidden_channels_dp=c["hidden_channels_duration_predictor"],
+            out_channels=c.audio["num_mels"],
+            encoder_type=c.encoder_type,
+            encoder_params=c.encoder_params,
+            use_encoder_prenet=c["use_encoder_prenet"],
+            inference_noise_scale=c.inference_noise_scale,
+            num_flow_blocks_dec=12,
+            kernel_size_dec=5,
+            dilation_rate=1,
+            num_block_layers=4,
+            dropout_p_dec=0.05,
+            num_speakers=num_speakers,
+            c_in_channels=0,
+            num_splits=4,
+            num_squeeze=2,
+            sigmoid_scale=False,
+            mean_only=True,
+            speaker_embedding_dim=speaker_embedding_dim,
+        )
+    elif c.model.lower() == "speedy_speech":
+        model = MyModel(
+            num_chars=num_chars + getattr(c, "add_blank", False),
+            out_channels=c.audio["num_mels"],
+            hidden_channels=c["hidden_channels"],
+            positional_encoding=c["positional_encoding"],
+            encoder_type=c["encoder_type"],
+            encoder_params=c["encoder_params"],
+            decoder_type=c["decoder_type"],
+            decoder_params=c["decoder_params"],
+            c_in_channels=0,
+        )
+    elif c.model.lower() == "align_tts":
+        model = MyModel(
+            num_chars=num_chars + getattr(c, "add_blank", False),
+            out_channels=c.audio["num_mels"],
+            hidden_channels=c["hidden_channels"],
+            hidden_channels_dp=c["hidden_channels_dp"],
+            encoder_type=c["encoder_type"],
+            encoder_params=c["encoder_params"],
+            decoder_type=c["decoder_type"],
+            decoder_params=c["decoder_params"],
+            c_in_channels=0,
+        )
+    return model