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3
configs/model/cfm/default.yaml
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3
configs/model/cfm/default.yaml
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name: CFM
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solver: euler
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sigma_min: 1e-4
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configs/model/decoder/default.yaml
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configs/model/decoder/default.yaml
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channels: [256, 256]
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dropout: 0.05
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attention_head_dim: 64
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n_blocks: 1
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num_mid_blocks: 2
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num_heads: 2
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act_fn: snakebeta
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configs/model/encoder/default.yaml
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configs/model/encoder/default.yaml
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encoder_type: RoPE Encoder
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encoder_params:
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n_feats: ${model.n_feats}
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n_channels: 192
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filter_channels: 768
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filter_channels_dp: 256
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n_heads: 2
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n_layers: 6
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kernel_size: 3
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p_dropout: 0.1
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spk_emb_dim: 64
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n_spks: 1
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prenet: true
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duration_predictor_params:
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filter_channels_dp: ${model.encoder.encoder_params.filter_channels_dp}
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kernel_size: 3
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p_dropout: ${model.encoder.encoder_params.p_dropout}
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configs/model/matcha.yaml
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configs/model/matcha.yaml
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defaults:
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- _self_
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- encoder: default.yaml
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- decoder: default.yaml
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- cfm: default.yaml
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- optimizer: adam.yaml
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_target_: matcha.models.matcha_tts.MatchaTTS
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n_vocab: 178
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n_spks: ${data.n_spks}
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spk_emb_dim: 64
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n_feats: 80
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data_statistics: ${data.data_statistics}
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out_size: null # Must be divisible by 4
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4
configs/model/optimizer/adam.yaml
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4
configs/model/optimizer/adam.yaml
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_target_: torch.optim.Adam
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_partial_: true
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lr: 1e-4
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weight_decay: 0.0
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