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FelixChan
2025-11-27 15:44:17 +08:00
parent e16c84aab2
commit a34d39430e
153 changed files with 25705 additions and 53 deletions
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16
Amadeus/symbolic_yamls/config-accelerate.yaml
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@ -1,7 +1,9 @@
defaults:
# - nn_params: nb8_embSum_NMT
# - nn_params: remi8
- nn_params: oct8_embSum_diff_t2m_150M_pretrainingv2
# - nn_params: oct8_embSum_diff_t2m_300M_pretrainingv3
# - nn_params: oct8_embSum_diff_t2m_150M_pretrainingv2
- nn_params: oct8_embSum_har_t2m_600M_pretrainingv3
# - nn_params: nb8_embSum_diff_t2m_600M_pretrainingv2
# - nn_params: nb8_embSum_diff_t2m_600M_finetunningv2
# - nn_params: nb8_embSum_subPararell
@ -15,7 +17,7 @@ defaults:
# - nn_params: remi8_main12_head_16_dim512
# - nn_params: nb5_embSum_diff_main12head16dim768_sub3
dataset: Melody # Pop1k7, Pop909, SOD, LakhClean,PretrainingDataset FinetuneDataset
dataset: msmidi # Pop1k7, Pop909, SOD, LakhClean,PretrainingDataset FinetuneDataset
captions_path: dataset/midicaps/train_set.json
# dataset: SymphonyNet_Dataset # Pop1k7, Pop909, SOD, LakhClean
@ -23,28 +25,28 @@ captions_path: dataset/midicaps/train_set.json
use_ddp: True # True, False | distributed data parallel
use_fp16: True # True, False | mixed precision training
use_diff: True # True,use diffusion in subdecoder
use_diff: False # True,use diffusion in subdecoder
diff_steps: 8 # number of diffusion steps
use_dispLoss: True
use_dispLoss: False
lambda_weight: 0.5
tau: 0.5
train_params:
device: cuda
batch_size: 10
batch_size: 9
grad_clip: 1.0
num_iter: 300000 # total number of iterations
num_cycles_for_inference: 10 # number of cycles for inference, iterations_per_validation_cycle * num_cycles_for_inference
num_cycles_for_model_checkpoint: 1 # number of cycles for model checkpoint, iterations_per_validation_cycle * num_cycles_for_model_checkpoint
iterations_per_training_cycle: 10 # number of iterations for logging training loss
iterations_per_validation_cycle: 3000 # number of iterations for validation process
input_length: 3072 # input sequence length3072
input_length: 2048 # input sequence length3072
# you can use focal loss, it it's not used, set focal_gamma to 0
focal_alpha: 1
focal_gamma: 0
# learning rate scheduler: 'cosinelr', 'cosineannealingwarmuprestarts', 'not-using', please check train_utils.py for more details
scheduler : cosinelr
initial_lr: 0.00001
initial_lr: 0.0003
decay_step_rate: 0.8 # means it will reach its lowest point at decay_step_rate * total_num_iter
num_steps_per_cycle: 20000 # number of steps per cycle for 'cosineannealingwarmuprestarts'
warmup_steps: 2000 #number of warmup steps

2
Amadeus/symbolic_yamls/nn_params/oct8_embSum_diff_t2m_150M_pretrainingv2.yaml
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@ -5,7 +5,7 @@ model_name: AmadeusModel
input_embedder_name: SummationEmbedder
main_decoder_name: XtransformerNewPretrainingDecoder
sub_decoder_name: DiffusionDecoder
model_dropout: 0.2
model_dropout: 0
input_embedder:
num_layer: 1
num_head: 8

19
Amadeus/symbolic_yamls/nn_params/oct8_embSum_diff_t2m_150M_pretrainingv3.yaml Normal file
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@ -0,0 +1,19 @@
encoding_scheme: oct
num_features: 8
vocab_name: MusicTokenVocabOct
model_name: AmadeusModel
input_embedder_name: SummationEmbedder
main_decoder_name: XtransformerNewPretrainingDecoder
sub_decoder_name: DiffusionDecoderV2
model_dropout: 0
input_embedder:
num_layer: 1
num_head: 8
main_decoder:
dim_model: 768
num_layer: 16
num_head: 12
sub_decoder:
decout_window_size: 1 # 1 means no previous decoding output added
num_layer: 1
feature_enricher_use: False

19
Amadeus/symbolic_yamls/nn_params/oct8_embSum_diff_t2m_300M_pretrainingv3.yaml Normal file
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@ -0,0 +1,19 @@
encoding_scheme: oct
num_features: 8
vocab_name: MusicTokenVocabOct
model_name: AmadeusModel
input_embedder_name: SummationEmbedder
main_decoder_name: XtransformerNewPretrainingDecoder
sub_decoder_name: DiffusionDecoderV2
model_dropout: 0
input_embedder:
num_layer: 1
num_head: 8
main_decoder:
dim_model: 1080
num_layer: 13
num_head: 12
sub_decoder:
decout_window_size: 1 # 1 means no previous decoding output added
num_layer: 1
feature_enricher_use: False

19
Amadeus/symbolic_yamls/nn_params/oct8_embSum_har_t2m_300M_pretrainingv3 copy.yaml Normal file
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@ -0,0 +1,19 @@
encoding_scheme: oct
num_features: 8
vocab_name: MusicTokenVocabOct
model_name: AmadeusModel
input_embedder_name: SummationEmbedder
main_decoder_name: XtransformerNewPretrainingDecoder
sub_decoder_name: DiffusionDecoderV2
model_dropout: 0
input_embedder:
num_layer: 1
num_head: 8
main_decoder:
dim_model: 1080
num_layer: 13
num_head: 12
sub_decoder:
decout_window_size: 1 # 1 means no previous decoding output added
num_layer: 1
feature_enricher_use: False

19
Amadeus/symbolic_yamls/nn_params/oct8_embSum_har_t2m_300M_pretrainingv3.yaml Normal file
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@ -0,0 +1,19 @@
encoding_scheme: oct
num_features: 8
vocab_name: MusicTokenVocabOct
model_name: AmadeusModel
input_embedder_name: SummationEmbedder
main_decoder_name: XtransformerNewPretrainingDecoder
sub_decoder_name: SelfAttention
model_dropout: 0
input_embedder:
num_layer: 1
num_head: 8
main_decoder:
dim_model: 1080
num_layer: 13
num_head: 12
sub_decoder:
decout_window_size: 3 # 1 means no previous decoding output added
num_layer: 1
feature_enricher_use: False

19
Amadeus/symbolic_yamls/nn_params/oct8_embSum_har_t2m_600M_pretrainingv3.yaml Normal file
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@ -0,0 +1,19 @@
encoding_scheme: oct
num_features: 8
vocab_name: MusicTokenVocabOct
model_name: AmadeusModel
input_embedder_name: SummationEmbedder
main_decoder_name: XtransformerNewPretrainingDecoder
sub_decoder_name: SelfAttention
model_dropout: 0
input_embedder:
num_layer: 1
num_head: 8
main_decoder:
dim_model: 1272
num_layer: 20
num_head: 12
sub_decoder:
decout_window_size: 1 # 1 means no previous decoding output added
num_layer: 1
feature_enricher_use: False