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Submodule RNABERT
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project: scprint_ablation | ||
seed_everything: 50 | ||
set_float32_matmul_precision: True | ||
wandblog: all | ||
log_freq: 200 | ||
log_graph: True | ||
trainer: | ||
precision: 16-mixed | ||
strategy: ddp_find_unused_parameters_true | ||
gradient_clip_val: 40 | ||
log_every_n_steps: 100 | ||
limit_train_batches: 5000 | ||
gradient_clip_algorithm: norm | ||
limit_val_batches: 4000 | ||
limit_test_batches: 1 # we don't perform tests this way | ||
reload_dataloaders_every_n_epochs: 20 | ||
max_epochs: 21 | ||
accumulate_grad_batches: 1 | ||
logger: | ||
- class_path: lightning.pytorch.loggers.WandbLogger | ||
init_args: | ||
project: ${project} | ||
save_dir: /lustre/fswork/projects/rech/xeg/uat95fg/ #/pasteur/zeus/projets/p02/ml4ig_hot/Users/jkalfon/ #/data/log/ | ||
offline: False | ||
callbacks: | ||
- class_path: lightning.pytorch.callbacks.StochasticWeightAveraging | ||
init_args: | ||
swa_lrs: 0.03 | ||
- class_path: lightning.pytorch.callbacks.ModelCheckpoint | ||
init_args: | ||
monitor: val_loss | ||
save_top_k: 3 | ||
save_last: True | ||
scprint_training: | ||
run_full_forward: False | ||
# noise: [0.6] | ||
do_ecs: False | ||
do_denoise: False | ||
class_embd_diss_scale: 0.1 | ||
do_generate: True | ||
test_every: 5 | ||
do_cce: False | ||
mask_ratio: 0.3 #["TF"] | ||
model: | ||
dropout: 0.1 | ||
num_heads_kv: 2 | ||
transformer: flash | ||
mvc_decoder: inner product | ||
residual_in_fp32: True | ||
checkpointing: True | ||
cell_specific_blocks: True | ||
fused_dropout_add_ln: False | ||
prenorm: True | ||
fused_mlp: False | ||
fused_bias_fc: False | ||
drop_path_rate: 0 | ||
freeze_embeddings: True | ||
normalization: log | ||
pred_embedding: | ||
- cell_type_ontology_term_id | ||
data: | ||
organisms: | ||
- NCBITaxon:9606 | ||
gene_position_tolerance: 10_000 | ||
gene_embeddings: /lustre/fswork/projects/rech/xeg/uat95fg/gene_embeddings.parquet | ||
collection_name: scPRINT-V2 (100 random humans) #scPRINT-V2 (good quality) | ||
how: random expr | ||
max_len: 2200 | ||
pin_memory: True | ||
prefetch_factor: 3 | ||
# metacell_mode: 0.2 | ||
weight_scaler: 200 | ||
do_gene_pos: ./data/main/biomart_pos.parquet | ||
add_zero_genes: 0 | ||
train_oversampling_per_epoch: 0.15 | ||
validation_split: 0.05 | ||
test_split: 0.02 | ||
batch_size: 32 | ||
num_workers: 20 | ||
hierarchical_clss: | ||
- cell_type_ontology_term_id | ||
- tissue_ontology_term_id | ||
- disease_ontology_term_id | ||
- age_group | ||
- assay_ontology_term_id | ||
- self_reported_ethnicity_ontology_term_id | ||
clss_to_weight: | ||
- clust_cell_type | ||
- tissue_ontology_term_id | ||
- disease_ontology_term_id | ||
- age_group | ||
- assay_ontology_term_id | ||
- self_reported_ethnicity_ontology_term_id | ||
- sex_ontology_term_id | ||
- organism_ontology_term_id | ||
- cell_culture | ||
# - nnz | ||
clss_to_predict: | ||
- cell_type_ontology_term_id | ||
- tissue_ontology_term_id | ||
- disease_ontology_term_id | ||
- age_group | ||
- assay_ontology_term_id | ||
- self_reported_ethnicity_ontology_term_id | ||
- sex_ontology_term_id | ||
- organism_ontology_term_id |
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###### | ||
scprint_training: | ||
run_full_forward: True | ||
noise: [0.6] | ||
do_denoise: True | ||
class_embd_diss_scale: 0.1 | ||
do_generate: True | ||
do_cce: True | ||
|
||
###### TF masking | ||
scprint_training: | ||
mask_ratio: ["TF"] | ||
|
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##### | ||
scprint_training: | ||
do_ecs: True | ||
|
||
##### Test cheap vs esm2 vs learnt | ||
|
||
|
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##### untrained model’s performance | ||
trainer: | ||
limit_train_batches: 1 | ||
limit_val_batches: 200 | ||
limit_test_batches: 1 # we don't perform tests this way | ||
max_epochs: 2 | ||
scprint_training: | ||
test_every: 1 | ||
|
||
##### Test attention bias faded vs none (MAKE SURE RIGHT DIR (T)) | ||
model: | ||
attn_bias: full | ||
|
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##### | ||
model: | ||
dropout: 0 | ||
num_heads_kv: 4 | ||
|
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##### | ||
model: | ||
cell_specific_blocks: False | ||
|
||
##### | ||
model: | ||
freeze_embeddings: False | ||
|
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##### | ||
model: | ||
normalization: sum | ||
|
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##### no zinb vs mse vs both | ||
model: | ||
zinb: False | ||
|
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##### no zinb vs mse vs both | ||
scprint_training: | ||
zinb_and_mse: True | ||
|
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#### | ||
model: | ||
depth_atinput: True | ||
|
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#### | ||
scprint_training: | ||
do_mvc: True | ||
|
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##### need to run them until the end | ||
data: | ||
organisms: | ||
- NCBITaxon:9606 | ||
- NCBITaxon:10090 | ||
collection_name: scPRINT-V2 (good quality) | ||
|
||
##### need to run them until the end | ||
data: | ||
organisms: | ||
- NCBITaxon:9606 | ||
- NCBITaxon:10090 | ||
collection_name: scPRINT-V2 full | ||
|
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##### | ||
data: | ||
gene_position_tolerance: 1000 | ||
|
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##### | ||
data: | ||
do_gene_pos: False | ||
|
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##### | ||
data: | ||
weight_scaler: 3000 | ||
|
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##### Test multi context vs fixed | ||
scprint_training: | ||
var_context_length: True | ||
data: | ||
max_len: 3200 | ||
|
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###### | ||
data: | ||
metacell_mode: 0.2 | ||
|
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##### | ||
data: | ||
clss_to_weight: | ||
- clust_cell_type | ||
- tissue_ontology_term_id | ||
- disease_ontology_term_id | ||
- age_group | ||
- assay_ontology_term_id | ||
- self_reported_ethnicity_ontology_term_id | ||
- sex_ontology_term_id | ||
- organism_ontology_term_id | ||
- cell_culture | ||
- nnz | ||
|
||
##### | ||
data: | ||
clss_to_weight: | ||
- cell_type_ontology_term_id | ||
- tissue_ontology_term_id | ||
- disease_ontology_term_id | ||
- age_group | ||
- assay_ontology_term_id | ||
- self_reported_ethnicity_ontology_term_id | ||
- sex_ontology_term_id | ||
- organism_ontology_term_id |
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