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Remove self-conditioning and late-stage distortion #95

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Remove self-conditioning and late-stage distortion #95

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13 changes: 0 additions & 13 deletions scripts/inference.py
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Original file line number Diff line number Diff line change
Expand Up @@ -132,11 +132,6 @@ def parse_args():
default=100,
help="Number of integration steps (default: 100)",
)
p.add_argument(
"--use_sc",
action="store_true",
help="Use self-conditioning during integration",
)

p.add_argument(
"--save_gifs",
Expand Down Expand Up @@ -321,7 +316,6 @@ def run_inference_batch(
graphs: list,
method: str,
num_steps: int,
use_sc: bool,
device: str,
water_ratio: float = None,
) -> list:
Expand All @@ -333,7 +327,6 @@ def run_inference_batch(
graphs: List of HeteroData graphs
method: Integration method ('euler' or 'rk4')
num_steps: Number of integration steps
use_sc: Whether to use self-conditioning
device: Device to run on
water_ratio: If provided, sample num_residues * water_ratio waters

Expand All @@ -347,7 +340,6 @@ def run_inference_batch(
results = flow_matcher.rk4_integrate(
graphs,
num_steps=num_steps,
use_sc=use_sc,
device=device,
return_trajectory=True,
water_ratio=water_ratio,
Expand All @@ -356,7 +348,6 @@ def run_inference_batch(
results = flow_matcher.euler_integrate(
graphs,
num_steps=num_steps,
use_sc=use_sc,
device=device,
water_ratio=water_ratio,
)
Expand Down Expand Up @@ -441,7 +432,6 @@ def main():
# Create FlowMatcher
flow_matcher = FlowMatcher(
model=model,
p_self_cond=config.get("p_self_cond", 0.5),
sampling_strategy=config.get("sampling_strategy", "uniform_ball"),
)

Expand Down Expand Up @@ -476,7 +466,6 @@ def main():

# run inference
logger.info(f"Running inference with method={args.method}, steps={args.num_steps}")
logger.info(f"Self-conditioning: {args.use_sc}")
logger.info(f"Threshold for metrics: {args.threshold}Å")
logger.info(f"Batch size: {args.batch_size}")

Expand Down Expand Up @@ -526,7 +515,6 @@ def main():
batch_graphs,
method=args.method,
num_steps=args.num_steps,
use_sc=args.use_sc,
device=args.device,
water_ratio=args.water_ratio,
)
Expand Down Expand Up @@ -627,7 +615,6 @@ def main():
"checkpoint": args.checkpoint,
"method": args.method,
"num_steps": args.num_steps,
"use_sc": args.use_sc,
"threshold": args.threshold,
"include_mates": include_mates,
"water_ratio": args.water_ratio,
Expand Down
14 changes: 0 additions & 14 deletions scripts/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -369,13 +369,6 @@ def parse_args():
)
p.add_argument("--step_gamma", type=float, default=0.5, help="StepLR gamma")

# flow matching
p.add_argument("--use_self_cond", action="store_true")
p.add_argument("--p_self_cond", type=float, default=0.5)
p.add_argument("--use_distortion", action="store_true")
p.add_argument("--p_distort", type=float, default=0.2)
p.add_argument("--t_distort", type=float, default=0.5)
p.add_argument("--sigma_distort", type=float, default=0.5)

# checkpointing
p.add_argument("--save_dir", type=str, default="/home/srivasv/flow_checkpoints")
Expand Down Expand Up @@ -680,7 +673,6 @@ def run_eval_sampling(
out = flow_matcher.rk4_integrate(
graph,
num_steps=args.rk4_steps,
use_sc=args.use_self_cond,
device=device,
return_trajectory=True,
)[0] # rk4_integrate returns a list, get the single result
Expand Down Expand Up @@ -772,7 +764,6 @@ def train_epoch(

metrics = flow_matcher.training_step(
batch,
use_self_conditioning=args.use_self_cond,
accumulation_steps=args.grad_accum_steps,
)

Expand Down Expand Up @@ -1119,12 +1110,7 @@ def main():

flow_matcher = FlowMatcher(
model=model,
p_self_cond=args.p_self_cond,
sampling_strategy=args.sampling_strategy,
use_distortion=args.use_distortion,
p_distort=args.p_distort,
t_distort=args.t_distort,
sigma_distort=args.sigma_distort,
)

optimizer = AdamW(
Expand Down
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