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Improve inference helper and update documentation #5

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4 changes: 2 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@ import numpy as np
from torch.utils.data import DataLoader
from torchvision.transforms import v2
from torchvision.transforms import InterpolationMode
from github.datasets.h5py_dataset import H5PYDataset
from phoenix.datasets.h5py_dataset import H5PYDataset

gene_path = './xenium_human_multi.npy'
gene_list = list(np.load(gene_path))
Expand Down Expand Up @@ -122,7 +122,7 @@ print("Output:", output.size())

To predict gene expression from histology images use
```python
from github.helpers.inference import FlowPipeline
from phoenix.helpers.inference import FlowPipeline

pipeline = FlowPipeline(
model=flow_model,
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4 changes: 2 additions & 2 deletions phoenix/helpers/inference.py
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Expand Up @@ -63,9 +63,9 @@ def __call__(self, gene_list: list, dataloader: DataLoader):

pred_list, coords_list = [], []
for batch in tqdm(dataloader, desc='Flow sampling'):
image, coords = batch[0].cuda(), batch[1]
image, coords = batch[0].to(device), batch[1]
feats = self.model.vision_forward(image)
noise = torch.randn(image.size(0), len(gene_list), 1).cuda()
noise = torch.randn(image.size(0), len(gene_list), 1, device=device)

gex_pred = run_flow(
flow_model=self.model,
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