From 5e48a30e9ae260a98613967ca419f66e29e7e0b6 Mon Sep 17 00:00:00 2001
From: Adit <aditshah@berkeley.edu>
Date: Tue, 6 Jun 2023 18:19:35 +0200
Subject: [PATCH 1/3] Minor changes to make it runnable

---
 TM/__init__.py                   |  0
 TM/data/additional_transforms.py | 28 ++++++++++++++++++++++++++++
 TM/data/preprocess.py            |  2 +-
 3 files changed, 29 insertions(+), 1 deletion(-)
 create mode 100644 TM/__init__.py
 create mode 100644 TM/data/additional_transforms.py

diff --git a/TM/__init__.py b/TM/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/TM/data/additional_transforms.py b/TM/data/additional_transforms.py
new file mode 100644
index 0000000..4f6c2e0
--- /dev/null
+++ b/TM/data/additional_transforms.py
@@ -0,0 +1,28 @@
+# Copyright 2017-present, Facebook, Inc.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+
+import torch
+from PIL import ImageEnhance
+
+transformtypedict=dict(Brightness=ImageEnhance.Brightness, Contrast=ImageEnhance.Contrast, Sharpness=ImageEnhance.Sharpness, Color=ImageEnhance.Color)
+
+
+
+class ImageJitter(object):
+    def __init__(self, transformdict):
+        self.transforms = [(transformtypedict[k], transformdict[k]) for k in transformdict]
+
+
+    def __call__(self, img):
+        out = img
+        randtensor = torch.rand(len(self.transforms))
+
+        for i, (transformer, alpha) in enumerate(self.transforms):
+            r = alpha*(randtensor[i]*2.0 -1.0) + 1
+            out = transformer(out).enhance(r).convert('RGB')
+
+        return out
diff --git a/TM/data/preprocess.py b/TM/data/preprocess.py
index 1b4de62..d7e63e6 100644
--- a/TM/data/preprocess.py
+++ b/TM/data/preprocess.py
@@ -5,7 +5,7 @@
 '''
 
 from anndata import read_h5ad
-import scanpy.api as sc
+import scanpy as sc
 import pandas as pd
 from collections import Counter
 import numpy as np

From f02b9b8e9f112c191b256e689ef3eea23ff7fe11 Mon Sep 17 00:00:00 2001
From: Adit <aditshah@berkeley.edu>
Date: Tue, 6 Jun 2023 18:22:33 +0200
Subject: [PATCH 2/3] Actually don't need addl transforms, that's just images

---
 TM/data/__init__.py              |  1 -
 TM/data/additional_transforms.py | 28 ----------------------------
 2 files changed, 29 deletions(-)
 delete mode 100644 TM/data/additional_transforms.py

diff --git a/TM/data/__init__.py b/TM/data/__init__.py
index d77d51f..d5e29d0 100755
--- a/TM/data/__init__.py
+++ b/TM/data/__init__.py
@@ -1,4 +1,3 @@
 from . import datamgr
 from . import dataset
-from . import additional_transforms
 from . import feature_loader
diff --git a/TM/data/additional_transforms.py b/TM/data/additional_transforms.py
deleted file mode 100644
index 4f6c2e0..0000000
--- a/TM/data/additional_transforms.py
+++ /dev/null
@@ -1,28 +0,0 @@
-# Copyright 2017-present, Facebook, Inc.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-
-import torch
-from PIL import ImageEnhance
-
-transformtypedict=dict(Brightness=ImageEnhance.Brightness, Contrast=ImageEnhance.Contrast, Sharpness=ImageEnhance.Sharpness, Color=ImageEnhance.Color)
-
-
-
-class ImageJitter(object):
-    def __init__(self, transformdict):
-        self.transforms = [(transformtypedict[k], transformdict[k]) for k in transformdict]
-
-
-    def __call__(self, img):
-        out = img
-        randtensor = torch.rand(len(self.transforms))
-
-        for i, (transformer, alpha) in enumerate(self.transforms):
-            r = alpha*(randtensor[i]*2.0 -1.0) + 1
-            out = transformer(out).enhance(r).convert('RGB')
-
-        return out

From 28f4d9f0ebdbb74a0770ef344005c8c9705ccb05 Mon Sep 17 00:00:00 2001
From: Adit Shah <aditshah00@gmail.com>
Date: Tue, 6 Jun 2023 19:43:54 +0200
Subject: [PATCH 3/3] Remove import

---
 TM/data/datamgr.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/TM/data/datamgr.py b/TM/data/datamgr.py
index f4551cd..40bd1b4 100755
--- a/TM/data/datamgr.py
+++ b/TM/data/datamgr.py
@@ -4,7 +4,6 @@
 from PIL import Image
 import numpy as np
 import torchvision.transforms as transforms
-import data.additional_transforms as add_transforms
 from data.dataset import SimpleDataset, SetDataset, EpisodicBatchSampler
 from abc import abstractmethod