Delete tensorflow version

MANIFEST.in

@@ -1,2 +1,2 @@
 # MANIFEST.in
-include fcd/ChemNet_v0.13_pretrained.h5
+include fcd/ChemNet_v0.13_pretrained.pt

README.md

@@ -11,27 +11,21 @@ You can install the FCD using
 pip install fcd
 ```
 
-rdkit is best install via conda
-```
-conda install rdkit -c rdkit
-```
-
 # Requirements
 ```
-python>3<3.8
 numpy
-tensorflow>1.8
-keras>2.1
+torch
 scipy
+rdkit
 ```
-rdkit is causing troubles with python3.8 for me. You might wanna opt for 3.7.
-For the effect of versions on results see `tests/test_results.csv`.
-Using the current versions of tensorflow (2.1.0) and keras (2.3.1) results differ from previous versions but
-are probably negligible.
-
 
+# Updates
 ## Version 1.1 changes
 - Got rid of unneeded imports
 - `load_ref_model` doesn't need an argument any more to load a model.
 - `canonical` and `canonical_smiles` now return `None` for invalid smiles.
-- Added `get_fcd` as a quick way to get a the fcd score from two lists of smiles.
+- Added `get_fcd` as a quick way to get a the fcd score from two lists of smiles.
+
+## Version 1.2 changes
+- Ported the package to pytorch with the help of https://github.com/insilicomedicine/fcd_torch
+- pytorch allows a lighter package and is more popular than Tensorflow which saves an additional install

fcd/__init__.py

@@ -1,4 +1,4 @@
-from .FCD import calculate_frechet_distance, build_masked_loss, masked_accuracy, get_one_hot, myGenerator_predict, \
-    load_ref_model, get_predictions, canonical, canonical_smiles, get_fcd
+from .fcd import get_fcd, get_predictions, load_ref_model
+from .utils import calculate_frechet_distance, canonical_smiles
 
-__version__ = "1.1"
+__version__ = "1.2"

fcd_torch/fcd.py → fcd/fcd.py

@@ -30,7 +30,7 @@ def load_ref_model(model_path: Optional[str] = None):
 
     if model_path is None:
         chemnet_model_filename = "ChemNet_v0.13_pretrained.pt"
-        model_bytes = pkgutil.get_data("fcd_torch", chemnet_model_filename)
+        model_bytes = pkgutil.get_data("fcd", chemnet_model_filename)
 
         tmpdir = tempfile.TemporaryDirectory()
         model_path = os.path.join(tmpdir.name, chemnet_model_filename)