Download Built-in model parameters from ASE_ANI (#481)

* download resources from ASE_ANI

* update gitignore

* get resources with request

* fix flke8

* rm svn checkout for resources

* update

* fix flake8

.gitignore

@@ -30,6 +30,9 @@ dist
 *.swo
 /download
 /download.tar.xz
+/torchani/resources/*.info
+/torchani/resources/ani-1ccx_8x
+/torchani/resources/ani-2x_8x
 *.qdrep
 *.qdstrm
 *.zip

download.sh

@@ -1,4 +1,5 @@
 #!/bin/bash
 
+# download the data
 wget https://www.dropbox.com/sh/2c8zdqc1hrqsgwy/AAD6l24ngoiFa6DRapF6HPk5a/ -O download.zip
 unzip download.zip -d download || [[ $? == 2 ]]  # unzip return 2 for dropbox created zip file

torchani/models.py

@@ -24,10 +24,12 @@
     model0.species_to_tensor(['C', 'H', 'H', 'H', 'H'])
 """
 import os
+import io
+import requests
+import zipfile
 import torch
 from torch import Tensor
 from typing import Tuple, Optional
-from pkg_resources import resource_filename
 from . import neurochem
 from .nn import SpeciesConverter, SpeciesEnergies
 from .aev import AEVComputer
@@ -70,21 +72,36 @@ def _from_neurochem_resources(cls, info_file_path, periodic_table_index=False, m
 
     @staticmethod
     def _parse_neurochem_resources(info_file_path):
-        def get_resource(file_path):
-            package_name = '.'.join(__name__.split('.')[:-1])
-            return resource_filename(package_name, 'resources/' + file_path)
-
-        info_file = get_resource(info_file_path)
+        def get_resource(resource_path, file_path):
+            return os.path.join(resource_path, 'resources/' + file_path)
+
+        resource_path = os.path.dirname(__file__)
+        local_dir = os.path.expanduser('~/.local/torchani')
+
+        if not os.path.isfile(get_resource(resource_path, info_file_path)):
+            if not os.path.isfile(get_resource(local_dir, info_file_path)):
+                print('Downloading ANI model parameters ...')
+                resource_res = requests.get("https://www.dropbox.com/sh/otrzul6yuye8uzs/AABuaihE22vtaB_rdrI0r6TUa?dl=1")
+                resource_zip = zipfile.ZipFile(io.BytesIO(resource_res.content))
+                try:
+                    resource_zip.extractall(resource_path)
+                except PermissionError:
+                    resource_zip.extractall(local_dir)
+                    resource_path = local_dir
+            else:
+                resource_path = local_dir
+
+        info_file = get_resource(resource_path, info_file_path)
 
         with open(info_file) as f:
             # const_file: Path to the file with the builtin constants.
             # sae_file: Path to the file with the Self Atomic Energies.
             # ensemble_prefix: Prefix of the neurochem resource directories.
             lines = [x.strip() for x in f.readlines()][:4]
             const_file_path, sae_file_path, ensemble_prefix_path, ensemble_size = lines
-            const_file = get_resource(const_file_path)
-            sae_file = get_resource(sae_file_path)
-            ensemble_prefix = get_resource(ensemble_prefix_path)
+            const_file = get_resource(resource_path, const_file_path)
+            sae_file = get_resource(resource_path, sae_file_path)
+            ensemble_prefix = get_resource(resource_path, ensemble_prefix_path)
             ensemble_size = int(ensemble_size)
             consts = neurochem.Constants(const_file)
         return consts, sae_file, ensemble_prefix, ensemble_size