Merge pull request #1468 from zhengbw0324/master

FIX: update scipy version

conda/meta.yaml

@@ -11,7 +11,7 @@ requirements:
   host:
     - python
     - numpy >=1.17.2
-    - scipy ==1.6.0
+    - scipy >=1.6.0
     - pandas >=1.0.5
     - tqdm >=4.48.2
     - pyyaml >=5.1.0
@@ -20,12 +20,12 @@ requirements:
     - colorlog==4.7.2
     - colorama==0.4.4
     - tensorboard >=2.5.0
-    - tabulate>=0.8.10
-    - plotly>=4.0.0
+    - tabulate >=0.8.10
+    - plotly >=4.0.0
   run:
     - python
     - numpy >=1.17.2
-    - scipy ==1.6.0
+    - scipy >=1.6.0
     - pandas >=1.0.5
     - tqdm >=4.48.2
     - pyyaml >=5.1.0
@@ -34,8 +34,8 @@ requirements:
     - colorlog==4.7.2
     - colorama==0.4.4
     - tensorboard >=2.5.0
-    - tabulate>=0.8.10
-    - plotly>=4.0.0
+    - tabulate >=0.8.10
+    - plotly >=4.0.0
 test:
   imports:
     - recbole

recbole/model/context_aware_recommender/fwfm.py

@@ -58,7 +58,9 @@ def __init__(self, config, dataset):
         self._get_feature2field()
         self.num_fields = len(set(self.feature2field.values()))  # the number of fields
         self.num_pair = self.num_fields * self.num_fields
-
+        self.weight = torch.randn(
+            self.num_fields, self.num_fields, 1, requires_grad=True, device=self.device
+        )
         self.loss = nn.BCEWithLogitsLoss()
 
         # parameters initialization
@@ -106,17 +108,7 @@ def fwfm_layer(self, infeature):
         """
         # get r(Fi, Fj)
         batch_size = infeature.shape[0]
-        para = (
-            torch.randn(self.num_fields * self.num_fields * self.embedding_size)
-            .expand(batch_size, self.num_fields * self.num_fields * self.embedding_size)
-            .to(self.device)
-        )  # [batch_size*num_pairs*emb_dim]
-        para = para.reshape(
-            batch_size, self.num_fields, self.num_fields, self.embedding_size
-        )
-        r = nn.Parameter(
-            para, requires_grad=True
-        )  # [batch_size, num_fields, num_fields, emb_dim]
+        weight = self.weight.expand(batch_size, -1, -1, -1)
 
         fwfm_inter = list()  # [batch_size, num_fields, emb_dim]
         for i in range(self.num_features - 1):

requirements.txt

@@ -1,6 +1,6 @@
 torch>=1.10.0
 numpy>=1.17.2
-scipy==1.6.0
+scipy>=1.6.0
 hyperopt==0.2.5
 pandas>=1.0.5
 tqdm>=4.48.2

setup.py

@@ -9,7 +9,7 @@
 install_requires = [
     "torch>=1.10.0",
     "numpy>=1.17.2",
-    "scipy==1.6.0",
+    "scipy>=1.6.0",
     "pandas>=1.0.5",
     "tqdm>=4.48.2",
     "colorlog==4.7.2",