update pytorch classifier

Author: minhitbk

art/attacks/carlini_unittest.py

@@ -227,45 +227,3 @@ def test_ptclassifier(self):
 
 
 
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art/classifiers/pytorch.py

@@ -68,7 +68,7 @@ def predict(self, inputs, logits=False):
         # if not logits:
         #     exp = np.exp(preds - np.max(preds, axis=1, keepdims=True))
         #     preds = exp / np.sum(exp, axis=1, keepdims=True)
-        (logit_output, output) = self._model(torch.from_numpy(inputs))
+        (logit_output, output) = self._model(torch.from_numpy(inputs).float())
 
         if logits:
             preds = logit_output.detach().numpy()
@@ -114,6 +114,9 @@ def fit(self, inputs, outputs, batch_size=128, nb_epochs=10):
                     i_batch = torch.from_numpy(inputs[ind[m*batch_size:]])
                     o_batch = torch.from_numpy(outputs[ind[m * batch_size:]])
 
+                # Cast to float
+                i_batch = i_batch.float()
+
                 # Zero the parameter gradients
                 self._optimizer.zero_grad()
 
@@ -137,6 +140,7 @@ def class_gradient(self, inputs, logits=False):
         """
         # Convert the inputs to Tensors
         x = torch.from_numpy(inputs)
+        x = x.float()
         x.requires_grad = True
 
         # Compute the gradient and return
@@ -177,6 +181,7 @@ def loss_gradient(self, inputs, labels):
         """
         # Convert the inputs to Tensors
         inputs_t = torch.from_numpy(inputs)
+        inputs_t = inputs_t.float()
         inputs_t.requires_grad = True
 
         # Convert the labels to Tensors
@@ -219,3 +224,6 @@ def loss_gradient(self, inputs, labels):
     #     return results
 
 
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