fix bugs

PranavUikey · Jan 19, 2021 · ed2212f · ed2212f
1 parent e90fc3b
commit ed2212f
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Showing 7 changed files with 48 additions and 43 deletions.
diff --git a/CAT/__init__.py b/CAT/__init__.py
@@ -1,5 +1,3 @@
-# coding: utf-8
-
-from .dataset import *
-from .model import *
-from .strategy import *
+import CAT.dataset
+import CAT.model
+import CAT.strategy
diff --git a/CAT/dataset/adaptest_dataset.py b/CAT/dataset/adaptest_dataset.py
@@ -27,8 +27,8 @@ def __init__(self, data, concept_map,
                          num_students, num_questions, num_concepts)
 
         # initialize tested and untested set
-        self.tested = None
-        self.untested = None
+        self._tested = None
+        self._untested = None
         self.reset()
 
     def apply_selection(self, student_idx, question_idx):
@@ -38,27 +38,27 @@ def apply_selection(self, student_idx, question_idx):
             student_idx: int
             question_idx: int
         """
-        assert question_idx in self.untested[student_idx], \
+        assert question_idx in self._untested[student_idx], \
             'Selected question not allowed'
-        self.untested[student_idx].remove(question_idx)
-        self.tested[student_idx].append(question_idx)
+        self._untested[student_idx].remove(question_idx)
+        self._tested[student_idx].append(question_idx)
 
     def reset(self):
         """ 
         Set tested set empty
         """
-        self.tested = defaultdict(deque)
-        self.untested = defaultdict(set)
+        self._tested = defaultdict(deque)
+        self._untested = defaultdict(set)
         for sid in self.data:
-            self.untested[sid] = set(self.data[sid].keys())
+            self._untested[sid] = set(self.data[sid].keys())
 
     @property
     def tested(self):
-        return self.tested
+        return self._tested
 
     @property
     def untested(self):
-        return self.untested
+        return self._untested
 
     def get_tested_dataset(self, last=False):
         """
@@ -69,7 +69,7 @@ def get_tested_dataset(self, last=False):
             TrainDataset
         """
         triplets = []
-        for sid, qids in self.tested.items():
+        for sid, qids in self._tested.items():
             if last:
                 qid = qids[-1]
                 triplets.append((sid, qid, self.data[sid][qid]))

diff --git a/CAT/dataset/dataset.py b/CAT/dataset/dataset.py
@@ -13,18 +13,18 @@ def __init__(self, data, concept_map,
             num_questions: int, total question number
             num_concepts: int, total concept number
         """
-        self.raw_data = data
-        self.concept_map = concept_map
+        self._raw_data = data
+        self._concept_map = concept_map
         self.n_students = num_students
         self.n_questions = num_questions
         self.n_concepts = num_concepts
 
         # reorganize datasets
-        self.data = {}
+        self._data = {}
         for sid, qid, correct in data:
-            self.data.setdefault(sid, {})
-            self.data[sid].setdefault(qid, {})
-            self.data[sid][qid] = correct
+            self._data.setdefault(sid, {})
+            self._data[sid].setdefault(qid, {})
+            self._data[sid][qid] = correct
 
         student_ids = set(x[0] for x in data)
         question_ids = set(x[1] for x in data)
@@ -51,12 +51,12 @@ def num_concepts(self):
 
     @property
     def raw_data(self):
-        return self.raw_data
+        return self._raw_data
 
     @property
     def data(self):
-        return self.data
+        return self._data
 
     @property
     def concept_map(self):
-        return self.concept_map
+        return self._concept_map
diff --git a/CAT/dataset/train_dataset.py b/CAT/dataset/train_dataset.py
@@ -25,8 +25,7 @@ def __init__(self, data, concept_map,
 
     def __getitem__(self, item):
         sid, qid, score = self.raw_data[item]
-        concepts = self.concept_map[qid]
-        return sid, qid, score, concepts
+        return sid, qid, score
 
     def __len__(self):
         return len(self.raw_data)
diff --git a/CAT/model/IRT.py b/CAT/model/IRT.py
@@ -11,11 +11,11 @@
 try:
     # for python module
     from .abstract_model import AbstractModel
-    from ..dataset import AdapTestDataset, TrainDataset, _Dataset
+    from ..dataset import AdapTestDataset, TrainDataset, Dataset
 except (ImportError, SystemError):  # pragma: no cover
     # for python script
     from abstract_model import AbstractModel
-    from dataset import AdapTestDataset, TrainDataset, _Dataset
+    from dataset import AdapTestDataset, TrainDataset, Dataset
 
 
 class IRT(nn.Module):
@@ -57,7 +57,7 @@ def __init__(self, **config):
     def name(self):
         return 'Item Response Theory'
 
-    def init_model(self, data: _Dataset):
+    def init_model(self, data: Dataset):
         self.model = IRT(data.num_students, data.num_questions, self.config['num_dim'])
 
     def train(self, train_data: TrainDataset):
@@ -74,7 +74,7 @@ def train(self, train_data: TrainDataset):
         for ep in range(1, epochs + 1):
             loss = 0.0
             log_step = 1
-            for cnt, (student_ids, question_ids, labels, _) in enumerate(train_loader):
+            for cnt, (student_ids, question_ids, labels) in enumerate(train_loader):
                 student_ids = student_ids.to(device)
                 question_ids = question_ids.to(device)
                 labels = labels.to(device).float()
@@ -83,7 +83,7 @@ def train(self, train_data: TrainDataset):
                 optimizer.zero_grad()
                 bz_loss.backward()
                 optimizer.step()
-                loss += bz_loss.item()
+                loss += bz_loss.data.float()
                 if cnt % log_step == 0:
                     logging.info('Epoch [{}] Batch [{}]: loss={:.5f}'.format(ep, cnt, loss / cnt))
 
@@ -118,16 +118,16 @@ def adaptest_update(self, adaptest_data: AdapTestDataset):
         for ep in range(1, epochs + 1):
             loss = 0.0
             log_steps = 100
-            for cnt, (student_ids, question_ids, correctness, _) in enumerate(dataloader):
+            for cnt, (student_ids, question_ids, labels) in enumerate(dataloader):
                 student_ids = student_ids.to(device)
                 question_ids = question_ids.to(device)
-                correctness = correctness.to(device).float()
+                labels = labels.to(device).float()
                 pred = self.model(student_ids, question_ids).view(-1)
-                bz_loss = self._loss_function(pred, correctness)
+                bz_loss = self._loss_function(pred, labels)
                 optimizer.zero_grad()
                 bz_loss.backward()
                 optimizer.step()
-                loss += bz_loss.item()
+                loss += bz_loss.data.float()
                 if cnt % log_steps == 0:
                     print('Epoch [{}] Batch [{}]: loss={:.3f}'.format(ep, cnt, loss / cnt))
 

diff --git a/CAT/model/abstract_model.py b/CAT/model/abstract_model.py
@@ -1,10 +1,10 @@
 from abc import ABC, abstractmethod
 try:
     # for python module
-    from ..dataset import AdapTestDataset, TrainDataset, _Dataset
+    from ..dataset import AdapTestDataset, TrainDataset, Dataset
 except (ImportError, SystemError):  # pragma: no cover
     # for python script
-    from dataset import AdapTestDataset, TrainDataset, _Dataset
+    from dataset import AdapTestDataset, TrainDataset, Dataset
 
 
 class AbstractModel(ABC):
@@ -23,7 +23,7 @@ def evaluate(self, adaptest_data: AdapTestDataset):
         raise NotImplementedError
 
     @abstractmethod
-    def init_model(self, data: _Dataset):
+    def init_model(self, data: Dataset):
         raise NotImplementedError
 
     @abstractmethod

diff --git a/CAT/strategy/random_strategy.py b/CAT/strategy/random_strategy.py
@@ -1,7 +1,15 @@
 import numpy as np
-from .abstract_strategy import AbstractStrategy
-from ..model import AbstractModel
-from ..dataset import AdapTestDataset
+
+try:
+    # for python module
+    from .abstract_strategy import AbstractStrategy
+    from ..model import AbstractModel
+    from ..dataset import AdapTestDataset
+except (ImportError, SystemError):  # pragma: no cover
+    # for python script
+    from abstract_strategy import AbstractStrategy
+    from model import AbstractModel
+    from dataset import AdapTestDataset
 
 
 class RandomStrategy(AbstractStrategy):
@@ -17,5 +25,5 @@ def adaptest_select(self, model: AbstractModel, adaptest_data: AdapTestDataset):
         selection = {}
         for sid in range(adaptest_data.num_students):
             untested_questions = np.array(list(adaptest_data.untested[sid]))
-            selection[sid] = np.random.randint(len(untested_questions))
+            selection[sid] = untested_questions[np.random.randint(len(untested_questions))]
         return selection