Merge branch 'master' of https://github.com/PaddlePaddle/PaddleHub

tests/test_downloader.py

@@ -18,7 +18,7 @@ import paddle_hub as hub
 
 class TestDownloader(unittest.TestCase):
     def test_download(self):
-        link = "http://paddlehub.bj.bcebos.com/word2vec/word2vec-dim16-simple-example-2.tar.gz"
+        link = "https://paddlehub.cdn.bcebos.com/word2vec/word2vec_test_module.tar.gz"
         module_path = hub.download_and_uncompress(link)
 
 

tests/test_export_n_load_module.py

@@ -154,36 +154,40 @@ def test_create_w2v_module(use_gpu=False):
         main_program.global_block().var("fourthw"),
     ]
     signature = hub.create_signature(
-        "default", inputs=module_inputs, outputs=[pred_prob])
+        "default",
+        inputs=module_inputs,
+        outputs=[pred_prob],
+        feed_names=["firstw", "secondw", "thirdw", "fourthw"],
+        fetch_names=["pred_prob"])
     hub.create_module(
-        sign_arr=signature,
-        program=fluid.default_main_program(),
-        module_dir=saved_module_dir,
-        word_dict=dictionary)
+        sign_arr=signature, module_dir=saved_module_dir, word_dict=dictionary)
 
 
 def test_load_w2v_module(use_gpu=False):
     saved_module_dir = "./tmp/word2vec_test_module"
     w2v_module = hub.Module(module_dir=saved_module_dir)
-    feed_list, fetch_list, program, generator = w2v_module(
+    feed_dict, fetch_dict, program = w2v_module(
         sign_name="default", trainable=False)
     with fluid.program_guard(main_program=program):
-        with fluid.unique_name.guard(generator):
-            pred_prob = fetch_list[0]
-            pred_word = fluid.layers.argmax(x=pred_prob, axis=1)
-            # set place, executor, datafeeder
-            place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace()
-            exe = fluid.Executor(place)
-            feeder = fluid.DataFeeder(place=place, feed_list=feed_list)
-
-            word_ids = [[1, 2, 3, 4]]
-            result = exe.run(
-                fluid.default_main_program(),
-                feed=feeder.feed(word_ids),
-                fetch_list=[pred_word],
-                return_numpy=True)
-
-            print(result)
+        pred_prob = fetch_dict["pred_prob"]
+        pred_word = fluid.layers.argmax(x=pred_prob, axis=1)
+        # set place, executor, datafeeder
+        place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace()
+        exe = fluid.Executor(place)
+        feed_vars = [
+            feed_dict["firstw"], feed_dict["secondw"], feed_dict["thirdw"],
+            feed_dict["fourthw"]
+        ]
+        feeder = fluid.DataFeeder(place=place, feed_list=feed_vars)
+
+        word_ids = [[1, 2, 3, 4]]
+        result = exe.run(
+            fluid.default_main_program(),
+            feed=feeder.feed(word_ids),
+            fetch_list=[pred_word],
+            return_numpy=True)
+
+        print(result)
 
 
 if __name__ == "__main__":

tests/test_module.py

@@ -15,19 +15,36 @@
 
 import unittest
 import paddle_hub as hub
+import paddle.fluid as fluid
 
 
 class TestModule(unittest.TestCase):
     #TODO(ZeyuChen): add setup for test envrinoment prepration
     def test_word2vec_module_usage(self):
-        pass
-        # url = "http://paddlehub.cdn.bcebos.com/word2vec/word2vec-dim16-simple-example-2.tar.gz"
-        # module = Module(module_url=url)
-        # inputs = [["it", "is", "new"], ["hello", "world"]]
-        # tensor = module._process_input(inputs)
-        # print(tensor)
-        # result = module(inputs)
-        # print(result)
+        url = "https://paddlehub.cdn.bcebos.com/word2vec/word2vec_test_module.tar.gz"
+        w2v_module = hub.Module(module_url=url)
+        feed_dict, fetch_dict, program = w2v_module(
+            sign_name="default", trainable=False)
+        with fluid.program_guard(main_program=program):
+            pred_prob = fetch_dict["pred_prob"]
+            pred_word = fluid.layers.argmax(x=pred_prob, axis=1)
+            # set place, executor, datafeeder
+            place = fluid.CPUPlace()
+            exe = fluid.Executor(place)
+            feed_vars = [
+                feed_dict["firstw"], feed_dict["secondw"], feed_dict["thirdw"],
+                feed_dict["fourthw"]
+            ]
+            feeder = fluid.DataFeeder(place=place, feed_list=feed_vars)
+
+            word_ids = [[1, 2, 3, 4]]
+            result = exe.run(
+                fluid.default_main_program(),
+                feed=feeder.feed(word_ids),
+                fetch_list=[pred_word],
+                return_numpy=True)
+
+            self.assertEqual(result[0], 5)
 
     def test_senta_module_usage(self):
         pass