fix some path/download problems (#3643)

PaddleRec/din/README.md

@@ -41,6 +41,9 @@ cd data && sh data_process.sh && cd ..
 pip install pandas
 ```
 
+**Windows系统下请用户自行下载数据进行解压，下载链接为:[reviews_Electronics](http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/reviews_Electronics_5.json.gz)和[meta_Electronics](http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/meta_Electronics.json.gz)。**
+
+
 * Step 2: 产生训练集、测试集和config文件
 ```
 python build_dataset.py

PaddleRec/din/train.py

@@ -136,8 +136,8 @@ def train():
 
                 if (global_step > 400000 and global_step % PRINT_STEP == 0) or (
                         global_step <= 400000 and global_step % 50000 == 0):
-                    save_dir = args.model_dir + "/global_step_" + str(
-                        global_step)
+                    save_dir = os.path.join(args.model_dir, "/global_step_" + str(
+                        global_step))
                     feed_var_name = [
                         "hist_item_seq", "hist_cat_seq", "target_item",
                         "target_cat", "label", "mask", "target_item_seq",

PaddleRec/gnn/README.md

@@ -40,11 +40,12 @@ SR-GNN模型的介绍可以参阅论文[Session-based Recommendation with Graph
 
 * Step 1: 运行如下命令,下载DIGINETICA数据集并进行预处理
 ```
-cd data && sh download.sh
+cd data && python download.py
 ```
 
 * Step 2: 产生训练集、测试集和config文件
 ```
+mkdir diginetica
 python preprocess.py --dataset diginetica
 cd ..
 ```

PaddleRec/gnn/data/download.py

+import requests
+import sys
+import time
+import os
+
+lasttime = time.time()
+FLUSH_INTERVAL = 0.1
+
+
+def progress(str, end=False):
+    global lasttime
+    if end:
+        str += "\n"
+        lasttime = 0
+    if time.time() - lasttime >= FLUSH_INTERVAL:
+        sys.stdout.write("\r%s" % str)
+        lasttime = time.time()
+        sys.stdout.flush()
+
+
+def _download_file(url, savepath, print_progress):
+    r = requests.get(url, stream=True)
+    total_length = r.headers.get('content-length')
+
+    if total_length is None:
+        with open(savepath, 'wb') as f:
+            shutil.copyfileobj(r.raw, f)
+    else:
+        with open(savepath, 'wb') as f:
+            dl = 0
+            total_length = int(total_length)
+            starttime = time.time()
+            if print_progress:
+                print("Downloading %s" % os.path.basename(savepath))
+            for data in r.iter_content(chunk_size=4096):
+                dl += len(data)
+                f.write(data)
+                if print_progress:
+                    done = int(50 * dl / total_length)
+                    progress("[%-50s] %.2f%%" %
+                             ('=' * done, float(100 * dl) / total_length))
+        if print_progress:
+            progress("[%-50s] %.2f%%" % ('=' * 50, 100), end=True)
+
+
+_download_file("https://sr-gnn.bj.bcebos.com/train-item-views.csv",
+               "./train-item-views.csv", True)

PaddleRec/gnn/data/download.sh

-#!/bin/bash
-
-wget --no-check-certificate https://sr-gnn.bj.bcebos.com/train-item-views.csv
-mkdir diginetica

PaddleRec/gnn/infer.py

@@ -60,7 +60,7 @@ def infer(args):
     infer_program = fluid.default_main_program().clone(for_test=True)
 
     for epoch_num in range(args.start_index, args.last_index + 1):
-        model_path = args.model_path + "epoch_" + str(epoch_num)
+        model_path = os.path.join(args.model_path,  "epoch_" + str(epoch_num))
         try:
             if not os.path.exists(model_path):
                 raise ValueError()

PaddleRec/gnn/train.py

@@ -139,7 +139,7 @@ def train():
         except fluid.core.EOFException:
             py_reader.reset()
         logger.info("epoch loss: %.4lf" % (np.mean(epoch_sum)))
-        save_dir = args.model_path + "/epoch_" + str(i)
+        save_dir = os.path.join(args.model_path, "epoch_" + str(i))
         fetch_vars = [loss, acc]
         fluid.io.save_inference_model(save_dir, feed_list, fetch_vars, exe)
         logger.info("model saved in " + save_dir)