remove run_ce and fix typo (#704)

* remove run_ce and fix typo

* remove run_ce for md

09.gan/README.cn.md

@@ -311,7 +311,7 @@ train_reader = paddle.batch(
 ```python
 if use_gpu:
     exe = fluid.Executor(fluid.CUDAPlace(0))
-else：
+else:
     exe = fluid.Executor(fluid.CPUPlace())
 
 exe.run(fluid.default_startup_program())
@@ -390,7 +390,7 @@ for pass_id in range(epoch):
                                  fetch_list={dg_loss})[0][0]
             losses[1].append(dg_loss_n)
         t_time += (time.time() - s_time)
-        if batch_id % 10 == 0 and not run_ce:
+        if batch_id % 10 == 0 :
             if not os.path.exists(output):
                 os.makedirs(output)
             # 每轮的生成结果

09.gan/dc_gan.py

@@ -41,7 +41,6 @@ add_arg('batch_size',        int,   128,          "Minibatch size.")
 add_arg('epoch',             int,   20,        "The number of epoched to be trained.")
 add_arg('output',            str,   "./output_dcgan", "The directory the model and the test result to be saved to.")
 add_arg('use_gpu',           bool,  True,       "Whether to use GPU to train.")
-add_arg('run_ce',            bool,  False,       "Whether to run for model ce.")
 # yapf: enable
 
 
@@ -52,9 +51,6 @@ def loss(x, label):
 
 def train(args):
 
-    if args.run_ce:
-        np.random.seed(10)
-        fluid.default_startup_program().random_seed = 90
     d_program = fluid.Program()
     dg_program = fluid.Program()
 
@@ -92,13 +88,9 @@ def train(args):
         exe = fluid.Executor(fluid.CUDAPlace(0))
     exe.run(fluid.default_startup_program())
 
-    if args.run_ce:
-        train_reader = paddle.batch(
-            paddle.dataset.mnist.train(), batch_size=args.batch_size)
-    else:
-        train_reader = paddle.batch(
-            paddle.reader.shuffle(paddle.dataset.mnist.train(), buf_size=60000),
-            batch_size=args.batch_size)
+    train_reader = paddle.batch(
+        paddle.reader.shuffle(paddle.dataset.mnist.train(), buf_size=60000),
+        batch_size=args.batch_size)
 
     NUM_TRAIN_TIMES_OF_DG = 2
     const_n = np.random.uniform(
@@ -155,7 +147,7 @@ def train(args):
                     fetch_list={dg_loss})[0][0]
                 losses[1].append(dg_loss_n)
             t_time += (time.time() - s_time)
-            if batch_id % 10 == 0 and not args.run_ce:
+            if batch_id % 10 == 0:
                 if not os.path.exists(args.output):
                     os.makedirs(args.output)
                 # generate image each batch
@@ -174,10 +166,6 @@ def train(args):
                                                   batch_id),
                     bbox_inches='tight')
                 plt.close(fig)
-    if args.run_ce:
-        print("kpis,dcgan_d_train_cost,{}".format(np.mean(losses[0])))
-        print("kpis,dcgan_g_train_cost,{}".format(np.mean(losses[1])))
-        print("kpis,dcgan_duration,{}".format(t_time / args.epoch))
 
 
 if __name__ == "__main__":

09.gan/index.cn.html

@@ -353,7 +353,7 @@ train_reader = paddle.batch(
 ```python
 if use_gpu:
     exe = fluid.Executor(fluid.CUDAPlace(0))
-else：
+else:
     exe = fluid.Executor(fluid.CPUPlace())
 
 exe.run(fluid.default_startup_program())
@@ -432,7 +432,7 @@ for pass_id in range(epoch):
                                  fetch_list={dg_loss})[0][0]
             losses[1].append(dg_loss_n)
         t_time += (time.time() - s_time)
-        if batch_id % 10 == 0 and not run_ce:
+        if batch_id % 10 == 0 :
             if not os.path.exists(output):
                 os.makedirs(output)
             # 每轮的生成结果