From 2445fef38642183297a422ae1d33c7ff0fdbcef1 Mon Sep 17 00:00:00 2001
From: ruri <shipeng1108@163.com>
Date: Tue, 3 Dec 2019 15:41:54 +0800
Subject: [PATCH] Fix density sample (#21506)

---
 python/paddle/fluid/layers/detection.py | 76 ++++++++++++-------------
 1 file changed, 38 insertions(+), 38 deletions(-)

diff --git a/python/paddle/fluid/layers/detection.py b/python/paddle/fluid/layers/detection.py
index 25bada5cb39..226ab2c9293 100644
--- a/python/paddle/fluid/layers/detection.py
+++ b/python/paddle/fluid/layers/detection.py
@@ -1858,14 +1858,14 @@ def density_prior_box(input,
 
         .. code-block:: python
 
-	    #declarative mode
+            #declarative mode
 
-	    import paddle.fluid as fluid
-	    import numpy as np
+            import paddle.fluid as fluid
+            import numpy as np
 
-	    input = fluid.data(name="input", shape=[None,3,6,9])
-	    image = fluid.data(name="image", shape=[None,3,9,12])
-	    box, var = fluid.layers.density_prior_box(
+            input = fluid.data(name="input", shape=[None,3,6,9])
+            image = fluid.data(name="image", shape=[None,3,9,12])
+            box, var = fluid.layers.density_prior_box(
                  input=input,
                  image=image,
                  densities=[4, 2, 1],
@@ -1874,45 +1874,45 @@ def density_prior_box(input,
                  clip=True,
                  flatten_to_2d=True)
 
-	    place = fluid.CPUPlace()
-	    exe = fluid.Executor(place)
-	    exe.run(fluid.default_startup_program())
- 
-	    # prepare a batch of data
-	    input_data = np.random.rand(1,3,6,9).astype("float32")
-	    image_data = np.random.rand(1,3,9,12).astype("float32")
+            place = fluid.CPUPlace()
+            exe = fluid.Executor(place)
+            exe.run(fluid.default_startup_program())
  
-	    box_out, var_out = exe.run(
-	        fluid.default_main_program(),
+            # prepare a batch of data
+            input_data = np.random.rand(1,3,6,9).astype("float32")
+            image_data = np.random.rand(1,3,9,12).astype("float32")
+
+            box_out, var_out = exe.run(
+                fluid.default_main_program(),
                 feed={"input":input_data,
-	              "image":image_data},
+                      "image":image_data},
                 fetch_list=[box,var],
                 return_numpy=True)
- 
-	    print(mask_out.shape)
-	    # (1134, 4)
-            print(z_out.shape)
-	    # (1134, 4)
 
+            # print(box_out.shape)
+            # (1134, 4)
+            # print(var_out.shape)
+            # (1134, 4)
 
-	    #imperative mode
-	    import paddle.fluid.dygraph as dg
 
-	    with dg.guard(place) as g:
-    		input = dg.to_variable(input_data)
-    		image = dg.to_variable(image_data)
-    		box, var = fluid.layers.density_prior_box(
-		    input=input,
-		    image=image,
-		    densities=[4, 2, 1],
-		    fixed_sizes=[32.0, 64.0, 128.0],
-		    fixed_ratios=[1.],
-		    clip=True)
-
-    		print(box.shape)
-		# [6L, 9L, 21L, 4L]
-		print(var.shape)
-		# [6L, 9L, 21L, 4L]
+            #imperative mode
+            import paddle.fluid.dygraph as dg
+
+            with dg.guard(place) as g:
+                input = dg.to_variable(input_data)
+                image = dg.to_variable(image_data)
+                box, var = fluid.layers.density_prior_box(
+                    input=input,
+                    image=image,
+                    densities=[4, 2, 1],
+                    fixed_sizes=[32.0, 64.0, 128.0],
+                    fixed_ratios=[1.],
+                    clip=True)
+
+                # print(box.shape)
+                # [6L, 9L, 21L, 4L]
+                # print(var.shape)
+                # [6L, 9L, 21L, 4L]
 
     """
     helper = LayerHelper("density_prior_box", **locals())
-- 
GitLab