add roi_align api

paddle/fluid/API.spec

@@ -114,6 +114,7 @@ paddle.fluid.layers.pad ArgSpec(args=['x', 'paddings', 'pad_value', 'name'], var
 paddle.fluid.layers.pad_constant_like ArgSpec(args=['x', 'y', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None))
 paddle.fluid.layers.label_smooth ArgSpec(args=['label', 'prior_dist', 'epsilon', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 0.1, 'float32', None))
 paddle.fluid.layers.roi_pool ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale'], varargs=None, keywords=None, defaults=(1, 1, 1.0))
+paddle.fluid.layers.roi_align ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale', 'sampling_ratio'], varargs=None, keywords=None, defaults=(1, 1, 1.0, -1))
 paddle.fluid.layers.dice_loss ArgSpec(args=['input', 'label', 'epsilon'], varargs=None, keywords=None, defaults=(1e-05,))
 paddle.fluid.layers.image_resize ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'resample'], varargs=None, keywords=None, defaults=(None, None, None, 'BILINEAR'))
 paddle.fluid.layers.image_resize_short ArgSpec(args=['input', 'out_short_len', 'resample'], varargs=None, keywords=None, defaults=('BILINEAR',))

paddle/fluid/operators/roi_align_op.cc

@@ -132,6 +132,7 @@ class ROIAlignOpMaker : public framework::OpProtoAndCheckerMaker {
                  "and pooled_w, likewise for height")
         .SetDefault(-1);
     AddComment(R"DOC(
+    
     )DOC");
   }
 };

python/paddle/fluid/layers/nn.py

@@ -94,6 +94,7 @@ __all__ = [
     'pad_constant_like',
     'label_smooth',
     'roi_pool',
+    'roi_align',
     'dice_loss',
     'image_resize',
     'image_resize_short',
@@ -5177,6 +5178,53 @@ def roi_pool(input, rois, pooled_height=1, pooled_width=1, spatial_scale=1.0):
     return pool_out
 
 
+@templatedoc()
+def roi_align(input,
+              rois,
+              pooled_height=1,
+              pooled_width=1,
+              spatial_scale=1.0,
+              sampling_ratio=-1):
+    """
+    ${comment}
+
+    Args:
+        input (Variable): ${x_comment}
+        rois (Variable): ROIs (Regions of Interest) to pool over.
+        pooled_height (integer): ${pooled_height_comment} Default: 1
+        pooled_width (integer): ${pooled_width_comment} Default: 1
+        spatial_scale (float): ${spatial_scale_comment} Default: 1.0
+        sampling_ratio(intger): ${sampling_ratio_comment} Default: -1
+
+    Returns:
+        Variable: ${out_comment}.
+    Examples:
+        .. code-block:: python
+
+            align_out = fluid.layers.roi_align(input=x, 
+                                               rois=rois, 
+                                               pooled_height=7, 
+                                               pooled_width=7,
+                                               spatial_scale=0.5,
+                                               sampling_ratio=-1)
+    """
+    helper = LayerHelper('roi_align', **locals())
+    dtype = helper.input_dtype()
+    align_out = helper.create_tmp_variable(dtype)
+    helper.append_op(
+        type="roi_align",
+        inputs={"X": input,
+                "ROIs": rois},
+        outputs={"Out": align_out},
+        attrs={
+            "pooled_height": pooled_height,
+            "pooled_width": pooled_width,
+            "spatial_scale": spatial_scale,
+            "sampling_ratio": sampling_ratio
+        })
+    return align_out
+
+
 def dice_loss(input, label, epsilon=0.00001):
     """
     Dice loss for comparing the similarity of two batch of data,

python/paddle/fluid/tests/unittests/test_layers.py

@@ -444,6 +444,16 @@ class TestBook(unittest.TestCase):
             self.assertIsNotNone(output)
         print(str(program))
 
+    def test_roi_align(self):
+        program = Program()
+        with program_guard(program):
+            x = layers.data(name="x", shape=[256, 30, 30], dtype="float32")
+            rois = layers.data(
+                name="rois", shape=[4], dtype="float32", lod_level=1)
+            output = layers.roi_align(x, rois, 14, 14, 0.5, 2)
+            self.assertIsNotNone(output)
+        print(str(program))
+
     def test_resize_bilinear(self):
         program = Program()
         with program_guard(program):