Adding Operators (#738)
* Adding Floor and Abs Opertors in autograd and sonnx
* Update test_operation.py
diff --git a/python/singa/autograd.py b/python/singa/autograd.py
index 0fe7b2c..ddfbf03 100644
--- a/python/singa/autograd.py
+++ b/python/singa/autograd.py
@@ -4299,6 +4299,50 @@
return Ceil()(x)[0]
+class Floor(Operator):
+ """
+ Floor takes one input data (Tensor) and produces one output data (Tensor),
+ where the floor is, `y = floor(x)`, is applied to the tensor elementwise
+ """
+
+ def __init__(self):
+ super(Floor, self).__init__()
+
+ def forward(self, x):
+ """
+ forward of floor
+ Args:
+ x (CTensor): input tensor
+ Returns:
+ the output CTensor
+ """
+ return singa.Floor(x)
+
+ def backward(self, dy):
+ """
+ backward of floor. Derivative of floor is 0
+ Args:
+ dy (CTensor): gradient tensor
+ Returns:
+ the gradient tensor over the input tensor.
+ """
+ dy = singa.Tensor(dy.shape(), dy.device())
+ dy.SetFloatValue(0.)
+ return dy
+
+
+def floor(x):
+ """
+ floor takes one input data (Tensor) and produces one output data (Tensor)
+ the value of floor is `y = floor(x)`, is applied to the tensor elementwise.
+ Args:
+ x(Tensor): input tensor.
+ Returns:
+ the output tensor
+ """
+ return Floor()(x)[0]
+
+
class Split(Operator):
"""
Init a Split, Split a tensor into a list of tensors, along the specified
diff --git a/python/singa/sonnx.py b/python/singa/sonnx.py
index db04e73..6ff7cef 100755
--- a/python/singa/sonnx.py
+++ b/python/singa/sonnx.py
@@ -1089,6 +1089,8 @@
'Unsqueeze': 'Unsqueeze',
'NonZero': 'NonZero',
'Ceil': 'Ceil',
+ 'Floor': 'Floor',
+ 'Abs': 'Abs',
# special op
'ScatterElements': 'ScatterElements',
'Cast': 'Cast',
diff --git a/test/python/test_operation.py b/test/python/test_operation.py
index 35de47c..54d2513 100755
--- a/test/python/test_operation.py
+++ b/test/python/test_operation.py
@@ -2881,6 +2881,28 @@
def test_ceil_gpu(self):
self.ceil_test(gpu_dev)
+ def floor_test(self,dev):
+ X = np.array([-1.9,1.2]).astype(np.float32)
+ DY = np.ones((2),dtype=np.float32)
+ y = np.floor(X)
+ x = tensor.from_numpy(X)
+ dy = tensor.from_numpy(DY)
+ x.to_device(dev)
+ dy.to_device(dev)
+
+ result = autograd.floor(x)
+ dx = result.creator.backward(dy.data)
+ DX = np.zeros((2),dtype=np.float32)
+ np.testing.assert_array_almost_equal(tensor.to_numpy(result),y,decimal=5)
+ np.testing.assert_array_almost_equal(tensor.to_numpy(tensor.from_raw_tensor(dx)),DX,decimal=5)
+
+ def test_floor_cpu(self):
+ self.floor_test(cpu_dev)
+
+ @unittest.skipIf(not singa_wrap.USE_CUDA, 'CUDA is not enabled')
+ def test_floor_gpu(self):
+ self.floor_test(gpu_dev)
+
def _test_scatter_elements(self, dev):
# testing witout axis
data = np.zeros((3, 3), dtype=np.float32)
