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The following commit(s) were added to refs/heads/master by this push:
new a018b2d SINGA-474 fix origin conflict
new ed8ff36 Merge pull request #516 from ShichengChen/operatorConflict
a018b2d is described below
commit a018b2d84f4407bddc10e486f86cfe611c445aee
Author: ShichengChen <[email protected]>
AuthorDate: Thu Aug 15 11:55:09 2019 +0800
SINGA-474 fix origin conflict
---
python/singa/autograd.py | 5 +----
test/python/test_operation.py | 28 ++++++++++++++++++++++++++--
2 files changed, 27 insertions(+), 6 deletions(-)
diff --git a/python/singa/autograd.py b/python/singa/autograd.py
index 64f7342..a480aab 100644
--- a/python/singa/autograd.py
+++ b/python/singa/autograd.py
@@ -460,8 +460,7 @@ def clip(x,min,max):
class Identity(Operation):
def __init__(self):
super(Identity, self).__init__()
- x(CTensor): equal to input tensor
- """
+ def forward(self,x):
return x
def backward(self, dy):
@@ -2186,13 +2185,11 @@ class Log(Operation):
if training:
self.input = x
return singa.Log(x)
-
def backward(self, dy):
dx = singa.PowFloat(self.input,-1)
dx = singa.__mul__(dy, dx)
return dx
-
def log(x):
return Log()(x)[0]
diff --git a/test/python/test_operation.py b/test/python/test_operation.py
index 7f3eebc..8111e11 100755
--- a/test/python/test_operation.py
+++ b/test/python/test_operation.py
@@ -459,7 +459,7 @@ class TestPythonOperation(unittest.TestCase):
np.testing.assert_array_almost_equal(tensor.to_numpy(result), XT)
self.check_shape(dx.shape(), (3, 2))
-
+
def test_Cos_cpu(self):
X = np.array([0.8, -1.2, 3.3, -3.6, -0.5, 0.5]).reshape(3,
2).astype(np.float32)
XT = np.cos(X)
@@ -1221,12 +1221,20 @@ class TestPythonOperation(unittest.TestCase):
dy.to_device(gpu_dev)
result = autograd.transpose(x,(1,2,0))
+ dx = result.creator.backward(dy.data)
+ 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)),
grad, decimal=5)
def test_Sign_cpu(self):
X = np.array([0.8, -1.2, 3.3, -3.6, -0.5, 0.5]).reshape(3,
2).astype(np.float32)
XT = np.sign(X)
+ DY = np.ones((3, 2), dtype = np.float32)
+ x = tensor.from_numpy(X)
+ dy = tensor.from_numpy(DY)
+ x.to_device(gpu_dev)
+ dy.to_device(gpu_dev)
result = autograd.sign(x)
dx = result.creator.backward(dy.data)
DX = np.multiply(DY,0)
@@ -1238,16 +1246,27 @@ class TestPythonOperation(unittest.TestCase):
def test_Sign_gpu(self):
X = np.array([0.8, -1.2, 3.3, -3.6, -0.5, 0.5]).reshape(3,
2).astype(np.float32)
XT = np.sign(X)
-
+ DY = np.ones((3, 2), dtype = np.float32)
+
+ x = tensor.from_numpy(X)
+ dy = tensor.from_numpy(DY)
+ x.to_device(gpu_dev)
+ dy.to_device(gpu_dev)
result = autograd.sign(x)
dx = result.creator.backward(dy.data)
DX = np.multiply(DY,0)
+ np.testing.assert_array_almost_equal(tensor.to_numpy(result), XT,
decimal=5)
+
np.testing.assert_array_almost_equal(tensor.to_numpy(tensor.from_raw_tensor(dx)),
DX, decimal=5)
def test_Log_cpu(self):
X = np.array([0.1,1.0,0.4,1.4,0.9,2.0]).reshape(3,2).astype(np.float32)
XT = np.log(X)
DY = np.ones((3, 2), dtype = np.float32)
+ x = tensor.from_numpy(X)
+ dy = tensor.from_numpy(DY)
+ x.to_device(gpu_dev)
+ dy.to_device(gpu_dev)
result = autograd.log(x)
dx = result.creator.backward(dy.data)
#dx = 1/x
@@ -1260,7 +1279,12 @@ class TestPythonOperation(unittest.TestCase):
def test_Log_gpu(self):
X = np.array([0.1,1.0,0.4,1.4,0.9,2.0]).reshape(3,2).astype(np.float32)
XT = np.log(X)
+ DY = np.ones((3, 2), dtype = np.float32)
+ x = tensor.from_numpy(X)
+ dy = tensor.from_numpy(DY)
+ x.to_device(gpu_dev)
+ dy.to_device(gpu_dev)
result = autograd.log(x)
dx = result.creator.backward(dy.data)
#dx = 1/x
