nudles commented on a change in pull request #478: SINGA-473 (Implement ONNX
Operators in Autograd: Trigonometry functions)
URL: https://github.com/apache/incubator-singa/pull/478#discussion_r308032764
##########
File path: test/python/test_operation.py
##########
@@ -322,6 +322,294 @@ def test_LeakyRelu(self):
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)
+ x = tensor.from_numpy(X)
+ x.to_device(cpu_dev)
+
+ result = autograd.cos(x)
+ dx = result.creator.backward(x.data)
+
+ np.testing.assert_array_almost_equal(tensor.to_numpy(result), XT,
decimal=5)
+ self.check_shape(dx.shape(), (3, 2))
+
+ def test_Cos_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.cos(X)
+ x = tensor.from_numpy(X)
+ x.to_device(gpu_dev)
+
+ result = autograd.cos(x)
+ dx = result.creator.backward(x.data)
+
+ np.testing.assert_array_almost_equal(tensor.to_numpy(result), XT,
decimal=5)
+ self.check_shape(dx.shape(), (3, 2))
+
+ def test_Cosh_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.cosh(X)
+ x = tensor.from_numpy(X)
+ x.to_device(cpu_dev)
+
+ result = autograd.cosh(x)
+ dx = result.creator.backward(x.data)
+
+ np.testing.assert_array_almost_equal(tensor.to_numpy(result), XT,
decimal=5)
Review comment:
the backward results are not tested..
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