From 03063f2510f3ce8cebdddc04f1ca54a8b84a2317 Mon Sep 17 00:00:00 2001
From: Chaitanya Prakash Bapat <chai.bapat@gmail.com>
Date: Thu, 15 Aug 2019 23:45:07 -0700
Subject: [PATCH] Add power, exponent, log ops large tensor support (#15794)

* power, exponent, log ops

* lint

* Trigger notification

* Trigger notification

* Trigger notification
---
 tests/nightly/test_large_array.py | 66 +++++++++++++++++++++++++++++++
 1 file changed, 66 insertions(+)

diff --git a/tests/nightly/test_large_array.py b/tests/nightly/test_large_array.py
index 585748ee59b1..02c867720609 100644
--- a/tests/nightly/test_large_array.py
+++ b/tests/nightly/test_large_array.py
@@ -444,6 +444,72 @@ def test_topk():
     assert l.sum() == np.sum(np.arange(0, SMALL_Y))
 
 
+def test_exponent_logarithm_operators():
+    a = 2*nd.ones(shape=(LARGE_X, SMALL_Y))
+    # exponent
+    result = nd.exp(a)
+    assert result[0][-1] == 7.389056
+    assert result.shape == a.shape
+
+    # exponent minus 1
+    result = nd.expm1(a)
+    assert result[0][-1] == 6.389056
+    assert result.shape == a.shape
+
+    # log2
+    result = nd.log2(a)
+    assert result[0][-1] == 1
+    assert result.shape == a.shape
+
+    # log10
+    result = nd.log10(a)
+    assert result[0][-1] == 0.30103
+    assert result.shape == a.shape
+
+    # log1p
+    result = nd.log1p(a)
+    assert result[0][-1] == 1.0986123
+    assert result.shape == a.shape
+
+    # log
+    result = nd.log(a)
+    assert result[0][-1] == 0.6931472
+    assert result.shape == a.shape
+
+
+def test_power_operators():
+    a = 2*nd.ones(shape=(LARGE_X, SMALL_Y))
+    # sqrt
+    result = nd.sqrt(a)
+    assert result[0][-1] == 1.4142135
+    assert result.shape == a.shape
+
+    # rsqrt
+    result = nd.rsqrt(a)
+    assert result[0][-1] == 0.70710677
+    assert result.shape == a.shape
+
+    # cbrt
+    result = nd.cbrt(a)
+    assert result[0][-1] == 1.2599211
+    assert result.shape == a.shape
+
+    # rcbrt
+    result = nd.rcbrt(a)
+    assert result[0][-1] == 0.7937005
+    assert result.shape == a.shape
+
+    # square
+    result = nd.square(a)
+    assert result[0][-1] == 4
+    assert result.shape == a.shape
+
+    # reciprocal
+    result = nd.reciprocal(a)
+    assert result[0][-1] == 0.5
+    assert result.shape == a.shape
+
+
 def test_sequence_mask():
     # Sequence Mask input [max_sequence_length, batch_size, other_feature_dims]
     # test with input batch_size = 2