access2rohit commented on a change in pull request #19541:
URL: https://github.com/apache/incubator-mxnet/pull/19541#discussion_r538948795
##########
File path: tests/nightly/test_np_large_array.py
##########
@@ -1312,6 +1312,219 @@ def test_polyval():
assert poly.grad.shape == poly.shape
assert poly.grad[0] == 4
+
+@use_np
+def test_rot90():
+ inp = np.zeros((1, 2, INT_OVERFLOW))
+ inp[-1, -1, -1] = 1
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.rot90(inp, axes=(1,2))
+ out.backward()
+ assert out.shape == (1, INT_OVERFLOW, 2)
+ assert out[0, 0, 1] == 1
+ assert inp.grad.shape == inp.shape
+ assert inp.grad[-1, -1, -1] == 1
+
+
+@use_np
+def test_squeeze():
+ inp = np.zeros((2, 1, INT_OVERFLOW))
+ inp[-1, -1, -1] = 1
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.squeeze(inp, axis=1)
+ out.backward()
+ assert out.shape == (2, INT_OVERFLOW)
+ assert out[-1, -1] == 1
+ assert inp.grad.shape == inp.shape
+ assert inp.grad[-1, -1, -1] == 1
+
+
+@use_np
+def test_tile():
+ inp = np.array([[0, 1],[2, 3]])
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.tile(inp, (1, HALF_INT_OVERFLOW))
+ out.backward()
+ assert out.shape == (2, INT_OVERFLOW)
+ assert out[-1, -1] == 3
+ assert inp.grad.shape == inp.shape
+ assert inp.grad[-1, -1] == HALF_INT_OVERFLOW
+
+
+@use_np
+def test_trace():
+ N = 2**16
+ inp1 = np.eye(N)
+ inp1.attach_grad()
+ with mx.autograd.record():
+ out1 = np.trace(inp1)
+ out1.backward()
+ assert out1 == N
+ assert inp1.grad.shape == inp1.shape
+ assert inp1.grad[0, 0] == 1 and inp1.grad[-1, -1] == 1
+ inp2 = np.zeros((2, INT_OVERFLOW))
+ inp2[-1, -1] = 1
+ inp2.attach_grad()
+ with mx.autograd.record():
+ out2 = np.trace(inp2, offset=INT_OVERFLOW-2)
+ out2.backward()
+ assert out2 == 1
+ assert inp2.grad.shape == inp2.shape
+ assert inp2.grad[0, -2] == 1 and inp2.grad[-1, -1] == 1
+
+
+@use_np
+def test_tri():
+ N = 2**16
+ data1 = np.tri(N)
+ assert data1.shape == (N, N)
+ assert data1[0, 0] == 1 and data1[-1, -1] == 1
+ assert data1[0, -1] == 0 and data1[-1, 0] == 1
+ data2 = np.tri(2, INT_OVERFLOW, INT_OVERFLOW-2)
Review comment:
same
##########
File path: tests/nightly/test_np_large_array.py
##########
@@ -1312,6 +1312,219 @@ def test_polyval():
assert poly.grad.shape == poly.shape
assert poly.grad[0] == 4
+
+@use_np
+def test_rot90():
+ inp = np.zeros((1, 2, INT_OVERFLOW))
+ inp[-1, -1, -1] = 1
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.rot90(inp, axes=(1,2))
+ out.backward()
+ assert out.shape == (1, INT_OVERFLOW, 2)
+ assert out[0, 0, 1] == 1
+ assert inp.grad.shape == inp.shape
+ assert inp.grad[-1, -1, -1] == 1
+
+
+@use_np
+def test_squeeze():
+ inp = np.zeros((2, 1, INT_OVERFLOW))
+ inp[-1, -1, -1] = 1
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.squeeze(inp, axis=1)
+ out.backward()
+ assert out.shape == (2, INT_OVERFLOW)
+ assert out[-1, -1] == 1
+ assert inp.grad.shape == inp.shape
+ assert inp.grad[-1, -1, -1] == 1
+
+
+@use_np
+def test_tile():
+ inp = np.array([[0, 1],[2, 3]])
+ inp.attach_grad()
+ with mx.autograd.record():
+ out = np.tile(inp, (1, HALF_INT_OVERFLOW))
+ out.backward()
+ assert out.shape == (2, INT_OVERFLOW)
+ assert out[-1, -1] == 3
+ assert inp.grad.shape == inp.shape
+ assert inp.grad[-1, -1] == HALF_INT_OVERFLOW
+
+
+@use_np
+def test_trace():
+ N = 2**16
+ inp1 = np.eye(N)
+ inp1.attach_grad()
+ with mx.autograd.record():
+ out1 = np.trace(inp1)
+ out1.backward()
+ assert out1 == N
+ assert inp1.grad.shape == inp1.shape
+ assert inp1.grad[0, 0] == 1 and inp1.grad[-1, -1] == 1
+ inp2 = np.zeros((2, INT_OVERFLOW))
+ inp2[-1, -1] = 1
+ inp2.attach_grad()
+ with mx.autograd.record():
+ out2 = np.trace(inp2, offset=INT_OVERFLOW-2)
+ out2.backward()
+ assert out2 == 1
+ assert inp2.grad.shape == inp2.shape
+ assert inp2.grad[0, -2] == 1 and inp2.grad[-1, -1] == 1
+
+
+@use_np
+def test_tri():
+ N = 2**16
+ data1 = np.tri(N)
+ assert data1.shape == (N, N)
+ assert data1[0, 0] == 1 and data1[-1, -1] == 1
+ assert data1[0, -1] == 0 and data1[-1, 0] == 1
+ data2 = np.tri(2, INT_OVERFLOW, INT_OVERFLOW-2)
+ assert data2.shape == (2, INT_OVERFLOW)
+ assert data2[0, -1] == 0 and data2[-1, -1] == 1
+
+
+@use_np
+def test_tril():
+ N = 2**16
+ inp1 = np.ones((N, N))
+ inp1.attach_grad()
+ with mx.autograd.record():
+ out1 = np.tril(inp1)
+ out1.backward()
+ assert out1.shape == (N, N)
+ assert out1[-1, -1] == 1 and out1[0, -1] == 0 and out1[-1, 0] == 1
+ assert inp1.grad.shape == inp1.shape
+ assert inp1.grad[-1, -1] == 1 and inp1.grad[0, -1] == 0 and \
+ inp1.grad[-1, 0] == 1
+ inp2 = np.ones((2, INT_OVERFLOW))
Review comment:
same
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