feat(lite): add assert log for set_data_by_share

and set_data_by_copy. pylite network input is not
correct when input np is not continuous

GitOrigin-RevId: 1bdeae970a1c3ab723c7bfec8fb4ee53f40e1cfb

lite/pylite/megenginelite/tensor.py

@@ -423,6 +423,9 @@ class LiteTensor(object):
                 numpy.ndarray or ctypes data
         """
         if isinstance(data, np.ndarray):
+            assert data.flags[
+                "C_CONTIGUOUS"
+            ], "input numpy is not continuous, please call input = np.ascontiguousarray(input) before call set_data_by_share"
             assert (
                 self.is_continue
             ), "set_data_by_share can only apply in continue tensor."
@@ -474,6 +477,9 @@ class LiteTensor(object):
             self.copy_from(cpu_tensor)
 
         elif type(data) == np.ndarray:
+            assert data.flags[
+                "C_CONTIGUOUS"
+            ], "input numpy is not continuous, please call input = np.ascontiguousarray(input) before call set_data_by_copy"
             self.layout = LiteLayout(data.shape, data.dtype)
             cpu_tensor.layout = LiteLayout(data.shape, data.dtype)
             cdata = data.ctypes.data_as(POINTER(c_type))

lite/pylite/test/test_tensor.py

@@ -4,6 +4,7 @@ import functools
 
 import numpy as np
 
+import pytest
 from megenginelite import *
 
 
@@ -89,6 +90,32 @@ def test_tensor_set_data():
     assert real_data[1][3] == 20
 
 
+def test_set_data_by_copy_not_continuous():
+    layout = LiteLayout()
+    tensor = LiteTensor(layout)
+
+    arr = np.arange(6).reshape(2, 3).astype(np.uint8).transpose(1, 0)
+
+    with pytest.raises(AssertionError):
+        tensor.set_data_by_copy(arr)
+
+    arr = np.ascontiguousarray(arr)
+    tensor.set_data_by_copy(arr)
+
+
+def test_set_data_by_share_not_continuous():
+    layout = LiteLayout([2, 3], "int8")
+    tensor = LiteTensor(layout)
+
+    arr = np.arange(6).reshape(2, 3).astype(np.uint8).transpose(1, 0)
+
+    with pytest.raises(AssertionError):
+        tensor.set_data_by_share(arr, 2 * 3)
+
+    arr = np.ascontiguousarray(arr)
+    tensor.set_data_by_share(arr.ctypes.data, 2 * 3)
+
+
 def test_fill_zero():
     layout = LiteLayout([4, 8], "int16")
     tensor1 = LiteTensor(layout)