[fix issue#9976] The assignment problem in NDArray (apache#9981)

* fix the assignment problem in NDArray

* add ndarray assignment test

* fix test_ndarray_assignment()

* fix comparison precision for test_ndarray_assignment

* rename test_ndarray_assignment to test_assign_a_row_to_ndarray and fix the dtype in the test

include/mxnet/ndarray.h

@@ -325,6 +325,10 @@ class NDArray {
   inline Engine::VarHandle var() const {
     return ptr_->var;
   }
+  /*! \return byte offset in chunk of the ndarray*/
+  inline size_t byte_offset() const {
+    return byte_offset_;
+  }
   /*!
    * \brief save the content into binary stream
    * \param strm the output stream

src/ndarray/ndarray.cc

@@ -1128,7 +1128,7 @@ void CopyFromToImpl(const NDArray& from, const NDArray& to,
 }
 
 void CopyFromTo(const NDArray& from, const NDArray& to, int priority) {
-  if (from.var() == to.var()) {
+  if (from.var() == to.var() && from.byte_offset() == to.byte_offset()) {
     // skip to copy to itself
     return;
   }

tests/python/unittest/test_ndarray.py

@@ -1099,6 +1099,35 @@ def test_assign_float_value_to_ndarray():
     b[0] = a[0]
     assert same(a, b.asnumpy())
 
+@with_seed()
+def test_assign_a_row_to_ndarray():
+    """Test case from https://github.com/apache/incubator-mxnet/issues/9976"""
+    H, W = 10, 10
+    dtype = np.float32
+    a_np = np.random.random((H, W)).astype(dtype)
+    a_nd = mx.nd.array(a_np)
+
+    # assign directly
+    a_np[0] = a_np[1]
+    a_nd[0] = a_nd[1]
+    assert same(a_np, a_nd.asnumpy())
+
+    # assign a list
+    v = np.random.random(W).astype(dtype).tolist()
+    a_np[1] = v
+    a_nd[1] = v 
+    assert same(a_np, a_nd.asnumpy())
+
+    # assign a np.ndarray
+    v = np.random.random(W).astype(dtype)
+    a_np[2] = v
+    a_nd[2] = v 
+    assert same(a_np, a_nd.asnumpy())
+
+    # assign by slice 
+    a_np[0, :] = a_np[1]
+    a_nd[0, :] = a_nd[1]
+    assert same(a_np, a_nd.asnumpy())
 
 if __name__ == '__main__':
     import nose