Fix issues in tensor_to_tensor()

python/taichi/_kernels.py

@@ -133,8 +133,17 @@ def vector_to_image(mat: template(), arr: ndarray_type.ndarray()):
 
 @kernel
 def tensor_to_tensor(tensor: template(), other: template()):
-    for I in grouped(tensor):
-        tensor[I] = other[I]
+    tensor_offset = static(tensor.snode.ptr.offset)
+    tensor_shape = static(tensor.shape)
+    tensor_offset_new = static([0] * len(tensor_shape) if len(tensor_offset) == 0 else tensor_offset)
+
+    other_offset = static(other.snode.ptr.offset)
+    other_shape = static(other.shape)
+    other_offset_new = static([0] * len(other_shape) if len(other_offset) == 0 else other_offset)
+
+    for I in grouped(ndrange(*tensor_shape)):
+        print('index ', I)
+        tensor[I + tensor_offset_new] = other[I + other_offset_new]
 
 
 @kernel

tests/python/test_field.py

@@ -248,6 +248,20 @@ def test_field_copy_from_with_mismatch_shape():
             x.copy_from(other)
 
 
+@test_utils.test()
+@pytest.mark.parametrize("shape, x_offset, other_offset", [((), (), ()), (8, 4, 0), (8, 0, -4), (8, -4, -4), (8, 8, -4), ((6, 12), (0, 0), (-6, -6)), ((6, 12), (-6, -6), (0, 0)), ((6, 12), (-6, -6), (-6, -6))])
+@pytest.mark.parametrize("dtype", [ti.i32, ti.f32])
+def test_field_copy_from_with_offset(shape, dtype, x_offset, other_offset):
+    x = ti.field(dtype=ti.f32, shape=shape, offset=x_offset)
+    other = ti.field(dtype=dtype, shape=shape, offset=other_offset)
+    other.fill(1)
+    x.copy_from(other)
+    convert = lambda arr: arr[0] if len(arr) == 1 else arr
+    assert convert(x.shape) == shape
+    assert x.dtype == ti.f32
+    assert (x.to_numpy() == 1).all()
+
+
 @test_utils.test()
 def test_field_copy_from_with_non_filed_object():
     import numpy as np