Fix issues in ext_arr_to_tensor()

python/taichi/_kernels.py

@@ -148,8 +148,12 @@ def tensor_to_tensor(tensor: template(), other: template()):
 
 @kernel
 def ext_arr_to_tensor(arr: ndarray_type.ndarray(), tensor: template()):
+    offset = static(tensor.snode.ptr.offset)
+    shape = static(tensor.shape)
+    # default value of offset is [], replace it with [0] * len
+    offset_new = static([0] * len(shape) if len(offset) == 0 else offset)
     for I in grouped(tensor):
-        tensor[I] = arr[I]
+        tensor[I] = arr[I - offset_new]
 
 
 @kernel

tests/python/test_field.py

@@ -84,6 +84,30 @@ def test_scalr_field_from_numpy(dtype, shape):
     x.from_numpy(arr)
 
 
+@pytest.mark.parametrize("dtype", data_types)
+@pytest.mark.parametrize("shape, offset", [((), ()), (8, 0), (8, 8), (8, -4), ((6, 12), (-4, -4)), ((6, 12), (-4, 4)), ((6, 12), (4, -4)), ((6, 12), (8, 8))])
+@test_utils.test(arch=get_host_arch_list())
+def test_scalr_field_from_numpy_with_offset(dtype, shape, offset):
+    import numpy as np
+
+    x = ti.field(dtype=dtype, shape=shape, offset=offset)
+    # use the corresponding dtype for the numpy array.
+    numpy_dtypes = {
+        ti.i32: np.int32,
+        ti.f32: np.float32,
+        ti.f64: np.float64,
+        ti.i64: np.int64,
+    }
+    arr = np.ones(shape, dtype=numpy_dtypes[dtype])
+    x.from_numpy(arr)
+
+    def mat_equal(A, B, tol=1e-6):
+        return np.max(np.abs(A - B)) < tol
+
+    tol = 1e-5 if dtype == ti.f32 else 1e-12
+    assert mat_equal(x.to_numpy(), arr, tol=tol)
+
+
 @pytest.mark.parametrize("dtype", data_types)
 @pytest.mark.parametrize("shape", field_shapes)
 @test_utils.test(arch=get_host_arch_list())