[bug] [refactor] Fix error when ti.init() not called by deprecating Expr.layout_materialized

.gitignore

@@ -1,8 +1,8 @@
 *.swp
 *.swo
 /.vs
-/tags
 /.*_localrc
+/tags
 /Debug
 *.sdf
 /x64

python/taichi/lang/expr.py

@@ -36,7 +36,7 @@ def __init__(self, *args, tb=None):
 
     @python_scope
     def __setitem__(self, key, value):
-        impl.get_runtime().try_materialize()
+        impl.get_runtime().materialize()
         self.initialize_accessor()
         if key is None:
             key = ()
@@ -49,7 +49,7 @@ def __setitem__(self, key, value):
 
     @python_scope
     def __getitem__(self, key):
-        impl.get_runtime().try_materialize()
+        impl.get_runtime().materialize()
         self.initialize_accessor()
         if key is None:
             key = ()
@@ -114,7 +114,7 @@ def fill(self, val):
         from .meta import fill_tensor
         fill_tensor(self, val)
 
-    @deprecated('tensor.parent()', 'tensor.snode().parent()')
+    #@deprecated('tensor.parent()', 'tensor.snode().parent()')
     def parent(self, n=1):
         import taichi as ti
         p = self.snode().parent(n)

python/taichi/lang/impl.py

@@ -143,7 +143,6 @@ def __init__(self, kernels=None):
         self.target_tape = None
         self.inside_complex_kernel = False
         self.kernels = kernels or []
-        Expr.materialize_layout_callback = self.materialize
 
     def get_num_compiled_functions(self):
         return len(self.compiled_functions) + len(self.compiled_grad_functions)
@@ -162,15 +161,10 @@ def create_program(self):
         if self.prog is None:
             self.prog = taichi_lang_core.Program()
 
-    def try_materialize(self):
-        if not Expr.layout_materialized:
-            Expr.materialize_layout_callback()
-
     def materialize(self):
         if self.materialized:
             return
         self.create_program()
-        Expr.layout_materialized = True
 
         def layout():
             for func in self.layout_functions:
@@ -188,8 +182,7 @@ def clear(self):
         if self.prog:
             self.prog.finalize()
             self.prog = None
-        Expr.materialize_layout_callback = None
-        Expr.layout_materialized = False
+        self.materialized = False
 
     def get_tape(self, loss=None):
         from .tape import Tape
@@ -279,8 +272,13 @@ def var(dt, shape=None, offset=None, needs_grad=False):
     assert (offset is not None and shape is None
             ) == False, f'The shape cannot be None when offset is being set'
 
-    assert not get_runtime(
-    ).materialized, 'No new variables can be declared after kernel invocations or Python-scope tensor accesses.'
+    if get_runtime().materialized:
+        raise RuntimeError(
+            "No new variables can be declared after materialization, i.e. kernel invocations "
+            "or Python-scope tensor accesses. I.e., data layouts must be specified before "
+            "any computation. Try appending ti.init() or ti.reset() "
+            "right after 'import taichi as ti' if you are using Jupyter notebook."
+        )
 
     # primal
     x = Expr(taichi_lang_core.make_id_expr(""))

python/taichi/lang/snode.py

@@ -53,7 +53,7 @@ def lazy_grad(self):
         self.ptr.lazy_grad()
 
     def parent(self, n=1):
-        impl.get_runtime().try_materialize()
+        impl.get_runtime().materialize()
         p = self.ptr
         while p and n > 0:
             p = p.parent
@@ -73,7 +73,7 @@ def dim(self):
 
     @property
     def shape(self):
-        impl.get_runtime().try_materialize()
+        impl.get_runtime().materialize()
         dim = self.ptr.num_active_indices()
         ret = [self.ptr.get_num_elements_along_axis(i) for i in range(dim)]
 

python/taichi/misc/test.py

@@ -23,3 +23,11 @@ def __ne__(self, other):
 
 def allclose(x, y, **kwargs):
     return x == approx(y, **kwargs)
+
+
+def make_temp_file(*args, **kwargs):
+    import os
+    from tempfile import mkstemp
+    fd, name = mkstemp(*args, **kwargs)
+    os.close(fd)
+    return name

tests/python/test_image_io.py

@@ -1,14 +1,8 @@
 import taichi as ti
 import numpy as np
+from taichi import make_temp_file
 import pytest
 import os
-from tempfile import mkstemp
-
-
-def make_temp(*args, **kwargs):
-    fd, name = mkstemp(*args, **kwargs)
-    os.close(fd)
-    return name
 
 
 # jpg is also supported but hard to test here since it's lossy:
@@ -28,7 +22,7 @@ def test_image_io(resx, resy, comp, ext, is_tensor, dt):
     pixel = np.random.randint(256, size=shape, dtype=ti.to_numpy_type(dt))
     if is_tensor:
         pixel_t.from_numpy(pixel)
-    fn = make_temp(suffix='.' + ext)
+    fn = make_temp_file(suffix='.' + ext)
     if is_tensor:
         ti.imwrite(pixel_t, fn)
     else:
@@ -50,7 +44,7 @@ def test_image_io_vector(resx, resy, comp, ext, dt):
     pixel = np.random.rand(*shape, comp).astype(ti.to_numpy_type(dt))
     pixel_t = ti.Vector(comp, dt, shape)
     pixel_t.from_numpy(pixel)
-    fn = make_temp(suffix='.' + ext)
+    fn = make_temp_file(suffix='.' + ext)
     ti.imwrite(pixel_t, fn)
     pixel_r = (ti.imread(fn).astype(ti.to_numpy_type(dt)) + 0.5) / 256.0
     assert np.allclose(pixel_r, pixel, atol=2e-2)
@@ -70,7 +64,7 @@ def test_image_io_uint(resx, resy, comp, ext, dt):
     pixel = np.random.randint(256, size=(*shape, comp), dtype=np_type) * np_max
     pixel_t = ti.Vector(comp, dt, shape)
     pixel_t.from_numpy(pixel)
-    fn = make_temp(suffix='.' + ext)
+    fn = make_temp_file(suffix='.' + ext)
     ti.imwrite(pixel_t, fn)
     pixel_r = ti.imread(fn).astype(np_type) * np_max
     assert (pixel_r == pixel).all()

tests/python/test_runtime.py

@@ -0,0 +1,61 @@
+import taichi as ti
+from taichi import make_temp_file
+import sys, os
+
+
+def test_without_init():
+    # We want to check if Taichi works well without ``ti.init()``.
+    # But in test ``ti.init()`` will always be called in last ``@ti.all_archs``.
+    # So we have to create a new Taichi instance, i.e. test in a sandbox.
+    content = '''
+import taichi as ti
+assert ti.cfg.arch == ti.cpu
+
+x = ti.var(ti.i32, (2, 3))
+assert x.shape == (2, 3)
+
+x[1, 2] = 4
+assert x[1, 2] == 4
+'''
+    filename = make_temp_file()
+    with open(filename, 'w') as f:
+        f.write(content)
+    assert os.system(f'{sys.executable} {filename}') == 0
+
+
+@ti.all_archs
+@ti.all_archs
+@ti.must_throw(RuntimeError)
+def test_materialization_after_kernel():
+    x = ti.var(ti.f32, (3, 4))
+
+    @ti.kernel
+    def func():
+        print(x[2, 3])
+
+    func()
+
+    y = ti.var(ti.f32, (2, 3))
+    # ERROR: No new variable should be declared after kernel invocation!
+
+
+@ti.all_archs
+@ti.must_throw(RuntimeError)
+def test_materialization_after_access():
+    x = ti.var(ti.f32, (3, 4))
+
+    print(x[2, 3])
+
+    y = ti.var(ti.f32, (2, 3))
+    # ERROR: No new variable should be declared after Python-scope tensor access!
+
+
+@ti.all_archs
+@ti.must_throw(RuntimeError)
+def test_materialization_after_get_shape():
+    x = ti.var(ti.f32, (3, 4))
+
+    print(x.shape)
+
+    y = ti.var(ti.f32, (2, 3))
+    # ERROR: No new variable should be declared after Python-scope tensor access!