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[Misc] Strictly check ndim with external array #7126

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Jan 12, 2023
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[Misc] Strictly check ndim with external array #7126

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afb7731
Strictly check ndim with external array when ndim is present in ndarr…
turbo0628 Jan 11, 2023
444be47
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Jan 11, 2023
4dcdc97
Skip check when element shape has None
turbo0628 Jan 12, 2023
45b4ebf
Add tests for ndim check
turbo0628 Jan 12, 2023
731d454
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Jan 12, 2023
719176d
Clear field dim in docs
turbo0628 Jan 12, 2023
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2 changes: 1 addition & 1 deletion python/taichi/lang/_ndarray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -137,7 +137,7 @@ def _ndarray_matrix_from_numpy(self, arr, as_vector):
raise TypeError(f"{np.ndarray} expected, but {type(arr)} provided")
if tuple(self.arr.total_shape()) != tuple(arr.shape):
raise ValueError(
f"Mismatch shape: {tuple(self.arr.shape)} expected, but {tuple(arr.shape)} provided"
f"Mismatch shape: {tuple(self.arr.total_shape())} expected, but {tuple(arr.shape)} provided"
)
if not arr.flags.c_contiguous:
arr = np.ascontiguousarray(arr)
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21 changes: 17 additions & 4 deletions python/taichi/lang/kernel_impl.py
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Expand Up @@ -416,11 +416,24 @@ def extract_arg(arg, anno):
shape = tuple(shape)
element_shape = ()
if isinstance(anno.dtype, MatrixType):
if len(shape) < anno.dtype.ndim:
raise ValueError(
f"Invalid argument into ti.types.ndarray() - required element_dim={anno.dtype.ndim}, "
f"but the argument has only {len(shape)} dimensions")
if anno.ndim is not None:
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if len(shape) != anno.dtype.ndim + anno.ndim:
raise ValueError(
f"Invalid argument into ti.types.ndarray() - required array has ndim={anno.ndim} element_dim={anno.dtype.ndim}, "
f"but the argument has only {len(shape)} dimensions"
)
else:
if len(shape) < anno.dtype.ndim:
raise ValueError(
f"Invalid argument into ti.types.ndarray() - required element_dim={anno.dtype.ndim}, "
f"but the argument has only {len(shape)} dimensions"
)
element_shape = shape[-anno.dtype.ndim:]
if element_shape != anno.dtype.get_shape():
raise ValueError(
f"Invalid argument into ti.types.ndarray() - required element_shape={anno.dtype.get_shape()}, "
f"but the argument has element shape of {element_shape}"
)
return to_taichi_type(
arg.dtype), len(shape), element_shape, Layout.AOS
if isinstance(anno, sparse_matrix_builder):
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3 changes: 0 additions & 3 deletions tests/python/test_ndarray.py
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Expand Up @@ -483,9 +483,6 @@ def func(a: ti.types.ndarray(ti.types.vector(n=10, dtype=ti.i32))):
v = np.zeros((6, 10), dtype=np.int32)
func(v)
assert impl.get_runtime().get_num_compiled_functions() == 1
v = np.zeros((6, 11), dtype=np.int32)
func(v)
assert impl.get_runtime().get_num_compiled_functions() == 2


@test_utils.test(arch=supported_archs_taichi_ndarray)
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