kainzhong commented on code in PR #604:
URL: https://github.com/apache/tvm-ffi/pull/604#discussion_r3352763175
##########
python/tvm_ffi/cython/tensor.pxi:
##########
@@ -276,6 +276,52 @@ cdef class Tensor(CObject):
"""Tensor shape as a tuple of integers."""
return tuple(self.cdltensor.shape[i] for i in
range(self.cdltensor.ndim))
+ @property
+ def ndim(self) -> int:
+ """Number of dimensions of the tensor."""
+ return self.cdltensor.ndim
+
+ def numel(self) -> int:
+ """Total number of elements in the tensor."""
+ cdef int64_t count = 1
+ cdef int i
+ for i in range(self.cdltensor.ndim):
+ count *= self.cdltensor.shape[i]
+ return count
+
+ def size(self, idx: int) -> int:
+ """Get the size of the ``idx``-th dimension. Negative ``idx`` counts
from the last dimension.
+ """
+ cdef int ndim = self.cdltensor.ndim
+ if idx < -ndim or idx >= ndim:
+ raise IndexError(
+ f"Dimension {idx} out of range for tensor with {ndim}
dimensions"
+ )
+ if idx < 0:
+ idx += ndim
+ return self.cdltensor.shape[idx]
+
+ def is_contiguous(self) -> bool:
+ """True if the Tensor is C-contiguous (row-major), False otherwise."""
+ if self.cdltensor.strides == NULL:
+ return True
Review Comment:
I think this matches the C++ API implementation in
https://github.com/apache/tvm-ffi/blob/8ccfe1b9d05fb7e067f8d5b98ac60159c23bb35e/include/tvm/ffi/container/tensor.h#L57
Looks like `strides` will handle this case correctly. In my (4, 0, 4) case
the strides is (0, 4, 1), which matches `is_contiguous`'s expected stride so it
still returns True
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