Cannot do mul for int tensors
Nobody has claimed this yet.
Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 45/100
- Issue type
- Bug
- Clarity
- Clearly specified
- Activity status
- Stale
- Domain
- machine-learning
Research direction
Reproduce the failure with the provided Python test case, then inspect tensor.cc around line 932 and the Mul operator's CUDA handling for int tensors. Done means the test runs without the unknown data type error and returns the expected product for the int32 inputs.
Written by the indexing model from the issue text.
Description
Hi, @dcslin , we cannot do the mul operator for int tensors:
The error is:
F0324 05:04:22.542809 14739 tensor.cc:932] Unknown combination of data type kInt and language kCuda
please use this test case:
x1 = np.array([1], dtype=np.int32)
x2 = np.array([256], dtype=np.int32)
x1 = tensor.from_numpy(x1)
x1.to_device(gpu_dev)
x2 = tensor.from_numpy(x2)
x2.to_device(gpu_dev)
y = autograd.Mul()(x1, x2)
print(tensor.to_numpy(y[0]))
- Dominant language
- C++
- Stars
- 3.6k
- Forks
- 1.3k
- PR merge metrics
- No merged PRs in 30d
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
More from apache/singa
-
Difficulty 2/5 1-3 hours Newbie friendliness 42/100
-
Difficulty 5/5 Over a week Newbie friendliness 20/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 15/100
-
Difficulty 4/5 3-5 days Newbie friendliness 35/100
Similar issues
-
Difficulty 1/5 Under an hour Newbie friendliness 90/100
AXERA-TECH/ax-llm#77 ·
-
Difficulty 1/5 Under an hour Newbie friendliness 90/100
games-on-whales/wolf#509 ·
-
Difficulty 2/5 1-3 hours Newbie friendliness 82/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
-
bug-unconfirmed
Difficulty 2/5 1-3 hours Newbie friendliness 76/100