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The following code currently fails due to JIT not supporting the summarization of tensor lists:
from typing import List import torch def test_func(x: List[torch.Tensor]) -> torch.Tensor: return sum(x) test_input = [torch.randn(1,2,4,4) for i in range(5)] out_test = test_func(test_input) # Works jit_test = torch.jit.script(test_func) # Fails out_jit = jit_test(test_input)
It would be nice if JIT would work here for use cases like these.
No response
This feature already works in normal PyTorch and it's simple enough that many would probably expect it to work in JIT.
The text was updated successfully, but these errors were encountered:
regular sum also seems not very nice in terms of computational complexity (unless JIT can optimize it). A related feature request: #27522
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🚀 The feature, motivation and pitch
The following code currently fails due to JIT not supporting the summarization of tensor lists:
It would be nice if JIT would work here for use cases like these.
Alternatives
No response
Additional context
This feature already works in normal PyTorch and it's simple enough that many would probably expect it to work in JIT.
The text was updated successfully, but these errors were encountered: