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Tensor::is_sequential() may need more strict conditions. (Minor fixes #111)
Executor::tensor_memcpy_host_to_device() will cause unknown error if the tensors on the host device is not sequential. We need more check about the tensor on the host or mabe need a python warpper for this (Improve Python interfaces #48)
Sometime if the tensor is padded, the allgather operation might overwrite the recv tensor, and the allreduce tensor will also be incorrect. (@chhwang: now send/recv checks contiguity)
Current layernorm and sofxmax operation is scheduled using a quite hack way, might needs for more update in the future. (Minor updates #59)
When using python -m unittest discover -s . -p "test_*.py" to run all unittest, the snedrecv test will fail, but when we run them seperately, their will be no problem. Seems that in some cases the previous runtime context is not destroyed when one unittest finished and another unittest start. This problem also exist in the current main branch. (@chhwang: this is the test code's issue, won't fix for now)
Tensor::is_sequential()
may need more strict conditions. (Minor fixes #111)Executor::tensor_memcpy_host_to_device()
will cause unknown error if the tensors on the host device is not sequential. We need more check about the tensor on the host or mabe need a python warpper for this (Improve Python interfaces #48)ark.init()
is not working. (Fix init #39)[ ] Support both source and destination offsets inmoved to the next versionNetIbQp::stage_send()
ark/ark/ops/ops_all_gather.cc
Lines 19 to 23 in 420c236
ops_matmul_test.cc
is not checking error rates correctly (New unit test framework for operators #91)send_mm
andrecv_mm
are temporarily broken (Revisions around schedulers #52)[ ] Offsets of importing/exporting tensors are not properly handledmoved to the next versionThe text was updated successfully, but these errors were encountered: