I'm at a loss to explain why this happens, but not setting the manifest file explicitly in the linker fixes it.
### Testing locally
* With `/MANIFESTFILE:bin\torch_python.dll.manifest`
```
C:\PROGRA~2\MICROS~2\2019\BUILDT~1\VC\Tools\MSVC\1428~1.293\bin\Hostx64\x64\link.exe /nologo @CMakeFiles\torch_python.rsp /out:bin\torch_python.dll /implib:lib\torch_python.lib /pdb:bin\torch_python.pdb /dll /version:0.0 /machine:x64 /ignore:4049 /ignore:4217 /ignore:4099 /INCREMENTAL:NO /NODEFAULTLIB:LIBCMT.LIB -WHOLEARCHIVE:C:/actions-runner/_work/pytorch/pytorch/build/lib/onnx.lib /MANIFEST /MANIFESTFILE:bin\torch_python.dll.manifest
LINK : fatal error LNK1000: Internal error during CImplib::EmitImportThunk
```
* Work fine without the flag
```
C:\PROGRA~2\MICROS~2\2019\BUILDT~1\VC\Tools\MSVC\1428~1.293\bin\Hostx64\x64\link.exe /nologo @CMakeFiles\torch_python.rsp /out:bin\torch_python.dll /implib:lib\torch_python.lib /pdb:bin\torch_python.pdb /dll /version:0.0 /machine:x64 /ignore:4049 /ignore:4217 /ignore:4099 /INCREMENTAL:NO /NODEFAULTLIB:LIBCMT.LIB -WHOLEARCHIVE:C:/actions-runner/_work/pytorch/pytorch/build/lib/onnx.lib /MANIFEST
```
In both case, the `/MANIFEST` flag is set, so the manifest file is there. In the latter case, the filename comes by appending `.manifest` suffix to `bin\torch_python.dll`. Thus, it's still correctly be `bin\torch_python.dll.manifest`. Weird.
```
C:\actions-runner\_work\pytorch\pytorch>ls -la build/bin/torch_*
-rwxr-xr-x 1 runneruser 197121 246796288 Jan 11 04:30 build/bin/torch_cpu.dll
-rw-r--r-- 1 runneruser 197121 381 Jan 11 04:26 build/bin/torch_cpu.dll.manifest
-rwxr-xr-x 1 runneruser 197121 9728 Jan 11 03:55 build/bin/torch_global_deps.dll
-rw-r--r-- 1 runneruser 197121 381 Jan 11 03:55 build/bin/torch_global_deps.dll.manifest
-rwxr-xr-x 1 runneruser 197121 11746816 Jan 11 04:31 build/bin/torch_python.dll
-rw-r--r-- 1 runneruser 197121 381 Jan 11 04:30 build/bin/torch_python.dll.manifest
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/91988
Approved by: https://github.com/malfet, https://github.com/Blackhex, https://github.com/ZainRizvi
Summary:
- Added 2D-Convolution NHWC support
- on ROCm 4.3, with `PYTORCH_MIOPEN_SUGGEST_NHWC=1` flag
- May need to force MIOpen to search for solutions ( see examples below for flags )
**PYTORCH_MIOPEN_SUGGEST_NHWC Environment Flag**
MIOpen does not officially support NHWC yet, although convolution support has been added to tip-of-tree of MIOpen. This flag is intended to be a short-lived flag to explicitly turn on NHWC support until ROCm officially supports NHWC and performance is verified.
**Examples**
1. Example usage 1 : Run test on ROCm4.3
`PYTORCH_TEST_WITH_ROCM=1 PYTORCH_MIOPEN_SUGGEST_NHWC=1 MIOPEN_FIND_ENFORCE=4 MIOPEN_DEBUG_CONV_GEMM=0 MIOPEN_FIND_MODE=1 pytest test_nn.py -v -k "test_conv_cudnn_nhwc" `
2. Example usage 2: Run the following with `PYTORCH_MIOPEN_SUGGEST_NHWC=1` on ROCm4.3.
```
#!/usr/bin/env python3
import torch
model = torch.nn.Conv2d(8, 4, 3).cuda().half()
model = model.to(memory_format=torch.channels_last)
input = torch.randint(1, 10, (2, 8, 4, 4), dtype=torch.float32, requires_grad=True)
input = input.to(device="cuda", memory_format=torch.channels_last, dtype=torch.float16)
# should print True for is_contiguous(channels_last), and strides must match NHWC format
print(input.is_contiguous(memory_format=torch.channels_last), input.shape, input.stride() )
out = model(input)
# should print True for is_contiguous(channels_last), and strides must match NHWC format
print("Contiguous channel last :", out.is_contiguous(memory_format=torch.channels_last), " out shape :", out.shape, "out stride :", out.stride() )
```
See https://pytorch.org/tutorials/intermediate/memory_format_tutorial.html for more examples.
cc jeffdaily sunway513 jithunnair-amd ROCmSupport
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63617
Reviewed By: saketh-are
Differential Revision: D30730800
Pulled By: ezyang
fbshipit-source-id: 61906a0f30be8299e6547d312ae6ac91cc7c3238
Summary:
Related Issue: https://github.com/pytorch/pytorch/issues/57691
This PR introduces an API for checking environment variables:
```c++
optional<bool> check_env(const char *name)
```
Reads the environment variable name and returns
- `optional<true>`, if set equal to "1"
- `optional<false>`, if set equal to "0"
- `nullopt`, otherwise
Issues a warning if the environment variable was set to any value other than 0 or 1
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59052
Test Plan:
Manually run the following test case:
- Apply this diff to the repo
```
diff --git a/torch/csrc/Exceptions.cpp b/torch/csrc/Exceptions.cpp
index d008643f70..990d254f0d 100644
--- a/torch/csrc/Exceptions.cpp
+++ b/torch/csrc/Exceptions.cpp
@@ -9,6 +9,9 @@
#include <torch/csrc/THP.h>
+#include <c10/util/Optional.h>
+#include <c10/util/env.h>
+
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
PyObject *THPException_FatalError;
@@ -23,18 +26,7 @@ bool THPException_init(PyObject *module)
namespace torch {
static bool compute_cpp_stack_traces_enabled() {
- auto envar = std::getenv("TORCH_SHOW_CPP_STACKTRACES");
- if (envar) {
- if (strcmp(envar, "0") == 0) {
- return false;
- }
- if (strcmp(envar, "1") == 0) {
- return true;
- }
- TORCH_WARN("ignoring invalid value for TORCH_SHOW_CPP_STACKTRACES: ", envar,
- " valid values are 0 or 1.");
- }
- return false;
+ return c10::utils::check_env("TORCH_SHOW_CPP_STACKTRACES").value_or(false);
}
bool get_cpp_stacktraces_enabled() {
```
This patch replaces the prior `std::getenv` usage in `torch/csrc/Exceptions.cpp` to use the new api.
- Run the following python3 script
```python
import torch
print(torch.__version__) # should print local version (not release)
a1 = torch.tensor([1,2,3])
a2 = torch.tensor([2])
a1 @ a2
```
using the following commands
```bash
python3 test.py # should not output CPP trace
TORCH_SHOW_CPP_STACKTRACES=1 python3 test.py # should output CPP trace
```
Reviewed By: ngimel
Differential Revision: D28799873
Pulled By: 1ntEgr8
fbshipit-source-id: 3e23353f48679ba8ce0364c049420ba4ff86ff09
