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Revert "Fix the device for cuDNN/cuBLAS handles (#1974)" #2329

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ksivaman wants to merge 2 commits into from
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Revert "Fix the device for cuDNN/cuBLAS handles (#1974)" #2329

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65a5d2a
Revert "Fix the device for cuDNN/cuBLAS handles (#1974)"
ksivaman Oct 31, 2025
f5c6871
Merge branch 'main' into revert_pr_1974
ksivaman Oct 31, 2025
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1 change: 0 additions & 1 deletion qa/L1_pytorch_distributed_unittest/test.sh
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Expand Up @@ -28,7 +28,6 @@ pip install git+https://github.com/NVIDIA/nvidia-dlfw-inspect.git

pip3 install pytest==8.2.1 || error_exit "Failed to install pytest"

python3 -m pytest -v -s --junitxml=$XML_LOG_DIR/pytest_test_sanity.xml $TE_PATH/tests/pytorch/distributed/test_sanity.py || test_fail "test_sanity.py"
python3 -m pytest -v -s --junitxml=$XML_LOG_DIR/pytest_test_numerics.xml $TE_PATH/tests/pytorch/distributed/test_numerics.py || test_fail "test_numerics.py"
python3 -m pytest -v -s --junitxml=$XML_LOG_DIR/pytest_test_numerics_exact.xml $TE_PATH/tests/pytorch/distributed/test_numerics_exact.py || test_fail "test_numerics_exact.py"
python3 -m pytest -v -s --junitxml=$XML_LOG_DIR/pytest_test_fusible_ops.xml $TE_PATH/tests/pytorch/distributed/test_fusible_ops.py || test_fail "test_fusible_ops.py"
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120 changes: 0 additions & 120 deletions tests/pytorch/distributed/test_sanity.py
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2 changes: 1 addition & 1 deletion transformer_engine/pytorch/attention/dot_product_attention/dot_product_attention.py
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Expand Up @@ -975,7 +975,7 @@ def forward(
Whether to enforce output to be in FP8 or not.
"""

with torch.cuda.device(query_layer.device), self.prepare_forward(
with self.prepare_forward(
query_layer,
num_gemms=3,
allow_non_contiguous=True,
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4 changes: 1 addition & 3 deletions transformer_engine/pytorch/module/grouped_linear.py
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Expand Up @@ -766,9 +766,7 @@ def forward(
if skip_fp8_weight_update is not None:
is_first_microbatch = False

with torch.cuda.device(
getattr(self, list(self.named_parameters())[0][0]).device
), self.prepare_forward(inp, num_gemms=self.num_gemms) as inp:
with self.prepare_forward(inp, num_gemms=self.num_gemms) as inp:
weight_tensors = self._get_weight_tensors()
bias_tensors = [getattr(self, f"bias{i}") for i in range(self.num_gemms)]

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4 changes: 1 addition & 3 deletions transformer_engine/pytorch/module/layernorm_linear.py
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Expand Up @@ -1532,9 +1532,7 @@ def forward(
).is_fp8_ubuf():
fp8_grad = True

with torch.cuda.device(
getattr(self, list(self.named_parameters())[0][0]).device
), self.prepare_forward(
with self.prepare_forward(
inp, allow_non_contiguous=False # removed .contiguous from inside the layer
) as inp:

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4 changes: 1 addition & 3 deletions transformer_engine/pytorch/module/layernorm_mlp.py
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Expand Up @@ -1823,9 +1823,7 @@ def forward(
if get_ub("fc2_fprop", FP8GlobalStateManager.is_fp8_enabled()).is_fp8_ubuf():
fp8_output = True

with torch.cuda.device(
getattr(self, list(self.named_parameters())[0][0]).device
), self.prepare_forward(inp, num_gemms=2) as inp:
with self.prepare_forward(inp, num_gemms=2) as inp:

quantizers = (
self._get_quantizers(fp8_output)
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4 changes: 1 addition & 3 deletions transformer_engine/pytorch/module/linear.py
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Expand Up @@ -1419,9 +1419,7 @@ def forward(
).is_fp8_ubuf():
fp8_grad = True

with torch.cuda.device(
getattr(self, list(self.named_parameters())[0][0]).device
), self.prepare_forward(
with self.prepare_forward(
inp,
allow_non_contiguous=isinstance(inp, QuantizedTensor),
) as inp:
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