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new file: p/PyTorch/PyTorch-1.11.0-foss-2021a-CUDA-11.3.1.eb modified: p/PyTorch/PyTorch-1.11.0-fosscuda-2020b.eb new file: p/PyTorch/PyTorch-1.11.0_disable_failing_jit_cuda_fuser_tests.patch new file: p/PyTorch/PyTorch-1.11.0_fix_sharded_imports.patch new file: p/PyTorch/PyTorch-1.11.0_fix_skip_jit_cuda_fuser.patch new file: p/PyTorch/PyTorch-1.11.0_increase-distributed-test-timeout.patch new file: p/PyTorch/PyTorch-1.11.0_increase_c10d_gloo_timeout.patch new file: p/PyTorch/PyTorch-1.11.0_increase_test_tolerances_TF32.patch new file: p/PyTorch/PyTorch-1.11.0_skip_failing_ops_tests.patch
45 lines
1.7 KiB
Diff
45 lines
1.7 KiB
Diff
# Fixes a "NameError: name 'sharded_tensor' is not defined" error
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# for the test_named_params_with_sharded_tensor test
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# See https://github.com/pytorch/pytorch/pull/73309
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From 012d490ed76d8af8538d310a508b0e09a91b7632 Mon Sep 17 00:00:00 2001
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From: wanchaol <wanchaol@devvm3348.frc0.facebook.com>
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Date: Wed, 23 Feb 2022 12:10:39 -0800
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Subject: [PATCH] [shard] fix some imports in tests
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This fix some imports in sharded optimizer tests
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Differential Revision: [D34427252](https://our.internmc.facebook.com/intern/diff/D34427252/)
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[ghstack-poisoned]
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---
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.../_shard/sharded_optim/test_sharded_optim.py | 9 ++++++---
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1 file changed, 6 insertions(+), 3 deletions(-)
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diff --git a/test/distributed/_shard/sharded_optim/test_sharded_optim.py b/test/distributed/_shard/sharded_optim/test_sharded_optim.py
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index 085c928985eb..d3f1468aea3c 100644
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--- a/test/distributed/_shard/sharded_optim/test_sharded_optim.py
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+++ b/test/distributed/_shard/sharded_optim/test_sharded_optim.py
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@@ -2,7 +2,10 @@
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import torch
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import torch.optim as optim
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-import torch.distributed._shard.sharded_tensor
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+from torch.distributed._shard import (
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+ sharded_tensor,
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+ shard_parameter
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+)
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from copy import deepcopy
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from torch.distributed._shard.sharding_spec import (
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@@ -77,8 +80,8 @@ def shard_parameter(self):
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],
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)
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- sharded_tensor.shard_parameter(self.linear1, "weight", rowwise_sharding_spec)
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- sharded_tensor.shard_parameter(self.linear2, "weight", colwise_sharding_spec)
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+ shard_parameter(self.linear1, "weight", rowwise_sharding_spec)
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+ shard_parameter(self.linear2, "weight", colwise_sharding_spec)
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def forward(self, inp):
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return self.linear2(self.gelu(self.linear1(inp)))
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