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Correctness and perf fixes #354

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Merged
tjruwase merged 5 commits into from
Sep 3, 2020
Merged

Correctness and perf fixes #354

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1ebcd6c
Update test_sparse_attention.py
jeffra Sep 3, 2020
2228feb
jren changes
tjruwase Sep 3, 2020
5ff55d3
Merge remote-tracking branch 'origin' into jren_changes
tjruwase Sep 3, 2020
c8b1666
Merge with correctness/perf fixes
tjruwase Sep 3, 2020
2c71e49
Formatting fixes
tjruwase Sep 3, 2020
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9 changes: 4 additions & 5 deletions deepspeed/runtime/engine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,6 @@
import torch
import warnings
import torch.distributed as dist

from apex import amp
from torch.nn.modules import Module
from torch.distributed.distributed_c10d import _get_global_rank
Expand All @@ -27,9 +26,7 @@
ZERO_OPTIMIZATION_OPTIMIZER_STATES, ZERO_OPTIMIZATION_GRADIENTS
from deepspeed.runtime.csr_tensor import CSRTensor
import deepspeed.runtime.lr_schedules as lr_schedules

from deepspeed.ops.lamb import FusedLamb

from deepspeed.utils import logger
from deepspeed.utils.timer import ThroughputTimer, SynchronizedWallClockTimer

Expand Down Expand Up @@ -618,7 +615,8 @@ def _configure_zero_optimizer(self, optimizer):
cpu_offload=self.zero_cpu_offload(),
mpu=self.mpu,
postscale_gradients=self.postscale_gradients(),
gradient_predivide_factor=self.gradient_predivide_factor())
gradient_predivide_factor=self.gradient_predivide_factor(),
gradient_accumulation_steps=self.gradient_accumulation_steps())
else:
raise NotImplementedError("ZeRO stage {} not implemented".format(zero_stage))

Expand Down Expand Up @@ -724,7 +722,6 @@ def forward(self, *inputs, **kwargs):
return loss

def allreduce_gradients(self, bucket_size=MEMORY_OPT_ALLREDUCE_SIZE):

#Zero stage 2 communicates during non gradient accumulation boundaries as well
if self.zero_optimization_partition_gradients():
self.optimizer.overlapping_partition_gradients_reduce_epilogue()
Expand Down Expand Up @@ -780,6 +777,8 @@ def backward(self, loss, allreduce_gradients=True):
self.timers('backward_inner').start()

if self.zero_optimization():
self.optimizer.is_gradient_accumulation_boundary = self.is_gradient_accumulation_boundary(
)
self.optimizer.backward(loss)
elif self.amp_enabled():
# AMP requires delaying unscale when inside gradient accumulation boundaries
Expand Down
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