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[hybird optim] reduce rend/recv times for recompute #34248
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@@ -4840,6 +4840,39 @@ def _insert_send_recv(cur_id, prev_id): | |
}) | ||
extra_index_info['index'] += 1 | ||
elif self.schedule_mode == '1F1B': # 1F1B | ||
var_shape = list(var.shape) | ||
var_shape[0] = self.micro_batch_size if var_shape[ | ||
0] < 0 else var_shape[0] | ||
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numel = np.prod(var.shape) | ||
assert numel % self.mp_degree == 0, \ | ||
"The numel={} must be divisible by mp_degree={}".format(numel, self.mp_degree) | ||
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if 'subprog' in var.name: | ||
# For recompute, if the checkpoints var is layer_norm_6.tmp_2 | ||
# this var will be sent twice, layer_norm_6.tmp_2 for forward pass, | ||
# layer_norm_6.tmp_2.subprog_* for recompute pass. | ||
# We can store the first sent var and copy the value to the | ||
# second one to reduce one send/recv op. | ||
# The origin_ckpt_name is layer_norm_6.tmp_2, which will be used | ||
# to find the stored var for the forward pass. | ||
origin_name = var.name.split('subprog')[0][0:-1] | ||
associate_var = block.var(origin_name) | ||
block._insert_op_without_sync( | ||
index=index + extra_index_info['index'], | ||
type='assign', | ||
inputs={'X': [associate_var]}, | ||
outputs={'Out': [var]}, | ||
attrs={ | ||
'out_shape': var_shape, | ||
'dtype': var.dtype, | ||
self._op_device_key: cur_dev, | ||
self._op_role_key: op_role, | ||
'use_calc_stream': True, | ||
}) | ||
extra_index_info['index'] += 1 | ||
return | ||
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block._insert_op_without_sync( | ||
index=index + extra_index_info['index'], | ||
type='c_sync_calc_stream', | ||
|
@@ -4867,15 +4900,13 @@ def _insert_send_recv(cur_id, prev_id): | |
}) | ||
extra_index_info['index'] += 1 | ||
insert_index = None | ||
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||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 咋把这几个换行删了。。 |
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if int(op_role) == int(self._op_role.Backward): | ||
insert_index = extra_index_info[ | ||
'first_optimize_index'] | ||
new_op_role = self._op_role.Optimize | ||
else: | ||
insert_index = index | ||
new_op_role = self._op_role.Backward | ||
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sync_comm_op = block._insert_op_without_sync( | ||
index=insert_index + extra_index_info['index'], | ||
type='c_sync_comm_stream', | ||
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@@ -4886,18 +4917,9 @@ def _insert_send_recv(cur_id, prev_id): | |
self._op_role_key: new_op_role, | ||
'ring_id': ring_id, | ||
}) | ||
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if int(op_role) == int(self._op_role.Forward): | ||
sync_comm_op._set_attr('pipeline_flag', '') | ||
extra_index_info['index'] += 1 | ||
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var_shape = list(var.shape) | ||
var_shape[0] = self.micro_batch_size if var_shape[ | ||
0] < 0 else var_shape[0] | ||
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numel = np.prod(var.shape) | ||
assert numel % self.mp_degree == 0, \ | ||
"The numel={} must be divisible by mp_degree={}".format(numel, self.mp_degree) | ||
block._insert_op_without_sync( | ||
index=index + extra_index_info['index'], | ||
type='recv_v2' | ||
|
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@@ -17,6 +17,7 @@ list(APPEND DIST_TEST_OPS test_parallel_dygraph_sparse_embedding) | |
list(APPEND DIST_TEST_OPS test_parallel_dygraph_sparse_embedding_over_height) | ||
list(APPEND DIST_TEST_OPS test_parallel_dygraph_transformer) | ||
list(APPEND DIST_TEST_OPS test_fleet_pipeline_meta_optimizer) | ||
list(APPEND DIST_TEST_OPS test_fleet_pipeline_meta_optimizer_with_recompute) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 单测加到原来test_fleet_pipeline_meta_optimizer会出错吗 |
||
list(APPEND DIST_TEST_OPS test_fleet_raw_program_meta_optimizer) | ||
list(APPEND DIST_TEST_OPS test_fleet_graph_execution_meta_optimizer) | ||
list(APPEND DIST_TEST_OPS test_gen_nccl_id_op) | ||
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@@ -56,6 +57,7 @@ list(APPEND MIXED_DIST_TEST_OPS test_fleet_base_2) | |
list(APPEND MIXED_DIST_TEST_OPS test_fleet_base_3) | ||
list(APPEND MIXED_DIST_TEST_OPS test_fleet_recompute_meta_optimizer) | ||
list(APPEND MIXED_DIST_TEST_OPS test_fleet_pipeline_meta_optimizer) | ||
list(APPEND MIXED_DIST_TEST_OPS test_fleet_pipeline_meta_optimizer_with_recompute) | ||
list(APPEND MIXED_DIST_TEST_OPS test_fleet_raw_program_meta_optimizer) | ||
list(APPEND MIXED_DIST_TEST_OPS test_fleet_amp_meta_optimizer) | ||
list(APPEND MIXED_DIST_TEST_OPS test_fleet_amp_init) | ||
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76 changes: 76 additions & 0 deletions
76
python/paddle/fluid/tests/unittests/test_fleet_pipeline_meta_optimizer_with_recompute.py
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@@ -0,0 +1,76 @@ | ||
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
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import unittest | ||
import paddle | ||
import os | ||
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paddle.enable_static() | ||
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class TestFleetMetaOptimizer(unittest.TestCase): | ||
def setUp(self): | ||
os.environ["PADDLE_TRAINER_ID"] = "1" | ||
os.environ[ | ||
"PADDLE_TRAINER_ENDPOINTS"] = "127.0.0.1:36001,127.0.0.1:36002" | ||
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def test_pipeline_optimizer(self): | ||
import paddle.distributed.fleet as fleet | ||
import paddle.distributed.fleet.base.role_maker as role_maker | ||
role = role_maker.PaddleCloudRoleMaker(is_collective=True) | ||
fleet.init(role) | ||
with paddle.fluid.device_guard("gpu:0"): | ||
input_x = paddle.fluid.layers.data( | ||
name="x", shape=[32], dtype='float32') | ||
input_y = paddle.fluid.layers.data( | ||
name="y", shape=[1], dtype='int64') | ||
fc_1 = paddle.fluid.layers.fc(input=input_x, size=64, act='tanh') | ||
fc_2 = paddle.fluid.layers.fc(input=fc_1, size=64, act='tanh') | ||
fc_3 = paddle.fluid.layers.fc(input=fc_2, size=64, act='tanh') | ||
fc_4 = paddle.fluid.layers.fc(input=fc_3, size=64, act='tanh') | ||
fc_5 = paddle.fluid.layers.fc(input=fc_4, size=64, act='tanh') | ||
fc_6 = paddle.fluid.layers.fc(input=fc_5, size=64, act='tanh') | ||
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with paddle.fluid.device_guard("gpu:1"): | ||
fc_7 = paddle.fluid.layers.fc(input=fc_6, size=64, act='tanh') | ||
prediction = paddle.fluid.layers.fc(input=[fc_7], | ||
size=2, | ||
act='softmax') | ||
cost = paddle.fluid.layers.cross_entropy( | ||
input=prediction, label=input_y) | ||
avg_cost = paddle.fluid.layers.mean(x=cost) | ||
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strategy = paddle.distributed.fleet.DistributedStrategy() | ||
strategy.pipeline = True | ||
strategy.pipeline_configs = { | ||
'micro_batch_size': 1, | ||
'accumulate_steps': 2, | ||
'schedule_mode': '1F1B' | ||
} | ||
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checkpoints = ['fc_5.tmp_0', 'fc_7.tmp_0'] | ||
strategy.recompute = True | ||
strategy.recompute_configs = { | ||
"checkpoints": checkpoints, | ||
"enable_offload": False, | ||
"checkpoint_shape": [] | ||
} | ||
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optimizer = paddle.fluid.optimizer.Adam(0.01) | ||
optimizer = fleet.distributed_optimizer(optimizer, strategy=strategy) | ||
optimizer.minimize(avg_cost) | ||
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if __name__ == "__main__": | ||
unittest.main() |
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之后加一个断言,recompute这个情况下op_role为backward