forked from OSSInnovation/mindspore
!5351 move ParalleMode to Context
Merge pull request !5351 from yao_yf/parallel_context_collation
This commit is contained in:
commit
820f2cb4eb
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@ -28,7 +28,7 @@ from mindspore.parallel._auto_parallel_context import _set_auto_parallel_context
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_reset_auto_parallel_context
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__all__ = ['GRAPH_MODE', 'PYNATIVE_MODE', 'set_context', 'get_context', 'set_auto_parallel_context',
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'get_auto_parallel_context', 'reset_auto_parallel_context']
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'get_auto_parallel_context', 'reset_auto_parallel_context', 'ParallelMode']
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GRAPH_MODE = 0
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PYNATIVE_MODE = 1
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@ -647,3 +647,26 @@ def get_context(attr_key):
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raise ValueError(
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"Get context keyword %s is not recognized!" % attr_key)
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return getattr(_context(), attr_key)
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class ParallelMode:
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"""
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Parallel mode options.
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There are five kinds of parallel modes, "STAND_ALONE", "DATA_PARALLEL",
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"HYBRID_PARALLEL", "SEMI_AUTO_PARALLEL" and "AUTO_PARALLEL". Default: "STAND_ALONE".
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- STAND_ALONE: Only one processor working.
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- DATA_PARALLEL: Distributing the data across different processors.
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- HYBRID_PARALLEL: Achieving data parallelism and model parallelism manually.
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- SEMI_AUTO_PARALLEL: Achieving data parallelism and model parallelism by setting parallel strategies.
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- AUTO_PARALLEL: Achieving parallelism automatically.
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MODE_LIST: The list for all supported parallel modes.
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"""
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STAND_ALONE = "stand_alone"
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DATA_PARALLEL = "data_parallel"
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HYBRID_PARALLEL = "hybrid_parallel"
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SEMI_AUTO_PARALLEL = "semi_auto_parallel"
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AUTO_PARALLEL = "auto_parallel"
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MODE_LIST = [STAND_ALONE, DATA_PARALLEL, HYBRID_PARALLEL, SEMI_AUTO_PARALLEL, AUTO_PARALLEL]
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@ -20,7 +20,7 @@ from mindspore.common.parameter import Parameter
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from mindspore.common.initializer import initializer
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from mindspore._checkparam import Validator
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from mindspore.communication.management import get_group_size
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from mindspore.train.parallel_utils import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore.parallel._utils import _get_parallel_mode
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from ..cell import Cell
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from ..._checkparam import Validator as validator, Rel
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@ -129,9 +129,9 @@ class EmbeddingLookup(Cell):
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embedding_size (int): The size of each embedding vector.
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param_init (str): The initialize way of embedding table. Default: 'normal'.
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target (str): Specify the target where the op is executed. The value should in
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['DEVICE', 'CPU']. Default: 'CPU'.
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slice_mode (str): The slicing way in semi auto parallel/auto parallel. The value should get through
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nn.EmbeddingLookUpSplitMode. Default: 'batch_slice'.
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['DEVICE', 'CPU']. Default: 'CPU'.
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slice_mode (str): The slicing way in semi_auto_parallel/auto_parallel. The value should get through
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nn.EmbeddingLookUpSplitMode. Default: nn.EmbeddingLookUpSplitMode.BATCH_SLICE.
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manual_shapes (tuple): The accompaniment array in field slice mode.
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Inputs:
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@ -29,7 +29,7 @@ from mindspore._checkparam import Validator as validator
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from mindspore._checkparam import Rel
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from mindspore import log as logger
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from mindspore.parallel._utils import _get_global_rank, _get_device_num, _get_parallel_mode
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from mindspore.train.parallel_utils import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore import context
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from mindspore.nn.learning_rate_schedule import LearningRateSchedule
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@ -15,7 +15,7 @@
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"""Cell_wrapper."""
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from mindspore.parallel._utils import (_get_device_num, _get_mirror_mean,
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_get_parallel_mode)
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from mindspore.train.parallel_utils import ParallelMode
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from mindspore.context import ParallelMode
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from ...common import dtype as mstype
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from ...common.parameter import Parameter, ParameterTuple
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from ...ops import composite as C
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@ -251,8 +251,9 @@ class DistributedGradReducer(Cell):
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>>> from mindspore.ops import operations as P
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>>> from mindspore.ops import functional as F
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>>> from mindspore import context
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>>> from mindspore.context import ParallelMode
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>>> from mindspore import nn
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>>> from mindspore import ParallelMode, ParameterTuple
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>>> from mindspore import ParameterTuple
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>>>
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>>> device_id = int(os.environ["DEVICE_ID"])
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>>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=True,
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@ -15,7 +15,7 @@
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"""Loss scale cell for loss scale training."""
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import mindspore.context as context
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from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
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from mindspore.train.parallel_utils import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore.parallel._utils import _get_device_num, _get_parallel_mode, _get_mirror_mean
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from ..cell import Cell
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from ...common import Tensor, RowTensor
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@ -18,8 +18,7 @@ High-Level training interfaces.
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Helper functions in train piplines.
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"""
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from .model import Model
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from .parallel_utils import ParallelMode
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from .dataset_helper import DatasetHelper
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from . import amp
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__all__ = ["Model", "ParallelMode", "DatasetHelper", "amp"]
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__all__ = ["Model", "DatasetHelper", "amp"]
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@ -23,7 +23,7 @@ from ..nn.wrap.cell_wrapper import _VirtualDatasetCell
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from ..ops import functional as F
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from ..parallel._utils import _get_parallel_mode
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from .loss_scale_manager import DynamicLossScaleManager, LossScaleManager
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from .parallel_utils import ParallelMode
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from ..context import ParallelMode
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from .. import context
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__all__ = ["build_train_network"]
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@ -30,7 +30,7 @@ from ..parallel._utils import _get_parallel_mode, _get_device_num, _get_global_r
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from ..nn.metrics import Loss
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from .. import nn
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from ..nn.wrap.cell_wrapper import _VirtualDatasetCell
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from .parallel_utils import ParallelMode
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from ..context import ParallelMode
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from ..parallel._utils import _need_to_full, _to_full_tensor
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from ..common import dtype as mstype
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from .dataset_helper import DatasetHelper
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@ -1,41 +0,0 @@
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""Parallel utils"""
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__all__ = ["ParallelMode"]
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class ParallelMode:
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"""
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Parallel mode options.
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There are five kinds of parallel modes, "STAND_ALONE", "DATA_PARALLEL",
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"HYBRID_PARALLEL", "SEMI_AUTO_PARALLEL" and "AUTO_PARALLEL". Default: "STAND_ALONE".
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- STAND_ALONE: Only one processor working.
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- DATA_PARALLEL: Distributing the data across different processors.
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- HYBRID_PARALLEL: Achieving data parallelism and model parallelism manually.
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- SEMI_AUTO_PARALLEL: Achieving data parallelism and model parallelism by setting parallel strategies.
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- AUTO_PARALLEL: Achieving parallelism automatically.
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MODE_LIST: The list for all supported parallel modes.
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"""
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STAND_ALONE = "stand_alone"
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DATA_PARALLEL = "data_parallel"
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HYBRID_PARALLEL = "hybrid_parallel"
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SEMI_AUTO_PARALLEL = "semi_auto_parallel"
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AUTO_PARALLEL = "auto_parallel"
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MODE_LIST = [STAND_ALONE, DATA_PARALLEL, HYBRID_PARALLEL, SEMI_AUTO_PARALLEL, AUTO_PARALLEL]
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@ -17,7 +17,8 @@ import argparse
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from mindspore import context
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from mindspore.communication.management import init
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from mindspore.nn.optim.momentum import Momentum
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from mindspore import Model, ParallelMode
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from mindspore import Model
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from mindspore.context import ParallelMode
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
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from mindspore.train.callback import Callback, CheckpointConfig, ModelCheckpoint, TimeMonitor
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from src.md_dataset import create_dataset
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@ -26,7 +26,8 @@ import mindspore.common.dtype as mstype
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from mindspore import context, Tensor
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from mindspore.communication.management import init
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from mindspore.train.callback import CheckpointConfig, ModelCheckpoint, TimeMonitor
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from mindspore.train import Model, ParallelMode
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from mindspore.train import Model
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from mindspore.context import ParallelMode
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
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from mindspore.nn import SGD
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import mindspore.dataset.engine as de
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@ -28,7 +28,8 @@ from mindspore import context
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from mindspore.communication.management import init, get_rank
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from mindspore.nn.optim.momentum import Momentum
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
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from mindspore.train.model import Model, ParallelMode
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from mindspore.train.model import Model
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from mindspore.context import ParallelMode
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
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from src.config import cifar_cfg as cfg
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@ -21,7 +21,7 @@ import numpy as np
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore import context
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from mindspore import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore.communication.management import init, get_rank, get_group_size
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from mindspore.nn.optim.rmsprop import RMSProp
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
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@ -24,7 +24,8 @@ import mindspore.common.dtype as mstype
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from mindspore import context, Tensor
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from mindspore.communication.management import init
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from mindspore.train.callback import CheckpointConfig, ModelCheckpoint, TimeMonitor
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from mindspore.train import Model, ParallelMode
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from mindspore.train import Model
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from mindspore.context import ParallelMode
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
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from mindspore.nn import SGD
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import mindspore.dataset.engine as de
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@ -30,7 +30,8 @@ from mindspore.nn.loss.loss import _Loss
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from mindspore.ops import operations as P
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from mindspore.ops import functional as F
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from mindspore.common import dtype as mstype
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from mindspore.train.model import Model, ParallelMode
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from mindspore.train.model import Model
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from mindspore.context import ParallelMode
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, Callback
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from mindspore.train.loss_scale_manager import FixedLossScaleManager
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
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@ -22,7 +22,8 @@ import numpy as np
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from mindspore import context
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from mindspore import Tensor
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from mindspore import nn
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from mindspore.train.model import Model, ParallelMode
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from mindspore.train.model import Model
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from mindspore.context import ParallelMode
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from mindspore.train.loss_scale_manager import FixedLossScaleManager
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig
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from mindspore.train.serialization import load_checkpoint
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@ -28,7 +28,8 @@ from mindspore.nn.loss.loss import _Loss
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from mindspore.ops import operations as P
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from mindspore.ops import functional as F
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from mindspore.common import dtype as mstype
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from mindspore.train.model import Model, ParallelMode
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from mindspore.train.model import Model
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from mindspore.context import ParallelMode
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, Callback
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from mindspore.train.loss_scale_manager import FixedLossScaleManager
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
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@ -22,7 +22,8 @@ from mindspore import Tensor
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from mindspore import dataset as de
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from mindspore.parallel._auto_parallel_context import auto_parallel_context
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from mindspore.nn.optim.momentum import Momentum
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from mindspore.train.model import Model, ParallelMode
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from mindspore.train.model import Model
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from mindspore.context import ParallelMode
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
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from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
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from mindspore.train.loss_scale_manager import FixedLossScaleManager
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@ -21,7 +21,8 @@ from mindspore import context
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from mindspore import Tensor
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from mindspore.parallel._auto_parallel_context import auto_parallel_context
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from mindspore.nn.optim.momentum import Momentum
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from mindspore.train.model import Model, ParallelMode
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from mindspore.train.model import Model
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from mindspore.context import ParallelMode
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
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from mindspore.train.loss_scale_manager import FixedLossScaleManager
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from mindspore.train.serialization import load_checkpoint
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@ -102,7 +102,8 @@ class DistributedGradReducerThor(Cell):
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>>> from mindspore.ops import functional as F
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>>> from mindspore import context
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>>> from mindspore import nn
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>>> from mindspore import ParallelMode, ParameterTuple
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>>> from mindspore import ParameterTuple
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>>> from mindspore.context import ParallelMode
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>>>
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>>> device_id = int(os.environ["DEVICE_ID"])
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>>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=True,
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@ -18,7 +18,7 @@ import math
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from mindspore.train.callback import RunContext
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from mindspore import context
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from mindspore import nn
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from mindspore.train.parallel_utils import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore.train.model import Model
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from mindspore.parallel._utils import _need_to_full, _to_full_tensor
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from mindspore.common.dtype import pytype_to_dtype
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@ -22,7 +22,7 @@ from mindspore import context
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from mindspore import Tensor
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from mindspore import dataset as de
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from mindspore.parallel._auto_parallel_context import auto_parallel_context
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from mindspore.train.model import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor, LossMonitor
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from mindspore.train.loss_scale_manager import FixedLossScaleManager
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from mindspore.communication.management import init, get_rank, get_group_size
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@ -20,7 +20,7 @@ import datetime
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import mindspore.nn as nn
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from mindspore import Tensor, context
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from mindspore import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore.nn.optim import Momentum
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from mindspore.communication.management import init, get_rank, get_group_size
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from mindspore.train.callback import ModelCheckpoint
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|
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@ -19,6 +19,7 @@ import mindspore.common.dtype as mstype
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import mindspore as ms
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import mindspore.nn as nn
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from mindspore import Parameter, context, Tensor
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from mindspore.context import ParallelMode
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from mindspore.parallel._auto_parallel_context import auto_parallel_context
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from mindspore.communication.management import get_group_size
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from mindspore.ops import operations as P
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@ -388,7 +389,7 @@ class TrainingWrapper(nn.Cell):
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self.reducer_flag = False
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self.grad_reducer = None
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self.parallel_mode = context.get_auto_parallel_context("parallel_mode")
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if self.parallel_mode in [ms.ParallelMode.DATA_PARALLEL, ms.ParallelMode.HYBRID_PARALLEL]:
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if self.parallel_mode in [ParallelMode.DATA_PARALLEL, ParallelMode.HYBRID_PARALLEL]:
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self.reducer_flag = True
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if self.reducer_flag:
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mean = context.get_auto_parallel_context("mirror_mean")
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@ -21,7 +21,8 @@ import mindspore.nn as nn
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from mindspore import context, Tensor
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from mindspore.communication.management import init
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from mindspore.train.callback import CheckpointConfig, ModelCheckpoint, LossMonitor, TimeMonitor
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from mindspore.train import Model, ParallelMode
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from mindspore.train import Model
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from mindspore.context import ParallelMode
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
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from src.ssd import SSD300, SSDWithLossCell, TrainingWrapper, ssd_mobilenet_v2
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from src.config import config
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@ -29,7 +29,8 @@ from mindspore import context
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from mindspore.communication.management import init, get_rank, get_group_size
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from mindspore.nn.optim.momentum import Momentum
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from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor, TimeMonitor
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from mindspore.train.model import Model, ParallelMode
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from mindspore.train.model import Model
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from mindspore.context import ParallelMode
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from mindspore.train.serialization import load_param_into_net, load_checkpoint
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from mindspore.train.loss_scale_manager import FixedLossScaleManager
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from src.dataset import vgg_create_dataset
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@ -16,7 +16,7 @@
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import numpy as np
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from mindspore.parallel._utils import (_get_device_num, _get_mirror_mean,
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_get_parallel_mode)
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from mindspore.train.parallel_utils import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore.common import dtype as mstype
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from mindspore.ops import composite as C
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from mindspore.ops import functional as F
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|
|
|
@ -21,7 +21,8 @@ import numpy as np
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import mindspore.nn as nn
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from mindspore import context
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from mindspore import dataset as de
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from mindspore.train.model import Model, ParallelMode
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from mindspore.train.model import Model
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from mindspore.context import ParallelMode
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from mindspore.nn.wrap import WithLossCell
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from mindspore.train.callback import TimeMonitor, LossMonitor, CheckpointConfig, ModelCheckpoint
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from mindspore.communication.management import init, get_group_size, get_rank
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@ -25,7 +25,7 @@ from pycocotools.coco import COCO
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from pycocotools.cocoeval import COCOeval
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from mindspore import Tensor
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from mindspore.train import ParallelMode
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from mindspore.context import ParallelMode
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from mindspore import context
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
|
||||
import mindspore as ms
|
||||
|
|
|
@ -17,6 +17,7 @@ import mindspore as ms
|
|||
import mindspore.nn as nn
|
||||
from mindspore.common.tensor import Tensor
|
||||
from mindspore import context
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore.ops import operations as P
|
||||
|
@ -417,7 +418,7 @@ class TrainingWrapper(nn.Cell):
|
|||
self.reducer_flag = False
|
||||
self.grad_reducer = None
|
||||
self.parallel_mode = context.get_auto_parallel_context("parallel_mode")
|
||||
if self.parallel_mode in [ms.ParallelMode.DATA_PARALLEL, ms.ParallelMode.HYBRID_PARALLEL]:
|
||||
if self.parallel_mode in [ParallelMode.DATA_PARALLEL, ParallelMode.HYBRID_PARALLEL]:
|
||||
self.reducer_flag = True
|
||||
if self.reducer_flag:
|
||||
mean = context.get_auto_parallel_context("mirror_mean")
|
||||
|
|
|
@ -18,7 +18,7 @@ import time
|
|||
import argparse
|
||||
import datetime
|
||||
|
||||
from mindspore import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore import Tensor
|
||||
import mindspore.nn as nn
|
||||
|
|
|
@ -25,7 +25,7 @@ from pycocotools.coco import COCO
|
|||
from pycocotools.cocoeval import COCOeval
|
||||
|
||||
from mindspore import Tensor
|
||||
from mindspore.train import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore import context
|
||||
from mindspore.train.serialization import load_checkpoint, load_param_into_net
|
||||
import mindspore as ms
|
||||
|
|
|
@ -17,6 +17,7 @@ import mindspore as ms
|
|||
import mindspore.nn as nn
|
||||
from mindspore.common.tensor import Tensor
|
||||
from mindspore import context
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore.ops import operations as P
|
||||
|
@ -417,7 +418,7 @@ class TrainingWrapper(nn.Cell):
|
|||
self.reducer_flag = False
|
||||
self.grad_reducer = None
|
||||
self.parallel_mode = context.get_auto_parallel_context("parallel_mode")
|
||||
if self.parallel_mode in [ms.ParallelMode.DATA_PARALLEL, ms.ParallelMode.HYBRID_PARALLEL]:
|
||||
if self.parallel_mode in [ParallelMode.DATA_PARALLEL, ParallelMode.HYBRID_PARALLEL]:
|
||||
self.reducer_flag = True
|
||||
if self.reducer_flag:
|
||||
mean = context.get_auto_parallel_context("mirror_mean")
|
||||
|
|
|
@ -19,7 +19,7 @@ import time
|
|||
import argparse
|
||||
import datetime
|
||||
|
||||
from mindspore import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore import Tensor
|
||||
from mindspore import context
|
||||
|
|
|
@ -19,6 +19,7 @@ import numpy as np
|
|||
import mindspore as ms
|
||||
import mindspore.nn as nn
|
||||
from mindspore import context, Tensor
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore.common.initializer import TruncatedNormal
|
||||
|
@ -652,7 +653,7 @@ class TrainingWrapper(nn.Cell):
|
|||
self.reducer_flag = False
|
||||
self.grad_reducer = None
|
||||
self.parallel_mode = context.get_auto_parallel_context("parallel_mode")
|
||||
if self.parallel_mode in [ms.ParallelMode.DATA_PARALLEL, ms.ParallelMode.HYBRID_PARALLEL]:
|
||||
if self.parallel_mode in [ParallelMode.DATA_PARALLEL, ParallelMode.HYBRID_PARALLEL]:
|
||||
self.reducer_flag = True
|
||||
if self.reducer_flag:
|
||||
mean = context.get_auto_parallel_context("mirror_mean")
|
||||
|
|
|
@ -29,7 +29,8 @@ import mindspore.nn as nn
|
|||
from mindspore import context, Tensor
|
||||
from mindspore.communication.management import init
|
||||
from mindspore.train.callback import CheckpointConfig, ModelCheckpoint, LossMonitor, TimeMonitor
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.train.serialization import load_checkpoint, load_param_into_net
|
||||
from mindspore.common.initializer import initializer
|
||||
|
||||
|
|
|
@ -24,7 +24,7 @@ import mindspore.communication.management as D
|
|||
import mindspore.common.dtype as mstype
|
||||
from mindspore import context
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.wrap.loss_scale import DynamicLossScaleUpdateCell
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor
|
||||
from mindspore.train.serialization import load_checkpoint, load_param_into_net
|
||||
|
|
|
@ -25,7 +25,7 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.parameter import Parameter
|
||||
from mindspore.common import dtype as mstype
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore import context
|
||||
from .bert_for_pre_training import clip_grad
|
||||
|
|
|
@ -24,7 +24,7 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.parameter import Parameter
|
||||
from mindspore.common import dtype as mstype
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore import context
|
||||
from mindspore.ops import _selected_ops
|
||||
|
|
|
@ -35,7 +35,7 @@ from mindspore import log as logger
|
|||
from mindspore.nn.optim import Lamb, Momentum, AdamWeightDecay
|
||||
from mindspore.nn.wrap.loss_scale import DynamicLossScaleUpdateCell
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.train.serialization import load_checkpoint, load_param_into_net
|
||||
|
||||
_current_dir = os.path.dirname(os.path.realpath(__file__))
|
||||
|
|
|
@ -27,7 +27,7 @@ from mindspore.ops import _selected_ops
|
|||
from mindspore.ops import composite as C
|
||||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from .bert_model import BertModel
|
||||
from .config import cfg
|
||||
from .lr_generator import get_bert_damping
|
||||
|
|
|
@ -102,7 +102,8 @@ class DistributedGradReducerThor(Cell):
|
|||
>>> from mindspore.ops import functional as F
|
||||
>>> from mindspore import context
|
||||
>>> from mindspore import nn
|
||||
>>> from mindspore import ParallelMode, ParameterTuple
|
||||
>>> from mindspore import ParameterTuple
|
||||
>>> from mindspore.context import ParallelMode
|
||||
>>>
|
||||
>>> device_id = int(os.environ["DEVICE_ID"])
|
||||
>>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=True,
|
||||
|
|
|
@ -36,7 +36,7 @@ from mindspore.parallel._utils import _need_to_full
|
|||
from mindspore.train import amp
|
||||
from mindspore.parallel._utils import _to_full_tensor
|
||||
from mindspore.train.callback import _InternalCallbackParam, RunContext, _CallbackManager
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from .dataset_helper import DatasetHelper
|
||||
|
||||
|
||||
|
|
|
@ -22,7 +22,7 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.parameter import Parameter
|
||||
from mindspore.common import dtype as mstype
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._utils import _get_device_num, _get_parallel_mode, _get_mirror_mean
|
||||
|
||||
from .transformer import Transformer
|
||||
|
|
|
@ -26,7 +26,8 @@ from mindspore.nn.optim import Adam, Lamb
|
|||
from mindspore.train.model import Model
|
||||
from mindspore.train.loss_scale_manager import DynamicLossScaleManager, FixedLossScaleManager
|
||||
from mindspore.train.callback import CheckpointConfig, ModelCheckpoint
|
||||
from mindspore import context, ParallelMode, Parameter
|
||||
from mindspore import context, Parameter
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication import management as MultiAscend
|
||||
from mindspore.train.serialization import load_checkpoint
|
||||
|
||||
|
|
|
@ -24,7 +24,7 @@ import mindspore.common.dtype as mstype
|
|||
from mindspore import context
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.train.callback import TimeMonitor
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.optim import AdamWeightDecay
|
||||
from mindspore.nn.wrap.loss_scale import DynamicLossScaleUpdateCell
|
||||
from mindspore import log as logger
|
||||
|
|
|
@ -26,7 +26,7 @@ from mindspore.common import dtype as mstype
|
|||
from mindspore.common.parameter import Parameter
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.train.serialization import load_checkpoint, load_param_into_net
|
||||
from .tinybert_model import BertModel, TinyBertModel, BertModelCLS
|
||||
|
||||
|
|
|
@ -22,7 +22,7 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.parameter import Parameter, ParameterTuple
|
||||
from mindspore.common import dtype as mstype
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._utils import _get_device_num, _get_parallel_mode, _get_mirror_mean
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore import context
|
||||
|
|
|
@ -29,7 +29,7 @@ from mindspore.train.callback import Callback, TimeMonitor
|
|||
from mindspore.train.serialization import load_checkpoint, load_param_into_net
|
||||
import mindspore.dataset.engine as de
|
||||
import mindspore.communication.management as D
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore import context
|
||||
|
||||
from src.transformer_for_train import TransformerTrainOneStepCell, TransformerNetworkWithLoss, \
|
||||
|
|
|
@ -19,7 +19,8 @@ import argparse
|
|||
import random
|
||||
import numpy as np
|
||||
|
||||
from mindspore import context, ParallelMode
|
||||
from mindspore import context
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import init, get_rank, get_group_size
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor
|
||||
|
|
|
@ -17,7 +17,7 @@ callbacks
|
|||
import time
|
||||
from mindspore.train.callback import Callback
|
||||
from mindspore import context
|
||||
from mindspore.train import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_rank
|
||||
|
||||
def add_write(file_path, out_str):
|
||||
|
|
|
@ -23,7 +23,7 @@ from mindspore.ops import operations as P
|
|||
from mindspore.nn import Dropout
|
||||
from mindspore.nn.optim import Adam, FTRL, LazyAdam
|
||||
from mindspore.common.initializer import Uniform, initializer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.communication.management import get_group_size
|
||||
|
||||
|
|
|
@ -20,7 +20,7 @@ import sys
|
|||
import mindspore.dataset.engine as de
|
||||
from mindspore import Model, context
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor
|
||||
from mindspore.train import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_rank, get_group_size, init
|
||||
from mindspore.parallel import set_multi_subgraphs
|
||||
from mindspore.nn.wrap.cell_wrapper import VirtualDatasetCellTriple
|
||||
|
|
|
@ -20,7 +20,7 @@ import sys
|
|||
import numpy as np
|
||||
from mindspore import Model, context
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor
|
||||
from mindspore.train import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_rank, get_group_size, init
|
||||
|
||||
from src.wide_and_deep import PredictWithSigmoid, TrainStepWrap, NetWithLossClass, WideDeepModel
|
||||
|
|
|
@ -20,7 +20,7 @@ import sys
|
|||
import numpy as np
|
||||
from mindspore import Model, context
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor
|
||||
from mindspore.train import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_rank, get_group_size, init
|
||||
|
||||
from src.wide_and_deep import PredictWithSigmoid, TrainStepWrap, NetWithLossClass, WideDeepModel
|
||||
|
|
|
@ -24,7 +24,7 @@ from mindspore.ops import operations as P
|
|||
from mindspore.nn import Dropout, Flatten
|
||||
from mindspore.nn.optim import Adam, FTRL
|
||||
from mindspore.common.initializer import Uniform, initializer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
|
||||
|
||||
|
|
|
@ -20,7 +20,7 @@ import numpy as np
|
|||
from mindspore import Model, context
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig
|
||||
from mindspore.train.callback import TimeMonitor
|
||||
from mindspore.train import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_rank, get_group_size, init
|
||||
|
||||
from src.wide_and_deep import PredictWithSigmoid, TrainStepWrap, NetWithLossClass, WideDeepModel
|
||||
|
|
|
@ -28,7 +28,8 @@ from mindspore.nn.optim.momentum import Momentum
|
|||
from mindspore.ops import operations as P
|
||||
from mindspore.parallel import set_algo_parameters
|
||||
from mindspore.train.callback import Callback
|
||||
from mindspore.train.model import Model, ParallelMode
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
|
||||
context.set_context(device_id=int(os.getenv('DEVICE_ID')))
|
||||
|
|
|
@ -30,7 +30,8 @@ from mindspore.nn.optim.momentum import Momentum
|
|||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor
|
||||
from mindspore.train.model import Model, ParallelMode
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
random.seed(1)
|
||||
np.random.seed(1)
|
||||
|
|
|
@ -30,7 +30,8 @@ from mindspore.nn.optim.momentum import Momentum
|
|||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMonitor
|
||||
from mindspore.train.model import Model, ParallelMode
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
random.seed(1)
|
||||
np.random.seed(1)
|
||||
|
|
|
@ -19,7 +19,7 @@ import os
|
|||
import sys
|
||||
from mindspore import Model, context
|
||||
from mindspore.train.callback import TimeMonitor
|
||||
from mindspore.train import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_rank, get_group_size, init
|
||||
from mindspore.parallel import set_multi_subgraphs
|
||||
from mindspore.nn.wrap.cell_wrapper import VirtualDatasetCellTriple
|
||||
|
|
|
@ -25,7 +25,7 @@ from mindspore.nn.optim import Adam, FTRL
|
|||
from mindspore.common.initializer import Uniform, initializer
|
||||
# from mindspore.train.callback import ModelCheckpoint, CheckpointConfig
|
||||
from mindspore.parallel._utils import _get_device_num, _get_parallel_mode, _get_mirror_mean
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.communication.management import get_group_size
|
||||
import numpy as np
|
||||
|
|
|
@ -20,7 +20,7 @@ import sys
|
|||
import numpy as np
|
||||
from mindspore import Model, context
|
||||
from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, TimeMonitor
|
||||
from mindspore.train import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_rank, get_group_size, init
|
||||
|
||||
from src.wide_and_deep import PredictWithSigmoid, TrainStepWrap, NetWithLossClass, WideDeepModel
|
||||
|
|
|
@ -19,6 +19,7 @@ import numpy as np
|
|||
import mindspore as ms
|
||||
import mindspore.nn as nn
|
||||
from mindspore import context, Tensor
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore.common.initializer import TruncatedNormal
|
||||
|
@ -652,7 +653,7 @@ class TrainingWrapper(nn.Cell):
|
|||
self.reducer_flag = False
|
||||
self.grad_reducer = None
|
||||
self.parallel_mode = context.get_auto_parallel_context("parallel_mode")
|
||||
if self.parallel_mode in [ms.ParallelMode.DATA_PARALLEL, ms.ParallelMode.HYBRID_PARALLEL]:
|
||||
if self.parallel_mode in [ParallelMode.DATA_PARALLEL, ParallelMode.HYBRID_PARALLEL]:
|
||||
self.reducer_flag = True
|
||||
if self.reducer_flag:
|
||||
mean = context.get_auto_parallel_context("mirror_mean")
|
||||
|
|
|
@ -24,7 +24,7 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.parameter import Parameter, ParameterTuple
|
||||
from mindspore.common import dtype as mstype
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore import context
|
||||
from .bert_model import BertModel
|
||||
|
|
|
@ -26,7 +26,7 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.parameter import Parameter, ParameterTuple
|
||||
from mindspore.common import dtype as mstype
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.communication.management import get_group_size
|
||||
from mindspore import context
|
||||
from mindspore.model_zoo.Bert_NEZHA.bert_model import BertModel
|
||||
|
|
|
@ -16,7 +16,7 @@
|
|||
from mindspore._checkparam import check_bool
|
||||
from mindspore.parallel._utils import _get_device_num, _get_parallel_mode, _to_full_shapes
|
||||
from mindspore.train._utils import _exec_datagraph, _get_types_and_shapes
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
def _send_data(dataset):
|
||||
"""Engine dataset to write data to tdt queue."""
|
||||
|
|
|
@ -103,7 +103,8 @@ class DistributedGradReducerThor(Cell):
|
|||
>>> from mindspore.ops import functional as F
|
||||
>>> from mindspore import context
|
||||
>>> from mindspore import nn
|
||||
>>> from mindspore import ParallelMode, ParameterTuple
|
||||
>>> from mindspore import ParameterTuple
|
||||
>>> from mindspore.context import ParallelMode
|
||||
>>>
|
||||
>>> device_id = int(os.environ["DEVICE_ID"])
|
||||
>>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=True,
|
||||
|
|
|
@ -30,7 +30,7 @@ from mindspore.parallel._utils import _get_parallel_mode, _get_device_num, _get_
|
|||
_get_parameter_broadcast, _device_number_check, _parameter_broadcast_check
|
||||
from mindspore.train import amp
|
||||
from mindspore.train.callback import _InternalCallbackParam, RunContext, _CallbackManager
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
from .dataset_helper import DatasetHelper
|
||||
|
||||
|
|
|
@ -24,7 +24,8 @@ import numpy as np
|
|||
from mindspore import context, Tensor
|
||||
from mindspore.communication.management import init
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from mindspore.train.model import Model, ParallelMode
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.train.callback import Callback
|
||||
from mindspore.train.loss_scale_manager import FixedLossScaleManager
|
||||
import mindspore.nn as nn
|
||||
|
|
|
@ -32,7 +32,8 @@ from mindspore.communication.management import init
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from mindspore.train.model import Model, ParallelMode
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
random.seed(1)
|
||||
np.random.seed(1)
|
||||
|
|
|
@ -32,7 +32,8 @@ from mindspore.nn.optim.momentum import Momentum
|
|||
from mindspore.ops import operations as P
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from mindspore.train.callback import Callback
|
||||
from mindspore.train.model import Model, ParallelMode
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
random.seed(1)
|
||||
np.random.seed(1)
|
||||
|
|
|
@ -25,7 +25,7 @@ from mindspore.common.api import _executor
|
|||
from mindspore.nn import Momentum
|
||||
from mindspore.nn import TrainOneStepCell, WithLossCell
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
|
||||
class DenseMMNet(nn.Cell):
|
||||
|
|
|
@ -21,7 +21,8 @@ import numpy as np
|
|||
|
||||
import mindspore.context as context
|
||||
import mindspore.nn as nn
|
||||
from mindspore import Tensor, Model, ParallelMode
|
||||
from mindspore import Tensor, Model
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.optim import Momentum
|
||||
from mindspore.ops import operations as P
|
||||
|
||||
|
|
|
@ -19,7 +19,8 @@ import numpy as np
|
|||
|
||||
import mindspore.context as context
|
||||
import mindspore.nn as nn
|
||||
from mindspore import Tensor, Model, ParallelMode
|
||||
from mindspore import Tensor, Model
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.nn.optim import Momentum
|
||||
from mindspore.ops.operations import TensorAdd
|
||||
from ....dataset_mock import MindData
|
||||
|
|
|
@ -26,7 +26,7 @@ from mindspore.nn import TrainOneStepCell, WithLossCell
|
|||
from mindspore.ops import composite as C
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.ops import functional as F
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.ops_common import convert
|
||||
from ....train_step_wrap import train_step_with_loss_warp
|
||||
|
||||
|
|
|
@ -22,7 +22,8 @@ from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.parallel import _cost_model_context as cost_model_context
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
|
||||
|
|
|
@ -24,7 +24,8 @@ from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.parallel._utils import _reset_op_id
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
|
||||
|
|
|
@ -23,7 +23,8 @@ from mindspore.common.parameter import Parameter
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import composite as C
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
from tests.ut.python.ops.test_math_ops import VirtualLoss
|
||||
|
||||
|
|
|
@ -29,7 +29,8 @@ from mindspore.ops import operations as P
|
|||
from mindspore.parallel import _cost_model_context as cost_model_context
|
||||
from mindspore.parallel import set_algo_parameters
|
||||
from mindspore.parallel._utils import _reset_op_id as resset_op_id
|
||||
from mindspore.train.model import Model, ParallelMode
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
|
||||
context.set_context(device_id=0)
|
||||
|
|
|
@ -26,7 +26,8 @@ from mindspore.nn.layer.pooling import MaxPool2d
|
|||
from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
||||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
dev_num = 8
|
||||
|
|
|
@ -27,7 +27,7 @@ from mindspore.nn.optim.momentum import Momentum
|
|||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train.model import Model
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
|
||||
|
|
|
@ -22,7 +22,8 @@ from mindspore.common.parameter import Parameter, ParameterTuple
|
|||
from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
||||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import composite as C, functional as F, operations as P
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.train.loss_scale_manager import DynamicLossScaleManager
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
|
|
|
@ -23,7 +23,8 @@ from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.parallel._utils import _reset_op_id
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
class Dataset(MindData):
|
||||
|
|
|
@ -27,7 +27,8 @@ from mindspore.nn.optim import Momentum
|
|||
from mindspore.ops import composite as C
|
||||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE)
|
||||
device_number = 32
|
||||
|
|
|
@ -25,7 +25,8 @@ from mindspore.ops import functional as F
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.nn.wrap.loss_scale import DynamicLossScaleUpdateCell
|
||||
import mindspore.nn as nn
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
|
||||
|
|
|
@ -25,7 +25,8 @@ from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.parallel._utils import _reset_op_id
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE)
|
||||
|
|
|
@ -25,7 +25,8 @@ from mindspore.nn.optim.momentum import Momentum
|
|||
from mindspore.ops import composite as C
|
||||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
from tests.ut.python.ops.test_math_ops import VirtualLoss
|
||||
|
||||
|
|
|
@ -29,7 +29,8 @@ from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.ops.operations import TensorAdd
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
dev_num = 8
|
||||
|
|
|
@ -23,7 +23,7 @@ from mindspore.nn import Dense
|
|||
from mindspore.nn import Momentum
|
||||
from mindspore.nn import TrainOneStepCell, WithLossCell
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train.parallel_utils import ParallelMode
|
||||
from mindspore.context import ParallelMode
|
||||
|
||||
|
||||
class Net(nn.Cell):
|
||||
|
|
|
@ -24,7 +24,8 @@ from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
|||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE)
|
||||
|
|
|
@ -28,7 +28,8 @@ from mindspore.ops import functional as F
|
|||
from mindspore.ops import operations as P
|
||||
from mindspore.ops.operations.comm_ops import _VirtualDataset
|
||||
from mindspore.parallel import set_algo_parameters
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
from tests.ut.python.ops.test_math_ops import VirtualLoss
|
||||
|
||||
|
|
|
@ -21,7 +21,8 @@ from mindspore.common.parameter import Parameter
|
|||
from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
|
||||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from tests.dataset_mock import MindData
|
||||
|
||||
|
||||
|
|
|
@ -20,7 +20,8 @@ import mindspore.context as context
|
|||
from mindspore import Tensor
|
||||
from mindspore import amp
|
||||
from mindspore import nn
|
||||
from mindspore.train import Model, ParallelMode
|
||||
from mindspore.train import Model
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.common import dtype as mstype
|
||||
from ....dataset_mock import MindData
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
|
|
Loading…
Reference in New Issue