forked from mindspore-Ecosystem/mindspore
!40159 clean code for master
Merge pull request !40159 from changzherui/clean_code_python2_ma
This commit is contained in:
Gitee
commit
16588a9eed
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@ -14,20 +14,20 @@
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# ============================================================================
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"""Top-level reference to dtype of common module."""
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from __future__ import absolute_import
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from . import dtype
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from .api import ms_function, ms_memory_recycle, ms_class, _convert_python_data
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from .dtype import Type, int8, byte, int16, short, int32, intc, int64, intp, \
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from mindspore.common import dtype
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from mindspore.common.api import ms_function, ms_memory_recycle, ms_class, _convert_python_data
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from mindspore.common.dtype import Type, int8, byte, int16, short, int32, intc, int64, intp, \
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uint8, ubyte, uint16, ushort, uint32, uintc, uint64, uintp, float16, half, \
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float32, single, float64, double, bool_, float_, list_, tuple_, int_, \
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uint, number, tensor, string, type_none, tensor_type, Int, \
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complex64, complex128, dtype_to_nptype, issubclass_, \
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dtype_to_pytype, pytype_to_dtype, get_py_obj_dtype
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from .dump import set_dump
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from .parameter import Parameter, ParameterTuple
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from .seed import set_seed, get_seed
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from .tensor import Tensor, RowTensor, SparseTensor, COOTensor, CSRTensor
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from .mutable import mutable
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from .jit_config import JitConfig
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from mindspore.common.dump import set_dump
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from mindspore.common.parameter import Parameter, ParameterTuple
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from mindspore.common.seed import set_seed, get_seed
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from mindspore.common.tensor import Tensor, RowTensor, SparseTensor, COOTensor, CSRTensor
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from mindspore.common.mutable import mutable
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from mindspore.common.jit_config import JitConfig
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# symbols from dtype
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__all__ = [
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@ -14,7 +14,7 @@
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# ============================================================================
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"""Define Monad default value."""
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from __future__ import absolute_import
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from .._c_expression import IOMonad, UMonad
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from mindspore._c_expression import IOMonad, UMonad
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# Universe monad default value.
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U = UMonad()
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@ -17,7 +17,7 @@
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from __future__ import absolute_import
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from collections import UserDict
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from .. import context
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from mindspore import context
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class Registry(UserDict):
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@ -31,21 +31,21 @@ import mindspore as ms
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from mindspore import context
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from mindspore import log as logger
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from mindspore._extends.remote import kernel_build_server
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from .tensor import Tensor as PythonTensor
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from .tensor import CSRTensor as PythonCSRTensor
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from .tensor import COOTensor as PythonCOOTensor
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from .tensor import RowTensor as PythonRowTensor
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from .initializer import initializer
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from .._c_expression import GraphExecutor_, Tensor, MetaTensor, CSRTensor, RowTensor, COOTensor, PynativeExecutor_
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from .._c_expression import verify_inputs_signature, init_exec_dataset, _set_dataset_mode_config, init_pipeline, \
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_ms_memory_recycle
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from ..parallel._tensor import _load_tensor_by_layout
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from ..parallel._ps_context import _is_role_pserver, _is_role_sched, _enable_distributed_mindrt
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from ..parallel._utils import _get_device_num, _get_global_rank, _need_to_full, _check_full_batch, _to_full_tensor, \
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_get_parameter_broadcast, _get_pipeline_stages
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from .._checkparam import Validator
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from ._utils import is_shape_unknown
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from ..common.mutable import mutable
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from mindspore.common.tensor import Tensor as PythonTensor
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from mindspore.common.tensor import CSRTensor as PythonCSRTensor
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from mindspore.common.tensor import COOTensor as PythonCOOTensor
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from mindspore.common.tensor import RowTensor as PythonRowTensor
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from mindspore.common.initializer import initializer
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from mindspore._c_expression import GraphExecutor_, Tensor, MetaTensor, CSRTensor, RowTensor, COOTensor,\
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PynativeExecutor_, verify_inputs_signature, init_exec_dataset, _set_dataset_mode_config, init_pipeline
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from mindspore.parallel._tensor import _load_tensor_by_layout
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from mindspore.parallel._ps_context import _is_role_pserver, _is_role_sched, _enable_distributed_mindrt
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from mindspore.parallel._utils import _get_device_num, _get_global_rank, _need_to_full, _check_full_batch, \
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_to_full_tensor, _get_parameter_broadcast, _get_pipeline_stages
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from mindspore._checkparam import Validator
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from mindspore.common._utils import is_shape_unknown
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from mindspore.common.mutable import mutable
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# store ms_function class compiled pipeline cache
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ms_compile_cache = set()
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@ -20,8 +20,8 @@ from __future__ import absolute_import
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from inspect import isfunction
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import numpy as np
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from mindspore import log as logger
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from .._c_expression import typing
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from .._c_expression.typing import Type
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from mindspore._c_expression import typing
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from mindspore._c_expression.typing import Type
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__dtype__ = [
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"int8", "byte",
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@ -21,10 +21,10 @@ import math
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from functools import reduce
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import numpy as np
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from scipy.stats import truncnorm
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from .seed import get_seed, _get_graph_seed
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from . import dtype as mstype
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from .tensor import Tensor
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from .._c_expression import random_normal
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from mindspore.common.seed import get_seed, _get_graph_seed
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from mindspore.common import dtype as mstype
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from mindspore.common.tensor import Tensor
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from mindspore._c_expression import random_normal
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_INITIALIZER_ALIAS = dict()
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@ -15,7 +15,7 @@
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"""mutable function for setting constants mutable."""
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from __future__ import absolute_import
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from ..common.tensor import Tensor
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from mindspore.common.tensor import Tensor
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class _Tuple(tuple):
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@ -22,21 +22,21 @@ import numbers
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import numpy as np
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from mindspore import log as logger
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from mindspore.log import _LogActionOnce
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from .._c_expression import ParamInfo
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from . import dtype as mstype
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from .. import context
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from ..parallel._utils import _get_parallel_mode
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from .initializer import initializer
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from .tensor import Tensor
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from .._checkparam import Validator
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from .._c_expression import Tensor as Tensor_
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from ..parallel._tensor import _get_slice_index
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from ..parallel._auto_parallel_context import auto_parallel_context
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from ..parallel._ps_context import _is_role_worker, _is_role_pserver, _is_role_sched, _clone_hash_table,\
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_is_fl_mode, _enable_distributed_mindrt
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from ..parallel._ps_context import _reinsert_hash_table_size
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from ..parallel._ps_context import _insert_weight_init_info, _insert_accumu_init_info
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from .seed import _get_global_and_op_seed
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from mindspore._c_expression import ParamInfo
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from mindspore.common import dtype as mstype
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from mindspore import context
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from mindspore.parallel._utils import _get_parallel_mode
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from mindspore.common.initializer import initializer
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from mindspore.common.tensor import Tensor
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from mindspore._checkparam import Validator
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from mindspore._c_expression import Tensor as Tensor_
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from mindspore.parallel._tensor import _get_slice_index
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from mindspore.parallel._auto_parallel_context import auto_parallel_context
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from mindspore.parallel._ps_context import _is_role_worker, _is_role_pserver, _is_role_sched, _clone_hash_table, \
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_is_fl_mode, _enable_distributed_mindrt
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from mindspore.parallel._ps_context import _reinsert_hash_table_size
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from mindspore.parallel._ps_context import _insert_weight_init_info, _insert_accumu_init_info
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from mindspore.common.seed import _get_global_and_op_seed
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__all__ = ['Parameter', 'ParameterTuple']
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@ -23,14 +23,14 @@ from mindspore.common._utils import is_shape_unknown
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from mindspore import context
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from mindspore import log as logger
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from . import dtype as mstype
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from ._register_for_tensor import tensor_operator_registry
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from .._c_expression import COOTensor as COOTensor_
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from .._c_expression import CSRTensor as CSRTensor_
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from .._c_expression import RowTensor as RowTensor_
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from .._c_expression import Tensor as Tensor_
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from .._checkparam import Rel
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from .._checkparam import Validator as validator
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from mindspore.common import dtype as mstype
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from mindspore.common._register_for_tensor import tensor_operator_registry
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from mindspore._c_expression import COOTensor as COOTensor_
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from mindspore._c_expression import CSRTensor as CSRTensor_
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from mindspore._c_expression import RowTensor as RowTensor_
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from mindspore._c_expression import Tensor as Tensor_
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from mindspore._checkparam import Rel
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from mindspore._checkparam import Validator as validator
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__all__ = ['Tensor', 'RowTensor', 'SparseTensor', 'COOTensor', 'CSRTensor']
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np_types = (np.int8, np.int16, np.int32, np.int64,
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@ -19,22 +19,21 @@ Pre-defined building blocks or computing units to construct neural networks.
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"""
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from __future__ import absolute_import
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from . import layer, loss, optim, metrics, wrap, grad, probability, sparse, dynamic_lr,\
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reinforcement
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from .learning_rate_schedule import *
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from .dynamic_lr import *
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from .cell import Cell, GraphCell
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from .layer import *
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from .loss import *
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from .optim import *
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from .metrics import *
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from .wrap import *
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from .grad import Jvp, Vjp
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from .sparse import *
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from .reinforcement import *
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from .transformer import AttentionMask, VocabEmbedding, MultiHeadAttention, FeedForward, TransformerEncoder, \
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TransformerDecoder, TransformerEncoderLayer, TransformerDecoderLayer, Transformer, TransformerOpParallelConfig, \
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EmbeddingOpParallelConfig, TransformerRecomputeConfig, MoEConfig, OpParallelConfig
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from mindspore.nn import layer, loss, optim, metrics, wrap, grad, probability, sparse, dynamic_lr, reinforcement
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from mindspore.nn.learning_rate_schedule import *
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from mindspore.nn.dynamic_lr import *
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from mindspore.nn.cell import Cell, GraphCell
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from mindspore.nn.layer import *
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from mindspore.nn.loss import *
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from mindspore.nn.optim import *
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from mindspore.nn.metrics import *
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from mindspore.nn.wrap import *
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from mindspore.nn.grad import Jvp, Vjp
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from mindspore.nn.sparse import *
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from mindspore.nn.reinforcement import *
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from mindspore.nn.transformer import AttentionMask, VocabEmbedding, MultiHeadAttention, FeedForward, \
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TransformerEncoder, TransformerDecoder, TransformerEncoderLayer, TransformerDecoderLayer, Transformer,\
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TransformerOpParallelConfig, EmbeddingOpParallelConfig, TransformerRecomputeConfig, MoEConfig, OpParallelConfig
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__all__ = ["Cell", "GraphCell"]
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__all__.extend(layer.__all__)
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@ -30,17 +30,17 @@ from mindspore.common.parameter import PARAMETER_NAME_DEFAULT
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from mindspore.common.hook_handle import HookHandle
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from mindspore.context import ParallelMode
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from mindspore.ops.composite import Shard
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from .. import context
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from .._c_expression import init_pipeline, update_func_graph_hyper_params, Cell_, FuncGraph, MixedPrecisionType
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from .._checkparam import Validator
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from ..common import dtype as mstype
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from ..common.api import _cell_graph_executor, _pynative_executor, _check_all_tensor, cells_compile_cache
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from ..common.parameter import Parameter, ParameterTuple
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from ..common.tensor import Tensor, CSRTensor, COOTensor
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from ..ops.operations import Cast
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from ..ops.primitive import Primitive
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from ..ops.operations import _inner_ops as inner
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from ..parallel._tensor import _load_tensor_by_layout
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from mindspore import context
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from mindspore._c_expression import init_pipeline, update_func_graph_hyper_params, Cell_, FuncGraph, MixedPrecisionType
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from mindspore._checkparam import Validator
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from mindspore.common import dtype as mstype
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from mindspore.common.api import _cell_graph_executor, _pynative_executor, _check_all_tensor, cells_compile_cache
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from mindspore.common.parameter import Parameter, ParameterTuple
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from mindspore.common.tensor import Tensor, CSRTensor, COOTensor
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from mindspore.ops.operations import Cast
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from mindspore.ops.primitive import Primitive
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from mindspore.ops.operations import _inner_ops as inner
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from mindspore.parallel._tensor import _load_tensor_by_layout
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class Cell(Cell_):
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@ -15,7 +15,7 @@
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"""Cells of grad function. Calculate the gradient of input network or function."""
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from __future__ import absolute_import
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from .cell_grad import Jvp, Vjp
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from mindspore.nn.grad.cell_grad import Jvp, Vjp
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__all__ = ['Jvp', 'Vjp']
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@ -15,12 +15,12 @@
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"""cell grad"""
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from __future__ import absolute_import
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from ..cell import Cell
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from ...ops import composite as C
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from ...ops import operations as P
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from ...ops.primitive import Primitive
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from ...common import dtype as mstype
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from ...common.api import ms_function
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from mindspore.nn.cell import Cell
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from mindspore.ops import composite as C
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from mindspore.ops import operations as P
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from mindspore.ops.primitive import Primitive
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from mindspore.common import dtype as mstype
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from mindspore.common.api import ms_function
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class _FirstGrad(Cell):
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@ -115,6 +115,7 @@ class Jvp(Cell):
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@ms_function
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def construct(self, *args):
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"""construct for jvp."""
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jvp_input = args[0:-1]
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v = args[-1]
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output = self.fn(*jvp_input)
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@ -155,9 +156,7 @@ class _JvpInner(Cell):
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self.tuple_len = Primitive("tuple_len")
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def compute_jvp(self, fn, v, jvp_input, output):
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"""
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Compute the jacobian-vector-product of the given fn, vector, inputs and outputs.
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"""
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"""Compute the jacobian-vector-product of the given fn, vector, inputs and outputs."""
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if self.issubclass_(self.typeof(output), mstype.tuple_):
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u = self.make_tuple()
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for i in range(self.tuple_len(output)):
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@ -18,10 +18,10 @@ from __future__ import division
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import math
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from ..common import dtype as mstype
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from ..ops import operations as P
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from .cell import Cell
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from .._checkparam import Validator as validator
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from mindspore.common import dtype as mstype
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from mindspore.ops import operations as P
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from mindspore.nn.cell import Cell
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from mindspore._checkparam import Validator as validator
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class LearningRateSchedule(Cell):
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@ -20,25 +20,25 @@ on the evaluation dataset. It's used to choose the best model.
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"""
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from __future__ import absolute_import
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from .accuracy import Accuracy
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from .hausdorff_distance import HausdorffDistance
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from .error import MAE, MSE
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from .metric import Metric, rearrange_inputs
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from .precision import Precision
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from .recall import Recall
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from .fbeta import Fbeta, F1
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from .dice import Dice
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from .roc import ROC
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from .auc import auc
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from .topk import TopKCategoricalAccuracy, Top1CategoricalAccuracy, Top5CategoricalAccuracy
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from .loss import Loss
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from .mean_surface_distance import MeanSurfaceDistance
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from .root_mean_square_surface_distance import RootMeanSquareDistance
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from .bleu_score import BleuScore
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from .cosine_similarity import CosineSimilarity
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from .occlusion_sensitivity import OcclusionSensitivity
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from .perplexity import Perplexity
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from .confusion_matrix import ConfusionMatrixMetric, ConfusionMatrix
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from mindspore.nn.metrics.accuracy import Accuracy
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from mindspore.nn.metrics.hausdorff_distance import HausdorffDistance
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from mindspore.nn.metrics.error import MAE, MSE
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from mindspore.nn.metrics.metric import Metric, rearrange_inputs
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from mindspore.nn.metrics.precision import Precision
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from mindspore.nn.metrics.recall import Recall
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from mindspore.nn.metrics.fbeta import Fbeta, F1
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from mindspore.nn.metrics.dice import Dice
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||||
from mindspore.nn.metrics.roc import ROC
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||||
from mindspore.nn.metrics.auc import auc
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||||
from mindspore.nn.metrics.topk import TopKCategoricalAccuracy, Top1CategoricalAccuracy, Top5CategoricalAccuracy
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from mindspore.nn.metrics.loss import Loss
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from mindspore.nn.metrics.mean_surface_distance import MeanSurfaceDistance
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from mindspore.nn.metrics.root_mean_square_surface_distance import RootMeanSquareDistance
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from mindspore.nn.metrics.bleu_score import BleuScore
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from mindspore.nn.metrics.cosine_similarity import CosineSimilarity
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from mindspore.nn.metrics.occlusion_sensitivity import OcclusionSensitivity
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||||
from mindspore.nn.metrics.perplexity import Perplexity
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||||
from mindspore.nn.metrics.confusion_matrix import ConfusionMatrixMetric, ConfusionMatrix
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||||
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__all__ = [
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"names",
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|
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|
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@ -16,7 +16,7 @@
|
|||
from __future__ import absolute_import
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||||
|
||||
import numpy as np
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from .metric import EvaluationBase, rearrange_inputs, _check_onehot_data
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||||
from mindspore.nn.metrics.metric import EvaluationBase, rearrange_inputs, _check_onehot_data
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|
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class Accuracy(EvaluationBase):
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|
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|
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|
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@ -18,7 +18,7 @@ from __future__ import absolute_import
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|||
from collections import Counter
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||||
import numpy as np
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||||
from mindspore._checkparam import Validator as validator
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||||
from .metric import Metric, rearrange_inputs
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from mindspore.nn.metrics.metric import Metric, rearrange_inputs
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|
||||
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class BleuScore(Metric):
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|
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|
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@ -17,7 +17,7 @@ from __future__ import absolute_import
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|||
|
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import numpy as np
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from mindspore._checkparam import Validator as validator
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||||
from .metric import Metric, rearrange_inputs
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||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class ConfusionMatrix(Metric):
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||||
|
|
|
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|
|
@ -17,7 +17,7 @@ from __future__ import absolute_import
|
|||
|
||||
import numpy as np
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class CosineSimilarity(Metric):
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ from __future__ import absolute_import
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class Dice(Metric):
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@ from __future__ import absolute_import
|
|||
|
||||
import numpy as np
|
||||
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class MAE(Metric):
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ import sys
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs, _check_onehot_data
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs, _check_onehot_data
|
||||
|
||||
|
||||
class Fbeta(Metric):
|
||||
|
|
|
|||
|
|
@ -22,7 +22,7 @@ import numpy as np
|
|||
|
||||
from mindspore.common.tensor import Tensor
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class _ROISpatialData(metaclass=ABCMeta):
|
||||
|
|
@ -114,8 +114,8 @@ class HausdorffDistance(Metric):
|
|||
string_list = ["euclidean", "chessboard", "taxicab"]
|
||||
distance_metric = validator.check_value_type("distance_metric", distance_metric, [str])
|
||||
self.distance_metric = validator.check_string(distance_metric, string_list, "distance_metric")
|
||||
self.percentile = percentile if percentile is None else validator.check_value_type("percentile",
|
||||
percentile, [float])
|
||||
self.percentile = percentile if percentile is None else \
|
||||
validator.check_value_type("percentile", percentile, [float])
|
||||
self.directed = directed if directed is None else validator.check_value_type("directed", directed, [bool])
|
||||
self.crop = crop if crop is None else validator.check_value_type("crop", crop, [bool])
|
||||
self.clear()
|
||||
|
|
|
|||
|
|
@ -15,7 +15,7 @@
|
|||
"""Loss for evaluation"""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class Loss(Metric):
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ from scipy.ndimage import morphology
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class MeanSurfaceDistance(Metric):
|
||||
|
|
|
|||
|
|
@ -20,7 +20,7 @@ import numpy as np
|
|||
from mindspore import nn
|
||||
from mindspore.common.tensor import Tensor
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
try:
|
||||
from tqdm import trange
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ import math
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class Perplexity(Metric):
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ import sys
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import EvaluationBase, rearrange_inputs, _check_onehot_data
|
||||
from mindspore.nn.metrics.metric import EvaluationBase, rearrange_inputs, _check_onehot_data
|
||||
|
||||
|
||||
class Precision(EvaluationBase):
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ import sys
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import EvaluationBase, rearrange_inputs, _check_onehot_data
|
||||
from mindspore.nn.metrics.metric import EvaluationBase, rearrange_inputs, _check_onehot_data
|
||||
|
||||
|
||||
class Recall(EvaluationBase):
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ from __future__ import absolute_import
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs, _binary_clf_curve
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs, _binary_clf_curve
|
||||
|
||||
|
||||
class ROC(Metric):
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ from scipy.ndimage import morphology
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .metric import Metric, rearrange_inputs
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs
|
||||
|
||||
|
||||
class RootMeanSquareDistance(Metric):
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@ from __future__ import absolute_import
|
|||
|
||||
import numpy as np
|
||||
|
||||
from .metric import Metric, rearrange_inputs, _check_onehot_data
|
||||
from mindspore.nn.metrics.metric import Metric, rearrange_inputs, _check_onehot_data
|
||||
|
||||
|
||||
class TopKCategoricalAccuracy(Metric):
|
||||
|
|
|
|||
|
|
@ -20,24 +20,24 @@ The optimizer is used to calculate and update the gradients.
|
|||
"""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from .optimizer import Optimizer
|
||||
from .momentum import Momentum
|
||||
from .adam import Adam, AdamWeightDecay, AdamOffload
|
||||
from .lamb import Lamb
|
||||
from .sgd import SGD
|
||||
from .asgd import ASGD
|
||||
from .rprop import Rprop
|
||||
from .lars import LARS
|
||||
from .ftrl import FTRL
|
||||
from .rmsprop import RMSProp
|
||||
from .proximal_ada_grad import ProximalAdagrad
|
||||
from .lazyadam import LazyAdam
|
||||
from .ada_grad import Adagrad
|
||||
from .thor import thor
|
||||
from .adafactor import AdaFactor
|
||||
from .adasum import AdaSumByDeltaWeightWrapCell, AdaSumByGradWrapCell
|
||||
from .adamax import AdaMax
|
||||
from .adadelta import Adadelta
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.momentum import Momentum
|
||||
from mindspore.nn.optim.adam import Adam, AdamWeightDecay, AdamOffload
|
||||
from mindspore.nn.optim.lamb import Lamb
|
||||
from mindspore.nn.optim.sgd import SGD
|
||||
from mindspore.nn.optim.asgd import ASGD
|
||||
from mindspore.nn.optim.rprop import Rprop
|
||||
from mindspore.nn.optim.lars import LARS
|
||||
from mindspore.nn.optim.ftrl import FTRL
|
||||
from mindspore.nn.optim.rmsprop import RMSProp
|
||||
from mindspore.nn.optim.proximal_ada_grad import ProximalAdagrad
|
||||
from mindspore.nn.optim.lazyadam import LazyAdam
|
||||
from mindspore.nn.optim.ada_grad import Adagrad
|
||||
from mindspore.nn.optim.thor import thor
|
||||
from mindspore.nn.optim.adafactor import AdaFactor
|
||||
from mindspore.nn.optim.adasum import AdaSumByDeltaWeightWrapCell, AdaSumByGradWrapCell
|
||||
from mindspore.nn.optim.adamax import AdaMax
|
||||
from mindspore.nn.optim.adadelta import Adadelta
|
||||
|
||||
__all__ = ['Optimizer', 'Momentum', 'LARS', 'Adam', 'AdamWeightDecay', 'LazyAdam', 'AdamOffload',
|
||||
'Lamb', 'SGD', 'ASGD', 'Rprop', 'FTRL', 'RMSProp', 'ProximalAdagrad', 'Adagrad', 'thor', 'AdaFactor',
|
||||
|
|
|
|||
|
|
@ -18,8 +18,9 @@ from __future__ import absolute_import
|
|||
from mindspore.ops import functional as F, composite as C, operations as P
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore.common.api import ms_function
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
|
||||
_ada_grad_opt = C.MultitypeFuncGraph("ada_grad_opt")
|
||||
|
||||
|
|
|
|||
|
|
@ -19,8 +19,8 @@ from mindspore.ops import functional as F, composite as C, operations as P
|
|||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore._checkparam import Rel
|
||||
from mindspore.common.tensor import Tensor
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
_adadelta_opt = C.MultitypeFuncGraph("adadelta_opt")
|
||||
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore._checkparam import Rel
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
from .optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
|
||||
|
||||
def _rms(update_tensor):
|
||||
|
|
|
|||
|
|
@ -28,9 +28,9 @@ from mindspore.common.parameter import Parameter
|
|||
from mindspore.common.tensor import Tensor
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore._checkparam import Rel
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from ._dist_optimizer_registry import _register_dist_optimizer
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim._dist_optimizer_registry import _register_dist_optimizer
|
||||
|
||||
_adam_opt = C.MultitypeFuncGraph("adam_opt")
|
||||
_fused_adam_weight_decay = C.MultitypeFuncGraph("fused_adam_weight_decay")
|
||||
|
|
|
|||
|
|
@ -22,8 +22,8 @@ from mindspore.common.tensor import Tensor
|
|||
import mindspore.common.dtype as mstype
|
||||
import mindspore
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
|
||||
class ASGD(Optimizer):
|
||||
|
|
|
|||
|
|
@ -19,9 +19,9 @@ from mindspore.ops import functional as F, composite as C, operations as P
|
|||
from mindspore.common.api import ms_function
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore._checkparam import Rel
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from ._dist_optimizer_registry import _register_dist_optimizer
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim._dist_optimizer_registry import _register_dist_optimizer
|
||||
|
||||
_ftrl_opt = C.MultitypeFuncGraph("ftrl_opt")
|
||||
|
||||
|
|
|
|||
|
|
@ -25,8 +25,8 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.api import ms_function
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore._checkparam import Rel
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
_lamb_opt = C.MultitypeFuncGraph("lamb_opt")
|
||||
|
||||
|
|
|
|||
|
|
@ -21,8 +21,8 @@ from mindspore.ops import functional as F
|
|||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore.common import Tensor, Parameter, dtype as mstype
|
||||
from mindspore.common.api import ms_function
|
||||
from .optimizer import _grad_scale, Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import _grad_scale, Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
_lars_opt = C.MultitypeFuncGraph("lars_opt")
|
||||
|
||||
|
|
|
|||
|
|
@ -25,9 +25,9 @@ from mindspore.common.parameter import Parameter
|
|||
from mindspore.common.tensor import Tensor
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore._checkparam import Rel
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from ._dist_optimizer_registry import _register_dist_optimizer
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim._dist_optimizer_registry import _register_dist_optimizer
|
||||
|
||||
_lazy_adam_opt = C.MultitypeFuncGraph("lazy_adam_opt")
|
||||
|
||||
|
|
|
|||
|
|
@ -21,9 +21,9 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.api import ms_function
|
||||
import mindspore.common.dtype as mstype
|
||||
from mindspore._checkparam import Validator
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from ._dist_optimizer_registry import _register_dist_optimizer
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim._dist_optimizer_registry import _register_dist_optimizer
|
||||
|
||||
|
||||
_momentum_opt = C.MultitypeFuncGraph("momentum_opt")
|
||||
|
|
|
|||
|
|
@ -35,7 +35,7 @@ from mindspore.parallel._ps_context import _is_ps_mode, _enable_distributed_mind
|
|||
from mindspore.context import ParallelMode
|
||||
from mindspore import context
|
||||
from mindspore.nn.learning_rate_schedule import LearningRateSchedule
|
||||
from ._dist_optimizer_registry import generate_dist_optimizer_list
|
||||
from mindspore.nn.optim._dist_optimizer_registry import generate_dist_optimizer_list
|
||||
|
||||
__all__ = ['Optimizer', 'opt_init_args_register']
|
||||
|
||||
|
|
@ -185,8 +185,8 @@ class Optimizer(Cell):
|
|||
"""initialize optimizer attributions"""
|
||||
weight_decay = self._preprocess_weight_decay(weight_decay)
|
||||
if self.is_group_lr:
|
||||
self.learning_rate = CellList(self.group_lr, auto_prefix=False) if self.dynamic_lr \
|
||||
else ParameterTuple(self.group_lr)
|
||||
self.learning_rate = CellList(self.group_lr, auto_prefix=False) \
|
||||
if self.dynamic_lr else ParameterTuple(self.group_lr)
|
||||
else:
|
||||
self.learning_rate = self._build_single_lr(learning_rate, 'learning_rate')
|
||||
|
||||
|
|
|
|||
|
|
@ -20,8 +20,8 @@ from mindspore.common import Tensor
|
|||
import mindspore.common.dtype as mstype
|
||||
from mindspore.common.api import ms_function
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
_proximal_ada_grad_opt = C.MultitypeFuncGraph("proximal_ada_grad_opt")
|
||||
|
||||
|
|
|
|||
|
|
@ -18,8 +18,8 @@ from __future__ import absolute_import
|
|||
from mindspore.ops import functional as F, composite as C, operations as P
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore.common.api import ms_function
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
_rmsprop_opt = C.MultitypeFuncGraph("rmsprop_opt")
|
||||
_centered_rmsprop_opt = C.MultitypeFuncGraph("rmsprop_opt")
|
||||
|
|
|
|||
|
|
@ -21,8 +21,8 @@ import mindspore.common.dtype as mstype
|
|||
from mindspore.common.api import ms_function
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore._checkparam import Rel
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
|
||||
class Rprop(Optimizer):
|
||||
|
|
|
|||
|
|
@ -21,8 +21,8 @@ from mindspore.common.tensor import Tensor
|
|||
from mindspore.common.api import ms_function
|
||||
import mindspore.common.dtype as mstype
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from .optimizer import Optimizer
|
||||
from .optimizer import opt_init_args_register
|
||||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.optim.optimizer import opt_init_args_register
|
||||
|
||||
_sgd_opt = C.MultitypeFuncGraph("sgd_opt")
|
||||
|
||||
|
|
|
|||
|
|
@ -15,7 +15,7 @@
|
|||
"""Sparse related transformation."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from .sparse import (SparseToDense, SparseTensorDenseMatmul)
|
||||
from mindspore.nn.sparse.sparse import (SparseToDense, SparseTensorDenseMatmul)
|
||||
|
||||
__all__ = [
|
||||
"SparseToDense",
|
||||
|
|
|
|||
|
|
@ -16,7 +16,7 @@
|
|||
from __future__ import absolute_import
|
||||
|
||||
from mindspore.ops import operations as P
|
||||
from ..cell import Cell
|
||||
from mindspore.nn.cell import Cell
|
||||
|
||||
|
||||
class SparseToDense(Cell):
|
||||
|
|
|
|||
|
|
@ -19,11 +19,12 @@ Use the Wrapper to combine the loss or build the training steps.
|
|||
"""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from .cell_wrapper import ForwardValueAndGrad, TrainOneStepCell, WithLossCell, WithGradCell, WithEvalCell, \
|
||||
ParameterUpdate, GetNextSingleOp, VirtualDatasetCellTriple, MicroBatchInterleaved, PipelineCell
|
||||
from .loss_scale import TrainOneStepWithLossScaleCell, DynamicLossScaleUpdateCell, FixedLossScaleUpdateCell
|
||||
from .grad_reducer import DistributedGradReducer
|
||||
from ..layer.timedistributed import TimeDistributed
|
||||
from mindspore.nn.wrap.cell_wrapper import ForwardValueAndGrad, TrainOneStepCell, WithLossCell, WithGradCell, \
|
||||
WithEvalCell, ParameterUpdate, GetNextSingleOp, VirtualDatasetCellTriple, MicroBatchInterleaved, PipelineCell
|
||||
from mindspore.nn.wrap.loss_scale import TrainOneStepWithLossScaleCell,\
|
||||
DynamicLossScaleUpdateCell, FixedLossScaleUpdateCell
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
from mindspore.nn.layer.timedistributed import TimeDistributed
|
||||
|
||||
|
||||
__all__ = [
|
||||
|
|
|
|||
|
|
@ -24,15 +24,15 @@ from mindspore.parallel._utils import _get_device_num, _get_gradients_mean,\
|
|||
from mindspore.context import ParallelMode
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore import ops, nn
|
||||
from ...common import dtype as mstype
|
||||
from ...common.parameter import Parameter, ParameterTuple
|
||||
from ...ops.primitive import constexpr
|
||||
from ...ops import composite as C
|
||||
from ...ops import functional as F
|
||||
from ...ops import operations as P
|
||||
from ...ops.operations.comm_ops import _VirtualDataset
|
||||
from ..cell import Cell
|
||||
from .grad_reducer import DistributedGradReducer
|
||||
from mindspore.common import dtype as mstype
|
||||
from mindspore.common.parameter import Parameter, ParameterTuple
|
||||
from mindspore.ops.primitive import constexpr
|
||||
from mindspore.ops import composite as C
|
||||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.ops.operations.comm_ops import _VirtualDataset
|
||||
from mindspore.nn.cell import Cell
|
||||
from mindspore.nn.wrap.grad_reducer import DistributedGradReducer
|
||||
|
||||
_get_datatype = C.MultitypeFuncGraph("_get_datatype")
|
||||
|
||||
|
|
@ -478,6 +478,7 @@ class _MicroBatch(Cell):
|
|||
self.strided_slice = P.StridedSlice()
|
||||
|
||||
def construct(self, i, *inputs):
|
||||
"""construct for _MicroBatch."""
|
||||
micro_inputs = ()
|
||||
for each_input in inputs:
|
||||
input_shape = self.shape(each_input)
|
||||
|
|
|
|||
|
|
@ -18,14 +18,14 @@ from __future__ import absolute_import
|
|||
import mindspore.context as context
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._utils import _get_enable_parallel_optimizer
|
||||
from .cell_wrapper import TrainOneStepCell
|
||||
from ..cell import Cell
|
||||
from ...common import Tensor, RowTensor
|
||||
from ...common.parameter import Parameter
|
||||
from ...ops import functional as F
|
||||
from ...ops import composite as C
|
||||
from ...ops import operations as P
|
||||
from ...common import dtype as mstype
|
||||
from mindspore.nn.wrap.cell_wrapper import TrainOneStepCell
|
||||
from mindspore.nn.cell import Cell
|
||||
from mindspore.common import Tensor, RowTensor
|
||||
from mindspore.common.parameter import Parameter
|
||||
from mindspore.ops import functional as F
|
||||
from mindspore.ops import composite as C
|
||||
from mindspore.ops import operations as P
|
||||
from mindspore.common import dtype as mstype
|
||||
|
||||
_grad_scale = C.MultitypeFuncGraph("grad_scale")
|
||||
reciprocal = P.Reciprocal()
|
||||
|
|
|
|||
|
|
@ -14,17 +14,17 @@
|
|||
# ============================================================================
|
||||
"""Auto mixed precision."""
|
||||
from __future__ import absolute_import
|
||||
from .. import nn
|
||||
from .._checkparam import Validator as validator
|
||||
from .._checkparam import Rel
|
||||
from ..common import dtype as mstype
|
||||
from ..nn.wrap.cell_wrapper import _TrainPipelineAccuStepCell
|
||||
from ..nn.wrap.loss_scale import _TrainPipelineWithLossScaleCell
|
||||
from ..ops import functional as F
|
||||
from ..parallel._utils import _get_pipeline_stages
|
||||
from .loss_scale_manager import DynamicLossScaleManager, LossScaleManager
|
||||
from .. import boost
|
||||
from .. import context
|
||||
|
||||
from mindspore import nn
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore._checkparam import Rel
|
||||
from mindspore.common import dtype as mstype
|
||||
from mindspore.nn.wrap.cell_wrapper import _TrainPipelineAccuStepCell
|
||||
from mindspore.nn.wrap.loss_scale import _TrainPipelineWithLossScaleCell
|
||||
from mindspore.ops import functional as F
|
||||
from mindspore.parallel._utils import _get_pipeline_stages
|
||||
from mindspore.train.loss_scale_manager import DynamicLossScaleManager, LossScaleManager
|
||||
from mindspore import boost, context
|
||||
|
||||
|
||||
AMP_WHITE_LIST = (
|
||||
|
|
@ -46,7 +46,7 @@ AMP_BLACK_LIST = (
|
|||
|
||||
|
||||
class _OutputTo16(nn.Cell):
|
||||
"Wrap cell for amp. Cast network output back to float16"
|
||||
"""Wrap cell for amp. Cast network output back to float16."""
|
||||
|
||||
def __init__(self, op):
|
||||
super(_OutputTo16, self).__init__(auto_prefix=False)
|
||||
|
|
|
|||
|
|
@ -13,27 +13,27 @@
|
|||
# limitations under the License.
|
||||
# ============================================================================
|
||||
"""Callback related classes and functions."""
|
||||
|
||||
from __future__ import absolute_import
|
||||
from ._callback import Callback
|
||||
from ._callback import CallbackManager as _CallbackManager
|
||||
from ._callback import InternalCallbackParam as _InternalCallbackParam
|
||||
from ._callback import RunContext
|
||||
from ._callback import checkpoint_cb_for_save_op as _checkpoint_cb_for_save_op
|
||||
from ._callback import set_cur_net as _set_cur_net
|
||||
from ._checkpoint import CheckpointConfig
|
||||
from ._checkpoint import CheckpointManager as _CheckpointManager
|
||||
from ._checkpoint import ModelCheckpoint
|
||||
from ._loss_monitor import LossMonitor
|
||||
from ._time_monitor import TimeMonitor
|
||||
from ._summary_collector import SummaryCollector
|
||||
from ._lr_scheduler_callback import LearningRateScheduler
|
||||
from ._landscape import SummaryLandscape
|
||||
from ._fl_manager import FederatedLearningManager
|
||||
from ._history import History
|
||||
from ._lambda_callback import LambdaCallback
|
||||
from ._early_stop import EarlyStopping
|
||||
from ._reduce_lr_on_plateau import ReduceLROnPlateau
|
||||
|
||||
from mindspore.train.callback._callback import Callback
|
||||
from mindspore.train.callback._callback import CallbackManager as _CallbackManager
|
||||
from mindspore.train.callback._callback import InternalCallbackParam as _InternalCallbackParam
|
||||
from mindspore.train.callback._callback import RunContext
|
||||
from mindspore.train.callback._callback import checkpoint_cb_for_save_op as _checkpoint_cb_for_save_op
|
||||
from mindspore.train.callback._callback import set_cur_net as _set_cur_net
|
||||
from mindspore.train.callback._checkpoint import CheckpointConfig
|
||||
from mindspore.train.callback._checkpoint import CheckpointManager as _CheckpointManager
|
||||
from mindspore.train.callback._checkpoint import ModelCheckpoint
|
||||
from mindspore.train.callback._loss_monitor import LossMonitor
|
||||
from mindspore.train.callback._time_monitor import TimeMonitor
|
||||
from mindspore.train.callback._summary_collector import SummaryCollector
|
||||
from mindspore.train.callback._lr_scheduler_callback import LearningRateScheduler
|
||||
from mindspore.train.callback._landscape import SummaryLandscape
|
||||
from mindspore.train.callback._fl_manager import FederatedLearningManager
|
||||
from mindspore.train.callback._history import History
|
||||
from mindspore.train.callback._lambda_callback import LambdaCallback
|
||||
from mindspore.train.callback._early_stop import EarlyStopping
|
||||
from mindspore.train.callback._reduce_lr_on_plateau import ReduceLROnPlateau
|
||||
|
||||
|
||||
__all__ = ["Callback", "LossMonitor", "TimeMonitor", "ModelCheckpoint",
|
||||
|
|
|
|||
|
|
@ -29,9 +29,9 @@ from mindspore.train.serialization import save_checkpoint, _save_graph
|
|||
from mindspore.parallel._ps_context import _is_role_pserver, _get_ps_mode_rank, _enable_distributed_mindrt
|
||||
from mindspore.parallel._cell_wrapper import destroy_allgather_cell
|
||||
from mindspore.parallel._recovery_context import _set_recovery_context, _get_recovery_context
|
||||
from ._callback import Callback, set_cur_net
|
||||
from ...common.tensor import Tensor
|
||||
from ...common.parameter import Parameter
|
||||
from mindspore.train.callback._callback import Callback, set_cur_net
|
||||
from mindspore.common.tensor import Tensor
|
||||
from mindspore.common.parameter import Parameter
|
||||
|
||||
_cur_dir = os.getcwd()
|
||||
_save_dir = _cur_dir
|
||||
|
|
|
|||
|
|
@ -29,7 +29,7 @@ from mindspore.ops import ReduceOp
|
|||
from mindspore.communication import get_group_size
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from ._callback import Callback, _handle_loss
|
||||
from mindspore.train.callback._callback import Callback, _handle_loss
|
||||
|
||||
|
||||
_smaller_better_metrics = ['hausdorff_distance', 'mae', 'mse', 'loss', 'perplexity',
|
||||
|
|
@ -133,7 +133,7 @@ class EarlyStopping(Callback):
|
|||
self.wait = 0
|
||||
self.stopped_epoch = 0
|
||||
self.best = np.Inf if self.mode == 'min' or \
|
||||
(self.mode == 'auto' and self.monitor in _smaller_better_metrics) else -np.Inf
|
||||
(self.mode == 'auto' and self.monitor in _smaller_better_metrics) else -np.Inf
|
||||
self.best_weights_param_dict = None
|
||||
|
||||
def on_train_epoch_end(self, run_context):
|
||||
|
|
@ -152,8 +152,8 @@ class EarlyStopping(Callback):
|
|||
|
||||
parallel_mode = auto_parallel_context().get_parallel_mode()
|
||||
rank_size = 1 if parallel_mode == ParallelMode.STAND_ALONE else get_group_size()
|
||||
current = current_value if rank_size == 1 else \
|
||||
self._reduce(Tensor(current_value.astype(np.float32))) / rank_size
|
||||
current = current_value if \
|
||||
rank_size == 1 else self._reduce(Tensor(current_value.astype(np.float32))) / rank_size
|
||||
|
||||
if current is None:
|
||||
return
|
||||
|
|
|
|||
|
|
@ -272,8 +272,8 @@ class FederatedLearningManager(Callback):
|
|||
"""
|
||||
Set the value of last parameters for adaptive synchronization.
|
||||
"""
|
||||
self._last_param = {_.name: deepcopy(_.asnumpy()) for _ in self._model.trainable_params()
|
||||
if self._as_prefix not in _.name}
|
||||
self._last_param = {_.name: deepcopy(_.asnumpy())
|
||||
for _ in self._model.trainable_params() if self._as_prefix not in _.name}
|
||||
|
||||
def step_end(self, run_context):
|
||||
"""
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ from __future__ import absolute_import
|
|||
import numpy as np
|
||||
|
||||
from mindspore.common.tensor import Tensor
|
||||
from ._callback import Callback
|
||||
from mindspore.train.callback._callback import Callback
|
||||
|
||||
|
||||
class History(Callback):
|
||||
|
|
|
|||
|
|
@ -15,7 +15,7 @@
|
|||
"""Lambda Callback class."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from ._callback import Callback
|
||||
from mindspore.train.callback._callback import Callback
|
||||
|
||||
|
||||
class LambdaCallback(Callback):
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ from __future__ import absolute_import
|
|||
import numpy as np
|
||||
|
||||
from mindspore._checkparam import Validator
|
||||
from ._callback import Callback, _handle_loss
|
||||
from mindspore.train.callback._callback import Callback, _handle_loss
|
||||
|
||||
|
||||
class LossMonitor(Callback):
|
||||
|
|
|
|||
|
|
@ -27,7 +27,7 @@ from mindspore import nn, ops
|
|||
from mindspore.communication import get_group_size
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._auto_parallel_context import auto_parallel_context
|
||||
from ._callback import Callback, _handle_loss
|
||||
from mindspore.train.callback._callback import Callback, _handle_loss
|
||||
|
||||
|
||||
_smaller_better_metrics = ['hausdorff_distance', 'mae', 'mse', 'loss', 'perplexity',
|
||||
|
|
@ -129,7 +129,7 @@ class ReduceLROnPlateau(Callback):
|
|||
self.cooldown_counter = 0
|
||||
self.wait = 0
|
||||
self.best = np.Inf if self.mode == 'min' or \
|
||||
(self.mode == 'auto' and self.monitor in _smaller_better_metrics) else -np.Inf
|
||||
(self.mode == 'auto' and self.monitor in _smaller_better_metrics) else -np.Inf
|
||||
|
||||
def on_train_epoch_end(self, run_context):
|
||||
"""
|
||||
|
|
|
|||
|
|
@ -40,7 +40,7 @@ from mindspore.train.callback._dataset_graph import DatasetGraph
|
|||
from mindspore.nn.optim.optimizer import Optimizer
|
||||
from mindspore.nn.loss.loss import LossBase
|
||||
from mindspore.train._utils import check_value_type, _make_directory
|
||||
from ..._c_expression import security
|
||||
from mindspore._c_expression import security
|
||||
|
||||
HYPER_CONFIG_ENV_NAME = "MINDINSIGHT_HYPER_CONFIG"
|
||||
HYPER_CONFIG_LEN_LIMIT = 100000
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ from __future__ import absolute_import
|
|||
import time
|
||||
|
||||
from mindspore._checkparam import Validator
|
||||
from ._callback import Callback
|
||||
from mindspore.train.callback._callback import Callback
|
||||
|
||||
|
||||
class TimeMonitor(Callback):
|
||||
|
|
|
|||
|
|
@ -23,12 +23,13 @@ from mindspore.common.api import _cell_graph_executor
|
|||
from mindspore.common._utils import is_shape_unknown
|
||||
from mindspore.dataset.engine import offload
|
||||
import mindspore.dataset as ds
|
||||
from .. import context, nn
|
||||
from ._utils import _exec_datagraph, _get_types_and_shapes, _construct_tensor_list
|
||||
from ..parallel._utils import _get_device_num, _get_global_rank, _need_to_full, _to_full_shapes, _get_pipeline_stages
|
||||
from ..parallel._ps_context import _is_role_worker, _is_role_pserver, _is_role_sched, _is_ps_mode, \
|
||||
from mindspore import context, nn
|
||||
from mindspore.train._utils import _exec_datagraph, _get_types_and_shapes, _construct_tensor_list
|
||||
from mindspore.parallel._utils import _get_device_num, _get_global_rank, _need_to_full, \
|
||||
_to_full_shapes, _get_pipeline_stages
|
||||
from mindspore.parallel._ps_context import _is_role_worker, _is_role_pserver, _is_role_sched, _is_ps_mode, \
|
||||
_enable_distributed_mindrt
|
||||
from ..ops import operations as P
|
||||
from mindspore.ops import operations as P
|
||||
|
||||
|
||||
def _send_data(dataset, epoch_num):
|
||||
|
|
|
|||
|
|
@ -15,8 +15,8 @@
|
|||
"""Loss scale manager abstract class."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from .._checkparam import Validator as validator
|
||||
from .. import nn
|
||||
from mindspore._checkparam import Validator as validator
|
||||
from mindspore import nn
|
||||
|
||||
|
||||
class LossScaleManager:
|
||||
|
|
|
|||
|
|
@ -24,29 +24,29 @@ import copy
|
|||
import numpy as np
|
||||
|
||||
from mindspore import log as logger
|
||||
from .serialization import save_checkpoint, load_checkpoint
|
||||
from .callback._checkpoint import ModelCheckpoint, _chg_ckpt_file_name_if_same_exist
|
||||
from ..common.tensor import Tensor
|
||||
from ..nn.metrics import get_metrics, get_metric_fn
|
||||
from .._checkparam import check_input_data, check_output_data, Validator
|
||||
from .callback import _InternalCallbackParam, RunContext, _CallbackManager, Callback, TimeMonitor
|
||||
from .callback import __all__ as internal_cb_names
|
||||
from .. import context
|
||||
from ..parallel._utils import _get_parallel_mode, _get_device_num, _get_global_rank, \
|
||||
from mindspore.train.serialization import save_checkpoint, load_checkpoint
|
||||
from mindspore.train.callback._checkpoint import ModelCheckpoint, _chg_ckpt_file_name_if_same_exist
|
||||
from mindspore.common.tensor import Tensor
|
||||
from mindspore.nn.metrics import get_metrics, get_metric_fn
|
||||
from mindspore._checkparam import check_input_data, check_output_data, Validator
|
||||
from mindspore.train.callback import _InternalCallbackParam, RunContext, _CallbackManager, Callback, TimeMonitor
|
||||
from mindspore.train.callback import __all__ as internal_cb_names
|
||||
from mindspore import context
|
||||
from mindspore.parallel._utils import _get_parallel_mode, _get_device_num, _get_global_rank, \
|
||||
_get_parameter_broadcast, _device_number_check, _parameter_broadcast_check, _parallel_predict_check, \
|
||||
_reset_op_id_with_offset
|
||||
from ..parallel._ps_context import _is_role_worker, _is_role_pserver, _is_role_sched, _is_ps_mode, _cache_enable, \
|
||||
_enable_distributed_mindrt
|
||||
from ..nn.metrics import Loss
|
||||
from .. import nn
|
||||
from ..boost import AutoBoost
|
||||
from ..context import ParallelMode
|
||||
from ..parallel._cost_model_context import _set_multi_subgraphs
|
||||
from ..parallel._recovery_context import _set_recovery_context, _get_recovery_context
|
||||
from .dataset_helper import DatasetHelper, connect_network_with_dataset
|
||||
from mindspore.parallel._ps_context import _is_role_worker, _is_role_pserver, _is_role_sched, _is_ps_mode, \
|
||||
_cache_enable, _enable_distributed_mindrt
|
||||
from mindspore.nn.metrics import Loss
|
||||
from mindspore import nn
|
||||
from mindspore.boost import AutoBoost
|
||||
from mindspore.context import ParallelMode
|
||||
from mindspore.parallel._cost_model_context import _set_multi_subgraphs
|
||||
from mindspore.parallel._recovery_context import _set_recovery_context, _get_recovery_context
|
||||
from mindspore.train.dataset_helper import DatasetHelper, connect_network_with_dataset
|
||||
from mindspore.common.api import _pynative_executor
|
||||
from mindspore.dataset.engine.datasets import _set_training_dataset, _reset_training_dataset
|
||||
from . import amp
|
||||
from ..common.api import _pynative_executor
|
||||
from ..dataset.engine.datasets import _set_training_dataset, _reset_training_dataset
|
||||
|
||||
|
||||
def _transfer_tensor_to_tuple(inputs):
|
||||
|
|
|
|||
|
|
@ -55,7 +55,7 @@ from mindspore.parallel._tensor import _load_tensor, _get_tensor_strategy, _get_
|
|||
from mindspore.parallel._tensor import _reshape_param_data, _reshape_param_data_with_weight
|
||||
from mindspore.parallel._utils import _infer_rank_list, _remove_repeated_slices
|
||||
from mindspore.train._utils import read_proto
|
||||
from .._c_expression import load_mindir, _encrypt, _decrypt, _is_cipher_file
|
||||
from mindspore._c_expression import load_mindir, _encrypt, _decrypt, _is_cipher_file
|
||||
|
||||
|
||||
tensor_to_ms_type = {"Int8": mstype.int8, "UInt8": mstype.uint8, "Int16": mstype.int16, "UInt16": mstype.uint16,
|
||||
|
|
|
|||
|
|
@ -16,7 +16,8 @@
|
|||
Summary related classes and functions. User can use SummaryRecord to dump the summary data, the summary is a series of
|
||||
operations to collect data for analysis and visualization.
|
||||
"""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from .summary_record import SummaryRecord
|
||||
from mindspore.train.summary.summary_record import SummaryRecord
|
||||
|
||||
__all__ = ["SummaryRecord"]
|
||||
|
|
|
|||
|
|
@ -13,9 +13,11 @@
|
|||
# limitations under the License.
|
||||
# ============================================================================
|
||||
"""Generate the lineage event which conform to proto format."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
import time
|
||||
|
||||
from ..lineage_pb2 import LineageEvent
|
||||
from mindspore.train.lineage_pb2 import LineageEvent
|
||||
|
||||
|
||||
def serialize_to_lineage_event(name, value):
|
||||
|
|
|
|||
|
|
@ -13,6 +13,8 @@
|
|||
# limitations under the License.
|
||||
# ============================================================================
|
||||
"""Generate the summary event which conform to proto format."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
import io
|
||||
import platform
|
||||
import time
|
||||
|
|
@ -25,9 +27,9 @@ from mindspore import context
|
|||
from mindspore.communication.management import get_rank
|
||||
from mindspore.communication.management import GlobalComm
|
||||
|
||||
from ..._checkparam import Validator
|
||||
from ..anf_ir_pb2 import DataType, ModelProto
|
||||
from ..summary_pb2 import Event
|
||||
from mindspore._checkparam import Validator
|
||||
from mindspore.train.anf_ir_pb2 import DataType, ModelProto
|
||||
from mindspore.train.summary_pb2 import Event
|
||||
|
||||
# define the MindSpore image format
|
||||
MS_IMAGE_TENSOR_FORMAT = 'NCHW'
|
||||
|
|
|
|||
|
|
@ -13,6 +13,8 @@
|
|||
# limitations under the License.
|
||||
# ============================================================================
|
||||
"""Write events to disk in a base directory."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
import os
|
||||
import time
|
||||
import signal
|
||||
|
|
@ -24,9 +26,9 @@ import psutil
|
|||
import mindspore.log as logger
|
||||
from mindspore.train.summary.enums import PluginEnum, WriterPluginEnum
|
||||
|
||||
from ._lineage_adapter import serialize_to_lineage_event
|
||||
from ._summary_adapter import package_graph_event, package_summary_event
|
||||
from .writer import LineageWriter, SummaryWriter, ExportWriter
|
||||
from mindspore.train.summary._lineage_adapter import serialize_to_lineage_event
|
||||
from mindspore.train.summary._summary_adapter import package_graph_event, package_summary_event
|
||||
from mindspore.train.summary.writer import LineageWriter, SummaryWriter, ExportWriter
|
||||
|
||||
try:
|
||||
from multiprocessing import get_context
|
||||
|
|
|
|||
|
|
@ -13,6 +13,8 @@
|
|||
# limitations under the License.
|
||||
# ============================================================================
|
||||
"""Summary's enumeration file."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from enum import Enum
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -13,6 +13,8 @@
|
|||
# limitations under the License.
|
||||
# ============================================================================
|
||||
"""Record the summary event."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
import atexit
|
||||
import os
|
||||
import re
|
||||
|
|
@ -23,13 +25,13 @@ from collections import defaultdict
|
|||
from mindspore import log as logger
|
||||
from mindspore.nn import Cell
|
||||
|
||||
from ..._c_expression import Tensor, security
|
||||
from ..._checkparam import Validator
|
||||
from ...common.api import _cell_graph_executor
|
||||
from .._utils import _check_lineage_value, _check_to_numpy, _make_directory, check_value_type
|
||||
from ._summary_adapter import get_event_file_name, package_graph_event
|
||||
from ._writer_pool import WriterPool
|
||||
from .enums import PluginEnum
|
||||
from mindspore._c_expression import Tensor, security
|
||||
from mindspore._checkparam import Validator
|
||||
from mindspore.common.api import _cell_graph_executor
|
||||
from mindspore.train._utils import _check_lineage_value, _check_to_numpy, _make_directory, check_value_type
|
||||
from mindspore.train.summary._summary_adapter import get_event_file_name, package_graph_event
|
||||
from mindspore.train.summary._writer_pool import WriterPool
|
||||
from mindspore.train.summary.enums import PluginEnum
|
||||
|
||||
# for the moment, this lock is for caution's sake,
|
||||
# there are actually no any concurrences happening.
|
||||
|
|
|
|||
|
|
@ -13,6 +13,8 @@
|
|||
# limitations under the License.
|
||||
# ============================================================================
|
||||
"""Writes events to disk in a logdir."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
import os
|
||||
import stat
|
||||
from urllib.parse import quote
|
||||
|
|
@ -23,11 +25,11 @@ import numpy as np
|
|||
from mindspore.train.summary.enums import PluginEnum, WriterPluginEnum
|
||||
from mindspore import log as logger
|
||||
|
||||
from .._utils import _make_directory
|
||||
from ._summary_adapter import package_init_event
|
||||
from ..._c_expression import security
|
||||
from mindspore.train._utils import _make_directory
|
||||
from mindspore.train.summary._summary_adapter import package_init_event
|
||||
from mindspore._c_expression import security
|
||||
if not security.enable_security():
|
||||
from ..._c_expression import EventWriter_
|
||||
from mindspore._c_expression import EventWriter_
|
||||
|
||||
|
||||
FREE_DISK_SPACE_TIMES = 32
|
||||
|
|
|
|||
|
|
@ -15,6 +15,6 @@
|
|||
"""convert to second order related classes and functions."""
|
||||
from __future__ import absolute_import
|
||||
|
||||
from .convert_utils import ConvertNetUtils, ConvertModelUtils
|
||||
from mindspore.train.train_thor.convert_utils import ConvertNetUtils, ConvertModelUtils
|
||||
|
||||
__all__ = ["ConvertNetUtils", "ConvertModelUtils"]
|
||||
|
|
|
|||
|
|
@ -32,7 +32,7 @@ from mindspore.train.dataset_helper import connect_network_with_dataset
|
|||
from mindspore.parallel._utils import _need_to_full, _to_full_tensor
|
||||
from mindspore.common.dtype import pytype_to_dtype
|
||||
from mindspore._c_expression import init_exec_dataset
|
||||
from .dataset_helper import DatasetHelper
|
||||
from mindspore.train.train_thor.dataset_helper import DatasetHelper
|
||||
|
||||
|
||||
def _convert_to_ms_type(types):
|
||||
|
|
|
|||
Loading…
Reference in New Issue