# Copyright 2021-2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# ============================================================================
"""Controlling dump behavior."""
from __future__ import absolute_import
from warnings import warn
import mindspore.context as context
from mindspore._c_expression import security
[文档]def set_dump(target, enabled=True):
"""
Enable or disable dump for the `target` and its contents.
`target` should be an instance of :class:`mindspore.nn.Cell` or :class:`mindspore.ops.Primitive` .
Please note that this API takes effect only when Synchronous Dump is enabled and the `dump_mode`
field in dump config file is ``"2"`` . See the `dump document
<https://www.mindspore.cn/tutorials/en/master/debug/dump.html>`_ for details.
The default enabled status for
a :class:`mindspore.nn.Cell` or :class:`mindspore.ops.Primitive` is False.
Note:
1. This API is only effective for GRAPH_MODE whose graph compilation level is O0/O1 with Ascend backend,
and can not work for fusion Primitive operators.
2. This API only supports being called before training starts.
If you call this API during training, it may not be effective.
3. After using `set_dump(Cell, True)` , operators in forward and backward
computation (computation generated by the grad operations) of the
cell will be dumped.
4. For :class:`mindspore.nn.SoftmaxCrossEntropyWithLogits` layer, the forward
computation and backward computation use the same set of
operators. So you can only see dump data from backward computation.
Please note that :class:`mindspore.nn.SoftmaxCrossEntropyWithLogits` layer will also use
the above operators internally when initialized with `sparse=True` and
`reduction="mean"` .
Args:
target (Union[Cell, Primitive]): The Cell instance or Primitive instance
to which the dump flag is set.
enabled (bool, optional): ``True`` means enable dump, ``False`` means disable dump.
Default: ``True`` .
Supported Platforms:
``Ascend``
Examples:
.. note::
Please set environment variable `MINDSPORE_DUMP_CONFIG` to the dump config file and set `dump_mode` field
in dump config file to 2 before running this example.
See `dump document <https://www.mindspore.cn/tutorials/en/master/debug/dump.html>`_ for details.
>>> import numpy as np
>>> import mindspore as ms
>>> import mindspore.nn as nn
>>> from mindspore import Tensor, set_dump
>>>
>>> ms.set_context(mode=ms.GRAPH_MODE)
>>> ms.set_device(device_target="Ascend")
>>>
>>> class MyNet(nn.Cell):
... def __init__(self):
... super().__init__()
... self.conv1 = nn.Conv2d(5, 6, 5, pad_mode='valid')
... self.relu1 = nn.ReLU()
...
... def construct(self, x):
... x = self.conv1(x)
... x = self.relu1(x)
... return x
>>>
>>> if __name__ == "__main__":
... net = MyNet()
... set_dump(net.conv1)
... input_tensor = Tensor(np.ones([1, 5, 10, 10], dtype=np.float32))
... output = net(input_tensor)
"""
if security.enable_security():
raise ValueError('The set_dump API is not supported, please recompile '
'source without "-s on".')
import mindspore.nn as nn # avoid circular import
from mindspore.ops import Primitive
if not isinstance(target, nn.Cell) and not isinstance(target, Primitive):
raise ValueError(f"The \"target\" parameter must be an instance of "
f"Cell or Primitive, "
f"but got an instance of {type(target)}.")
if not isinstance(enabled, bool):
raise ValueError("The \"enabled\" parameter must be bool.")
# Checking for device target and mode.
current_target = context.get_context("device_target")
if current_target != "Ascend":
# We will not return here in case user changed device_target later.
warn("Current device_target is {}, which is not supported by set_dump. "
"Only Ascend device target is supported currently. "
"If you have Ascend device, consider set device_target to Ascend "
"before calling set_dump.".format(current_target))
current_mode = context.get_context("mode")
if current_mode != context.GRAPH_MODE:
# We will not return here in case user changed mode later.
warn(
"Current mode is PYNATIVE_MODE, which is not supported by set_dump. "
"Only GRAPH_MODE is supported currently. "
"Consider set mode to GRAPH_MODE "
"before calling set_dump.")
# The actual set dump logic.
if isinstance(target, nn.Cell):
target.add_flags(dump=enabled)
for cell in target.cells():
set_dump(cell, enabled)
primitives = getattr(target, "_primitives", {})
for value in primitives.values():
if value and "dump" in value.attrs:
set_dump(value, enabled)
if isinstance(target, Primitive):
target.add_prim_attr("dump", "true" if enabled else "false")