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!48857 support precision_mode and jit_compile for mindspore.set_context 

Merge pull request !48857 from zhangyinxia/master
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i-robot 2023-02-21 02:40:31 +00:00 committed by Gitee
parent 5ab2fe68b3 87989f94e7
commit 40b3f79f8b
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GPG Key ID: 173E9B9CA92EEF8F
8 changed files with 145 additions and 8 deletions
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18
docs/api/api_python/mindspore/mindspore.set_context.rst
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@ -78,6 +78,8 @@ mindspore.set_context
| | memory_optimize_level | CPU/GPU/Ascend |
| +------------------------------+----------------------------+
| | memory_offload | GPU/Ascend |
| +------------------------------+----------------------------+
| | ascend_config | Ascend |
+-------------------------+------------------------------+----------------------------+
参数：
@ -167,6 +169,22 @@ mindspore.set_context
- ON：开启memory offload功能。在Ascend硬件平台，未设置环境变量“GRAPH_OP_RUN=1”时本参数不生效；设置memory_optimize_level='O1'时本参数不生效。
- OFF：关闭memory offload功能。
- **ascend_config** (dict) - 设置Ascend硬件平台专用的参数，默认不设置。当前只仅支持在Ascend910B硬件平台设置，其他平台不生效。
- **precision_mode** (str): 混合精度模式设置，Ascend910B硬件平台训练默认值：must_keep_origin_dtype，推理网络默认值：force_fp16。其值范围如下：
- force_fp16: 当算子既支持float16，又支持float32，直接选择float16.
- allow_fp32_to_fp16: 当算子不支持float32数据类型时，直接降低精度float16.
- allow_mix_precision: 自动混合精度，针对全网算子，按照内置的优化策略，自动将部分算子的精度降低到float16或bfloat16.
- must_keep_origin_dtype: 保持原图精度.
- force_fp32: 当算子既支持float16，又支持float32，直接选择float32.
- force_lowerprecision: 当算子支持float16或者bfloat16，又支持float32，直接选择float16或者bfloat16.
- allow_fp32_to_bf16: 当算子不支持float32数据类型时，直接降低精度到bfloat16.
- allow_fp32_to_lowprecision: 当算子不支持float32数据类型时，直接降低精度到float16或者bfloat16.
- allow_mix_precision_fp16: 自动混合精度，正对全网算子，按照内置的优化策略，自动将部分算子的精度降低到float16.
- allow_mix_precision_bf16: 自动混合精度，正对全网算子，按照内置的优化策略，自动将部分算子的精度降低到bfloat16.
- **jit_compile** (bool): 表示是否选择在线编译。默认值：True。当设置为False时，优先选择系统中已经编译好的算子二进制文件，提升编译性能。
异常：
- **ValueError** - 输入key不是上下文中的属性。

34
mindspore/ccsrc/plugin/device/ascend/hal/hardware/ge_device_context.cc
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@ -20,6 +20,7 @@
#include <algorithm>
#include <utility>
#include <map>
#include <set>
#include "include/transform/graph_ir/types.h"
#include "include/transform/graph_ir/utils.h"
#include "include/common/utils/utils.h"
@ -50,6 +51,7 @@ constexpr auto kMindsporeDumpConfig = "MINDSPORE_DUMP_CONFIG";
constexpr auto kOpDebugConfigFile = "ge_op_debug_config.ini";
constexpr char kGeDumpMode[3][7] = {"all", "input", "output"};
const std::set<std::string> kIgnoreGEShapeOps = {kSoftMarginLossOpName};
const std::set<std::string> kAscend910BVersions = {"Ascend910B1", "Ascend910B2", "Ascend910B3", "Ascend910B4"};
std::string GetGraphName(const FuncGraphPtr &graph) {
MS_EXCEPTION_IF_NULL(graph);
@ -577,6 +579,32 @@ void UseOpDebugConfig(std::map<std::string, std::string> *ge_options) {
MS_LOG(INFO) << "Use MS_COMPILER_OP_DEBUG_CONFIG:" << ge_op_debug_config;
}
}
void GeDeviceContext::SetAscendConfig(const std::shared_ptr<MsContext> &ms_context_ptr,
std::map<std::string, std::string> *ge_options) {
MS_EXCEPTION_IF_NULL(ms_context_ptr);
MS_EXCEPTION_IF_NULL(ge_options);
if (ms_context_ptr->get_param<std::string>(MS_CTX_PRECISION_MODE) != "") {
(*ge_options)["ge.exec.precision_mode"] = ms_context_ptr->get_param<std::string>(MS_CTX_PRECISION_MODE);
MS_LOG(INFO) << "Set precision_mode " << ms_context_ptr->get_param<std::string>(MS_CTX_PRECISION_MODE) << ".";
} else if (IsGeTrain()) {
auto soc_version = device::ascend::GetSocVersion();
if (kAscend910BVersions.count(soc_version) != 0) {
(*ge_options)["ge.exec.precision_mode"] = "must_keep_origin_dtype";
MS_LOG(INFO) << "Set precision_mode must_keep_origin_dtype. soc_version is " << soc_version;
} else {
(*ge_options)["ge.exec.precision_mode"] = "allow_fp32_to_fp16";
MS_LOG(INFO) << "Set precision_mode allow_fp32_to_fp16. soc_version is " << soc_version;
}
} else {
(*ge_options)["ge.exec.precision_mode"] = "force_fp16";
}
if (ms_context_ptr->get_param<bool>(MS_CTX_ENABLE_JIT_COMPILE)) {
(*ge_options)["ge.jit_compile"] = "1";
} else {
(*ge_options)["ge.jit_compile"] = "0";
}
}
void GeDeviceContext::GetGeOptions(const std::shared_ptr<MsContext> &ms_context_ptr,
std::map<std::string, std::string> *ge_options) {
@ -674,11 +702,7 @@ void GeDeviceContext::GetGeOptions(const std::shared_ptr<MsContext> &ms_context_
MS_LOG(WARNING) << "Set proto lib path failed!";
}
if (training) {
(*ge_options)["ge.exec.precision_mode"] = "allow_mix_precision";
} else {
(*ge_options)["ge.exec.precision_mode"] = "force_fp16";
}
SetAscendConfig(ms_context_ptr, ge_options);
(*ge_options)["ge.enableSmallChannel"] = "1";

2
mindspore/ccsrc/plugin/device/ascend/hal/hardware/ge_device_context.h
View File

@ -96,6 +96,8 @@ class GeDeviceContext : public DeviceInterface<GeGraphExecutor, GeDeviceResManag
bool FinalizeGe(const std::shared_ptr<MsContext> &inst_context);
void GetGeOptions(const std::shared_ptr<MsContext> &inst_context, std::map<std::string, std::string> *ge_options);
void SetHcclOptions(const std::shared_ptr<MsContext> &inst_context, std::map<std::string, std::string> *ge_options);
void SetAscendConfig(const std::shared_ptr<MsContext> &ms_context_ptr,
std::map<std::string, std::string> *ge_options);
void SetDisableReuseMemoryFlag(std::map<std::string, std::string> *ge_options) const;
std::unique_ptr<AscendDeprecatedInterface> deprecated_interface_;

2
mindspore/ccsrc/pybind_api/utils/ms_context_py.cc
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@ -93,6 +93,8 @@ void RegMsContext(const py::module *m) {
.value("profiling_options", MsCtxParam::MS_CTX_PROFILING_OPTIONS)
.value("save_dump_path", MsCtxParam::MS_CTX_SAVE_DUMP_PATH)
.value("deterministic", MsCtxParam::MS_CTX_DETERMINISTIC)
.value("precision_mode", MsCtxParam::MS_CTX_PRECISION_MODE)
.value("jit_compile", MsCtxParam::MS_CTX_ENABLE_JIT_COMPILE)
.value("save_graphs_path", MsCtxParam::MS_CTX_SAVE_GRAPHS_PATH)
.value("compile_cache_path", MsCtxParam::MS_CTX_COMPILE_CACHE_PATH)
.value("variable_memory_max_size", MsCtxParam::MS_CTX_VARIABLE_MEMORY_MAX_SIZE)

2
mindspore/core/utils/ms_context.cc
View File

@ -64,6 +64,7 @@ MsContext::MsContext(const std::string &policy, const std::string &target) {
set_param<bool>(MS_CTX_ENABLE_DUMP, false);
set_param<std::string>(MS_CTX_SAVE_DUMP_PATH, ".");
set_param<std::string>(MS_CTX_DETERMINISTIC, "OFF");
set_param<std::string>(MS_CTX_PRECISION_MODE, "");
set_param<std::string>(MS_CTX_ENV_CONFIG_PATH, "");
set_param<std::string>(MS_CTX_TUNE_MODE, "NO_TUNE");
set_param<std::string>(MS_CTX_GRAPH_KERNEL_FLAGS, "");
@ -117,6 +118,7 @@ MsContext::MsContext(const std::string &policy, const std::string &target) {
set_param<bool>(MS_CTX_ENABLE_RECOVERY, false);
set_param<bool>(MS_CTX_ENABLE_GE_HETEROGENOUS, false);
set_param<bool>(MS_CTX_DISABLE_FORMAT_TRANSFORM, false);
set_param<bool>(MS_CTX_ENABLE_JIT_COMPILE, true);
set_param<int>(MS_CTX_MEMORY_OPTIMIZE_LEVEL, kOptimizeO0);
set_param<uint32_t>(MS_CTX_OP_TIMEOUT, kOpTimeout);

2
mindspore/core/utils/ms_context.h
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@ -96,6 +96,7 @@ enum MsCtxParam : unsigned {
MS_CTX_ENABLE_RECOVERY,
MS_CTX_ENABLE_GE_HETEROGENOUS,
MS_CTX_DISABLE_FORMAT_TRANSFORM,
MS_CTX_ENABLE_JIT_COMPILE,
MS_CTX_TYPE_BOOL_END,
// parameter of type int
@ -139,6 +140,7 @@ enum MsCtxParam : unsigned {
MS_CTX_GRAPH_KERNEL_FLAGS,
MS_CTX_INFER_PRECISION_MODE, // GPU inference precision mode configured by Serving or Unify API.
MS_CTX_DETERMINISTIC,
MS_CTX_PRECISION_MODE,
MS_CTX_TYPE_STRING_END,
// parameter numbers of each type

68
mindspore/python/mindspore/context.py
View File

@ -244,6 +244,35 @@ class _Context:
f"{deterministic_options}, but got {deterministic}.")
self.set_param(ms_ctx_param.deterministic, deterministic)
def set_ascend_config(self, ascend_config):
"""
Enable ascend config.
Args:
ascend_config (dict): 'precision_mode'
- precision_mode (str): "force_fp16", "allow_fp32_to_fp16", "allow_mix_precision",
"must_keep_origin_dtype", "force_fp32", "force_lowerprecision", "allow_fp32_to_bf16",
"allow_fp32_to_lowprecision", "allow_mix_precision_fp16" and "allow_mix_precision_bf16".
"""
ascend_cfgs = {'precision_mode': ["force_fp16", "allow_fp32_to_fp16", "allow_mix_precision",
"must_keep_origin_dtype", "force_fp32", "force_lowerprecision",
"allow_fp32_to_bf16", "allow_fp32_to_lowprecision",
"allow_mix_precision_fp16", "allow_mix_precision_bf16"],
'jit_compile': [True, False]}
for ascend_key in ascend_config:
if ascend_key not in ascend_cfgs:
raise ValueError(f"For 'context.set_context', the key of argument 'ascend_config' must be one of "
f"{ascend_cfgs}, but got {ascend_key}.")
supported_modes = ascend_cfgs.get(ascend_key)
if ascend_config[ascend_key] not in supported_modes:
raise ValueError(f"For 'ascend_config', the value of argument {ascend_key} must be one of "
f"{supported_modes}, but got {ascend_config[ascend_key]}.")
if ascend_key == 'precision_mode':
self.set_param(ms_ctx_param.precision_mode, ascend_config[ascend_key])
if ascend_key == 'jit_compile':
self.set_param(ms_ctx_param.jit_compile, ascend_config[ascend_key])
def set_backend_policy(self, policy):
success = self._context_handle.set_backend_policy(policy)
if not success:
@ -421,7 +450,8 @@ class _Context:
'memory_optimize_level': set_memory_optimize_level,
'op_timeout': set_op_timeout,
'memory_offload': set_memory_offload,
'deterministic': set_deterministic
'deterministic': set_deterministic,
'ascend_config': set_ascend_config
}
@property
@ -706,7 +736,8 @@ def _check_target_specific_cfgs(device, arg_key):
'auto_tune_mode': ['Ascend'],
'max_device_memory': ['Ascend', 'GPU'],
'mempool_block_size': ['GPU', 'Ascend'],
'disable_format_transform': ['GPU']
'disable_format_transform': ['GPU'],
'ascend_config': ['Ascend']
}
# configs not in map device_cfgs are supposed to be suitable for all devices
if arg_key not in device_cfgs:
@ -728,7 +759,7 @@ def _check_target_specific_cfgs(device, arg_key):
max_device_memory=str, print_file_path=str, max_call_depth=int, env_config_path=str,
graph_kernel_flags=str, save_compile_cache=bool, runtime_num_threads=int, load_compile_cache=bool,
grad_for_scalar=bool, pynative_synchronize=bool, mempool_block_size=str, disable_format_transform=bool,
op_timeout=int, deterministic=str)
op_timeout=int, deterministic=str, ascend_config=dict)
def set_context(**kwargs):
"""
Set context for running environment.
@ -809,6 +840,8 @@ def set_context(**kwargs):
| | memory_optimize_level | CPU/GPU/Ascend |
| +------------------------------+----------------------------+
| | memory_offload | GPU/Ascend |
| +------------------------------+----------------------------+
| | ascend_config | Ascend |
+-------------------------+------------------------------+----------------------------+
Args:
@ -982,7 +1015,33 @@ def set_context(**kwargs):
when the environment variable "GRAPH_OP_RUN=1" is not set; This parameter does not take effect when
memory_optimize_level is set 'O1'.
- OFF: Turn off the memory Offload function.
ascend_config (dict): Set the parameters specific to Ascend hardware platform. It is not set by default.
Currently, only setting `precision_mode' and jit_compile are supported on Ascend910B hardware platform.
- precision_mode (str): Mixed precision mode setting, on Ascend910B hardware platform, the default
value of training network is must_keep_origin_dtype, and the default value of inference network
is force_fp16. The value range is as follows:
- force_fp16: When the operator supports both float16 and float32, select float16 directly.
- allow_fp32_to_fp16: When the operator does not support the float32 data type, directly reduce
the precision of float16.
- allow_mix_precision: Automatic mixing precision, facing the whole network operator, according
to the built-in optimization strategy, automatically reduces the precision of some operators
to float16 or bfloat16.
- must_keep_origin_dtype: Keep the accuracy of the original drawing.
- force_fp32: When the operator supports both float16 and float32, select float32 directly.
- force_lowerprecision: When the operator supports both float16 or bfloat16 and float32, select
float16 or bfloat16 directly.
- allow_fp32_to_bf16: When the operator does not support the float32 data type, directly reduce
the precision of bfloat16.
- allow_fp32_to_lowprecision: When the operator does not support the float32 data type, directly
reduce the precision of float16 or bfloat16.
- allow_mix_precision_fp16: Automatic mixing precision, facing the whole network operator, automatically
reduces the precision of some operators to float16 according to the built-in optimization strategy.
- allow_mix_precision_bf16: Automatic mixing precision, facing the whole network operator, according to
the built-in optimization strategy, automatically reduces the precision of some operators to bfloat16.
- jit_compile (bool): Whether to select online compilation. Default: True.
Raises:
ValueError: If input key is not an attribute in context.
@ -1014,6 +1073,7 @@ def set_context(**kwargs):
>>> ms.set_context(memory_optimize_level='O0')
>>> ms.set_context(memory_offload='ON')
>>> ms.set_context(deterministic='ON')
>>> ms.set_context(ascend_config={"precision_mode": "force_fp16", "jit_compile": True})
"""
ctx = _context()
# set device target first
@ -1029,6 +1089,8 @@ def set_context(**kwargs):
logger.warning(f"For 'context.set_context', '{key}' parameter is deprecated. "
"For details, please see the interface parameter API comments")
continue
if key in ('precision_mode', 'jit_compile'):
raise ValueError(f"Please set '{key}' through parameter ascend_config")
if key == 'save_graphs':
if value is True:
value = 2

25
tests/ut/python/pynative_mode/test_context.py
View File

@ -99,6 +99,31 @@ def test_max_device_memory_size():
context.set_context(max_device_memory="3.5G")
context.set_context.__wrapped__(max_device_memory="3GB")
def test_ascend_config():
""""
Feature: test_ascend_config function
Description: Test case for simplest ascend_config
Expectation: The results are as expected
"""
context.set_context(device_target="Ascend")
with pytest.raises(ValueError):
context.set_context(precision_mode="force_fp16")
with pytest.raises(ValueError):
context.set_context(jit_compile=True)
with pytest.raises(ValueError):
context.set_context(ascend_config={"precision_mode": "xxx"})
with pytest.raises(ValueError):
context.set_context(ascend_config={"xxxx": 1})
with pytest.raises(ValueError):
context.set_context(ascend_config={"jit_compile": "xxx"})
with pytest.raises(ValueError):
context.set_context(ascend_config={"jit_compile": 2})
with pytest.raises(ValueError):
context.set_context(ascend_config={"precision_mode": 2})
context.set_context.__wrapped__(ascend_config={"precision_mode": "force_fp16", "jit_compile": True})
def test_print_file_path():
"""test_print_file_path"""
with pytest.raises(IOError):