271 строка
8.5 KiB
Python
271 строка
8.5 KiB
Python
"""Container of compiled functions of TVM."""
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from __future__ import absolute_import as _abs
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import struct
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from collections import namedtuple
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from ._ffi.function import ModuleBase, _set_class_module
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from ._ffi.function import _init_api
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from ._ffi.libinfo import find_include_path
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from .contrib import cc as _cc, tar as _tar, util as _util
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ProfileResult = namedtuple("ProfileResult", ["mean", "results"])
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class Module(ModuleBase):
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"""Module container of all TVM generated functions"""
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def __repr__(self):
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return "Module(%s, %x)" % (self.type_key, self.handle.value)
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@property
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def type_key(self):
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"""Get type key of the module."""
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return _GetTypeKey(self)
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def get_source(self, fmt=""):
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"""Get source code from module, if available.
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Parameters
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----------
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fmt : str, optional
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The specified format.
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Returns
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-------
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source : str
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The result source code.
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"""
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return _GetSource(self, fmt)
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@property
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def imported_modules(self):
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"""Get imported modules
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Returns
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----------
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modules : list of Module
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The module
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"""
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nmod = _ImportsSize(self)
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return [_GetImport(self, i) for i in range(nmod)]
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def save(self, file_name, fmt=""):
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"""Save the module to file.
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This do not save the dependent device modules.
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See also export_shared
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Parameters
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----------
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file_name : str
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The name of the file.
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fmt : str
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The format of the file.
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See Also
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--------
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Module.export_library : export the module to shared library.
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"""
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_SaveToFile(self, file_name, fmt)
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def export_library(self,
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file_name,
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fcompile=None,
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**kwargs):
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"""Export the module and its imported device code one library.
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This function only works on host llvm modules.
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It will pack all the imported modules
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Parameters
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----------
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file_name : str
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The name of the shared library.
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fcompile : function(target, file_list, kwargs), optional
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Compilation function to use create dynamic library.
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If fcompile has attribute object_format, will compile host library
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to that format. Otherwise, will use default format "o".
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kwargs : dict, optional
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Additional arguments passed to fcompile
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"""
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if self.type_key == "stackvm":
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if not file_name.endswith(".stackvm"):
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raise ValueError("Module[%s]: can only be saved as stackvm format."
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"did you build with LLVM enabled?" % self.type_key)
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self.save(file_name)
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return
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if not (self.type_key == "llvm" or self.type_key == "c"):
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raise ValueError("Module[%s]: Only llvm and c support export shared" % self.type_key)
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temp = _util.tempdir()
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if fcompile is not None and hasattr(fcompile, "object_format"):
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object_format = fcompile.object_format
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else:
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if self.type_key == "llvm":
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object_format = "o"
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else:
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assert self.type_key == "c"
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object_format = "cc"
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path_obj = temp.relpath("lib." + object_format)
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self.save(path_obj)
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files = [path_obj]
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is_system_lib = self.type_key == "llvm" and self.get_function("__tvm_is_system_module")()
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if self.imported_modules:
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path_cc = temp.relpath("devc.cc")
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with open(path_cc, "w") as f:
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f.write(_PackImportsToC(self, is_system_lib))
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files.append(path_cc)
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if not fcompile:
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if file_name.endswith(".tar"):
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fcompile = _tar.tar
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else:
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fcompile = _cc.create_shared
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if self.type_key == "c":
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kwargs.update({'options': ["-I" + path for path in find_include_path()]})
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fcompile(file_name, files, **kwargs)
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def time_evaluator(self, func_name, ctx, number=10, repeat=1, min_repeat_ms=0):
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"""Get an evaluator that measures time cost of running function.
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Parameters
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----------
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func_name: str
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The name of the function in the module.
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ctx: TVMContext
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The context we should run this function on.
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number: int
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The number of times to run this function for taking average.
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We call these runs as one `repeat` of measurement.
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repeat: int, optional
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The number of times to repeat the measurement.
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In total, the function will be invoked (1 + number x repeat) times,
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where the first one is warm up and will be discarded.
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The returned result contains `repeat` costs,
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each of which is an average of `number` costs.
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min_repeat_ms: int, optional
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The minimum duration of one `repeat` in milliseconds.
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By default, one `repeat` contains `number` runs. If this parameter is set,
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the parameters `number` will be dynamically adjusted to meet the
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minimum duration requirement of one `repeat`.
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i.e., When the run time of one `repeat` falls below this time, the `number` parameter
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will be automatically increased.
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Note
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----
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The function will be invoked (1 + number x repeat) times,
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with the first call discarded in case there is lazy initialization.
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Returns
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-------
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ftimer : Function
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The function that takes same argument as func and returns a ProfileResult.
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The ProfileResult reports `repeat` time costs in seconds.
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"""
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try:
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feval = _RPCTimeEvaluator(
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self, func_name, ctx.device_type, ctx.device_id, number, repeat, min_repeat_ms)
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def evaluator(*args):
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"""Internal wrapped evaluator."""
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# Wrap feval so we can add more stats in future.
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blob = feval(*args)
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fmt = "@" + ("d" * repeat)
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results = struct.unpack(fmt, blob)
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mean = sum(results) / float(repeat)
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return ProfileResult(mean=mean, results=results)
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return evaluator
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except NameError:
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raise NameError("time_evaluate is only supported when RPC is enabled")
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def system_lib():
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"""Get system-wide library module singleton.
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System lib is a global module that contains self register functions in startup.
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Unlike normal dso modules which need to be loaded explicitly.
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It is useful in environments where dynamic loading api like dlopen is banned.
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To build system lib function, simply specify target option ```llvm --system-lib```
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The system lib will be available as long as the result code is linked by the program.
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The system lib is intended to be linked and loaded during the entire life-cyle of the program.
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If you want dynamic loading features, use dso modules instead.
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Returns
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-------
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module : Module
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The system-wide library module.
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"""
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return _GetSystemLib()
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def load(path, fmt=""):
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"""Load module from file.
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Parameters
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----------
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path : str
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The path to the module file.
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fmt : str, optional
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The format of the file, if not specified
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it will be inferred from suffix of the file.
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Returns
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-------
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module : Module
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The loaded module
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Note
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----
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This function will automatically call
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cc.create_shared if the path is in format .o or .tar
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"""
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# High level handling for .o and .tar file.
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# We support this to be consistent with RPC module load.
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if path.endswith(".o"):
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_cc.create_shared(path + ".so", path)
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path += ".so"
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elif path.endswith(".tar"):
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tar_temp = _util.tempdir()
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_tar.untar(path, tar_temp.temp_dir)
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files = [tar_temp.relpath(x) for x in tar_temp.listdir()]
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_cc.create_shared(path + ".so", files)
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path += ".so"
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# Redirect to the load API
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return _LoadFromFile(path, fmt)
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def enabled(target):
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"""Whether module runtime is enabled for target
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Parameters
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----------
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target : str
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The target device type.
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Returns
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-------
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enabled : bool
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Whether runtime is enabled.
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Examples
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--------
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The following code checks if gpu is enabled.
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>>> tvm.module.enabled("gpu")
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"""
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return _Enabled(target)
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_init_api("tvm.module")
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_set_class_module(Module)
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