tvm.target¶

Target description and codgen module.

TVM’s target string is in format <target_kind> [-option=value]....

Note

The list of options include:

-device=<device name>

The device name.
-mtriple=<target triple>

Specify the target triple, which is useful for cross compilation.
-mcpu=<cpuname>

Specify a specific chip in the current architecture to generate code for. By default this is infered from the target triple and autodetected to the current architecture.
-mattr=a1,+a2,-a3,…

Override or control specific attributes of the target, such as whether SIMD operations are enabled or not. The default set of attributes is set by the current CPU.
-mabi=<abi>

Generate code for the specified ABI, for example “lp64d”.
-system-lib

Build TVM system library module. System lib is a global module that contains self registered functions in program startup. User can get the module using tvm.runtime.system_lib. It is useful in environments where dynamic loading api like dlopen is banned. The system lib will be available as long as the result code is linked by the program.

We can use tvm.target.Target() to create a tvm.target.Target from the target string. We can also use other specific function in this module to create specific targets.

Classes:

`Target`(target[, host])	Target device information, use through TVM API.
`GenericFunc`	GenericFunc node reference.

Functions:

`create`(target)	Deprecated.
`cuda`([model, options])	Returns a cuda target.
`rocm`([model, options])	Returns a ROCM target.
`mali`([model, options])	Returns a ARM Mali GPU target.
`intel_graphics`([model, options])	Returns an Intel Graphics target.
`arm_cpu`([model, options])	Returns a ARM CPU target.
`rasp`([options])	Return a Raspberry 3b target.
`bifrost`([model, options])	Return an ARM Mali GPU target (Bifrost architecture).
`riscv_cpu`([model, options])	Returns a RISC-V CPU target.
`hexagon`([cpu_ver])	Returns a Hexagon target.
`make_compilation_config`(ctxt, targets[, ...])	Returns a CompilationConfig appropriate for targets and an optional host_target.
`list_tags`()	Returns a dict of tags, which maps each tag name to its corresponding target.
`generic_func`(fdefault)	Wrap a target generic function.
`get_native_generic_func`(name)	Get a generic function from the global registry.
`override_native_generic_func`(func_name)	Override a generic function defined in C++

class tvm.target.Target(target, host=None)¶

Target device information, use through TVM API.

Note

You can create target using the constructor or the following functions

tvm.target.arm_cpu() create arm_cpu target
tvm.target.cuda() create CUDA target
tvm.target.rocm() create ROCM target
tvm.target.mali() create Mali target
tvm.target.intel_graphics() create Intel Graphics target

Methods:

`current`([allow_none])	Returns the current target.
`list_kinds`()	Returns the list of available target names.
`check_and_update_host_consist`(target[, ...])	A helper function that merges a legacy "target, target_host" pair, then returns the merged target and its host field.

Attributes:

`model`	Returns model from the target if it exists.
`mcpu`	Returns the mcpu from the target if it exists.
`mattr`	Returns the mattr from the target if it exists.

static current(allow_none=True)¶

Returns the current target.

Parameters: allow_none (bool) – Whether allow the current target to be none
Raises: ValueError if current target is not set. –

property model¶: Returns model from the target if it exists.

property mcpu¶: Returns the mcpu from the target if it exists.

property mattr¶: Returns the mattr from the target if it exists.

static list_kinds()¶: Returns the list of available target names.

static check_and_update_host_consist(target, host=None, target_is_dict_key=True)¶

A helper function that merges a legacy “target, target_host” pair, then returns the merged target and its host field. The function is for legacy target and target host pair only, and should not be used in the new target system.

Parameters

target (Union[str, Dict[str, Any], Target]) – The target or heterogeneous target
host (Union[str, Dict[str, Any], Target, None]) – The target host
target_is_dict_key (Bool) – When the type of target is dict, whether Target is the key (Otherwise the value)

tvm.target.create(target)¶: Deprecated. Use the constructor of tvm.target.Target directly.

tvm.target.cuda(model='unknown', options=None)¶

Returns a cuda target.

Parameters

model (str) – The model of cuda device (e.g. 1080ti)
options (str or list of str) – Additional options

tvm.target.rocm(model='unknown', options=None)¶

Returns a ROCM target.

Parameters

model (str) – The model of this device
options (str or list of str) – Additional options

tvm.target.mali(model='unknown', options=None)¶

Returns a ARM Mali GPU target.

Parameters

model (str) – The model of this device
options (str or list of str) – Additional options

tvm.target.intel_graphics(model='unknown', options=None)¶

Returns an Intel Graphics target.

Parameters

model (str) – The model of this device
options (str or list of str) – Additional options

tvm.target.arm_cpu(model='unknown', options=None)¶

Returns a ARM CPU target. This function will also download pre-tuned op parameters when there is none.

Parameters

model (str) – SoC name or phone name of the arm board.
options (str or list of str) – Additional options

tvm.target.rasp(options=None)¶

Return a Raspberry 3b target.

Parameters: options (str or list of str) – Additional options

tvm.target.bifrost(model='unknown', options=None)¶

Return an ARM Mali GPU target (Bifrost architecture).

Parameters: options (str or list of str) – Additional options

tvm.target.riscv_cpu(model='sifive-u54', options=None)¶

Returns a RISC-V CPU target. Default: sifive-u54 rv64gc

Parameters

model (str) – CPU name.
options (str or list of str) – Additional options

tvm.target.hexagon(cpu_ver='v66', **kwargs)¶

Returns a Hexagon target.

Parameters

cpu_ver (str (default: "v66")) – CPU version used for code generation. Not all allowed cpu str will be valid, LLVM will throw an error.
parameters (Recognized keyword) –
----------------------------- –
hvx (int (default: 128)) – Size of HVX vector in bytes. Value of 0 disables HVX codegen.
sim_options (str or list of str (default: None)) – User defined sim arguments. CPU version defaults to cpu_ver. Otherwise, separate versions are used for codegen and sim. Not all allowed cpu strings will be valid, simulator will throw an error if invalid. Does not affect codegen.
llvm_options (str or list of str (default: None)) – User defined compiler arguments.
link_params (bool (default: False)) – Whether to link graph parameters into the LLVM module.

tvm.target.make_compilation_config(ctxt, targets, host_target=None)¶: Returns a CompilationConfig appropriate for targets and an optional host_target. Currently intended just for unit tests and will be replaced by a Python CompilationConfig class in the future. Note that targets must be a dictionary from IntImm objects to Targets and we do not support any of the lighter-weight conventions used by the various build(…) APIs.

tvm.target.list_tags() → Optional[Dict[str, tvm.target.target.Target]]¶

Returns a dict of tags, which maps each tag name to its corresponding target.

Returns: tag_dict – The dict of tags mapping each tag name to to its corresponding target. None if TVM is built in runtime-only mode.
Return type: Optional[Dict[str, Target]]

class tvm.target.GenericFunc¶

GenericFunc node reference. This represents a generic function that may be specialized for different targets. When this object is called, a specialization is chosen based on the current target.

Note

Do not construct an instance of this object, it should only ever be used as a return value from calling into C++.

Methods:

`set_default`(func[, allow_override])	Set the default function to be used if no specializations match the current target.
`register`(func, key_list[, allow_override])	Register a specialization for this GenericFunc.

set_default(func, allow_override=False)¶

Set the default function to be used if no specializations match the current target.

Parameters

func (function) – The default function
allow_override (bool) – Whether to allow the current default to be overridden

register(func, key_list, allow_override=False)¶

Register a specialization for this GenericFunc.

Parameters

func (function) – The function to be registered.
key (str or list of str) – The key to be registered.
allow_override (bool, optional) – Whether to allow existing keys to be overridden.

tvm.target.generic_func(fdefault)¶

Wrap a target generic function.

Generic function allows registration of further functions that can be dispatched on current target context. If no registered dispatch is matched, the fdefault will be called.

Parameters: fdefault (function) – The default function.
Returns: fgeneric – A wrapped generic function.
Return type: function

Example

import tvm
# wrap function as target generic
@tvm.target.generic_func
def my_func(a):
    return a + 1
# register specialization of my_func under target cuda
@my_func.register("cuda")
def my_func_cuda(a):
    return a + 2
# displays 3, because my_func is called
print(my_func(2))
# displays 4, because my_func_cuda is called
with tvm.target.cuda():
    print(my_func(2))

tvm.target.get_native_generic_func(name)¶

Get a generic function from the global registry. If no function is registered under the given name, a new generic function is created.

Parameters: name (string) – The name of the generic function to get
Returns: func – The generic function for the given name
Return type: GenericFunc

tvm.target.override_native_generic_func(func_name)¶

Override a generic function defined in C++

Generic function allows registration of further functions that can be dispatched on current target context. If no registered dispatch is matched, the fdefault will be called.

Parameters: func_name (string) – The name of the generic func to be overridden
Returns: fgeneric – A wrapped generic function.
Return type: function

Example

import tvm
# wrap function as target generic
@tvm.target.override_native_generic_func("my_func")
def my_func(a):
    return a + 1
# register specialization of my_func under target cuda
@my_func.register("cuda")
def my_func_cuda(a):
    return a + 2
# displays 3, because my_func is called
print(my_func(2))
# displays 4, because my_func_cuda is called
with tvm.target.cuda():
    print(my_func(2))