[Hybrid script] Backend support (apache#2477)

* a preliminary version is done?

* we no longer need the redundant hybrid/api.py

* support assert stmt

* cast supported

* intrin -> runtime; util is mainly in charge of compilation time

* assert statement

* fix python lint

* fix cpp lint

* on the way to module

* rollback .cc

* fix typo, no direct expose then

* @vinx13 ceil is added i guess?

* wip...

* temp commit

* fix import

* i preliminary version is done?

* on the way to build hybrid module

* nearly fixed...

* dumped python are equiv as original python

* on the way to bootstrap

* cpu bootstrap done

* bootstrap!

* fix lint

* fix doc

* resolve some review concerns

* support load/save

* fix lint

* thanks to xqdan fixed my typo

* fix build, make dump non-optional

* add vthread

* jesus why i added this

CMakeLists.txt

@@ -229,6 +229,7 @@ include(cmake/modules/contrib/Random.cmake)
 include(cmake/modules/contrib/Sort.cmake)
 include(cmake/modules/contrib/NNPack.cmake)
 include(cmake/modules/contrib/TensorRT.cmake)
+include(cmake/modules/contrib/HybridDump.cmake)
 
 add_library(tvm SHARED ${COMPILER_SRCS} ${RUNTIME_SRCS})
 add_library(tvm_topi SHARED ${TOPI_SRCS})

cmake/modules/contrib/HybridDump.cmake

@@ -0,0 +1,3 @@
+message(STATUS "Build with contrib.hybriddump")
+file(GLOB HYBRID_CONTRIB_SRC src/contrib/hybrid/*.cc)
+list(APPEND COMPILER_SRCS ${HYBRID_CONTRIB_SRC})

docs/langref/hybrid_script.rst

@@ -197,6 +197,20 @@ You can also do loop-thread bind by writing code like this:
        a[tx] = b[tx]
 
 
+Assert Statement
+~~~~~~~~~~~~~~~~
+
+Assert statement is supported, you can simply use it as it is in standard Python.
+
+.. code-block:: python
+
+    assert cond, mesg
+
+.. note::
+
+        ``Assert`` is NOT a function call. Users are encouraged to use assert in the way
+        presented above --- condition followed by message. It fits both Python AST and HalideIR.
+
 Keywords
 ~~~~~~~~
 - For keywords: ``serial``, ``range``, ``unroll``, ``parallel``, ``vectorize``, ``bind``, ``const_expr``

python/tvm/build_module.py

@@ -292,6 +292,25 @@ def get_binds(args, binds=None):
     return binds, arg_list
 
 
+def form_body(sch):
+    """According to the given schedule, form the raw body
+    Parameters
+    ----------
+    sch : tvm.schedule.Schedule
+    The given scheduler to form the raw body
+
+    Returns
+    -------
+    The body formed according to the given schedule
+    """
+    # normalize schedule first
+    sch = sch.normalize()
+    bounds = schedule.InferBound(sch)
+    stmt = schedule.ScheduleOps(sch, bounds)
+    stmt = ir_pass.InjectPrefetch(stmt)
+    return stmt
+
+
 def lower(sch,
           args,
           name="default_function",
@@ -337,11 +356,7 @@ def lower(sch,
 
     # Phase 0
     if isinstance(sch, schedule.Schedule):
-        # normalize schedule first
-        sch = sch.normalize()
-        bounds = schedule.InferBound(sch)
-        stmt = schedule.ScheduleOps(sch, bounds)
-        stmt = ir_pass.InjectPrefetch(stmt)
+        stmt = form_body(sch)
 
     for f in lower_phase0:
         stmt = f(stmt)

python/tvm/hybrid/__init__.py

@@ -4,8 +4,77 @@
 1. Users can write some preliminary versions of the computation patterns
 have not been supported yet and verify it across the real execution and
 python semantic emulation.
-2. Developers can build HalideIR by writing Python code.
+2. So far, it is a text format dedicated to HalideIR Phase 0. Refer tvm.lower
+for more details. A larger ambition of this module is to support all levels of
+HalideIR.
 """
 
-from .api import script
-from .parser import parse_python
+# TODO(@were): Make this module more complete.
+# 1. Support HalideIR dumping to Hybrid Script
+# 2. Support multi-level HalideIR
+
+from __future__ import absolute_import as _abs
+
+from .._ffi.base import decorate
+from .._ffi.function import _init_api
+from ..build_module import form_body
+
+from .module import HybridModule
+from .parser import source_to_op
+from .util import _pruned_source
+
+
+def script(pyfunc):
+    """Decorate a python function function as hybrid script.
+
+    The hybrid function support emulation mode and parsing to
+    the internal language IR.
+
+    Returns
+    -------
+    hybrid_func : function
+        A decorated hybrid script function.
+    """
+    def wrapped_func(func, *args, **kwargs): #pylint: disable=missing-docstring
+        from .util import _is_tvm_arg_types
+        if _is_tvm_arg_types(args):
+            src = _pruned_source(func)
+            return source_to_op(src, func.__globals__, args)
+
+        from .runtime import _enter_hybrid_runtime, _restore_runtime
+        intersect = _enter_hybrid_runtime(func)
+        value = func(*args, **kwargs)
+        _restore_runtime(func, intersect)
+        return value
+
+    return decorate(pyfunc, wrapped_func)
+
+
+def build(sch, inputs, outputs, name="hybrid_func"):
+    """Dump the corrent schedule to hybrid module
+
+    Parameters
+    ----------
+    sch: Schedule
+        The schedule to be dumped
+
+    inputs: An array of Tensors or Vars
+        The inputs of the function body
+
+    outputs: An array of Tensors
+        The outputs of the function body
+
+    Returns
+    -------
+    module: HybridModule
+        The built results is wrapped in a HybridModule.
+        The usage of HybridModule is roughly the same as normal TVM-built modules.
+    """
+
+    stmt = form_body(sch)
+    src = _Dump(stmt, inputs, outputs, name)
+
+    return HybridModule(src, name)
+
+
+_init_api("tvm.hybrid")

python/tvm/hybrid/calls.py

@@ -8,6 +8,7 @@
 from .. import ir_pass
 from ..stmt import For
 from .util import _internal_assert
+from ..intrin import call_pure_intrin
 
 #pylint: disable=redefined-builtin
 
@@ -104,3 +105,29 @@ def len(func_id, args):
     except: #pylint: disable=bare-except
         _internal_assert(args[0].shape.__len__() == 1, "Only one-dimension array can get len")
         return _api.convert(args[0].shape[0])
+
+
+def _cast(func_id, args):
+    _internal_assert(args.__len__() == 1 and isinstance(args[0], _expr.Expr), \
+                     "Only one expression can be cast")
+    return _make.Cast(func_id, args[0])
+
+float16 = float32 = float64 = _cast #pylint: disable=invalid-name
+int8 = int16 = int32 = int64 = _cast #pylint: disable=invalid-name
+uint8 = uint16 = uint32 = uint64 = _cast #pylint: disable=invalid-name
+
+
+def ceil_div(func_id, args):
+    _internal_assert(func_id == "ceil_div", "This function cannot be directly invoked!")
+    _internal_assert(args.__len__() == 2, "2 arguments expected for division!")
+    _internal_assert(isinstance(args[0], _expr.Expr), "Only expressions can div")
+    _internal_assert(isinstance(args[1], _expr.Expr), "Only expressions can div")
+    a, b = args[0], args[1]
+    return (a + b - 1) / b
+
+
+def likely(func_id, args):
+    _internal_assert(args.__len__() == 1, \
+                     "Only one expression can be likely")
+    _internal_assert(func_id == "likely", "This function cannot be directly invoked!")
+    return call_pure_intrin(args[0].dtype, 'likely', *args)

python/tvm/hybrid/module.py

@@ -0,0 +1,100 @@
+"""Methods and data structures to support dumping HalideIR to Hybrid Script.
+This allows users to do quick hack to generated HalideIR and cast it back to
+TVM modules.
+
+To enable this feature, you need to build with -DUSE_HYBRID_DUMP=ON.
+"""
+
+import ast
+import imp
+
+from ..contrib import util
+from .util import _internal_assert
+from .util import _is_tvm_arg_types
+from .parser import source_to_op
+
+
+class HybridModule(object):
+    """The usage of Hybrid Module is very similar to conventional TVM module,
+    but conventional TVM module requires a function body which is already fully
+    lowered. This contradicts to the fact that Hybrid Module is originally a text
+    format for Phase 0 HalideIR. Thus, a totally separated module is defined."""
+
+
+    def __init__(self, src=None, name=None):
+        """The constructor of this a hybrid module
+
+        Parameters
+        ----------
+        src : str
+            The source code of this module
+
+        name : str
+            The name of this module
+        """
+        self.src_ = self.name = self.func_ = self.root_ = None
+        if src is not None:
+            temp = util.tempdir()
+            dst = temp.relpath("script.py")
+            with open(dst, 'w') as f:
+                f.write("import tvm\n@tvm.hybrid.script\n%s" % src)
+
+            if name is not None:
+                self.name = name
+            self.load(dst)
+
+
+    def __call__(self, *args):
+        if _is_tvm_arg_types(args):
+            return source_to_op(self.root_, globals(), args)
+        return self.func_(*args)
+
+
+    def get_source(self):
+        return self.src_
+
+
+    def save(self, path):
+        if not path.endswith('.py'):
+            path = path + '.py'
+        with open(path, 'w') as f:
+            f.write(self.src_)
+
+
+    def load(self, path):
+        """Load the module from a python file
+
+        Parameters
+        ----------
+        path : str
+            Path to the given python file
+        """
+        with open(path, 'r') as f:
+            self.src_ = f.read()
+
+        src = self.src_
+
+        class FindFunc(ast.NodeVisitor):
+            """ Find the function in module to be loaded module. """
+            #pylint: disable=invalid-name
+            def __init__(self):
+                self.name = None
+                self.root = None
+
+
+            def visit_FunctionDef(self, node):
+                _internal_assert(self.name is None, "For now, only one function supported!")
+                self.name = node.name
+                _internal_assert(self.root is None, "For now, only one function supported!")
+                self.root = node
+
+        root = ast.parse(src)
+        finder = FindFunc()
+        finder.visit(root)
+        _internal_assert(finder.name is not None and finder.root is not None, \
+                         "No function found!")
+        if self.name is None:
+            self.name = finder.name
+        self.root_ = finder.root
+        py_module = imp.load_source(self.name, path)
+        self.func_ = getattr(py_module, self.name)