[Hybrid Script] Add max_num_threads (apache#2672)

* i think it works for now?

* fix lint

* fix 2/3 compat

* fix py2 again

* fine, i gave up

python/tvm/hybrid/calls.py

@@ -4,6 +4,7 @@
 from .. import api as _api
 from .. import expr as _expr
 from .. import make as _make
+from .. import target as _tgt
 from ..container import Array
 from .. import ir_pass
 from ..stmt import For
@@ -123,11 +124,22 @@ def ceil_div(func_id, args):
     _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
+    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)
+
+
+def max_num_threads(func_id, args):
+    _internal_assert(func_id == "max_num_threads", "This function cannot be directly invoked!")
+    _internal_assert(args.__len__() <= 1, "At most one argument accepted!")
+    if args.__len__() == 0:
+        res = _tgt.current_target().max_num_threads
+    else:
+        _internal_assert(isinstance(args[0], _expr.UIntImm), "In tvm bool should be uint")
+        res = _tgt.current_target(args[0].value).max_num_threads
+    return _api.convert(res)

python/tvm/hybrid/parser.py

@@ -219,6 +219,8 @@ def visit_Expr(self, node):
 
     def visit_Name(self, node):
         name = node.id
+        if sys.version_info[0] == 2 and name in ['True', 'False']:
+            return _api.convert(eval(name)) #pylint: disable=eval-used
         ty, entry = self.symbols[name]
         _internal_assert(name in self.symbols, "Unknown symbol %s!" % name)
         if ty in [Symbol.LoopVar, Symbol.Input, Symbol.ConstLoopVar]:
@@ -248,6 +250,10 @@ def visit_Num(self, node):
         return _api.const(node.n, dtype)
 
 
+    def visit_NameConstant(self, node):
+        return _api.convert(node.value)
+
+
     def visit_AugAssign(self, node):
         buf = self.visit(node.target)
         rhs = self.visit(node.value)
@@ -450,17 +456,18 @@ def visit_Call(self, node):
 
         func_id = node.func.id
         args = [self.visit(i) for i in node.args]
-        try:
+        # Intrinsics'
+        if hasattr(calls, func_id):
             return getattr(calls, func_id)(func_id, args)
-        except AttributeError:
-            _internal_assert(func_id in self.symbols.keys(), \
-                             "The function called is not in the context either!")
-            ty, entry = self.symbols[func_id]
-            _internal_assert(ty is Symbol.Callable, \
-                             "Are you sure what you call is a function?!")
-            outs = entry(*args)
-            op = outs.op if isinstance(outs, Tensor) else outs[0].op
-            return op
+        # Contexts'
+        _internal_assert(func_id in self.symbols.keys(), \
+                         "The function called (%s) is not in the context either!" % func_id)
+        ty, entry = self.symbols[func_id]
+        _internal_assert(ty is Symbol.Callable, \
+                         "Are you sure what you call is a function?!")
+        outs = entry(*args)
+        op = outs.op if isinstance(outs, Tensor) else outs[0].op
+        return op
 
 
     def visit_For(self, node):

python/tvm/hybrid/preprocessor.py

@@ -59,6 +59,9 @@ def visit_AugAssign(self, node):
 
 
     def visit_Name(self, node):
+        # If it is True or False, we do not worry about it!
+        if sys.version_info[0] == 2 and node.id in ['True', 'False']:
+            return
         # If it is from the argument list or loop variable, we do not worry about it!
         if node.id in self._args.keys():
             return

python/tvm/hybrid/runtime.py

@@ -1,6 +1,7 @@
 """Intrinsics of TVM-Python Hybrid Script for Python emulation runtime"""
 
 import numpy
+from .. import target
 
 
 class bind(object): #pylint: disable=invalid-name
@@ -72,34 +73,40 @@ def sigmoid(x):
     return 1 / (1 + numpy.exp(-x))
 
 
+def max_num_threads(allow_none=True):
+    """Get max number of threads for GPU targets."""
+    return target.current_target(allow_none).max_num_threads
+
+
 HYBRID_GLOBALS = {
-    'unroll'       : range,
-    'vectorize'    : range,
-    'parallel'     : range,
-    'const_range'  : range,
-    'bind'         : bind,
-    'allocate'     : allocate,
-    'output_tensor': allocate,
-    'sqrt'         : numpy.sqrt,
-    'log'          : numpy.log,
-    'tanh'         : numpy.tanh,
-    'power'        : numpy.power,
-    'exp'          : numpy.exp,
-    'sigmoid'      : sigmoid,
-    'popcount'     : popcount,
-    'likely'       : lambda cond: cond,
-    'uint8'        : numpy.uint8,
-    'uint16'       : numpy.uint16,
-    'uint32'       : numpy.uint32,
-    'uint64'       : numpy.uint64,
-    'int8'         : numpy.int8,
-    'int16'        : numpy.int16,
-    'int32'        : numpy.int32,
-    'int64'        : numpy.int64,
-    'float16'      : numpy.float16,
-    'float32'      : numpy.float32,
-    'float64'      : numpy.float64,
-    'ceil_div'     : lambda a, b: (a + b - 1) / b
+    'unroll'         : range,
+    'vectorize'      : range,
+    'parallel'       : range,
+    'const_range'    : range,
+    'bind'           : bind,
+    'allocate'       : allocate,
+    'output_tensor'  : allocate,
+    'sqrt'           : numpy.sqrt,
+    'log'            : numpy.log,
+    'tanh'           : numpy.tanh,
+    'power'          : numpy.power,
+    'exp'            : numpy.exp,
+    'sigmoid'        : sigmoid,
+    'popcount'       : popcount,
+    'likely'         : lambda cond: cond,
+    'uint8'          : numpy.uint8,
+    'uint16'         : numpy.uint16,
+    'uint32'         : numpy.uint32,
+    'uint64'         : numpy.uint64,
+    'int8'           : numpy.int8,
+    'int16'          : numpy.int16,
+    'int32'          : numpy.int32,
+    'int64'          : numpy.int64,
+    'float16'        : numpy.float16,
+    'float32'        : numpy.float32,
+    'float64'        : numpy.float64,
+    'ceil_div'       : lambda a, b: (a + b - 1) // b,
+    'max_num_threads': max_num_threads
 }
 
 

src/contrib/hybrid/codegen_hybrid.cc

@@ -400,6 +400,8 @@ void CodeGenHybrid::ReserveKeywords() {
   GetUniqueName("for");
   GetUniqueName("in");
   GetUniqueName("range");
+  GetUniqueName("True");
+  GetUniqueName("False");
   GetUniqueName("unroll");
   GetUniqueName("const_range");
   GetUniqueName("parallel");
@@ -434,6 +436,7 @@ void CodeGenHybrid::ReserveKeywords() {
   GetUniqueName("float32");
   GetUniqueName("float64");
   GetUniqueName("ceil_div");
+  GetUniqueName("max_num_threads");
 }
 
 void CodeGenHybrid::DumpStmt(const Stmt &stmt,

tests/python/unittest/test_hybrid_script.py

@@ -350,6 +350,22 @@ def foo(a):
     func, ins, outs = run_and_check(foo, [a], target='cuda')
     run_and_check(func, ins, outs=outs, target='cuda')
 
+    @tvm.hybrid.script
+    def max_threads(a):
+        b = output_tensor(a.shape, a.dtype)
+        n = a.shape[0]
+        m = max_num_threads(True)
+        for i in bind('threadIdx.x', m):
+            for j in bind('blockIdx.x', ceil_div(n, m)):
+                if i * m + j < n:
+                    b[i * m + j] = a[i * m + j] + a[i * m + j]
+        return b
+
+    a = tvm.placeholder((10000, ), 'float32')
+    with tvm.target.create('cuda'):
+        func, ins, outs = run_and_check(max_threads, [a], target='cuda')
+        run_and_check(func, ins, outs=outs, target='cuda')
+
 
 def test_math_intrin():
     @script