[TOPI] Bitserial low-precision convolution

python/tvm/intrin.py

@@ -154,6 +154,31 @@ def call_extern(dtype, func_name, *args):
         dtype, func_name, convert(args), _Call.Extern, None, 0)
 
 
+def call_llvm_intrin(dtype, name, *args):
+    """Build expression by calling an llvm intrinsic function
+
+    Parameters
+    ----------
+    dtype : str
+       The data type of the result.
+
+    name : str
+       The name of the llvm intrinsic function.
+
+    args : list
+       Poistional arguments.
+
+    Returns
+    -------
+    call : Expr
+        The call expression.
+    """
+    import tvm
+    llvm_id = tvm.codegen.llvm_lookup_intrinsic_id(name)
+    assert llvm_id != 0, "%s is not an LLVM intrinsic" % name
+    return call_pure_intrin(dtype, 'llvm_intrin', tvm.const(llvm_id, 'uint32'), *args)
+
+
 def exp(x):
     """Take exponetial of input x.
 

src/codegen/llvm/llvm_module.cc

@@ -282,6 +282,15 @@ class LLVMModuleNode final : public runtime::ModuleNode {
   std::shared_ptr<llvm::LLVMContext> ctx_;
 };
 
+unsigned LookupLLVMIntrinsic(const std::string& name) {
+  return llvm::Function::lookupIntrinsicID(name);
+}
+
+TVM_REGISTER_API("codegen.llvm_lookup_intrinsic_id")
+.set_body([](TVMArgs args, TVMRetValue* rv) {
+    *rv = static_cast<int64_t>(LookupLLVMIntrinsic(args[0]));
+  });
+
 TVM_REGISTER_API("codegen.build_llvm")
 .set_body([](TVMArgs args, TVMRetValue* rv) {
     std::shared_ptr<LLVMModuleNode> n = std::make_shared<LLVMModuleNode>();

tests/python/unittest/test_codegen_llvm.py

@@ -17,6 +17,16 @@ def test_llvm_intrin():
     func = tvm.ir_pass.MakeAPI(body, "prefetch", [A], 0, True)
     fcode = tvm.build(func, None, "llvm")
 
+def test_llvm_lookup_intrin():
+    ib = tvm.ir_builder.create()
+    m = tvm.var("m")
+    A = ib.pointer("uint8x8", name="A")
+    x = tvm.call_llvm_intrin("uint8x8", "llvm.ctpop.i8", tvm.const(1, 'uint32'), A)
+    ib.emit(x)
+    body = ib.get()
+    func = tvm.ir_pass.MakeAPI(body, "ctpop", [A], 1, True)
+    fcode = tvm.build(func, None, "llvm")
+
 def test_llvm_add_pipeline():
     nn = 1024
     n = tvm.convert(nn)
@@ -324,3 +334,4 @@ def test_alignment():
     test_llvm_flip_pipeline()
     test_llvm_madd_pipeline()
     test_llvm_temp_space()
+    test_llvm_lookup_intrin()

topi/python/topi/generic/nn.py

@@ -143,6 +143,41 @@ def schedule_depthwise_conv2d_nhwc(outs):
     """
     return _default_schedule(outs, False)
 
+@tvm.target.generic_func
+def schedule_bitserial_conv2d_nchw(outs):
+    """Schedule for bitserial_conv2d_nchw
+
+    Parameters
+    ----------
+    outs: Array of Tensor
+          The computation graph description of bitserial_conv2d_nchw
+          in the format of an array of tensors.
+
+    Returns
+    -------
+    sch: Schedule
+        The computation schedule for the op.
+    """
+    return _default_schedule(outs, False)
+
+
+@tvm.target.generic_func
+def schedule_bitserial_conv2d_nhwc(outs):
+    """Schedule for bitserial_conv2d_nhwc
+
+    Parameters
+    ----------
+    outs: Array of Tensor
+          The computation graph description of bitserial_conv2d_nchw
+          in the format of an array of tensors.
+
+    Returns
+    -------
+    sch: Schedule
+        The computation schedule for the op.
+    """
+    return _default_schedule(outs, False)
+
 
 @tvm.target.override_native_generic_func("schedule_reduce")
 def schedule_reduce(outs):

topi/python/topi/nn/__init__.py

@@ -16,4 +16,5 @@
 from .bnn import *
 from .upsampling import *
 from .local_response_norm import *
+from .bitserial_conv2d import *
 from .l2_normalize import *