feat(disable_tf32): Add a new API to disable TF32

Signed-off-by: Naren Dasan <[email protected]>
Signed-off-by: Naren Dasan <[email protected]>

Author: narendasan

core/conversion/conversionctx/ConversionCtx.cpp

@@ -12,6 +12,7 @@ namespace conversion {
 std::ostream& operator<<(std::ostream& os, const BuilderSettings& s) {
     os << "Settings requested for TensorRT engine:"                                        \
        << "\n    Operating Precision: " << s.op_precision                                  \
+       << "\n    TF32 Floating Point Computation Enabled: " << !s.disable_tf32             \
        << "\n    Make Refittable Engine: " << s.refit                                      \
        << "\n    Debuggable Engine: " << s.debug                                           \
        << "\n    Strict Types: " << s.strict_types                                         \
@@ -77,6 +78,10 @@ ConversionCtx::ConversionCtx(BuilderSettings build_settings)
   }
   op_precision = settings.op_precision;
 
+  if (settings.disable_tf32) {
+    cfg->clearFlag(nvinfer1::BuilderFlag::kTF32);
+  }
+
   if (settings.refit) {
     cfg->setFlag(nvinfer1::BuilderFlag::kREFIT);
   }

core/conversion/conversionctx/ConversionCtx.h

@@ -24,6 +24,7 @@ struct Device {
 
 struct BuilderSettings {
   nvinfer1::DataType op_precision = nvinfer1::DataType::kFLOAT;
+  bool disable_tf32 = false;
   bool refit = false;
   bool debug = false;
   bool strict_types = false;

cpp/api/include/trtorch/trtorch.h

@@ -239,6 +239,15 @@ struct TRTORCH_API CompileSpec {
    */
   DataType op_precision = DataType::kFloat;
 
+  /**
+   * Prevent Float32 layers from using TF32 data format
+   *
+   * TF32 computes inner products by rounding the inputs to 10-bit mantissas
+   * before multiplying, but accumulates the sum using 23-bit mantissas.
+   * This is the behavior of FP32 layers by default.
+   */
+  bool disable_tf32 = false;
+
   /**
    * Build a refitable engine
    */

cpp/api/src/compile_spec.cpp

@@ -89,6 +89,7 @@ core::CompileSpec to_internal_compile_spec(CompileSpec external) {
       internal.convert_info.engine_settings.op_precision = nvinfer1::DataType::kFLOAT;
   }
 
+  internal.convert_info.engine_settings.disable_tf32 = external.disable_tf32;
   internal.convert_info.engine_settings.refit = external.refit;
   internal.convert_info.engine_settings.debug = external.debug;
   internal.convert_info.engine_settings.strict_types = external.strict_types;

cpp/trtorchc/main.cpp

@@ -163,6 +163,12 @@ int main(int argc, char** argv) {
       "(Only used when targeting DLA (device-type)) Lets engine run layers on GPU if they are not supported on DLA",
       {"allow-gpu-fallback"});
 
+  args::Flag disable_tf32(
+      parser,
+      "disable-tf32",
+      "Prevent Float32 layers from using the TF32 data format",
+      {"disable-tf32"});
+
   args::ValueFlag<std::string> op_precision(
       parser,
       "precision",
@@ -263,6 +269,10 @@ int main(int argc, char** argv) {
     compile_settings.device.allow_gpu_fallback = true;
   }
 
+  if (disable_tf32) {
+    compile_settings.disable_tf32 = true;
+  }
+
   std::string calibration_cache_file_path = "";
   if (calibration_cache_file) {
     calibration_cache_file_path = resolve_path(args::get(calibration_cache_file));

py/trtorch/_compile_spec.py

@@ -135,6 +135,10 @@ def _parse_compile_spec(compile_spec: Dict[str, Any]) -> trtorch._C.CompileSpec:
     if "op_precision" in compile_spec:
         info.op_precision = _parse_op_precision(compile_spec["op_precision"])
 
+    if "disable_tf32" in compile_spec:
+        assert isinstance(compile_spec["disable_tf32"], bool)
+        info.disable_tf32 = compile_spec["disable_tf32"]
+
     if "refit" in compile_spec:
         assert isinstance(compile_spec["refit"], bool)
         info.refit = compile_spec["refit"]
@@ -201,6 +205,7 @@ def TensorRTCompileSpec(compile_spec: Dict[str, Any]) -> torch.classes.tensorrt.
                             "allow_gpu_fallback": false, # (DLA only) Allow layers unsupported on DLA to run on GPU
                         },
                         "op_precision": torch.half, # Operating precision set to FP16
+                        "disable_tf32": False, # Force FP32 layers to use traditional as FP32 format vs the default behavior of rounding the inputs to 10-bit mantissas before multiplying, but accumulates the sum using 23-bit mantissas
                         "refit": False, # enable refit
                         "debug": False, # enable debuggable engine
                         "strict_types": False, # kernels should strictly run in operating precision
@@ -239,6 +244,7 @@ def TensorRTCompileSpec(compile_spec: Dict[str, Any]) -> torch.classes.tensorrt.
 
     backend_spec.set_device(d)
     backend_spec.set_op_precision(int(parsed_spec.op_precision))
+    backend_spec.set_disable_tf32(parsed_spec.disable_tf32)
     backend_spec.set_refit(parsed_spec.refit)
     backend_spec.set_debug(parsed_spec.debug)
     backend_spec.set_refit(parsed_spec.refit)

py/trtorch/_compiler.py

@@ -99,6 +99,7 @@ def convert_method_to_trt_engine(module: torch.jit.ScriptModule, method_name: st
                         "allow_gpu_fallback": false, # (DLA only) Allow layers unsupported on DLA to run on GPU
                     },
                     "op_precision": torch.half, # Operating precision set to FP16
+                    "disable_tf32": False, # Force FP32 layers to use traditional as FP32 format vs the default behavior of rounding the inputs to 10-bit mantissas before multiplying, but accumulates the sum using 23-bit mantissas
                     "refit": false, # enable refit
                     "debug": false, # enable debuggable engine
                     "strict_types": false, # kernels should strictly run in operating precision

py/trtorch/csrc/register_tensorrt_classes.cpp

@@ -32,6 +32,7 @@ void RegisterTRTCompileSpec() {
           .def("__str__", &trtorch::pyapi::CompileSpec::stringify);
 
   ADD_FIELD_GET_SET_REGISTRATION(TRTCompileSpecTSRegistration, trtorch::pyapi::CompileSpec, op_precision);
+  ADD_FIELD_GET_SET_REGISTRATION(TRTCompileSpecTSRegistration, trtorch::pyapi::CompileSpec, disable_tf32);
   ADD_FIELD_GET_SET_REGISTRATION(TRTCompileSpecTSRegistration, trtorch::pyapi::CompileSpec, refit);
   ADD_FIELD_GET_SET_REGISTRATION(TRTCompileSpecTSRegistration, trtorch::pyapi::CompileSpec, debug);
   ADD_FIELD_GET_SET_REGISTRATION(TRTCompileSpecTSRegistration, trtorch::pyapi::CompileSpec, strict_types);

py/trtorch/csrc/tensorrt_classes.cpp

@@ -99,6 +99,7 @@ core::CompileSpec CompileSpec::toInternalCompileSpec() {
   }
   auto info = core::CompileSpec(internal_input_ranges);
   info.convert_info.engine_settings.op_precision = toTRTDataType(op_precision);
+  info.convert_info.engine_settings.disable_tf32 = disable_tf32;
   info.convert_info.engine_settings.refit = refit;
   info.convert_info.engine_settings.debug = debug;
   info.convert_info.engine_settings.strict_types = strict_types;
@@ -128,6 +129,7 @@ std::string CompileSpec::stringify() {
   }
   ss << "     ]" << std::endl;
   ss << "     \"Op Precision\": " << to_str(op_precision) << std::endl;
+  ss << "     \"TF32 Disabled\": " << disable_tf32 << std::endl;
   ss << "     \"Refit\": " << refit << std::endl;
   ss << "     \"Debug\": " << debug << std::endl;
   ss << "     \"Strict Types\": " << strict_types << std::endl;

py/trtorch/csrc/tensorrt_classes.h

@@ -99,6 +99,7 @@ struct CompileSpec : torch::CustomClassHolder {
   }
 
   ADD_ENUM_GET_SET(op_precision, DataType, static_cast<int64_t>(DataType::kChar));
+  ADD_FIELD_GET_SET(disable_tf32, bool);
   ADD_FIELD_GET_SET(refit, bool);
   ADD_FIELD_GET_SET(debug, bool);
   ADD_FIELD_GET_SET(strict_types, bool);
@@ -111,6 +112,7 @@ struct CompileSpec : torch::CustomClassHolder {
 
   std::vector<InputRange> input_ranges;
   DataType op_precision = DataType::kFloat;
+  bool disable_tf32 = false;
   bool refit = false;
   bool debug = false;
   bool strict_types = false;