[cherry-pick] Inference add type check in copy_from_cpu (#36552)

paddle/fluid/inference/api/analysis_predictor.cc

@@ -36,6 +36,7 @@
 #include "paddle/fluid/inference/analysis/helper.h"
 #include "paddle/fluid/inference/analysis/passes/memory_optimize_pass.h"
 #include "paddle/fluid/inference/api/helper.h"
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
 #include "paddle/fluid/inference/api/paddle_inference_pass.h"
 #include "paddle/fluid/inference/utils/io_utils.h"
 #include "paddle/fluid/inference/utils/singleton.h"
@@ -56,6 +57,7 @@
 
 #if PADDLE_WITH_TENSORRT
 #include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
+#include "paddle/fluid/inference/tensorrt/helper.h"
 #include "paddle/fluid/inference/tensorrt/trt_int8_calibrator.h"
 #endif
 
@@ -1469,6 +1471,22 @@ int GetNumBytesOfDataType(DataType dtype) {
 
 std::string GetVersion() { return paddle::get_version(); }
 
+std::tuple<int, int, int> GetTrtCompileVersion() {
+#ifdef PADDLE_WITH_TENSORRT
+  return paddle::inference::tensorrt::GetTrtCompileVersion();
+#else
+  return std::tuple<int, int, int>{0, 0, 0};
+#endif
+}
+
+std::tuple<int, int, int> GetTrtRuntimeVersion() {
+#ifdef PADDLE_WITH_TENSORRT
+  return paddle::inference::tensorrt::GetTrtRuntimeVersion();
+#else
+  return std::tuple<int, int, int>{0, 0, 0};
+#endif
+}
+
 std::string UpdateDllFlag(const char *name, const char *value) {
   return paddle::UpdateDllFlag(name, value);
 }

paddle/fluid/inference/api/analysis_predictor_tester.cc

@@ -359,6 +359,15 @@ TEST(AnalysisPredictor, set_xpu_device_id) {
 namespace paddle_infer {
 
 TEST(Predictor, Run) {
+  auto trt_compile_ver = GetTrtCompileVersion();
+  auto trt_runtime_ver = GetTrtRuntimeVersion();
+  LOG(INFO) << "trt compile version: " << std::get<0>(trt_compile_ver) << "."
+            << std::get<1>(trt_compile_ver) << "."
+            << std::get<2>(trt_compile_ver);
+  LOG(INFO) << "trt runtime version: " << std::get<0>(trt_runtime_ver) << "."
+            << std::get<1>(trt_runtime_ver) << "."
+            << std::get<2>(trt_runtime_ver);
+
   Config config;
   config.SetModel(FLAGS_dirname);
 

paddle/fluid/inference/api/paddle_inference_api.h

@@ -169,6 +169,8 @@ PD_INFER_DECL std::shared_ptr<Predictor> CreatePredictor(
 PD_INFER_DECL int GetNumBytesOfDataType(DataType dtype);
 
 PD_INFER_DECL std::string GetVersion();
+PD_INFER_DECL std::tuple<int, int, int> GetTrtCompileVersion();
+PD_INFER_DECL std::tuple<int, int, int> GetTrtRuntimeVersion();
 PD_INFER_DECL std::string UpdateDllFlag(const char* name, const char* value);
 
 namespace services {

paddle/fluid/inference/tensorrt/engine.cc

@@ -196,6 +196,19 @@ void TensorRTEngine::FreezeNetwork() {
 #if IS_TRT_VERSION_GE(6000)
     LOG(INFO) << "Run Paddle-TRT Dynamic Shape mode.";
     for (auto &input : min_input_shape_) {
+#if IS_TRT_VERSION_LT(7000)
+      // trt6 will check all_of input > 0
+      if (!(std::all_of(input.second.begin(), input.second.end(),
+                        [](int x) { return x > 0; }) &&
+            std::all_of(max_input_shape_[input.first].begin(),
+                        max_input_shape_[input.first].end(),
+                        [](int x) { return x > 0; }) &&
+            std::all_of(optim_input_shape_[input.first].begin(),
+                        optim_input_shape_[input.first].end(),
+                        [](int x) { return x > 0; }))) {
+        continue;
+      }
+#endif
       VLOG(4) << "TRT dynamic_shape set " << input.first
               << " min: " << Vec2Str(input.second)
               << ", max: " << Vec2Str(max_input_shape_[input.first])

paddle/fluid/inference/tensorrt/helper.h

@@ -73,8 +73,24 @@ static nvinfer1::IPluginRegistry* GetPluginRegistry() {
 static int GetInferLibVersion() {
   return static_cast<int>(dy::getInferLibVersion());
 }
+#else
+static int GetInferLibVersion() { return 0; }
 #endif
 
+static std::tuple<int, int, int> GetTrtRuntimeVersion() {
+  int ver = GetInferLibVersion();
+  int major = ver / 1000;
+  ver -= major * 1000;
+  int minor = ver / 100;
+  int patch = ver - minor * 100;
+  return std::tuple<int, int, int>{major, minor, patch};
+}
+
+static std::tuple<int, int, int> GetTrtCompileVersion() {
+  return std::tuple<int, int, int>{NV_TENSORRT_MAJOR, NV_TENSORRT_MINOR,
+                                   NV_TENSORRT_PATCH};
+}
+
 // A logger for create TensorRT infer builder.
 class NaiveLogger : public nvinfer1::ILogger {
  public:

paddle/fluid/pybind/inference_api.cc

@@ -330,6 +330,8 @@ void BindInferenceApi(py::module *m) {
   m->def("paddle_dtype_size", &paddle::PaddleDtypeSize);
   m->def("paddle_tensor_to_bytes", &SerializePDTensorToBytes);
   m->def("get_version", &paddle_infer::GetVersion);
+  m->def("get_trt_compile_version", &paddle_infer::GetTrtCompileVersion);
+  m->def("get_trt_runtime_version", &paddle_infer::GetTrtRuntimeVersion);
   m->def("get_num_bytes_of_data_type", &paddle_infer::GetNumBytesOfDataType);
 }
 
@@ -739,10 +741,11 @@ void BindZeroCopyTensor(py::module *m) {
 void BindPaddleInferTensor(py::module *m) {
   py::class_<paddle_infer::Tensor>(*m, "PaddleInferTensor")
       .def("reshape", &paddle_infer::Tensor::Reshape)
-      .def("copy_from_cpu", &PaddleInferTensorCreate<int32_t>)
-      .def("copy_from_cpu", &PaddleInferTensorCreate<int64_t>)
-      .def("copy_from_cpu", &PaddleInferTensorCreate<float>)
-      .def("copy_from_cpu", &PaddleInferTensorCreate<paddle_infer::float16>)
+      .def("copy_from_cpu_bind", &PaddleInferTensorCreate<int32_t>)
+      .def("copy_from_cpu_bind", &PaddleInferTensorCreate<int64_t>)
+      .def("copy_from_cpu_bind", &PaddleInferTensorCreate<float>)
+      .def("copy_from_cpu_bind",
+           &PaddleInferTensorCreate<paddle_infer::float16>)
       .def("copy_to_cpu", &PaddleInferTensorToNumpy)
       .def("shape", &paddle_infer::Tensor::shape)
       .def("set_lod", &paddle_infer::Tensor::SetLoD)

python/paddle/fluid/inference/__init__.py

@@ -14,4 +14,4 @@
 
 from .wrapper import Config, DataType, PlaceType, PrecisionType, Tensor, Predictor
 
-from ..core import create_predictor, get_version, get_num_bytes_of_data_type, PredictorPool
+from ..core import create_predictor, get_version, get_num_bytes_of_data_type, PredictorPool, get_trt_compile_version, get_trt_runtime_version

python/paddle/fluid/inference/wrapper.py

@@ -15,9 +15,24 @@
 from ..core import AnalysisConfig, PaddleDType, PaddlePlace
 from ..core import PaddleInferPredictor, PaddleInferTensor
 
+import numpy as np
+
 DataType = PaddleDType
 PlaceType = PaddlePlace
 PrecisionType = AnalysisConfig.Precision
 Config = AnalysisConfig
 Tensor = PaddleInferTensor
 Predictor = PaddleInferPredictor
+
+
+def tensor_copy_from_cpu(self, data):
+    '''
+    Support input type check based on tensor.copy_from_cpu.
+    '''
+    if not isinstance(data, np.ndarray):
+        raise TypeError(
+            "In copy_from_cpu, we only support numpy ndarray data type.")
+    self.copy_from_cpu_bind(data)
+
+
+Tensor.copy_from_cpu = tensor_copy_from_cpu

python/paddle/fluid/tests/unittests/test_inference_api.py

@@ -14,10 +14,14 @@
 
 import os, shutil
 import unittest
+import paddle
+paddle.enable_static()
 import numpy as np
 import paddle.fluid as fluid
 from paddle.fluid.core import PaddleTensor
 from paddle.fluid.core import PaddleDType
+from paddle.inference import Config, Predictor, create_predictor
+from paddle.inference import get_trt_compile_version, get_trt_runtime_version
 
 
 class TestInferenceApi(unittest.TestCase):
@@ -54,5 +58,60 @@ class TestInferenceApi(unittest.TestCase):
                          tensor_float.ravel().tolist())
 
 
+def get_sample_model():
+    place = fluid.CPUPlace()
+    exe = fluid.Executor(place)
+
+    main_program = fluid.Program()
+    startup_program = fluid.Program()
+    with fluid.program_guard(main_program, startup_program):
+        data = fluid.data(name="data", shape=[-1, 6, 64, 64], dtype="float32")
+        conv_out = fluid.layers.conv2d(
+            input=data,
+            num_filters=3,
+            filter_size=3,
+            groups=1,
+            padding=0,
+            bias_attr=False,
+            act=None)
+    exe.run(startup_program)
+    serialized_program = paddle.static.serialize_program(
+        data, conv_out, program=main_program)
+    serialized_params = paddle.static.serialize_persistables(
+        data, conv_out, executor=exe, program=main_program)
+    return serialized_program, serialized_params
+
+
+class TestInferenceBaseAPI(unittest.TestCase):
+    def get_config(self, model, params):
+        config = Config()
+        config.set_model_buffer(model, len(model), params, len(params))
+        config.enable_use_gpu(100, 0)
+        return config
+
+    def test_apis(self):
+        print('trt compile version:', get_trt_compile_version())
+        print('trt runtime version:', get_trt_runtime_version())
+        program, params = get_sample_model()
+        config = self.get_config(program, params)
+        predictor = create_predictor(config)
+        in_names = predictor.get_input_names()
+        in_handle = predictor.get_input_handle(in_names[0])
+        in_data = np.ones((1, 6, 32, 32)).astype(np.float32)
+        in_handle.copy_from_cpu(in_data)
+        predictor.run()
+
+    def test_wrong_input(self):
+        with self.assertRaises(TypeError):
+            program, params = get_sample_model()
+            config = self.get_config(program, params)
+            predictor = create_predictor(config)
+            in_names = predictor.get_input_names()
+            in_handle = predictor.get_input_handle(in_names[0])
+            in_data = np.ones((1, 6, 64, 64)).astype(np.float32)
+            in_handle.copy_from_cpu(list(in_data))
+            predictor.run()
+
+
 if __name__ == '__main__':
     unittest.main()

python/paddle/inference/__init__.py

@@ -20,6 +20,8 @@ from ..fluid.inference import Tensor  # noqa: F401
 from ..fluid.inference import Predictor  # noqa: F401
 from ..fluid.inference import create_predictor  # noqa: F401
 from ..fluid.inference import get_version  # noqa: F401
+from ..fluid.inference import get_trt_compile_version  # noqa: F401
+from ..fluid.inference import get_trt_runtime_version  # noqa: F401
 from ..fluid.inference import get_num_bytes_of_data_type  # noqa: F401
 from ..fluid.inference import PredictorPool  # noqa: F401
 
@@ -32,6 +34,8 @@ __all__ = [  # noqa
     'Predictor',
     'create_predictor',
     'get_version',
+    'get_trt_compile_version',
+    'get_trt_runtime_version',
     'get_num_bytes_of_data_type',
     'PredictorPool'
 ]