remove input dim check in op_teller and update ut (#37097)

* remove input dim check of activation in op_teller

* remove input dim check of concat in op_teller

* remove input dim check of clip in op_teller

* remove input dim check of scale in op_teller

* remove input dim check in op_teller

* update attr check of slice in op_teller

paddle/fluid/inference/tensorrt/op_teller.cc

@@ -204,12 +204,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
                 << " op does not support input's dim is 1 in tensorrt.";
         return false;
       }
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "activation op does not support input's dim is 2 in "
-                   "tensorrt static shape, the output shape has diff.";
-        return false;
-      }
     }
 
     if (op_type == "pool2d") {
@@ -458,12 +452,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
       auto x_var_name = desc.Input("X")[0];
       auto* x_var_desc = block->FindVar(x_var_name);
       const auto x_shape = x_var_desc->GetShape();
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "softmax op does not support input's dim is 2 in tensorrt "
-                   "static shape, the output shape has diff.";
-        return false;
-      }
     }
     if (op_type == "group_norm") {
       if (!with_dynamic_shape) return false;
@@ -489,22 +477,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
           return false;
         }
       }
-      auto* block = desc.Block();
-      if (block == nullptr) {
-        VLOG(3) << "The block desc is nullptr, we can't continue to analyze. "
-                   "Developers need to check whether block_desc is passed in "
-                   "the pass.";
-        return false;
-      }
-      auto x_var_name = desc.Input("X")[0];
-      auto* x_var_desc = block->FindVar(x_var_name);
-      const auto x_shape = x_var_desc->GetShape();
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "concat op does not support input's dim is 2 in tensorrt "
-                   "static shape, the output shape has diff.";
-        return false;
-      }
     }
     if (op_type == "transpose2" || op_type == "transpose") {
       if (!desc.HasAttr("axis")) {
@@ -831,12 +803,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
       auto x_var_name = desc.Input("X")[0];
       auto* x_var_desc = block->FindVar(x_var_name);
       const auto x_shape = x_var_desc->GetShape();
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "batch_norm op does not support input's dim is 2 in "
-                   "tensorrt static shape, the output shape has diff.";
-        return false;
-      }
     }
 
     if (op_type == "split") {
@@ -924,13 +890,8 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
         VLOG(3) << "The output_length should be equal to the output size.";
         return false;
       }
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "split op does not support input's dim is 2 in tensorrt "
-                   "static shape. The output shape has diff.";
-        return false;
-      }
     }
+
     if (op_type == "scale") {
       auto scale_inputs = desc.Inputs();
       if (scale_inputs.find("ScaleTensor") != scale_inputs.end()) {
@@ -948,11 +909,27 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
       auto x_var_name = desc.Input("X")[0];
       auto* x_var_desc = block->FindVar(x_var_name);
       const auto x_shape = x_var_desc->GetShape();
-      if (!with_dynamic_shape && x_shape.size() == 1) return false;
+      if (!with_dynamic_shape && x_shape.size() == 1) {
+        VLOG(3) << "Scale op does not support 1-dimensional input in tensorrt";
+        return false;
+      }
     }
+
     if (op_type == "slice") {
+      if (desc.HasAttr("decrease_axis")) {
+        std::vector<int> decrease_axis =
+            BOOST_GET_CONST(std::vector<int>, desc.GetAttr("decrease_axis"));
+        if (decrease_axis.size() > 0) {
+          VLOG(3) << "Invalid slice decrease_axis. decrease_axis.size() > 0"
+                     "is not supported in TensorRT";
+          return false;
+        }
+      }
+
       if (!desc.HasAttr("axes") || !desc.HasAttr("starts") ||
-          !desc.HasAttr("ends") || !desc.HasAttr("decrease_axis")) {
+          !desc.HasAttr("ends")) {
+        VLOG(3) << "The necessary attributes of the slice operator axes "
+                   "or starts or ends are missing.";
         return false;
       } else {
         std::vector<int> axes =
@@ -961,14 +938,10 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
             BOOST_GET_CONST(std::vector<int>, desc.GetAttr("starts"));
         std::vector<int> ends =
             BOOST_GET_CONST(std::vector<int>, desc.GetAttr("ends"));
-        std::vector<int> decrease_axis =
-            BOOST_GET_CONST(std::vector<int>, desc.GetAttr("decrease_axis"));
+
         if (axes.size() != starts.size() || axes.size() != ends.size()) {
-          return false;
-        }
-        if (decrease_axis.size() > 0) {
-          VLOG(3) << "Invalid slice decrease_axis. decrease_axis.size() > 0"
-                     "is not supported in TensorRT";
+          VLOG(3) << "The shape of attributes of the slice operator axes "
+                     "or starts or ends are not equal.";
           return false;
         }
         if (!with_dynamic_shape) {
@@ -1082,12 +1055,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
         VLOG(3) << "gelu op does not support input's dim is 1 in tensorrt.";
         return false;
       }
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "gelu op does not support input's dim is 2 in tensorrt "
-                   "static shape, the output shape has diff.";
-        return false;
-      }
     }
 
     if (op_type == "layer_norm") {
@@ -1207,29 +1174,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
       }
     }
 
-    if (op_type == "scale") {
-      auto* block = desc.Block();
-      if (block == nullptr) {
-        VLOG(3) << "The block desc is nullptr, we can't continue to analyze. "
-                   "Developers need to check whether block_desc is passed in "
-                   "the pass.";
-        return false;
-      }
-      auto x_var_name = desc.Input("X")[0];
-      auto* x_var_desc = block->FindVar(x_var_name);
-      const auto x_shape = x_var_desc->GetShape();
-      if (x_shape.size() == 1) {
-        VLOG(3) << "scale op does not support input's dim is 1 in tensorrt.";
-        return false;
-      }
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "scale op does not support input's dim is 2 in tensorrt "
-                   "static shape, the output shape has diff.";
-        return false;
-      }
-    }
-
     if (op_type == "swish") {
       auto* block = desc.Block();
       if (block == nullptr) {
@@ -1245,12 +1189,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
         VLOG(3) << "swish op does not support input's dim is 1 in tensorrt.";
         return false;
       }
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "swish op does not support input's dim is 2 in tensorrt "
-                   "static shape, the output shape has diff.";
-        return false;
-      }
     }
 
     if (op_type == "prelu") {
@@ -1288,13 +1226,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
         return false;
       }
 
-      if (!with_dynamic_shape) {
-        if (x_shape.size() == 2) {
-          VLOG(3) << "prelu op does not support input's dim is 2 in tensorrt.";
-          return false;
-        }
-      }
-
 #if IS_TRT_VERSION_LT(7000)
       if (!with_dynamic_shape) {
         // TODO(inference): fix trt6 static plugin error.
@@ -1546,12 +1477,6 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
         VLOG(3) << "clip op does not support input's dim is 1 in tensorrt.";
         return false;
       }
-      // TODO(inference): fix
-      if (x_shape.size() == 2 && !with_dynamic_shape) {
-        VLOG(3) << "clip op does not support input's dim is 2 in tensorrt "
-                   "static shape, the output shape has diff.";
-        return false;
-      }
     }
 
     if (op_type == "reduce_sum" || op_type == "reduce_mean") {
@@ -1667,15 +1592,17 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
       if (!with_dynamic_shape) {
         auto* block = desc.Block();
         if (block == nullptr) {
-          VLOG(3) << "The block is null.";
+          VLOG(3) << "The block desc is nullptr, we can't continue to analyze. "
+                     "Developers need to check whether block_desc is passed in "
+                     "the pass.";
           return false;
         }
         auto x_var_name = desc.Input("X")[0];
         auto* x_var_desc = block->FindVar(x_var_name);
         const auto x_shape = x_var_desc->GetShape();
-        if (x_shape.size() <= 2) {
-          VLOG(3) << "hard_sigmoid op does not support input's dim less than 3 "
-                     "in tensorrt.";
+        if (x_shape.size() == 1) {
+          VLOG(3) << "Hard sigmoid does not support 1-dimensional input in "
+                     "tensorrt";
           return false;
         }
       }

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_activation.py

@@ -126,18 +126,7 @@ class TrtConvertActivationTest(TrtLayerAutoScanTest):
         yield self.create_inference_config(), generate_trt_nodes_num(attrs,
                                                                      True), 1e-5
 
-    def add_skip_trt_case(self):
-        def teller1(program_config, predictor_config):
-            if self.dims == 2:
-                return True
-            return False
-
-        self.add_skip_case(
-            teller1, SkipReasons.TRT_NOT_IMPLEMENTED,
-            "When input dims is 2, pulgin will product a 4 dims output.")
-
     def test(self):
-        self.add_skip_trt_case()
         self.run_test()
 
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_batch_norm.py

@@ -212,18 +212,6 @@ class TrtConvertBatchNormTest(TrtLayerAutoScanTest):
         self.add_skip_case(teller1, SkipReasons.TRT_NOT_SUPPORT,
                            "INPUT MomentumTensor NOT SUPPORT")
 
-        def teller2(program_config, predictor_config):
-            if len(
-                    program_config.inputs['batch_norm_input'].shape
-            ) == 2 and not predictor_config.tensorrt_dynamic_shape_enabled():
-                return True
-            return False
-
-        self.add_skip_case(
-            teller2, SkipReasons.TRT_NOT_IMPLEMENTED,
-            "The output shape has diff, but we can add shuffle layer to resolve it."
-        )
-
     def test(self):
         self.add_skip_trt_case()
         self.run_test()

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_clip.py

@@ -146,21 +146,7 @@ class TrtConvertClipTest(TrtLayerAutoScanTest):
         yield self.create_inference_config(), generate_trt_nodes_num(attrs,
                                                                      True), 1e-5
 
-    def add_skip_trt_case(self):
-        def teller1(program_config, predictor_config):
-            if len(
-                    program_config.inputs['input_data'].shape
-            ) == 2 and not predictor_config.tensorrt_dynamic_shape_enabled():
-                return True
-            return False
-
-        self.add_skip_case(
-            teller1, SkipReasons.TRT_NOT_IMPLEMENTED,
-            "The output shape has diff, but we can add shuffle layer to resolve it."
-        )
-
     def test(self):
-        self.add_skip_trt_case()
         self.run_test()
 
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_concat.py

@@ -318,18 +318,6 @@ class TrtConvertConcatTest(TrtLayerAutoScanTest):
         self.add_skip_case(teller1, SkipReasons.TRT_NOT_SUPPORT,
                            "INPUT AxisTensor NOT SUPPORT")
 
-        def teller2(program_config, predictor_config):
-            if len(
-                    program_config.inputs['concat_input1'].shape
-            ) == 2 and not predictor_config.tensorrt_dynamic_shape_enabled():
-                return True
-            return False
-
-        self.add_skip_case(
-            teller2, SkipReasons.TRT_NOT_IMPLEMENTED,
-            "The output shape has diff, but we can add shuffle layer to resolve it."
-        )
-
     def test(self):
         self.add_skip_trt_case()
         self.run_test()

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_gelu.py

@@ -126,18 +126,7 @@ class TrtConvertGeluTest(TrtLayerAutoScanTest):
         yield self.create_inference_config(), generate_trt_nodes_num(attrs,
                                                                      True), 1e-5
 
-    def add_skip_trt_case(self):
-        def teller1(program_config, predictor_config):
-            if self.dims == 2:
-                return True
-            return False
-
-        self.add_skip_case(
-            teller1, SkipReasons.TRT_NOT_IMPLEMENTED,
-            "When input dims is 2, pulgin will product a 4 dims output.")
-
     def test(self):
-        self.add_skip_trt_case()
         self.run_test()
 
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_hard_sigmoid.py

@@ -106,20 +106,7 @@ class TrtConvertHardSigmoidTest_dim_2(TrtLayerAutoScanTest):
         self.trt_param.precision = paddle_infer.PrecisionType.Half
         yield self.create_inference_config(), (1, 2), 1e-5
 
-    def add_skip_trt_case(self):
-        def teller(program_config, predictor_config):
-            if len(self.dynamic_shape.
-                   min_input_shape) == 0 and self.input_dim == 2:
-                return True
-            return False
-
-        self.add_skip_case(
-            teller, SkipReasons.TRT_NOT_SUPPORT,
-            "Need to repair the case: the output of trt and GPU has diff when inputs' dims is 2 in static shape mode."
-        )
-
     def test(self):
-        self.add_skip_trt_case()
         self.run_test()
 
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_prelu.py

@@ -176,17 +176,6 @@ class TrtConvertPreluTest(TrtLayerAutoScanTest):
         self.add_skip_case(teller1, SkipReasons.TRT_NOT_SUPPORT,
                            "Trt does not support 1-dimensional input.")
 
-        def teller2(program_config, predictor_config):
-            if (len(self.dynamic_shape.min_input_shape) == 0):
-                if self.dim1 != 0 and self.dim2 == 0 and self.dim3 == 0:
-                    return True
-            return False
-
-        self.add_skip_case(
-            teller2, SkipReasons.TRT_NOT_SUPPORT,
-            "Need to repair the case: the output of GPU and tensorrt has diff when the input dimension is 2 in static shape mode."
-        )
-
         ver = paddle_infer.get_trt_compile_version()
         if ver[0] * 1000 + ver[1] * 100 + ver[0] * 10 < 7000:
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_scale.py

@@ -145,7 +145,7 @@ class TrtConvertScaleTest(TrtLayerAutoScanTest):
 
     def add_skip_trt_case(self):
         def teller1(program_config, predictor_config):
-            if len(program_config.weights) == 1:
+            if self.num_input == 0:
                 return True
             return False
 
@@ -153,7 +153,7 @@ class TrtConvertScaleTest(TrtLayerAutoScanTest):
                            "INPUT ScaleTensor and Shape NOT SUPPORT")
 
         def teller2(program_config, predictor_config):
-            if self.dims == 1 and self.dynamic_shape.min_input_shape == 0:
+            if self.dims == 1 and len(self.dynamic_shape.min_input_shape) == 0:
                 return True
             return False
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_softmax.py

@@ -135,21 +135,7 @@ class TrtConvertSoftmaxTest(TrtLayerAutoScanTest):
         yield self.create_inference_config(), generate_trt_nodes_num(attrs,
                                                                      True), 1e-5
 
-    def add_skip_trt_case(self):
-        def teller1(program_config, predictor_config):
-            if len(
-                    program_config.inputs['softmax_input'].shape
-            ) == 2 and not predictor_config.tensorrt_dynamic_shape_enabled():
-                return True
-            return False
-
-        self.add_skip_case(
-            teller1, SkipReasons.TRT_NOT_IMPLEMENTED,
-            "The output shape has diff, but we can add shuffle layer to resolve it."
-        )
-
     def test(self):
-        self.add_skip_trt_case()
         self.run_test()
 
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_split.py

@@ -227,18 +227,6 @@ class TrtConvertSplitTest(TrtLayerAutoScanTest):
             teller1, SkipReasons.TRT_NOT_SUPPORT,
             "INPUT AxisTensor AND SectionsTensorList NOT SUPPORT.")
 
-        def teller2(program_config, predictor_config):
-            if len(
-                    program_config.inputs['split_input'].shape
-            ) == 2 and not predictor_config.tensorrt_dynamic_shape_enabled():
-                return True
-            return False
-
-        self.add_skip_case(
-            teller2, SkipReasons.TRT_NOT_IMPLEMENTED,
-            "The output shape has diff, but we can add shuffle layer to resolve it."
-        )
-
     def test(self):
         self.add_skip_trt_case()
         self.run_test()

python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_swish.py

@@ -126,18 +126,7 @@ class TrtConvertSwishTest(TrtLayerAutoScanTest):
         yield self.create_inference_config(), generate_trt_nodes_num(attrs,
                                                                      True), 1e-5
 
-    def add_skip_trt_case(self):
-        def teller1(program_config, predictor_config):
-            if self.dims == 2:
-                return True
-            return False
-
-        self.add_skip_case(
-            teller1, SkipReasons.TRT_NOT_IMPLEMENTED,
-            "When input dims is 2, pulgin will product a 4 dims output.")
-
     def test(self):
-        self.add_skip_trt_case()
         self.run_test()