add test (#35100)

paddle/fluid/inference/tensorrt/op_teller.cc

@@ -562,7 +562,7 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8,
 
     if (op_type == "slice") {
       if (!desc.HasAttr("axes") || !desc.HasAttr("starts") ||
-          !desc.HasAttr("ends")) {
+          !desc.HasAttr("ends") || !desc.HasAttr("decrease_axis")) {
         return false;
       } else {
         std::vector<int> axes =
@@ -571,9 +571,16 @@ 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";
+          return false;
+        }
         if (!with_dynamic_shape) {
           for (size_t i = 0; i < axes.size(); i++) {
             if (axes[i] == 0) {

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

+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+# 
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+# 
+#     http://www.apache.org/licenses/LICENSE-2.0
+# 
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from trt_layer_auto_scan_test import TrtLayerAutoScanTest, SkipReasons
+from program_config import TensorConfig, ProgramConfig
+import numpy as np
+import paddle.inference as paddle_infer
+from functools import partial
+from typing import Optional, List, Callable, Dict, Any, Set
+import unittest
+
+
+class TrtConvertSliceTest(TrtLayerAutoScanTest):
+    def is_program_valid(self, program_config: ProgramConfig) -> bool:
+        inputs = program_config.inputs
+        weights = program_config.weights
+        attrs = [
+            program_config.ops[i].attrs
+            for i in range(len(program_config.ops))
+        ]
+
+        for x in attrs[0]["decrease_axis"]:
+            if x < 0:
+                return False
+        for x in range(len(attrs[0]["axes"])):
+            start = 0
+            end = 0
+            if attrs[0]["starts"][x] < 0:
+                start = attrs[0]["starts"][x] + inputs['input_data'].shape[
+                    attrs[0]["axes"][x]]
+            else:
+                start = attrs[0]["starts"][x]
+            if attrs[0]["ends"][x] < 0:
+                end = attrs[0]["ends"][x] + inputs['input_data'].shape[attrs[0][
+                    "axes"][x]]
+            else:
+                end = attrs[0]["ends"][x]
+            start = max(0, start)
+            end = max(0, end)
+            if start >= end:
+                return False
+
+        return True
+
+    def sample_program_configs(self):
+        def generate_input1(attrs: List[Dict[str, Any]]):
+            return np.ones([1, 3, 64, 64]).astype(np.float32)
+
+        for axes in [[0, 1], [1, 3], [2, 3]]:
+            for starts in [[0, 1], [-4, -3]]:
+                for ends in [[2, 2], [-1, -2], [5, 5]]:
+                    for decrease_axis in [[], [1], [2], [-1], [-100]]:
+                        for infer_flags in [[-1]]:
+                            dics = [{
+                                "axes": axes,
+                                "starts": starts,
+                                "ends": ends,
+                                "decrease_axis": decrease_axis,
+                                "infer_flags": infer_flags
+                            }]
+
+                            ops_config = [{
+                                "op_type": "slice",
+                                "op_inputs": {
+                                    "Input": ["input_data"]
+                                },
+                                "op_outputs": {
+                                    "Out": ["slice_output_data"]
+                                },
+                                "op_attrs": dics[0]
+                            }]
+                            ops = self.generate_op_config(ops_config)
+
+                            program_config = ProgramConfig(
+                                ops=ops,
+                                weights={},
+                                inputs={
+                                    "input_data": TensorConfig(data_gen=partial(
+                                        generate_input1, dics))
+                                },
+                                outputs=["slice_output_data"])
+
+                            yield program_config
+
+    def sample_predictor_configs(
+            self, program_config) -> (paddle_infer.Config, List[int], float):
+        def generate_dynamic_shape(attrs):
+            self.dynamic_shape.min_input_shape = {"input_data": [1, 3, 32, 32]}
+            self.dynamic_shape.max_input_shape = {"input_data": [4, 3, 64, 64]}
+            self.dynamic_shape.opt_input_shape = {"input_data": [1, 3, 64, 64]}
+
+        def clear_dynamic_shape():
+            self.dynamic_shape.min_input_shape = {}
+            self.dynamic_shape.max_input_shape = {}
+            self.dynamic_shape.opt_input_shape = {}
+
+        def generate_trt_nodes_num(attrs, dynamic_shape):
+            inputs = program_config.inputs
+            if len(attrs[0]["decrease_axis"]) != 0:
+                return 0, 3
+            if dynamic_shape:
+                for i in range(len(attrs[0]["starts"])):
+                    if attrs[0]["starts"][i] < 0 or attrs[0]["ends"][i] < 0:
+                        return 0, 3
+            if not dynamic_shape:
+                for x in attrs[0]["axes"]:
+                    if x == 0:
+                        return 0, 3
+            return 1, 2
+
+        attrs = [
+            program_config.ops[i].attrs
+            for i in range(len(program_config.ops))
+        ]
+
+        # for static_shape
+        clear_dynamic_shape()
+        self.trt_param.precision = paddle_infer.PrecisionType.Float32
+        yield self.create_inference_config(), generate_trt_nodes_num(
+            attrs, False), 1e-5
+        self.trt_param.precision = paddle_infer.PrecisionType.Half
+        yield self.create_inference_config(), generate_trt_nodes_num(
+            attrs, False), 1e-4
+
+        # for dynamic_shape
+        generate_dynamic_shape(attrs)
+        self.trt_param.precision = paddle_infer.PrecisionType.Float32
+        yield self.create_inference_config(), generate_trt_nodes_num(attrs,
+                                                                     True), 1e-5
+        self.trt_param.precision = paddle_infer.PrecisionType.Half
+        yield self.create_inference_config(), generate_trt_nodes_num(attrs,
+                                                                     True), 1e-4
+
+    def test(self):
+        self.run_test()
+
+
+if __name__ == "__main__":
+    unittest.main()