From 75d5e3bf327f963f1ffb547ce9b7205ebc84de5f Mon Sep 17 00:00:00 2001 From: baoachun <962571062@qq.com> Date: Mon, 13 Sep 2021 12:51:54 +0800 Subject: [PATCH] add gather trt converter test case (#35523) --- paddle/fluid/inference/tensorrt/op_teller.cc | 11 + .../ir/inference/test_trt_convert_gather.py | 213 ++++++++++++++++++ 2 files changed, 224 insertions(+) create mode 100644 python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_gather.py diff --git a/paddle/fluid/inference/tensorrt/op_teller.cc b/paddle/fluid/inference/tensorrt/op_teller.cc index 56d4da97eb5..9ece7b39c99 100644 --- a/paddle/fluid/inference/tensorrt/op_teller.cc +++ b/paddle/fluid/inference/tensorrt/op_teller.cc @@ -319,6 +319,17 @@ bool OpTeller::Tell(const framework::ir::Node* node, bool use_no_calib_int8, if (op_type == "gather") { if (!with_dynamic_shape) return false; + + if (with_dynamic_shape) { + auto* block = desc.Block(); + auto* x_var_desc = block->FindVar(desc.Input("X")[0]); + const auto x_shape = x_var_desc->GetShape(); + if (x_shape.size() == 1) { + VLOG(3) << "Gather does not support 1-dimensional input in tensorrt"; + return false; + } + } + auto inputs = desc.InputArgumentNames(); for (auto& input : inputs) { if (input == "Axis" && desc.Input("Axis").size() > 0) return false; diff --git a/python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_gather.py b/python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_gather.py new file mode 100644 index 00000000000..9a3c9aff61b --- /dev/null +++ b/python/paddle/fluid/tests/unittests/ir/inference/test_trt_convert_gather.py @@ -0,0 +1,213 @@ +# 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 logging + + +class TrtConvertGatherTest(TrtLayerAutoScanTest): + def is_program_valid(self, program_config: ProgramConfig) -> bool: + inputs = program_config.inputs + attrs = [ + program_config.ops[i].attrs + for i in range(len(program_config.ops)) + ] + if len(inputs['input_data'].shape) <= attrs[0]['axis']: + return False + + return True + + def sample_program_configs(self): + def generate_input1(shape): + return np.random.random(shape).astype(np.float32) + + def generate_input2(index): + return np.array(index).astype(np.int32) + + def generate_input3(axis): + return np.array([axis]).astype(np.int32) + + for shape in [[32], [16, 64], [32, 16, 16], [32, 64, 16, 32]]: + for index in [[1, 4], [4, 8]]: + for axis in [0, 1, 2, 3]: + for overwrite in [True, False]: + for input in [{ + "X": ["input_data"], + "Index": ["index_data"] + }, { + "X": ["input_data"], + "Index": ["index_data"], + "Axis": ["axis_data"] + }]: + self.shape = shape + self.axis = axis + self.input_num = len(input) + dics = [{"overwrite": overwrite, "axis": axis}] + ops_config = [{ + "op_type": "gather", + "op_inputs": input, + "op_outputs": { + "Out": ["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, shape)), + "index_data": TensorConfig(data_gen=partial( + generate_input2, index)), + } if len(input) == 2 else { + "input_data": TensorConfig(data_gen=partial( + generate_input1, shape)), + "index_data": TensorConfig(data_gen=partial( + generate_input2, index)), + "axis_data": TensorConfig(data_gen=partial( + generate_input3, axis)), + }, + outputs=["output_data"]) + + yield program_config + + def sample_predictor_configs( + self, program_config) -> (paddle_infer.Config, List[int], float): + def generate_dynamic_shape(attrs): + if len(self.shape) == 1: + self.dynamic_shape.min_input_shape = { + "input_data": [4], + "index_data": [1] + } + self.dynamic_shape.max_input_shape = { + "input_data": [128], + "index_data": [4] + } + self.dynamic_shape.opt_input_shape = { + "input_data": [16], + "index_data": [2] + } + elif len(self.shape) == 2: + self.dynamic_shape.min_input_shape = { + "input_data": [2, 4], + "index_data": [1] + } + self.dynamic_shape.max_input_shape = { + "input_data": [256, 256], + "index_data": [4] + } + self.dynamic_shape.opt_input_shape = { + "input_data": [64, 32], + "index_data": [2] + } + elif len(self.shape) == 3: + self.dynamic_shape.min_input_shape = { + "input_data": [2, 4, 4], + "index_data": [1] + } + self.dynamic_shape.max_input_shape = { + "input_data": [128, 256, 256], + "index_data": [4] + } + self.dynamic_shape.opt_input_shape = { + "input_data": [16, 64, 32], + "index_data": [2] + } + elif len(self.shape) == 4: + self.dynamic_shape.min_input_shape = { + "input_data": [2, 4, 4, 2], + "index_data": [1] + } + self.dynamic_shape.max_input_shape = { + "input_data": [128, 256, 128, 256], + "index_data": [4] + } + self.dynamic_shape.opt_input_shape = { + "input_data": [16, 64, 16, 32], + "index_data": [2] + } + + def clear_dynamic_shape(): + self.dynamic_shape.max_input_shape = {} + self.dynamic_shape.min_input_shape = {} + self.dynamic_shape.opt_input_shape = {} + + def generate_trt_nodes_num(dynamic_shape): + if self.input_num == 3: + return 0, 5 + else: + if dynamic_shape and self.axis == 0: + return 1, 3 + else: + return 0, 4 + + 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( + False), 1e-5 + self.trt_param.precision = paddle_infer.PrecisionType.Half + yield self.create_inference_config(), generate_trt_nodes_num( + False), 1e-5 + + # for dynamic_shape + generate_dynamic_shape(attrs) + self.trt_param.precision = paddle_infer.PrecisionType.Float32 + yield self.create_inference_config(), generate_trt_nodes_num(True), 1e-5 + self.trt_param.precision = paddle_infer.PrecisionType.Half + yield self.create_inference_config(), generate_trt_nodes_num(True), 1e-5 + + def add_skip_trt_case(self): + def teller1(program_config, predictor_config): + if len(self.dynamic_shape.min_input_shape) != 0: + inputs = program_config.inputs + if len(inputs['input_data'].shape) == 1 or len(inputs[ + 'index_data'].shape) == 1: + return True + return False + + self.add_skip_case( + teller1, SkipReasons.TRT_NOT_SUPPORT, + "Need to repair the case: trt reshape out failed for dynamic shape mode when inputs' dims==1." + ) + + def teller2(program_config, predictor_config): + inputs = program_config.inputs + if "axis_data" in inputs.keys(): + return True + return False + + self.add_skip_case( + teller2, SkipReasons.TRT_NOT_SUPPORT, + "Need to repair the case: trt do not support axis tensor input.") + + def test(self): + self.add_skip_trt_case() + self.run_test() + + +if __name__ == "__main__": + unittest.main() -- GitLab