# Copyright (c) 2024 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. import unittest import numpy as np from tensorrt_test_base import TensorRTBaseTest import paddle class TestMatmulTRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.matmul self.api_args = { "x": np.random.randn(2, 3).astype("float32"), "y": np.random.randn(3, 2).astype("float32"), "transpose_x": False, "transpose_y": False, } self.program_config = {"feed_list": ["x", "y"]} self.min_shape = {"x": [1, 3], "y": [3, 2]} self.opt_shape = {"x": [1, 3], "y": [3, 2]} self.max_shape = {"x": [5, 3], "y": [3, 2]} def test_trt_result(self): self.check_trt_result(rtol=1e-3, atol=1e-3) class TestTransposeTRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.transpose self.api_args = { "x": np.random.randn(2, 3, 4).astype("float32"), "perm": [1, 0, 2], } self.program_config = {"feed_list": ["x"]} self.min_shape = {"x": [1, 3, 4]} self.opt_shape = {"x": [1, 3, 4]} self.max_shape = {"x": [5, 3, 4]} def test_trt_result(self): self.check_trt_result() class TestBmmTRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.bmm self.api_args = { "x": np.random.randn(2, 2, 3).astype("float32"), "y": np.random.randn(2, 3, 2).astype("float32"), } self.program_config = {"feed_list": ["x", "y"]} self.min_shape = {"x": [1, 2, 3], "y": [1, 3, 2]} self.opt_shape = {"x": [1, 2, 3], "y": [1, 3, 2]} self.max_shape = {"x": [5, 2, 3], "y": [5, 3, 2]} def test_trt_result(self): self.check_trt_result() class TestFlipTRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.flip self.api_args = { "x": np.random.randn(2, 3, 4).astype("float32"), "axis": [0, 2], } self.program_config = {"feed_list": ["x"]} self.min_shape = {"x": [1, 3, 4]} self.opt_shape = {"x": [1, 3, 4]} self.max_shape = {"x": [5, 3, 4]} def test_trt_result(self): self.check_trt_result() class TestFlipNegAxisTRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.flip self.api_args = { "x": np.random.randn(2, 3, 4).astype("float32"), "axis": [-1, -3], } self.program_config = {"feed_list": ["x"]} self.min_shape = {"x": [1, 3, 4]} self.opt_shape = {"x": [1, 3, 4]} self.max_shape = {"x": [5, 3, 4]} def test_trt_result(self): self.check_trt_result() class TestFlipIntTRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.flip self.api_args = { "x": np.random.randn(2, 3, 4).astype("int64"), "axis": [0, 2], } self.program_config = {"feed_list": ["x"]} self.min_shape = {"x": [1, 3, 4]} self.opt_shape = {"x": [1, 3, 4]} self.max_shape = {"x": [5, 3, 4]} def test_trt_result(self): self.check_trt_result() class TestFlipIntNegAxisTRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.flip self.api_args = { "x": np.random.randn(2, 3, 4).astype("int64"), "axis": [-1, -3], } self.program_config = {"feed_list": ["x"]} self.min_shape = {"x": [1, 3, 4]} self.opt_shape = {"x": [1, 3, 4]} self.max_shape = {"x": [5, 3, 4]} def test_trt_result(self): self.check_trt_result() class TestPNormTRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.linalg.norm self.api_args = { "x": np.random.randn(2, 3, 4).astype("float32"), "p": 2, "axis": -1, "keepdim": False, } self.program_config = {"feed_list": ["x"]} self.min_shape = {"x": [1, 3, 4]} self.opt_shape = {"x": [2, 3, 4]} self.max_shape = {"x": [4, 3, 4]} def test_trt_result(self): self.check_trt_result() class TestPNormCase1TRTPattern(TensorRTBaseTest): def setUp(self): self.python_api = paddle.linalg.norm self.api_args = { "x": np.random.randn(2, 3).astype("float16"), "p": 2, "axis": -1, "keepdim": False, } self.program_config = {"feed_list": ["x"]} self.min_shape = {"x": [1, 3]} self.opt_shape = {"x": [2, 3]} self.max_shape = {"x": [4, 3]} def test_trt_result(self): self.check_trt_result(precision_mode="fp16") if __name__ == '__main__': unittest.main()