wehub-resource-sync
541 lines
18 KiB
Python
541 lines
18 KiB
Python
# 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 TestGreaterThanFloat32TRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.greater_than
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("float32"),
|
|
"y": np.random.randn(3).astype("float32"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [5, 3], "y": [3]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestGreaterThanInt64TRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.greater_than
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("int64"),
|
|
"y": np.random.randn(3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLessThanFloat32TRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.less_than
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("float32"),
|
|
"y": np.random.randn(3).astype("float32"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [5, 3], "y": [3]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLessThanInt64TRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.less_than
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("int64"),
|
|
"y": np.random.randn(3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestEqualFloatTRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.equal
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("float32"),
|
|
"y": np.random.randn(3).astype("float32"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestEqualIntTRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.equal
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("int64"),
|
|
"y": np.random.randn(3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestNotEqualFloatTRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.not_equal
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("float32"),
|
|
"y": np.random.randn(3).astype("float32"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestNotEqualIntTRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.not_equal
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("int64"),
|
|
"y": np.random.randn(3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestAndRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_and
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("bool"),
|
|
"y": np.random.randn(3).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [5, 3], "y": [3]}
|
|
|
|
def test_trt_result_fp16(self):
|
|
self.check_trt_result(precision_mode="fp16")
|
|
|
|
def test_trt_result_fp32(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestAndRTPatternDifferentShapes(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_and
|
|
self.api_args = {
|
|
"x": np.random.randn(4, 5).astype("bool"),
|
|
"y": np.random.randn(1, 5).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 5], "y": [1, 5]}
|
|
self.opt_shape = {"x": [2, 5], "y": [1, 5]}
|
|
self.max_shape = {"x": [10, 5], "y": [1, 5]}
|
|
|
|
def test_trt_result_fp16(self):
|
|
self.check_trt_result(precision_mode="fp16")
|
|
|
|
def test_trt_result_fp32(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestAndRTPatternDifferentShapes1(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_and
|
|
self.api_args = {
|
|
"x": np.random.randint(0, 2, (2, 3)).astype("bool"),
|
|
"y": np.random.randint(0, 2, (2, 3)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [1, 3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [2, 3]}
|
|
self.max_shape = {"x": [5, 3], "y": [5, 3]}
|
|
|
|
def test_trt_result_fp16(self):
|
|
self.check_trt_result(precision_mode="fp16")
|
|
|
|
def test_trt_result_fp32(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestOrRTPatternBroadcast(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_or
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 1).astype("bool"),
|
|
"y": np.random.randn(2, 3).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [2, 1], "y": [2, 3]}
|
|
self.opt_shape = {"x": [2, 1], "y": [2, 3]}
|
|
self.max_shape = {"x": [2, 1], "y": [2, 3]}
|
|
|
|
def test_trt_result_fp16(self):
|
|
self.check_trt_result(precision_mode="fp16")
|
|
|
|
def test_trt_result_fp32(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestOrRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_or
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("bool"),
|
|
"y": np.random.randn(3).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [5, 3], "y": [3]}
|
|
|
|
def test_trt_result_fp16(self):
|
|
self.check_trt_result(precision_mode="fp16")
|
|
|
|
def test_trt_result_fp32(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestNotRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_not
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x"]}
|
|
self.min_shape = {"x": [1, 3]}
|
|
self.opt_shape = {"x": [2, 3]}
|
|
self.max_shape = {"x": [5, 3]}
|
|
|
|
def test_trt_result_fp16(self):
|
|
self.check_trt_result(precision_mode="fp16")
|
|
|
|
def test_trt_result_fp32(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestNotRTPatternEdgeCase(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_not
|
|
self.api_args = {
|
|
"x": np.zeros((2, 3)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x"]}
|
|
self.min_shape = {"x": [1, 3]}
|
|
self.opt_shape = {"x": [2, 3]}
|
|
self.max_shape = {"x": [5, 3]}
|
|
|
|
def test_trt_result_fp16(self):
|
|
self.check_trt_result(precision_mode="fp16")
|
|
|
|
def test_trt_result_fp32(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLogicalOrTRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_or
|
|
|
|
def test_trt_result(self):
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(3,)).astype("bool"),
|
|
"y": np.random.choice([True, False], size=(3,)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
self.check_trt_result()
|
|
|
|
def test_trt_diff_shape_result(self):
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(2, 3)).astype("bool"),
|
|
"y": np.random.choice([True, False], size=(3)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [4, 3], "y": [3]}
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestAndRTPatternErrorType(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_and
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("int32"),
|
|
"y": np.random.randn(3).astype("int32"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [5, 3], "y": [3]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_marker(expected_result=False)
|
|
|
|
|
|
class TestOrRTPatternErrorType(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_or
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("int32"),
|
|
"y": np.random.randn(3).astype("int32"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [5, 3], "y": [3]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_marker(expected_result=False)
|
|
|
|
|
|
class TestNotRTINT8(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_not
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("int8"),
|
|
}
|
|
self.program_config = {"feed_list": ["x"]}
|
|
self.min_shape = {"x": [1, 3]}
|
|
self.opt_shape = {"x": [2, 3]}
|
|
self.max_shape = {"x": [5, 3]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_marker(expected_result=False)
|
|
|
|
|
|
class TestNotRTINT64(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.bitwise_not
|
|
self.api_args = {
|
|
"x": np.random.randn(2, 3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x"]}
|
|
self.min_shape = {"x": [1, 3]}
|
|
self.opt_shape = {"x": [2, 3]}
|
|
self.max_shape = {"x": [5, 3]}
|
|
|
|
def test_trt_result_fp16(self):
|
|
self.check_trt_result(precision_mode="fp16")
|
|
|
|
def test_trt_result_fp32(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLogicalOrMarker(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_or
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("int64"),
|
|
"y": np.random.randn(3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.target_marker_op = "pd_op.logical_or"
|
|
|
|
def test_trt_result(self):
|
|
self.check_marker(expected_result=False)
|
|
|
|
|
|
class TestLogicalAndTRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_and
|
|
|
|
def test_trt_result(self):
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(3,)).astype("bool"),
|
|
"y": np.random.choice([True, False], size=(3,)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
self.check_trt_result()
|
|
|
|
def test_trt_diff_shape_result(self):
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(2, 3)).astype("bool"),
|
|
"y": np.random.choice([True, False], size=(3)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [4, 3], "y": [3]}
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLogicalAndMarker(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_and
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("int64"),
|
|
"y": np.random.randn(3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.target_marker_op = "pd_op.logical_and"
|
|
|
|
def test_trt_result(self):
|
|
self.check_marker(expected_result=False)
|
|
|
|
|
|
class TestLogicalOr_TRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_or_
|
|
|
|
def test_trt_result(self):
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(3,)).astype("bool"),
|
|
"y": np.random.choice([True, False], size=(3,)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
self.check_trt_result()
|
|
|
|
def test_trt_diff_shape_result(self):
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(2, 3)).astype("bool"),
|
|
"y": np.random.choice([True, False], size=(3)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [4, 3], "y": [3]}
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLogicalOr_Marker(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_or_
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("int64"),
|
|
"y": np.random.randn(3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.target_marker_op = "pd_op.logical_or_"
|
|
|
|
def test_trt_result(self):
|
|
self.check_marker(expected_result=False)
|
|
|
|
|
|
class TestLogicalNotTRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_not
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(2, 3)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x"]}
|
|
self.min_shape = {"x": [2, 3]}
|
|
self.opt_shape = {"x": [2, 3]}
|
|
self.max_shape = {"x": [2, 3]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLogicalNotCase1TRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_not
|
|
self.api_args = {"x": np.random.random([2]).astype("bool")}
|
|
self.program_config = {"feed_list": ["x"]}
|
|
self.min_shape = {"x": [2]}
|
|
self.opt_shape = {"x": [2]}
|
|
self.max_shape = {"x": [2]}
|
|
|
|
def test_trt_result(self):
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLogicalXorTRTPattern(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_xor
|
|
|
|
def test_trt_result(self):
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(3,)).astype("bool"),
|
|
"y": np.random.choice([True, False], size=(3,)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1], "y": [1]}
|
|
self.opt_shape = {"x": [2], "y": [2]}
|
|
self.max_shape = {"x": [5], "y": [5]}
|
|
self.check_trt_result()
|
|
|
|
def test_trt_diff_shape_result(self):
|
|
self.api_args = {
|
|
"x": np.random.choice([True, False], size=(2, 3)).astype("bool"),
|
|
"y": np.random.choice([True, False], size=(3)).astype("bool"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.min_shape = {"x": [1, 3], "y": [3]}
|
|
self.opt_shape = {"x": [2, 3], "y": [3]}
|
|
self.max_shape = {"x": [4, 3], "y": [3]}
|
|
self.check_trt_result()
|
|
|
|
|
|
class TestLogicalXorMarker(TensorRTBaseTest):
|
|
def setUp(self):
|
|
self.python_api = paddle.logical_xor
|
|
self.api_args = {
|
|
"x": np.random.randn(3).astype("int64"),
|
|
"y": np.random.randn(3).astype("int64"),
|
|
}
|
|
self.program_config = {"feed_list": ["x", "y"]}
|
|
self.target_marker_op = "pd_op.logical_xor"
|
|
|
|
def test_trt_result(self):
|
|
self.check_marker(expected_result=False)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|