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#!/usr/bin/env python3 | ||
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# Copyright (c) 2023 CINN 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. | ||
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import numpy as np | ||
from op_test import OpTest, OpTestTool | ||
from op_test_helper import TestCaseHelper | ||
import paddle | ||
import cinn | ||
from cinn.frontend import * | ||
from cinn.common import * | ||
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@OpTestTool.skip_if(not is_compiled_with_cuda(), | ||
"x86 test will be skipped due to timeout.") | ||
class TestNegativeOp(OpTest): | ||
def setUp(self): | ||
print(f"\nRunning {self.__class__.__name__}: {self.case}") | ||
self.prepare_inputs() | ||
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def prepare_inputs(self): | ||
self.x_np = self.random( | ||
shape=self.case["x_shape"], | ||
dtype=self.case["x_dtype"], | ||
low=-100, | ||
high=100) | ||
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def build_paddle_program(self, target): | ||
x = paddle.to_tensor(self.x_np, stop_gradient=True) | ||
out = paddle.neg(x) | ||
self.paddle_outputs = [out] | ||
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def build_cinn_program(self, target): | ||
builder = NetBuilder("unary_elementwise_test") | ||
x = builder.create_input( | ||
self.nptype2cinntype(self.case["x_dtype"]), self.case["x_shape"], | ||
"x") | ||
out = builder.negative(x) | ||
prog = builder.build() | ||
res = self.get_cinn_output(prog, target, [x], [self.x_np], [out]) | ||
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self.cinn_outputs = [res[0]] | ||
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def test_check_results(self): | ||
self.check_outputs_and_grads() | ||
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class TestNegativeOpShape(TestCaseHelper): | ||
def init_attrs(self): | ||
self.class_name = "TestNegativeOpShape" | ||
self.cls = TestNegativeOp | ||
self.inputs = [{ | ||
"x_shape": [1], | ||
}, { | ||
"x_shape": [1024], | ||
}, { | ||
"x_shape": [1, 2048], | ||
}, { | ||
"x_shape": [32, 64], | ||
}, { | ||
"x_shape": [1, 1, 1], | ||
}, { | ||
"x_shape": [16, 8, 4, 2], | ||
}, { | ||
"x_shape": [16, 8, 4, 2, 1], | ||
}] | ||
self.dtypes = [{ | ||
"x_dtype": "float32", | ||
}] | ||
self.attrs = [] | ||
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class TestNegativeOpDtype(TestCaseHelper): | ||
def init_attrs(self): | ||
self.class_name = "TestNegativeOpDtype" | ||
self.cls = TestNegativeOp | ||
self.inputs = [{ | ||
"x_shape": [32, 64], | ||
}] | ||
self.dtypes = [ | ||
{ | ||
"x_dtype": "int8", | ||
}, | ||
{ | ||
"x_dtype": "int16", | ||
}, | ||
{ | ||
"x_dtype": "int32", | ||
}, | ||
{ | ||
"x_dtype": "int64", | ||
}, | ||
{ | ||
"x_dtype": "float16", | ||
"max_relative_error": 1e-3 | ||
}, | ||
{ | ||
"x_dtype": "float32", | ||
}, | ||
{ | ||
"x_dtype": "float64", | ||
}, | ||
] | ||
self.attrs = [] | ||
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if __name__ == "__main__": | ||
TestNegativeOpShape().run() | ||
TestNegativeOpDtype().run() |