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Add reduce test using new test helper (PaddlePaddle#1379)
* Add reduce test using new test helper * Fix output shape error when numel = 1 Add cast op on paddle reduce_sum when dtype is int32 * Fix reduce result error when keepdim = True
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| Original file line number | Diff line number | Diff line change |
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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. | ||
|
|
||
| import unittest | ||
| 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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|
|
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| @OpTestTool.skip_if(not is_compiled_with_cuda(), | ||
| "x86 test will be skipped due to timeout.") | ||
| class TestReduceOp(OpTest): | ||
| def setUp(self): | ||
| print(f"\nRunning {self.__class__.__name__}: {self.case}") | ||
| self.prepare_inputs() | ||
|
|
||
| def prepare_inputs(self): | ||
| self.x_np = self.random( | ||
| shape=self.case["shape"], dtype=self.case["dtype"]) | ||
|
|
||
| def build_paddle_program(self, target): | ||
| x = paddle.to_tensor(self.x_np, stop_gradient=True) | ||
| if self.case["op_type"] == "sum": | ||
| out = paddle.sum( | ||
| x, axis=self.case["axis"], keepdim=self.case["keepdim"]) | ||
| if self.case["dtype"] == "int32": | ||
| out = out.cast(self.case["dtype"]) | ||
| elif self.case["op_type"] == "prod": | ||
| out = paddle.prod( | ||
| x, axis=self.case["axis"], keepdim=self.case["keepdim"]) | ||
| elif self.case["op_type"] == "max": | ||
| out = paddle.max( | ||
| x, axis=self.case["axis"], keepdim=self.case["keepdim"]) | ||
| elif self.case["op_type"] == "min": | ||
| out = paddle.min( | ||
| x, axis=self.case["axis"], keepdim=self.case["keepdim"]) | ||
| elif self.case["op_type"] == "all": | ||
| out = paddle.all( | ||
| x, axis=self.case["axis"], keepdim=self.case["keepdim"]) | ||
| elif self.case["op_type"] == "any": | ||
| out = paddle.any( | ||
| x, axis=self.case["axis"], keepdim=self.case["keepdim"]) | ||
| else: | ||
| out = paddle.assign(x) | ||
| self.paddle_outputs = [out] | ||
|
|
||
| def build_cinn_program(self, target): | ||
| builder = NetBuilder("reduce") | ||
| x = builder.create_input( | ||
| self.nptype2cinntype(self.case["dtype"]), self.case["shape"], "x") | ||
| if self.case["op_type"] == "sum": | ||
| out = builder.reduce_sum(x, self.case["axis"], | ||
| self.case["keepdim"]) | ||
| elif self.case["op_type"] == "prod": | ||
| out = builder.reduce_prod(x, self.case["axis"], | ||
| self.case["keepdim"]) | ||
| elif self.case["op_type"] == "max": | ||
| out = builder.reduce_max(x, self.case["axis"], | ||
| self.case["keepdim"]) | ||
| elif self.case["op_type"] == "min": | ||
| out = builder.reduce_min(x, self.case["axis"], | ||
| self.case["keepdim"]) | ||
| elif self.case["op_type"] == "all": | ||
| out = builder.reduce_all(x, self.case["axis"], | ||
| self.case["keepdim"]) | ||
| elif self.case["op_type"] == "any": | ||
| out = builder.reduce_any(x, self.case["axis"], | ||
| self.case["keepdim"]) | ||
| else: | ||
| out = builder.identity(x) | ||
| prog = builder.build() | ||
| res = self.get_cinn_output(prog, target, [x], [self.x_np], [out]) | ||
| self.cinn_outputs = res | ||
|
|
||
| def test_check_results(self): | ||
| max_relative_error = self.case[ | ||
| "max_relative_error"] if "max_relative_error" in self.case else 1e-5 | ||
| self.check_outputs_and_grads(max_relative_error=max_relative_error) | ||
|
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|
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| class TestReduceAll(TestCaseHelper): | ||
| def init_attrs(self): | ||
| self.class_name = "TestReduceOpCase" | ||
| self.cls = TestReduceOp | ||
| self.inputs = [ | ||
| { | ||
| "shape": [1], | ||
| "axis": [-1], | ||
| }, | ||
| { | ||
| "shape": [1024], | ||
| "axis": [0], | ||
| }, | ||
| { | ||
| "shape": [512, 256], | ||
| "axis": [1], | ||
| }, | ||
| { | ||
| "shape": [128, 64, 32], | ||
| "axis": [2], | ||
| }, | ||
| { | ||
| "shape": [16, 8, 4, 2], | ||
| "axis": [3], | ||
| }, | ||
| { | ||
| "shape": [16, 8, 4, 2, 1], | ||
| "axis": [3], | ||
| }, | ||
| { | ||
| "shape": [1, 1, 1, 1, 1], | ||
| "axis": [3], | ||
| }, | ||
| ] | ||
| self.dtypes = [ | ||
| # Paddle reduce not support | ||
| # { | ||
| # "dtype": "int16", | ||
| # }, | ||
| { | ||
| "dtype": "int32", | ||
| }, | ||
| { | ||
| "dtype": "int64", | ||
| }, | ||
| # Paddle reduce not support | ||
| # { | ||
| # "dtype": "float16", | ||
| # }, | ||
| { | ||
| "dtype": "float32", | ||
| }, | ||
| { | ||
| "dtype": "float64", | ||
| }, | ||
| ] | ||
| self.attrs = [ | ||
| { | ||
| "op_type": "sum", | ||
| "keepdim": True | ||
| }, | ||
| { | ||
| "op_type": "sum", | ||
| "keepdim": False | ||
| }, | ||
| { | ||
| "op_type": "prod", | ||
| "keepdim": True | ||
| }, | ||
| { | ||
| "op_type": "prod", | ||
| "keepdim": False | ||
| }, | ||
| { | ||
| "op_type": "max", | ||
| "keepdim": True | ||
| }, | ||
| { | ||
| "op_type": "max", | ||
| "keepdim": False | ||
| }, | ||
| { | ||
| "op_type": "min", | ||
| "keepdim": True | ||
| }, | ||
| { | ||
| "op_type": "min", | ||
| "keepdim": False | ||
| }, | ||
| ] | ||
|
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|
|
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| if __name__ == "__main__": | ||
| TestReduceAll().run() |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,87 @@ | ||
| # 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. | ||
|
|
||
| from test_reduce_op_new import TestReduceAll | ||
|
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|
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| class TestReduceForBool(TestReduceAll): | ||
| def init_attrs(self): | ||
| super().init_attrs() | ||
| self.dtypes = [{"dtype": "bool"}] | ||
| self.attrs = [ | ||
| { | ||
| "op_type": "all", | ||
| "keepdim": True | ||
| }, | ||
| { | ||
| "op_type": "all", | ||
| "keepdim": False | ||
| }, | ||
| { | ||
| "op_type": "any", | ||
| "keepdim": True | ||
| }, | ||
| { | ||
| "op_type": "any", | ||
| "keepdim": False | ||
| }, | ||
| ] | ||
|
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|
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| class TestReduceAxis(TestReduceAll): | ||
| def init_attrs(self): | ||
| super().init_attrs() | ||
| self.inputs = [ | ||
| { | ||
| "shape": [1, 512, 1], | ||
| "axis": [1], | ||
| }, | ||
| { | ||
| "shape": [1, 1024, 1], | ||
| "axis": [1], | ||
| }, | ||
| { | ||
| "shape": [1, 2048, 1], | ||
| "axis": [1], | ||
| }, | ||
| { | ||
| "shape": [64, 32, 16, 8, 4], | ||
| "axis": [0, 2], | ||
| }, | ||
| { | ||
| "shape": [64, 32, 16, 8, 4], | ||
| "axis": [1, 2, 3], | ||
| }, | ||
| { | ||
| # No axis, all reduce | ||
| "shape": [64, 32, 16, 8, 4], | ||
| "axis": [], | ||
| }, | ||
| ] | ||
| self.dtypes = [{"dtype": "float32"}] | ||
| self.attrs = [ | ||
| { | ||
| "op_type": "sum", | ||
| "keepdim": True, | ||
| }, | ||
| { | ||
| "op_type": "sum", | ||
| "keepdim": False, | ||
| }, | ||
| ] | ||
|
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|
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| if __name__ == "__main__": | ||
| TestReduceForBool().run() | ||
| TestReduceAxis().run() |