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- # Copyright (c) 2022 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 op_test_ipu import IPUOpTest
-
- import paddle
- import paddle.static
-
-
- class TestBase(IPUOpTest):
- def setUp(self):
- self.set_atol()
- self.set_training()
- self.set_feed()
- self.set_op_attrs()
-
- def set_atol(self):
- self.atol = 1e-6
- self.rtol = 1e-6
- self.atol_fp16 = 1e-3
- self.rtol_fp16 = 1e-3
-
- def set_feed(self):
- data = np.random.uniform(size=[1, 3, 8, 8])
- self.feed_fp32 = {'in_0': data.astype(np.float32)}
- self.feed_fp16 = {'in_0': data.astype(np.float16)}
- self.feed_shape = [x.shape for x in self.feed_fp32.values()]
- self.feed_list = list(self.feed_fp32.keys())
-
- def set_op_attrs(self):
- self.attrs = {}
- self.attrs['num_filters'] = 3
- self.attrs['filter_size'] = 3
- self.attrs['padding'] = 0
- self.attrs['stride'] = 1
- self.attrs['dilation'] = 1
- self.attrs['bias_attr'] = False
-
- @IPUOpTest.static_graph
- def build_model(self):
- x = paddle.static.data(
- name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
- )
- x = paddle.static.nn.conv2d_transpose(x, **self.attrs)
- self.fetch_list = [x.name]
-
- def run_model(self, exec_mode):
- self.run_op_test(exec_mode)
-
- def test(self):
- for m in IPUOpTest.ExecutionMode:
- if not self.skip_mode(m):
- self.build_model()
- self.run_model(m)
- self.check()
-
-
- class TestCase1(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['stride'] = 2
-
-
- @unittest.skip("Only support dilation=1")
- class TestCase2(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['stride'] = 2
- self.attrs['dilation'] = 2
-
-
- class TestCase3(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['padding'] = 2
-
-
- class TestCase4(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['padding'] = "SAME"
-
-
- class TestCase5(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['stride'] = 2
- self.attrs['padding'] = "SAME"
-
-
- class TestCase6(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['padding'] = "VALID"
-
-
- class TestCase7(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['padding'] = "VALID"
- self.attrs['stride'] = 2
-
-
- class TestCase8(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['filter_size'] = 4
- self.attrs['stride'] = 2
-
-
- class TestCase9(TestBase):
- # When bias_attr is not False, a Add Op will be added after conv2d_transpose Op.
- # When bias_attr = None, the bias value is 0.
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['bias_attr'] = None
-
-
- class TestCase10(TestBase):
- # When output_size is not None, the filter_size will be re-computed by output_size
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['filter_size'] = None
- self.attrs['output_size'] = [12, 12]
-
-
- class TestCase11(TestBase):
- def set_op_attrs(self):
- super().set_op_attrs()
- self.attrs['groups'] = 3
-
-
- # depthwise_conv2d_transpose Op
- class TestCase12(TestBase):
- def set_feed(self):
- data = np.random.uniform(size=[1, 3, 10, 10])
- weight = np.random.uniform(size=[3, 1, 3, 3])
- self.feed_fp32 = {
- 'in_0': data.astype(np.float32),
- 'in_1': weight.astype(np.float32),
- }
- self.feed_fp16 = {
- 'in_0': data.astype(np.float16),
- 'in_1': weight.astype(np.float16),
- }
- self.feed_shape = [x.shape for x in self.feed_fp32.values()]
- self.feed_list = list(self.feed_fp32.keys())
-
- def set_op_attrs(self):
- self.attrs = {}
- self.attrs['groups'] = 3
-
- @IPUOpTest.static_graph
- def build_model(self):
- x = paddle.static.data(
- name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
- )
- weight = paddle.static.data(
- name=self.feed_list[1], shape=self.feed_shape[1], dtype='float32'
- )
- x = paddle.nn.functional.conv2d_transpose(x, weight, **self.attrs)
- self.fetch_list = [x.name]
-
-
- if __name__ == "__main__":
- unittest.main()
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