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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_data_feed()
- self.set_feed_attr()
- self.set_op_attrs()
-
- def set_data_feed(self):
- data = np.random.uniform(size=[3, 4, 5, 6])
- self.feed_fp32 = {"in_0": data.astype(np.float32)}
- self.feed_fp16 = {"in_0": data.astype(np.float16)}
-
- def set_feed_attr(self):
- self.feed_shape = [x.shape for x in self.feed_fp32.values()]
- self.feed_list = list(self.feed_fp32.keys())
- self.feed_dtype = [x.dtype for x in self.feed_fp32.values()]
-
- def set_op_attrs(self):
- self.attrs = {
- "axes": [1, 2, 3],
- "starts": [-3, 0, 2],
- "ends": [3, 2, 4],
- "strides": [1, 1, 1],
- }
-
- @IPUOpTest.static_graph
- def build_model(self):
- x = paddle.static.data(
- name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
- )
- out = paddle.strided_slice(x, **self.attrs)
- self.fetch_list = [out.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_data_feed(self):
- data = np.random.uniform(size=[2, 4])
- self.feed_fp32 = {"in_0": data.astype(np.float32)}
- self.feed_fp16 = {"in_0": data.astype(np.float16)}
-
- def set_op_attrs(self):
- self.attrs = {
- "axes": [0, 1],
- "starts": [1, 3],
- "ends": [2, 0],
- "strides": [1, -1],
- }
-
-
- @unittest.skip('Only strides of 1 or -1 are supported.')
- class TestCase2(TestBase):
- def set_data_feed(self):
- data = np.random.uniform(size=[2, 4])
- self.feed_fp32 = {"in_0": data.astype(np.float32)}
- self.feed_fp16 = {"in_0": data.astype(np.float16)}
-
- def set_op_attrs(self):
- self.attrs = {
- "axes": [0, 1],
- "starts": [1, 3],
- "ends": [-1, 1000],
- "strides": [1, 3],
- }
-
-
- @unittest.skip('dynamic graph is not support on IPU')
- class TestCase3(TestBase):
- def set_data_feed(self):
- x = np.random.uniform(size=[4, 5, 6])
- s = np.array([0, 0, 2])
- e = np.array([3, 2, 4])
- self.feed_fp32 = {
- "x": x.astype(np.float32),
- "starts": s.astype(np.int32),
- "ends": e.astype(np.int32),
- }
- self.feed_fp16 = {
- "x": x.astype(np.float16),
- "starts": s.astype(np.int32),
- "ends": e.astype(np.int32),
- }
-
- def set_op_attrs(self):
- self.attrs = {"strides": [1, 1, 1], "axes": [0, 1, 2]}
-
- @IPUOpTest.static_graph
- def build_model(self):
- x = paddle.static.data(
- name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
- )
- starts = paddle.static.data(
- name=self.feed_list[1], shape=self.feed_shape[1], dtype='int32'
- )
- ends = paddle.static.data(
- name=self.feed_list[2], shape=self.feed_shape[2], dtype='int32'
- )
- out = paddle.strided_slice(x, starts=starts, ends=ends, **self.attrs)
- self.fetch_list = [out.name]
-
-
- if __name__ == "__main__":
- unittest.main()
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