From 50fb57c9b33f51a29a28c58591fe1d6bf754eef7 Mon Sep 17 00:00:00 2001 From: joeqiao12 <45232181+joeqiao12@users.noreply.github.com> Date: Fri, 18 Feb 2022 09:56:34 +0800 Subject: [PATCH] add flatten op pytest (#39534) --- .../unittests/mlu/test_flatten2_op_mlu.py | 113 ++++++ .../test_flatten_contigous_range_op_mlu.py | 331 ++++++++++++++++++ .../unittests/mlu/test_flatten_op_mlu.py | 77 ++++ 3 files changed, 521 insertions(+) create mode 100644 python/paddle/fluid/tests/unittests/mlu/test_flatten2_op_mlu.py create mode 100755 python/paddle/fluid/tests/unittests/mlu/test_flatten_contigous_range_op_mlu.py create mode 100644 python/paddle/fluid/tests/unittests/mlu/test_flatten_op_mlu.py diff --git a/python/paddle/fluid/tests/unittests/mlu/test_flatten2_op_mlu.py b/python/paddle/fluid/tests/unittests/mlu/test_flatten2_op_mlu.py new file mode 100644 index 00000000000..b5f79a92b19 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/mlu/test_flatten2_op_mlu.py @@ -0,0 +1,113 @@ +# 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. + +from __future__ import print_function + +import unittest +import numpy as np +import paddle.fluid as fluid +import paddle +import sys +sys.path.append("..") +from op_test import OpTest +paddle.enable_static() + + +class TestFlattenOp(OpTest): + def setUp(self): + self.place = paddle.device.MLUPlace(0) + self.__class__.use_mlu = True + self.op_type = "flatten2" + self.init_test_case() + self.inputs = {"X": np.random.random(self.in_shape).astype("float64")} + self.init_attrs() + self.outputs = { + "Out": self.inputs["X"].reshape(self.new_shape), + "XShape": np.random.random(self.in_shape).astype("float32") + } + + def test_check_output(self): + self.check_output_with_place(self.place, no_check_set=["XShape"]) + + def test_check_grad(self): + self.check_grad_with_place(self.place, ["X"], "Out") + + def init_test_case(self): + self.in_shape = (3, 2, 4, 5) + self.axis = 1 + self.new_shape = (3, 40) + + def init_attrs(self): + self.attrs = {"axis": self.axis} + + +class TestFlattenOp1(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.axis = 0 + self.new_shape = (1, 120) + + +class TestFlattenOpWithDefaultAxis(TestFlattenOp): + def init_test_case(self): + self.in_shape = (10, 2, 2, 3) + self.new_shape = (10, 12) + + def init_attrs(self): + self.attrs = {} + + +class TestFlattenOpSixDims(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 3, 2, 4, 4) + self.axis = 4 + self.new_shape = (36, 16) + + +class TestStaticFlattenInferShapePythonAPI(unittest.TestCase): + def execute_api(self, x, axis=1): + return fluid.layers.flatten(x, axis=axis) + + def test_static_api(self): + paddle.enable_static() + main_prog = paddle.static.Program() + with paddle.static.program_guard(main_prog, paddle.static.Program()): + x = paddle.static.data( + name="x", shape=[-1, 3, -1, -1], dtype='float32') + out = self.execute_api(x, axis=2) + self.assertTrue((-1, -1) == out.shape) + + +class TestFlatten2OpError(unittest.TestCase): + def test_errors(self): + with fluid.program_guard(fluid.Program(), fluid.Program()): + input_data = np.random.random((3, 2, 4, 5)).astype("float64") + + def test_Variable(): + # the input type must be Variable + fluid.layers.flatten(input_data, axis=1) + + self.assertRaises(TypeError, test_Variable) + + def test_type(): + # dtype must be float32, float64, int8, int32, int64, uint8. + x2 = fluid.layers.data( + name='x2', shape=[3, 2, 4, 5], dtype='float16') + fluid.layers.flatten(x2, axis=1) + + self.assertRaises(TypeError, test_type) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/mlu/test_flatten_contigous_range_op_mlu.py b/python/paddle/fluid/tests/unittests/mlu/test_flatten_contigous_range_op_mlu.py new file mode 100755 index 00000000000..8b14494ea09 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/mlu/test_flatten_contigous_range_op_mlu.py @@ -0,0 +1,331 @@ +# 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. + +from __future__ import print_function + +import numpy as np +import unittest +import sys +sys.path.append("..") +from op_test import OpTest +import paddle +import paddle.fluid as fluid + +paddle.enable_static() + + +class TestFlattenOp(OpTest): + def setUp(self): + self.set_mlu() + self.op_type = "flatten_contiguous_range" + self.place = paddle.MLUPlace(0) + + self.start_axis = 0 + self.stop_axis = -1 + self.dtype = np.float64 + self.init_test_case() + self.inputs = {"X": np.random.random(self.in_shape).astype(self.dtype)} + self.init_attrs() + self.outputs = { + "Out": self.inputs["X"].reshape(self.new_shape), + "XShape": np.random.random(self.in_shape).astype("float32") + } + + def set_mlu(self): + self.__class__.use_mlu = True + + def test_check_output(self): + self.check_output_with_place(self.place, no_check_set=["XShape"]) + + def test_check_grad(self): + #pass + self.check_grad_with_place(self.place, ["X"], "Out") + + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 0 + self.stop_axis = -1 + self.new_shape = (120) + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + +class TestFlattenOp_1(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 1 + self.stop_axis = 2 + self.new_shape = (3, 10, 4) + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + +class TestFlattenOp_2(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 0 + self.stop_axis = 1 + self.new_shape = (6, 5, 4) + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + +class TestFlattenOp_3(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 0 + self.stop_axis = 2 + self.new_shape = (30, 4) + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + +class TestFlattenOp_4(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = -2 + self.stop_axis = -1 + self.new_shape = (3, 2, 20) + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + +class TestFlattenOp_5(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 2 + self.stop_axis = 2 + self.new_shape = (3, 2, 5, 4) + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + +class TestFlattenOpSixDims(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 3, 2, 4, 4) + self.start_axis = 3 + self.stop_axis = 5 + self.new_shape = (3, 2, 3, 32) + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + +class TestFlattenOp_Float32(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 0 + self.stop_axis = 1 + self.new_shape = (6, 5, 4) + self.dtype = np.float32 + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + +class TestFlattenOp_int32(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 0 + self.stop_axis = 1 + self.new_shape = (6, 5, 4) + self.dtype = np.int32 + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + def test_check_grad(self): + pass + + +class TestFlattenOp_uint8(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 0 + self.stop_axis = 1 + self.new_shape = (6, 5, 4) + self.dtype = np.uint8 + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + def test_check_grad(self): + pass + + +class TestFlattenOp_int8(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 0 + self.stop_axis = 1 + self.new_shape = (6, 5, 4) + self.dtype = np.int8 + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + def test_check_grad(self): + pass + + +class TestFlattenOp_int64(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 5, 4) + self.start_axis = 0 + self.stop_axis = 1 + self.new_shape = (6, 5, 4) + self.dtype = np.int64 + + def init_attrs(self): + self.attrs = { + "start_axis": self.start_axis, + "stop_axis": self.stop_axis + } + + def test_check_grad(self): + pass + + +class TestFlatten2OpError(unittest.TestCase): + def test_errors(self): + image_shape = (2, 3, 4, 4) + x = np.arange(image_shape[0] * image_shape[1] * image_shape[2] * + image_shape[3]).reshape(image_shape) / 100. + x = x.astype('float32') + + def test_ValueError1(): + x_var = paddle.static.data( + name="x", shape=image_shape, dtype='float32') + out = paddle.flatten(x_var, start_axis=2, stop_axis=1) + + self.assertRaises(ValueError, test_ValueError1) + + def test_ValueError2(): + x_var = paddle.static.data( + name="x", shape=image_shape, dtype='float32') + paddle.flatten(x_var, start_axis=10, stop_axis=1) + + self.assertRaises(ValueError, test_ValueError2) + + def test_ValueError3(): + x_var = paddle.static.data( + name="x", shape=image_shape, dtype='float32') + paddle.flatten(x_var, start_axis=2, stop_axis=10) + + self.assertRaises(ValueError, test_ValueError3) + + def test_type(): + # dtype must be float32, float64, int8, int32, int64, uint8. + x2 = np.arange(image_shape[0] * image_shape[1] * image_shape[2] * + image_shape[3]).reshape(image_shape) / 100. + x2 = x2.astype('float16') + x2_var = paddle.fluid.data( + name='x2', shape=[3, 2, 4, 5], dtype='float16') + paddle.flatten(x2_var) + + self.assertRaises(TypeError, test_type) + + def test_InputError(): + out = paddle.flatten(x) + + self.assertRaises(ValueError, test_InputError) + + +class TestStaticFlattenPythonAPI(unittest.TestCase): + def execute_api(self, x, start_axis=0, stop_axis=-1): + return paddle.flatten(x, start_axis, stop_axis) + + def test_static_api(self): + paddle.enable_static() + np_x = np.random.rand(2, 3, 4, 4).astype('float32') + + main_prog = paddle.static.Program() + with paddle.static.program_guard(main_prog, paddle.static.Program()): + x = paddle.static.data( + name="x", shape=[2, 3, 4, 4], dtype='float32') + out = self.execute_api(x, start_axis=-2, stop_axis=-1) + + exe = paddle.static.Executor(place=paddle.MLUPlace(0)) + fetch_out = exe.run(main_prog, feed={"x": np_x}, fetch_list=[out]) + self.assertTrue((2, 3, 16) == fetch_out[0].shape) + + +class TestStaticInplaceFlattenPythonAPI(TestStaticFlattenPythonAPI): + def execute_api(self, x, start_axis=0, stop_axis=-1): + return x.flatten_(start_axis, stop_axis) + + +class TestFlattenPython(unittest.TestCase): + def test_python_api(self): + image_shape = (2, 3, 4, 4) + x = np.arange(image_shape[0] * image_shape[1] * image_shape[2] * + image_shape[3]).reshape(image_shape) / 100. + x = x.astype('float32') + + def test_InputError(): + out = paddle.flatten(x) + + self.assertRaises(ValueError, test_InputError) + + def test_Negative(): + paddle.disable_static(paddle.MLUPlace(0)) + img = paddle.to_tensor(x) + out = paddle.flatten(img, start_axis=-2, stop_axis=-1) + return out.numpy().shape + + res_shape = test_Negative() + self.assertTrue((2, 3, 16) == res_shape) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/mlu/test_flatten_op_mlu.py b/python/paddle/fluid/tests/unittests/mlu/test_flatten_op_mlu.py new file mode 100644 index 00000000000..a5503de7cca --- /dev/null +++ b/python/paddle/fluid/tests/unittests/mlu/test_flatten_op_mlu.py @@ -0,0 +1,77 @@ +# 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. + +from __future__ import print_function + +import unittest +import numpy as np +import sys +sys.path.append("..") +from op_test import OpTest + +import paddle +import paddle.fluid as fluid +paddle.enable_static() + + +class TestFlattenOp(OpTest): + def setUp(self): + self.place = paddle.device.MLUPlace(0) + self.__class__.use_mlu = True + self.op_type = "flatten" + self.init_test_case() + self.inputs = {"X": np.random.random(self.in_shape).astype("float64")} + self.init_attrs() + self.outputs = {"Out": self.inputs["X"].reshape(self.new_shape)} + + def test_check_output(self): + self.check_output_with_place(self.place) + + def test_check_grad(self): + self.check_grad_with_place(self.place, ["X"], "Out") + + def init_test_case(self): + self.in_shape = (3, 2, 2, 10) + self.axis = 1 + self.new_shape = (3, 40) + + def init_attrs(self): + self.attrs = {"axis": self.axis} + + +class TestFlattenOp1(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 2, 10) + self.axis = 0 + self.new_shape = (1, 120) + + +class TestFlattenOpWithDefaultAxis(TestFlattenOp): + def init_test_case(self): + self.in_shape = (10, 2, 2, 3) + self.new_shape = (10, 12) + + def init_attrs(self): + self.attrs = {} + + +class TestFlattenOpSixDims(TestFlattenOp): + def init_test_case(self): + self.in_shape = (3, 2, 3, 2, 4, 4) + self.axis = 4 + self.new_shape = (36, 16) + + +if __name__ == "__main__": + unittest.main() -- GitLab