Support slice write in dygraph_to_static. test=develop (#23055)
liym27
5 years ago
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5a202af90b
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import numpy as np
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import paddle.fluid as fluid
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from paddle.fluid.dygraph.jit import dygraph_to_static_graph
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SEED = 2020
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np.random.seed(SEED)
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def test_slice_without_control_flow(x):
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# Python slice will not be transformed.
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x = fluid.dygraph.to_variable(x)
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a = [x]
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a[0] = fluid.layers.fill_constant(shape=[2], value=2, dtype="float32")
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return a
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def test_slice_in_if(x):
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x = fluid.dygraph.to_variable(x)
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a = []
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if x.numpy()[0] > 0:
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a.append(x)
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else:
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a.append(
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fluid.layers.fill_constant(
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shape=[1, 2], value=9, dtype="int64"))
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if x.numpy()[0] > 0:
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a[0] = x
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return a
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def test_slice_in_while_loop(x, iter_num):
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x = fluid.dygraph.to_variable(x)
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iter_num = fluid.layers.fill_constant(
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shape=[1], value=iter_num, dtype="int32")
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a = []
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i = 0
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# Note: `i < iter_num` can't be supported in dygraph mode now,
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# but PR22892 is fixing it https://github.com/PaddlePaddle/Paddle/pull/22892.
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# If PR22892 merged, change `i < iter_num.numpy()[0]` to `i < iter_num`.
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while i < iter_num.numpy()[0]:
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a.append(x)
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i += 1
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i = 0
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while i < iter_num.numpy()[0]:
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a[i] = fluid.layers.fill_constant(shape=[2], value=2, dtype="float32")
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i += 1
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return a
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def test_slice_in_for_loop(x, iter_num):
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x = fluid.dygraph.to_variable(x)
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a = []
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for i in range(iter_num):
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a.append(x)
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for i in range(iter_num):
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a[i] = x
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return a
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class TestSliceWithoutControlFlow(unittest.TestCase):
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def setUp(self):
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self.input = np.random.random((3)).astype('int32')
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self.place = fluid.CUDAPlace(0) if fluid.is_compiled_with_cuda(
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) else fluid.CPUPlace()
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self.init_dygraph_func()
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def init_dygraph_func(self):
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self.dygraph_func = test_slice_without_control_flow
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def run_dygraph_mode(self):
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with fluid.dygraph.guard():
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res = self.dygraph_func(self.input)
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if isinstance(res, (list, tuple)):
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res = res[0]
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return res.numpy()
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def run_static_mode(self):
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main_program = fluid.Program()
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with fluid.program_guard(main_program):
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tensor_list = dygraph_to_static_graph(self.dygraph_func)(self.input)
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exe = fluid.Executor(self.place)
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static_res = exe.run(main_program, fetch_list=tensor_list[0])
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return static_res[0]
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def test_transformed_static_result(self):
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static_res = self.run_static_mode()
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dygraph_res = self.run_dygraph_mode()
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self.assertTrue(
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np.allclose(dygraph_res, static_res),
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msg='dygraph res is {}\nstatic_res is {}'.format(dygraph_res,
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static_res))
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class TestSliceInIf(TestSliceWithoutControlFlow):
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def init_dygraph_func(self):
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self.dygraph_func = test_slice_in_if
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def run_static_mode(self):
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main_program = fluid.Program()
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with fluid.program_guard(main_program):
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tensor_array = dygraph_to_static_graph(self.dygraph_func)(
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self.input)
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static_out = fluid.layers.array_read(
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tensor_array,
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i=fluid.layers.fill_constant(
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shape=[1], value=0, dtype='int64'))
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exe = fluid.Executor(self.place)
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numpy_res = exe.run(main_program, fetch_list=static_out)
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return numpy_res[0]
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class TestSliceInWhileLoop(TestSliceWithoutControlFlow):
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def setUp(self):
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self.iter_num = 3
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self.input = np.random.random((3)).astype('int32')
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self.place = fluid.CUDAPlace(0) if fluid.is_compiled_with_cuda(
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) else fluid.CPUPlace()
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self.init_dygraph_func()
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def init_dygraph_func(self):
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self.dygraph_func = test_slice_in_while_loop
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def run_dygraph_mode(self):
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with fluid.dygraph.guard():
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var_res = self.dygraph_func(self.input, self.iter_num)
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numpy_res = [ele.numpy() for ele in var_res]
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return numpy_res
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def run_static_mode(self):
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main_program = fluid.Program()
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with fluid.program_guard(main_program):
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tensor_array = dygraph_to_static_graph(self.dygraph_func)(
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self.input, self.iter_num)
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static_outs = []
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for i in range(self.iter_num):
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static_outs.append(
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fluid.layers.array_read(
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tensor_array,
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i=fluid.layers.fill_constant(
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shape=[1], value=i, dtype='int64')))
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exe = fluid.Executor(self.place)
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numpy_res = exe.run(main_program, fetch_list=static_outs)
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return numpy_res
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class TestSliceInForLoop(TestSliceInWhileLoop):
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def init_dygraph_func(self):
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self.dygraph_func = test_slice_in_for_loop
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if __name__ == '__main__':
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unittest.main()
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