wehub-resource-sync
608 lines
19 KiB
Python
608 lines
19 KiB
Python
# 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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import paddle
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paddle.set_default_dtype("float64")
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paddle.enable_static()
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import sys
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import unittest
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import numpy as np
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from convert import convert_params_for_net_static
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sys.path.append("../../rnn")
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from rnn_numpy import GRU, LSTM, SimpleRNN
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bidirectional_list = ["bidirectional", "bidirect"]
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class TestSimpleRNN(unittest.TestCase):
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def __init__(
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self, time_major=True, direction="forward", place="cpu", mode="RNN_TANH"
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):
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super().__init__("runTest")
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self.time_major = time_major
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self.direction = direction
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self.num_directions = 2 if direction in bidirectional_list else 1
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self.place = place
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self.mode = mode
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def test_with_initial_state(self):
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place = paddle.set_device(self.place)
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rnn1 = SimpleRNN(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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nonlinearity=self.mode,
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)
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mp = paddle.static.Program()
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sp = paddle.static.Program()
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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rnn2 = paddle.nn.SimpleRNN(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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activation=self.mode[4:].lower(),
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)
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exe = paddle.static.Executor(place)
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scope = paddle.base.Scope()
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with paddle.static.scope_guard(scope):
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exe.run(sp)
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convert_params_for_net_static(rnn1, rnn2, place)
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x = np.random.randn(12, 4, 16)
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if not self.time_major:
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x = np.transpose(x, [1, 0, 2])
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prev_h = np.random.randn(2 * self.num_directions, 4, 32)
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y1, h1 = rnn1(x, prev_h)
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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x_data = paddle.static.data(
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"input",
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[-1, -1, 16],
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dtype=paddle.framework.get_default_dtype(),
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)
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init_h = paddle.static.data(
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"init_h",
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[2 * self.num_directions, -1, 32],
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dtype=paddle.framework.get_default_dtype(),
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)
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y, h = rnn2(x_data, init_h)
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feed_dict = {x_data.name: x, init_h.name: prev_h}
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with paddle.static.scope_guard(scope):
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y2, h2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h])
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np.testing.assert_allclose(y1, y2, atol=1e-8, rtol=1e-5)
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np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
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def test_with_zero_state(self):
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place = paddle.set_device(self.place)
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rnn1 = SimpleRNN(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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nonlinearity=self.mode,
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)
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mp = paddle.static.Program()
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sp = paddle.static.Program()
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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rnn2 = paddle.nn.SimpleRNN(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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activation=self.mode[4:].lower(),
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)
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exe = paddle.static.Executor(place)
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scope = paddle.base.Scope()
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with paddle.static.scope_guard(scope):
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exe.run(sp)
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convert_params_for_net_static(rnn1, rnn2, place)
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x = np.random.randn(12, 4, 16)
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if not self.time_major:
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x = np.transpose(x, [1, 0, 2])
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y1, h1 = rnn1(x)
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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x_data = paddle.static.data(
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"input",
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[-1, -1, 16],
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dtype=paddle.framework.get_default_dtype(),
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)
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y, h = rnn2(x_data)
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feed_dict = {x_data.name: x}
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with paddle.static.scope_guard(scope):
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y2, h2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h])
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np.testing.assert_allclose(y1, y2, atol=1e-8, rtol=1e-5)
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np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
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def runTest(self):
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self.test_with_initial_state()
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self.test_with_zero_state()
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class TestGRU(unittest.TestCase):
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def __init__(self, time_major=True, direction="forward", place="cpu"):
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super().__init__("runTest")
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self.time_major = time_major
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self.direction = direction
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self.num_directions = 2 if direction in bidirectional_list else 1
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self.place = place
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def test_with_initial_state(self):
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# Since `set_device` is global, set `set_device` in `setUp` rather than
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# `__init__` to avoid using an error device set by another test case.
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place = paddle.set_device(self.place)
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rnn1 = GRU(
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16, 32, 2, time_major=self.time_major, direction=self.direction
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)
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mp = paddle.static.Program()
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sp = paddle.static.Program()
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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rnn2 = paddle.nn.GRU(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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)
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exe = paddle.static.Executor(place)
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scope = paddle.base.Scope()
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with paddle.static.scope_guard(scope):
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exe.run(sp)
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convert_params_for_net_static(rnn1, rnn2, place)
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x = np.random.randn(12, 4, 16)
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if not self.time_major:
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x = np.transpose(x, [1, 0, 2])
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prev_h = np.random.randn(2 * self.num_directions, 4, 32)
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y1, h1 = rnn1(x, prev_h)
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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x_data = paddle.static.data(
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"input",
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[-1, -1, 16],
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dtype=paddle.framework.get_default_dtype(),
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)
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init_h = paddle.static.data(
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"init_h",
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[2 * self.num_directions, -1, 32],
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dtype=paddle.framework.get_default_dtype(),
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)
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y, h = rnn2(x_data, init_h)
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feed_dict = {x_data.name: x, init_h.name: prev_h}
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with paddle.static.scope_guard(scope):
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y2, h2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h])
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np.testing.assert_allclose(y1, y2, atol=1e-8, rtol=1e-5)
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np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
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def test_with_zero_state(self):
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# Since `set_device` is global, set `set_device` in `setUp` rather than
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# `__init__` to avoid using an error device set by another test case.
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place = paddle.set_device(self.place)
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rnn1 = GRU(
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16, 32, 2, time_major=self.time_major, direction=self.direction
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)
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mp = paddle.static.Program()
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sp = paddle.static.Program()
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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rnn2 = paddle.nn.GRU(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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)
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exe = paddle.static.Executor(place)
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scope = paddle.base.Scope()
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with paddle.static.scope_guard(scope):
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exe.run(sp)
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convert_params_for_net_static(rnn1, rnn2, place)
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x = np.random.randn(12, 4, 16)
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if not self.time_major:
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x = np.transpose(x, [1, 0, 2])
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y1, h1 = rnn1(x)
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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x_data = paddle.static.data(
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"input",
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[-1, -1, 16],
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dtype=paddle.framework.get_default_dtype(),
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)
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y, h = rnn2(x_data)
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feed_dict = {x_data.name: x}
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with paddle.static.scope_guard(scope):
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y2, h2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h])
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np.testing.assert_allclose(y1, y2, atol=1e-8, rtol=1e-5)
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np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
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def runTest(self):
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self.test_with_initial_state()
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self.test_with_zero_state()
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class TestLSTM(unittest.TestCase):
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def __init__(self, time_major=True, direction="forward", place="cpu"):
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super().__init__("runTest")
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self.time_major = time_major
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self.direction = direction
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self.num_directions = 2 if direction in bidirectional_list else 1
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self.place = place
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def test_with_initial_state(self):
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# Since `set_device` is global, set `set_device` in `setUp` rather than
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# `__init__` to avoid using an error device set by another test case.
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place = paddle.set_device(self.place)
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rnn1 = LSTM(
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16, 32, 2, time_major=self.time_major, direction=self.direction
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)
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mp = paddle.static.Program()
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sp = paddle.static.Program()
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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rnn2 = paddle.nn.LSTM(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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)
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exe = paddle.static.Executor(place)
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scope = paddle.base.Scope()
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with paddle.static.scope_guard(scope):
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exe.run(sp)
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convert_params_for_net_static(rnn1, rnn2, place)
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x = np.random.randn(12, 4, 16)
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if not self.time_major:
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x = np.transpose(x, [1, 0, 2])
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prev_h = np.random.randn(
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2 * self.num_directions, 4, getattr(self, "proj_size", 32)
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)
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prev_c = np.random.randn(2 * self.num_directions, 4, 32)
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y1, (h1, c1) = rnn1(x, (prev_h, prev_c))
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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x_data = paddle.static.data(
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"input",
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[-1, -1, 16],
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dtype=paddle.framework.get_default_dtype(),
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)
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init_h = paddle.static.data(
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"init_h",
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[
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2 * self.num_directions,
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-1,
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getattr(self, "proj_size", 32),
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],
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dtype=paddle.framework.get_default_dtype(),
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)
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init_c = paddle.static.data(
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"init_c",
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[2 * self.num_directions, -1, 32],
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dtype=paddle.framework.get_default_dtype(),
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)
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y, (h, c) = rnn2(x_data, (init_h, init_c))
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feed_dict = {x_data.name: x, init_h.name: prev_h, init_c.name: prev_c}
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with paddle.static.scope_guard(scope):
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y2, h2, c2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h, c])
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np.testing.assert_allclose(y1, y2, atol=1e-8, rtol=1e-5)
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np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
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np.testing.assert_allclose(c1, c2, atol=1e-8, rtol=1e-5)
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def test_with_zero_state(self):
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# Since `set_device` is global, set `set_device` in `setUp` rather than
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# `__init__` to avoid using an error device set by another test case.
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place = paddle.set_device(self.place)
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rnn1 = LSTM(
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16, 32, 2, time_major=self.time_major, direction=self.direction
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)
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mp = paddle.static.Program()
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sp = paddle.static.Program()
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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rnn2 = paddle.nn.LSTM(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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)
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exe = paddle.static.Executor(place)
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scope = paddle.base.Scope()
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with paddle.static.scope_guard(scope):
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exe.run(sp)
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convert_params_for_net_static(rnn1, rnn2, place)
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x = np.random.randn(12, 4, 16)
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if not self.time_major:
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x = np.transpose(x, [1, 0, 2])
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y1, (h1, c1) = rnn1(x)
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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x_data = paddle.static.data(
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"input",
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[-1, -1, 16],
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dtype=paddle.framework.get_default_dtype(),
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)
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y, (h, c) = rnn2(x_data)
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feed_dict = {x_data.name: x}
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with paddle.static.scope_guard(scope):
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y2, h2, c2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h, c])
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np.testing.assert_allclose(y1, y2, atol=1e-8, rtol=1e-5)
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np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
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np.testing.assert_allclose(c1, c2, atol=1e-8, rtol=1e-5)
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def runTest(self):
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self.test_with_initial_state()
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self.test_with_zero_state()
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class TestLSTMWithProjSize(unittest.TestCase):
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def __init__(self, time_major=True, direction="forward", place="cpu"):
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super().__init__("runTest")
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self.time_major = time_major
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self.direction = direction
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self.num_directions = 2 if direction in bidirectional_list else 1
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self.place = place
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def test_with_initial_state(self):
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# Since `set_device` is global, set `set_device` in `setUp` rather than
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# `__init__` to avoid using an error device set by another test case.
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place = paddle.set_device(self.place)
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rnn1 = LSTM(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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proj_size=8,
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)
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mp = paddle.static.Program()
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sp = paddle.static.Program()
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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rnn2 = paddle.nn.LSTM(
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16,
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32,
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2,
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time_major=self.time_major,
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direction=self.direction,
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proj_size=8,
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)
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exe = paddle.static.Executor(place)
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scope = paddle.base.Scope()
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with paddle.static.scope_guard(scope):
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exe.run(sp)
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convert_params_for_net_static(rnn1, rnn2, place)
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self.proj_size = 8
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x = np.random.randn(12, 4, 16)
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if not self.time_major:
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x = np.transpose(x, [1, 0, 2])
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prev_h = np.random.randn(
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2 * self.num_directions, 4, getattr(self, "proj_size", 32)
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)
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prev_c = np.random.randn(2 * self.num_directions, 4, 32)
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y1, (h1, c1) = rnn1(x, (prev_h, prev_c))
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with (
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paddle.base.unique_name.guard(),
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paddle.static.program_guard(mp, sp),
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):
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x_data = paddle.static.data(
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"input",
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[-1, -1, 16],
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dtype=paddle.framework.get_default_dtype(),
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)
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init_h = paddle.static.data(
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"init_h",
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[
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2 * self.num_directions,
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-1,
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getattr(self, "proj_size", 32),
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],
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dtype=paddle.framework.get_default_dtype(),
|
|
)
|
|
init_c = paddle.static.data(
|
|
"init_c",
|
|
[2 * self.num_directions, -1, 32],
|
|
dtype=paddle.framework.get_default_dtype(),
|
|
)
|
|
y, (h, c) = rnn2(x_data, (init_h, init_c))
|
|
|
|
feed_dict = {x_data.name: x, init_h.name: prev_h, init_c.name: prev_c}
|
|
with paddle.static.scope_guard(scope):
|
|
y2, h2, c2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h, c])
|
|
|
|
np.testing.assert_allclose(y1, y2, atol=1e-8, rtol=1e-5)
|
|
np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
|
|
np.testing.assert_allclose(c1, c2, atol=1e-8, rtol=1e-5)
|
|
|
|
def test_with_zero_state(self):
|
|
# Since `set_device` is global, set `set_device` in `setUp` rather than
|
|
# `__init__` to avoid using an error device set by another test case.
|
|
place = paddle.set_device(self.place)
|
|
rnn1 = LSTM(
|
|
16,
|
|
32,
|
|
2,
|
|
time_major=self.time_major,
|
|
direction=self.direction,
|
|
proj_size=8,
|
|
)
|
|
|
|
mp = paddle.static.Program()
|
|
sp = paddle.static.Program()
|
|
with (
|
|
paddle.base.unique_name.guard(),
|
|
paddle.static.program_guard(mp, sp),
|
|
):
|
|
rnn2 = paddle.nn.LSTM(
|
|
16,
|
|
32,
|
|
2,
|
|
time_major=self.time_major,
|
|
direction=self.direction,
|
|
proj_size=8,
|
|
)
|
|
|
|
exe = paddle.static.Executor(place)
|
|
scope = paddle.base.Scope()
|
|
with paddle.static.scope_guard(scope):
|
|
exe.run(sp)
|
|
convert_params_for_net_static(rnn1, rnn2, place)
|
|
self.proj_size = 8
|
|
|
|
x = np.random.randn(12, 4, 16)
|
|
if not self.time_major:
|
|
x = np.transpose(x, [1, 0, 2])
|
|
|
|
y1, (h1, c1) = rnn1(x)
|
|
|
|
with (
|
|
paddle.base.unique_name.guard(),
|
|
paddle.static.program_guard(mp, sp),
|
|
):
|
|
x_data = paddle.static.data(
|
|
"input",
|
|
[-1, -1, 16],
|
|
dtype=paddle.framework.get_default_dtype(),
|
|
)
|
|
y, (h, c) = rnn2(x_data)
|
|
|
|
feed_dict = {x_data.name: x}
|
|
|
|
with paddle.static.scope_guard(scope):
|
|
y2, h2, c2 = exe.run(mp, feed=feed_dict, fetch_list=[y, h, c])
|
|
|
|
np.testing.assert_allclose(y1, y2, atol=1e-8, rtol=1e-5)
|
|
np.testing.assert_allclose(h1, h2, atol=1e-8, rtol=1e-5)
|
|
np.testing.assert_allclose(c1, c2, atol=1e-8, rtol=1e-5)
|
|
|
|
def runTest(self):
|
|
self.test_with_initial_state()
|
|
self.test_with_zero_state()
|
|
|
|
|
|
def load_tests(loader, tests, pattern):
|
|
suite = unittest.TestSuite()
|
|
devices = ["cpu", "gpu"] if paddle.base.is_compiled_with_cuda() else ["cpu"]
|
|
for direction in ["forward", "bidirectional", "bidirect"]:
|
|
for time_major in [True, False]:
|
|
for device in devices:
|
|
for test_class in [
|
|
TestSimpleRNN,
|
|
TestLSTM,
|
|
TestGRU,
|
|
TestLSTMWithProjSize,
|
|
]:
|
|
suite.addTest(test_class(time_major, direction, device))
|
|
if test_class == TestSimpleRNN:
|
|
suite.addTest(
|
|
test_class(
|
|
time_major, direction, device, mode="RNN_RELU"
|
|
)
|
|
)
|
|
return suite
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|