【2.0 API】Add conv1d_transpose API (#26356)

Author: wanghaoshuang

python/paddle/fluid/tests/unittests/test_conv1d_transpose_layer.py

@@ -0,0 +1,229 @@
+# Copyright (c) 2020 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 numpy as np
+import paddle
+from paddle import fluid, nn
+import paddle.fluid.dygraph as dg
+import paddle.nn.functional as F
+import paddle.fluid.initializer as I
+import unittest
+
+
+class ConvTranspose1dTestCase(unittest.TestCase):
+ def __init__(self,
+ methodName='runTest',
+ batch_size=4,
+ spartial_shape=16,
+ in_channels=6,
+ out_channels=8,
+ filter_size=3,
+ output_size=None,
+ padding=0,
+ output_padding=0,
+ stride=1,
+ dilation=1,
+ groups=1,
+ no_bias=False,
+ data_format="NCL",
+ dtype="float32"):
+ super(ConvTranspose1dTestCase, self).__init__(methodName)
+ self.batch_size = batch_size
+ self.in_channels = in_channels
+ self.out_channels = out_channels
+ self.spartial_shape = spartial_shape
+ self.filter_size = filter_size
+ self.output_size = output_size
+
+ self.padding = padding
+ self.output_padding = output_padding
+ self.stride = stride
+ self.dilation = dilation
+ self.groups = groups
+ self.no_bias = no_bias
+ self.data_format = data_format
+ self.dtype = dtype
+
+ def setUp(self):
+
+ self.channel_last = False if self.data_format == "NCL" else True
+ input_shape = (self.batch_size, self.in_channels,
+ self.spartial_shape) if not self.channel_last else (
+ self.batch_size,
+ self.spartial_shape,
+ self.in_channels, )
+ self.input = np.random.randn(*input_shape).astype(self.dtype)
+
+ if isinstance(self.filter_size, int):
+ filter_size = [self.filter_size]
+ else:
+ filter_size = self.filter_size
+ self.weight_shape = weight_shape = (self.in_channels, self.out_channels
+ // self.groups) + tuple(filter_size)
+ self.weight = np.random.uniform(
+ -1, 1, size=weight_shape).astype(self.dtype)
+ if not self.no_bias:
+ self.bias = np.random.uniform(
+ -1, 1, size=(self.out_channels, )).astype(self.dtype)
+ else:
+ self.bias = None
+
+ def functional(self, place):
+ main = fluid.Program()
+ start = fluid.Program()
+ with fluid.unique_name.guard():
+ with fluid.program_guard(main, start):
+ input_shape = (-1, self.in_channels,
+ -1) if not self.channel_last else (
+ -1, -1, self.in_channels)
+ x_var = fluid.data("input", input_shape, dtype=self.dtype)
+ w_var = fluid.data(
+ "weight", self.weight_shape, dtype=self.dtype)
+ b_var = fluid.data(
+ "bias", (self.out_channels, ), dtype=self.dtype)
+ y_var = F.conv_transpose1d(
+ x_var,
+ w_var,
+ None if self.no_bias else b_var,
+ output_size=self.output_size,
+ padding=self.padding,
+ output_padding=self.output_padding,
+ stride=self.stride,
+ dilation=self.dilation,
+ groups=self.groups,
+ data_format=self.data_format)
+ feed_dict = {"input": self.input, "weight": self.weight}
+ if self.bias is not None:
+ feed_dict["bias"] = self.bias
+ exe = fluid.Executor(place)
+ exe.run(start)
+ y_np, = exe.run(main, feed=feed_dict, fetch_list=[y_var])
+ return y_np
+
+ def paddle_nn_layer(self):
+ x_var = paddle.to_tensor(self.input)
+ conv = nn.ConvTranspose1d(
+ self.in_channels,
+ self.out_channels,
+ self.filter_size,
+ padding=self.padding,
+ output_padding=self.output_padding,
+ stride=self.stride,
+ dilation=self.dilation,
+ groups=self.groups,
+ data_format=self.data_format)
+ conv.weight.set_value(self.weight)
+ if not self.no_bias:
+ conv.bias.set_value(self.bias)
+ y_var = conv(x_var, output_size=self.output_size)
+ y_np = y_var.numpy()
+ return y_np
+
+ def _test_equivalence(self, place):
+ result1 = self.functional(place)
+ with dg.guard(place):
+ result2 = self.paddle_nn_layer()
+ np.testing.assert_array_almost_equal(result1, result2)
+
+ def runTest(self):
+ place = fluid.CPUPlace()
+ self._test_equivalence(place)
+
+ if fluid.core.is_compiled_with_cuda():
+ place = fluid.CUDAPlace(0)
+ self._test_equivalence(place)
+
+
+class ConvTranspose1dErrorTestCase(ConvTranspose1dTestCase):
+ def runTest(self):
+ place = fluid.CPUPlace()
+ with dg.guard(place):
+ with self.assertRaises(ValueError):
+ self.paddle_nn_layer()
+
+
+def add_cases(suite):
+ suite.addTest(ConvTranspose1dTestCase(methodName='runTest'))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest', stride=[2], no_bias=True, dilation=2))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest',
+ filter_size=(3),
+ output_size=[36],
+ stride=[2],
+ dilation=2))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest', stride=2, dilation=(2)))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest', padding="valid"))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest', padding='valid'))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest', filter_size=1, padding=3))
+ suite.addTest(ConvTranspose1dTestCase(methodName='runTest', padding=[2]))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest', data_format="NLC"))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest', groups=2, padding="valid"))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest',
+ out_channels=6,
+ in_channels=3,
+ groups=3,
+ padding="valid"))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest',
+ data_format="NLC",
+ spartial_shape=16,
+ output_size=18))
+ suite.addTest(
+ ConvTranspose1dTestCase(
+ methodName='runTest', data_format="NLC", stride=3,
+ output_padding=2))
+
+
+def add_error_cases(suite):
+ suite.addTest(
+ ConvTranspose1dErrorTestCase(
+ methodName='runTest', data_format="not_valid"))
+ suite.addTest(
+ ConvTranspose1dErrorTestCase(
+ methodName='runTest', in_channels=5, groups=2))
+ suite.addTest(
+ ConvTranspose1dErrorTestCase(
+ methodName='runTest', stride=2, output_padding=3))
+ suite.addTest(
+ ConvTranspose1dErrorTestCase(
+ methodName='runTest', output_size="not_valid"))
+
+
+def load_tests(loader, standard_tests, pattern):
+ suite = unittest.TestSuite()
+ add_cases(suite)
+ add_error_cases(suite)
+ return suite
+
+
+if __name__ == '__main__':
+ unittest.main()

python/paddle/nn/__init__.py

@@ -97,6 +97,7 @@
 from .layer.conv import Conv1d #DEFINE_ALIAS
 from .layer.conv import Conv2d #DEFINE_ALIAS
 from .layer.conv import Conv3d #DEFINE_ALIAS
+from .layer.conv import ConvTranspose1d #DEFINE_ALIAS
 from .layer.conv import ConvTranspose2d #DEFINE_ALIAS
 from .layer.conv import ConvTranspose3d #DEFINE_ALIAS
 # from .layer.conv import TreeConv #DEFINE_ALIAS

python/paddle/nn/functional/__init__.py

@@ -71,6 +71,7 @@
 from .common import assign #DEFINE_ALIAS
 from .common import interpolate #DEFINE_ALIAS
 from .conv import conv1d #DEFINE_ALIAS
+from .conv import conv_transpose1d #DEFINE_ALIAS
 from .conv import conv2d #DEFINE_ALIAS
 from .conv import conv_transpose2d #DEFINE_ALIAS
 from .conv import conv3d #DEFINE_ALIAS