【2.0 API】Add conv1d_transpose API (#26356)

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