From 7c4b9b577ae5358a28e64c033585ce9d8c2482d1 Mon Sep 17 00:00:00 2001 From: minqiyang Date: Thu, 4 Apr 2019 11:11:26 +0800 Subject: [PATCH] Polish code test=develop --- .../fluid/tests/unittests/test_layers.py | 73 ++++++++----------- 1 file changed, 30 insertions(+), 43 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index 850f4df0a..98b39256a 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -882,6 +882,9 @@ class TestBook(LayerTest): for method in methods: if not method.__name__.startswith('make_'): continue + self._low_data_bound = 0 + self._high_data_bound = 2 + self._batch_size = 2 self._feed_dict = {} self._force_to_use_cpu = False with self.static_graph(): @@ -909,15 +912,17 @@ class TestBook(LayerTest): def _get_np_data(self, shape, dtype, append_batch_size=True): np.random.seed(self.seed) if append_batch_size: - shape = [2] + shape + shape = [self._batch_size] + shape if dtype == 'float32': return np.random.random(shape).astype(dtype) elif dtype == 'float64': return np.random.random(shape).astype(dtype) elif dtype == 'int32': - return np.random.randint(0, 2, shape).astype(dtype) + return np.random.randint(self._low_data_bound, + self._high_data_bound, shape).astype(dtype) elif dtype == 'int64': - return np.random.randint(0, 2, shape).astype(dtype) + return np.random.randint(self._low_data_bound, + self._high_data_bound, shape).astype(dtype) def _get_data(self, name, @@ -1313,12 +1318,10 @@ class TestBook(LayerTest): return (output) def make_mean_iou(self): - # TODO(minqiyang): support gpu ut - self._force_to_use_cpu = True with fluid.framework._dygraph_place_guard(place=fluid.CPUPlace()): x = self._get_data(name='x', shape=[16], dtype='int32') - y = self._get_data(name='label', shape=[1], dtype='int32') - iou = layers.mean_iou(x, y, 2) + y = self._get_data(name='label', shape=[16], dtype='int32') + iou = layers.mean_iou(x, y, self._high_data_bound) return (iou) def make_argsort(self): @@ -1614,11 +1617,11 @@ class TestBook(LayerTest): out = layers.softshrink(input, name='softshrink') return (out) - def iou_similarity(self): + def make_iou_similarity(self): with program_guard(fluid.default_main_program(), fluid.default_startup_program()): - x = self._get_data(name="x", shape=[16], dtype="float32") - y = self._get_data(name="y", shape=[16], dtype="float32") + x = self._get_data(name="x", shape=[4], dtype="float32") + y = self._get_data(name="y", shape=[4], dtype="float32") out = layers.iou_similarity(x, y, name='iou_similarity') return (out) @@ -1668,9 +1671,16 @@ class TestBook(LayerTest): def make_kldiv_loss(self): with program_guard(fluid.default_main_program(), fluid.default_startup_program()): - x = self._get_data(name='x', shape=[32, 128, 128], dtype="float32") + x = self._get_data( + name='x', + shape=[32, 128, 128], + dtype="float32", + append_batch_size=False) target = self._get_data( - name='target', shape=[32, 128, 128], dtype="float32") + name='target', + shape=[32, 128, 128], + dtype="float32", + append_batch_size=False) loss = layers.kldiv_loss(x=x, target=target, reduction='batchmean') return (loss) @@ -1688,7 +1698,7 @@ class TestBook(LayerTest): out = layers.shuffle_channel(x, group=4) return (out) - def make_fsp(self): + def make_fsp_matrix(self): with program_guard(fluid.default_main_program(), fluid.default_startup_program()): x = self._get_data(name="X", shape=[16, 4, 4], dtype="float32") @@ -1696,6 +1706,13 @@ class TestBook(LayerTest): out = layers.fsp_matrix(x, y) return (out) + def make_pixel_shuffle(self): + with program_guard(fluid.default_main_program(), + fluid.default_startup_program()): + x = self._get_data(name="X", shape=[9, 4, 4], dtype="float32") + out = layers.pixel_shuffle(x, upscale_factor=3) + return (out) + def test_dynamic_lstmp(self): # TODO(minqiyang): dygraph do not support lod now with self.static_graph(): @@ -1908,36 +1925,6 @@ class TestBook(LayerTest): out = layers.flatten(x, axis=1, name="flatten") return (out) - def test_kldiv_loss(self): - with program_guard(fluid.default_main_program(), - fluid.default_startup_program()): - x = layers.data(name='x', shape=[32, 128, 128], dtype="float32") - target = layers.data( - name='target', shape=[32, 128, 128], dtype="float32") - loss = layers.kldiv_loss(x=x, target=target, reduction='batchmean') - return (loss) - - def test_temporal_shift(self): - with program_guard(fluid.default_main_program(), - fluid.default_startup_program()): - x = layers.data(name="X", shape=[16, 4, 4], dtype="float32") - out = layers.temporal_shift(x, seg_num=4, shift_ratio=0.2) - return (out) - - def test_shuffle_channel(self): - with program_guard(fluid.default_main_program(), - fluid.default_startup_program()): - x = layers.data(name="X", shape=[16, 4, 4], dtype="float32") - out = layers.shuffle_channel(x, group=4) - return (out) - - def test_pixel_shuffle(self): - with program_guard(fluid.default_main_program(), - fluid.default_startup_program()): - x = layers.data(name="X", shape=[9, 4, 4], dtype="float32") - out = layers.pixel_shuffle(x, upscale_factor=3) - return (out) - if __name__ == '__main__': unittest.main() -- GitLab