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提交 b976ba3e 编写于 作者: Y Youwei Song 提交者： hong
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fix unittests (#21786) 

test=develop
上级 73e97d39
隐藏空白更改
内联 并排
Showing with 14 addition and 25 deletion
python/paddle/fluid/tests/unittests/test_imperative_lod_tensor_to_selected_rows.py
浏览文件 @ b976ba3e
......@@ -29,20 +29,18 @@ from utils import DyGraphProgramDescTracerTestHelper
class SimpleNet(fluid.Layer):
def __init__(self,
name_scope,
hidden_size,
vocab_size,
num_steps=20,
init_scale=0.1,
is_sparse=False,
dtype='float32'):
super(SimpleNet, self).__init__(name_scope)
super(SimpleNet, self).__init__()
self.hidden_size = hidden_size
self.vocab_size = vocab_size
self.init_scale = init_scale
self.num_steps = num_steps
self.embedding = Embedding(
self.full_name(),
size=[vocab_size, hidden_size],
dtype=dtype,
is_sparse=is_sparse,
......@@ -100,7 +98,6 @@ class TestDygraphSimpleNet(unittest.TestCase):
fluid.default_main_program().random_seed = seed
simple_net = SimpleNet(
"simple_net",
hidden_size=hidden_size,
vocab_size=vocab_size,
num_steps=num_steps,
......@@ -120,7 +117,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
for i in range(batch_num):
x_data = np.arange(12).reshape(4, 3).astype('int64')
y_data = np.arange(1, 13).reshape(4, 3).astype('int64')
x_data = x_data.reshape((-1, num_steps, 1))
x_data = x_data.reshape((-1, num_steps))
y_data = y_data.reshape((-1, 1))
x = to_variable(x_data)
......@@ -143,7 +140,6 @@ class TestDygraphSimpleNet(unittest.TestCase):
fluid.default_main_program().random_seed = seed
simple_net = SimpleNet(
"simple_net",
hidden_size=hidden_size,
vocab_size=vocab_size,
num_steps=num_steps,
......@@ -153,7 +149,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
exe = fluid.Executor(place)
sgd = SGDOptimizer(learning_rate=1e-3)
x = fluid.layers.data(
name="x", shape=[-1, num_steps, 1], dtype='int64')
name="x", shape=[-1, num_steps], dtype='int64')
y = fluid.layers.data(name="y", shape=[-1, 1], dtype=dtype)
static_loss = simple_net(x, y)
......@@ -172,7 +168,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
for i in range(batch_num):
x_data = np.arange(12).reshape(4, 3).astype('int64')
y_data = np.arange(1, 13).reshape(4, 3).astype('int64')
x_data = x_data.reshape((-1, num_steps, 1))
x_data = x_data.reshape((-1, num_steps))
y_data = y_data.reshape((-1, 1))
fetch_list = [static_loss]
fetch_list.extend(static_param_name_list)
......
python/paddle/fluid/tests/unittests/test_imperative_selected_rows.py
浏览文件 @ b976ba3e
......@@ -24,10 +24,9 @@ import paddle.fluid.core as core
class SimpleNet(fluid.Layer):
def __init__(self, name_scope, vocab_size, hidden_size, dtype):
super(SimpleNet, self).__init__(name_scope)
def __init__(self, vocab_size, hidden_size, dtype):
super(SimpleNet, self).__init__()
self.emb = fluid.dygraph.Embedding(
self.full_name(),
size=[vocab_size, hidden_size],
dtype=dtype,
param_attr='emb.w',
......@@ -53,11 +52,10 @@ class TestSimpleNet(unittest.TestCase):
adam = SGDOptimizer(learning_rate=0.001)
# grad_clip = fluid.dygraph_grad_clip.GradClipByGlobalNorm(5.0)
input_word = np.array(
[[[1], [2]], [[2], [1]]]).astype('int64')
input_word = np.array([[1, 2], [2, 1]]).astype('int64')
input = to_variable(input_word)
simplenet = SimpleNet("SimpleNet", 20, 32, dtype)
simplenet = SimpleNet(20, 32, dtype)
input_emb, emb = simplenet(input)
try:
......@@ -99,11 +97,10 @@ class TestSimpleNet(unittest.TestCase):
grad_clip = fluid.dygraph_grad_clip.GradClipByGlobalNorm(
5.0)
input_word = np.array(
[[[1], [2]], [[2], [1]]]).astype('int64')
input_word = np.array([[1, 2], [2, 1]]).astype('int64')
input = to_variable(input_word)
simplenet = SimpleNet("SimpleNet", 20, 32, "float32")
simplenet = SimpleNet(20, 32, "float32")
input_emb, emb = simplenet(input)
try:
......
python/paddle/fluid/tests/unittests/test_imperative_selected_rows_to_lod_tensor.py
浏览文件 @ b976ba3e
......@@ -30,20 +30,18 @@ from paddle.fluid.dygraph.jit import TracedLayer
class SimpleNet(fluid.Layer):
def __init__(self,
name_scope,
hidden_size,
vocab_size,
num_steps=20,
init_scale=0.1,
is_sparse=False,
dtype='float32'):
super(SimpleNet, self).__init__(name_scope)
super(SimpleNet, self).__init__()
self.hidden_size = hidden_size
self.vocab_size = vocab_size
self.init_scale = init_scale
self.num_steps = num_steps
self.embedding = Embedding(
self.full_name(),
size=[vocab_size, hidden_size],
dtype=dtype,
is_sparse=is_sparse,
......@@ -109,7 +107,6 @@ class TestDygraphSimpleNet(unittest.TestCase):
fluid.default_main_program().random_seed = seed
simple_net = SimpleNet(
"simple_net",
hidden_size=hidden_size,
vocab_size=vocab_size,
num_steps=num_steps,
......@@ -130,7 +127,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
for i in range(batch_num):
x_data = np.arange(12).reshape(4, 3).astype('int64')
y_data = np.arange(1, 13).reshape(4, 3).astype('int64')
x_data = x_data.reshape((-1, num_steps, 1))
x_data = x_data.reshape((-1, num_steps))
y_data = y_data.reshape((-1, 1))
x = to_variable(x_data)
......@@ -153,7 +150,6 @@ class TestDygraphSimpleNet(unittest.TestCase):
fluid.default_main_program().random_seed = seed
simple_net = SimpleNet(
"simple_net",
hidden_size=hidden_size,
vocab_size=vocab_size,
num_steps=num_steps,
......@@ -163,7 +159,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
exe = fluid.Executor(place)
sgd = SGDOptimizer(learning_rate=1e-3)
x = fluid.layers.data(
name="x", shape=[-1, num_steps, 1], dtype='int64')
name="x", shape=[-1, num_steps], dtype='int64')
y = fluid.layers.data(name="y", shape=[-1, 1], dtype=dtype)
static_loss = simple_net(x, y)
......@@ -182,7 +178,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
for i in range(batch_num):
x_data = np.arange(12).reshape(4, 3).astype('int64')
y_data = np.arange(1, 13).reshape(4, 3).astype('int64')
x_data = x_data.reshape((-1, num_steps, 1))
x_data = x_data.reshape((-1, num_steps))
y_data = y_data.reshape((-1, 1))
fetch_list = [static_loss]
fetch_list.extend(static_param_name_list)
......
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