提交 a5dc2812 编写于 作者: M minqiyang 提交者: ceci3

increment resnet and ptbrnn's batch_num

test=develop
上级 3723dcc3
...@@ -243,7 +243,9 @@ class TestImperativePtbRnn(unittest.TestCase): ...@@ -243,7 +243,9 @@ class TestImperativePtbRnn(unittest.TestCase):
dy_loss = None dy_loss = None
last_hidden = None last_hidden = None
last_cell = None last_cell = None
for i in range(2): batch_num = 200
for i in range(batch_num):
x_data = np.arange(12).reshape(4, 3).astype('int64') x_data = np.arange(12).reshape(4, 3).astype('int64')
y_data = np.arange(1, 13).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, 1))
...@@ -302,7 +304,7 @@ class TestImperativePtbRnn(unittest.TestCase): ...@@ -302,7 +304,7 @@ class TestImperativePtbRnn(unittest.TestCase):
static_loss_value = None static_loss_value = None
static_last_cell_value = None static_last_cell_value = None
static_last_hidden_value = None static_last_hidden_value = None
for i in range(2): for i in range(batch_num):
x_data = np.arange(12).reshape(4, 3).astype('int64') x_data = np.arange(12).reshape(4, 3).astype('int64')
y_data = np.arange(1, 13).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, 1))
......
...@@ -231,7 +231,7 @@ class TestImperativeResnet(unittest.TestCase): ...@@ -231,7 +231,7 @@ class TestImperativeResnet(unittest.TestCase):
seed = 90 seed = 90
batch_size = train_parameters["batch_size"] batch_size = train_parameters["batch_size"]
batch_num = 2 batch_num = 50
with fluid.imperative.guard(): with fluid.imperative.guard():
fluid.default_startup_program().random_seed = seed fluid.default_startup_program().random_seed = seed
fluid.default_main_program().random_seed = seed fluid.default_main_program().random_seed = seed
......
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