未验证 提交 7c1aa0d6 编写于 作者: C cnn 提交者: GitHub

2.0rc api rename (#28088)

* rename manual_seed to seed

* rename xxx1d-->xxx1D, xxx2d-->xxx2D, xxx3d-->xxx3D

* rename manual_seed --> seed

* do not rename .cc, .cu and .h file

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* disable_static on doc example code

* donot change manual_seed on generator

* add enable_static on sample code

* convert python/paddle/fluid/layers/nn.py to bak

* fix typo

* fix code style

* fix seed to manual_seed when call functions of Generator()

* fix bug
上级 68c473e3
develop 2.0.1-rocm-post Ligoml-patch-1 OliverLPH-patch-1 OliverLPH-patch-2 PaddlePM-patch-1 PaddlePM-patch-2 ZHUI-patch-1 add_default_att add_model_benchmark_ci add_some_yaml_config addfile all_new_design_exec ascendrc ascendrelease cherry_undefined_var compile_windows delete_2.0.1-rocm-post delete_add_default_att delete_all_new_design_exec delete_ascendrc delete_compile_windows delete_delete_addfile delete_disable_iterable_dataset_unittest delete_fix_dataloader_memory_leak delete_fix_imperative_dygraph_error delete_fix_retry_ci delete_fix_undefined_var delete_improve_sccache delete_paralleltest delete_prv-disable-more-cache delete_revert-31068-fix_conv3d_windows delete_revert-31562-mean delete_revert-33630-bug-fix delete_revert-34159-add_npu_bce_logical_dev delete_revert-34910-spinlocks_for_allocator delete_revert-35069-revert-34910-spinlocks_for_allocator delete_revert-36057-dev/read_flags_in_ut dingjiaweiww-patch-1 disable_iterable_dataset_unittest dy2static enable_eager_model_test final_state_gen_python_c final_state_intermediate fix-numpy-issue fix_concat_slice fix_dataloader_memory_leak fix_imperative_dygraph_error fix_npu_ci fix_op_flops fix_retry_ci fix_rnn_docs fix_tensor_type fix_undefined_var fixiscan fixiscan1 fixiscan2 fixiscan3 improve_sccache incubate/infrt inplace_addto make_flag_adding_easier move_embedding_to_phi move_histogram_to_pten move_sgd_to_phi move_slice_to_pten move_temporal_shift_to_phi move_yolo_box_to_phi npu_fix_alloc paralleltest preln_ernie prv-disable-more-cache prv-md-even-more prv-onednn-2.5 pten_tensor_refactor release/2.0 release/2.0-rc1 release/2.1 release/2.2 release/2.3 release/2.3-fc-ernie-fix release/2.4 revert-31068-fix_conv3d_windows revert-31562-mean revert-32290-develop-hardlabel revert-33037-forci revert-33475-fix_cifar_label_dimension revert-33630-bug-fix revert-34159-add_npu_bce_logical_dev revert-34406-add_copy_from_tensor revert-34910-spinlocks_for_allocator revert-35069-revert-34910-spinlocks_for_allocator revert-36057-dev/read_flags_in_ut revert-36201-refine_fast_threaded_ssa_graph_executor revert-36985-add_license revert-37318-refactor_dygraph_to_eager revert-37926-eager_coreops_500 revert-37956-revert-37727-pylayer_support_tuple revert-38100-mingdong revert-38301-allocation_rearrange_pr revert-38703-numpy_bf16_package_reupload revert-38732-remove_useless_header_in_elementwise_mul_grad revert-38959-Reduce_Grad revert-39143-adjust_empty revert-39227-move_trace_op_to_pten revert-39268-dev/remove_concat_fluid_kernel revert-40170-support_partial_grad revert-41056-revert-40727-move_some_activaion_to_phi revert-41065-revert-40993-mv_ele_floordiv_pow revert-41068-revert-40790-phi_new revert-41944-smaller_inference_api_test revert-42149-do-not-reset-default-stream-for-stream-safe-cuda-allocator revert-43155-fix_ut_tempfile revert-43882-revert-41944-smaller_inference_api_test revert-45808-phi/simplify_size_op revert-46827-deform_comment rocm_dev_0217 support_weight_transpose test_benchmark_ci test_model_benchmark test_model_benchmark_ci zhiqiu-patch-1 v2.4.0-rc0 v2.3.2 v2.3.1 v2.3.0 v2.3.0-rc0 v2.2.2 v2.2.1 v2.2.0 v2.2.0-rc0 v2.2.0-bak0 v2.1.3 v2.1.2 v2.1.1 v2.1.0 v2.1.0-rc0 v2.0.2 v2.0.1 v2.0.0 v2.0.0-rc1
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......@@ -222,7 +222,7 @@ from .tensor.search import sort #DEFINE_ALIAS
from .tensor.to_string import set_printoptions
from .framework.random import manual_seed #DEFINE_ALIAS
from .framework.random import seed #DEFINE_ALIAS
from .framework.random import get_cuda_rng_state #DEFINE_ALIAS
from .framework.random import set_cuda_rng_state #DEFINE_ALIAS
from .framework import ParamAttr #DEFINE_ALIAS
......
......@@ -37,7 +37,7 @@ def auto_cast(enable=True, custom_white_list=None, custom_black_list=None):
import paddle
conv2d = paddle.nn.Conv2d(3, 2, 3, bias_attr=False)
conv2d = paddle.nn.Conv2D(3, 2, 3, bias_attr=False)
data = paddle.rand([10, 3, 32, 32])
with paddle.amp.auto_cast():
......
......@@ -50,7 +50,7 @@ class GradScaler(AmpScaler):
import paddle
model = paddle.nn.Conv2d(3, 2, 3, bias_attr=True)
model = paddle.nn.Conv2D(3, 2, 3, bias_attr=True)
optimizer = paddle.optimizer.SGD(learning_rate=0.01, parameters=model.parameters())
scaler = paddle.amp.GradScaler(init_loss_scaling=1024)
data = paddle.rand([10, 3, 32, 32])
......@@ -90,7 +90,7 @@ class GradScaler(AmpScaler):
import paddle
model = paddle.nn.Conv2d(3, 2, 3, bias_attr=True)
model = paddle.nn.Conv2D(3, 2, 3, bias_attr=True)
optimizer = paddle.optimizer.SGD(learning_rate=0.01, parameters=model.parameters())
scaler = paddle.amp.GradScaler(init_loss_scaling=1024)
data = paddle.rand([10, 3, 32, 32])
......@@ -122,7 +122,7 @@ class GradScaler(AmpScaler):
import paddle
model = paddle.nn.Conv2d(3, 2, 3, bias_attr=True)
model = paddle.nn.Conv2D(3, 2, 3, bias_attr=True)
optimizer = paddle.optimizer.SGD(learning_rate=0.01, parameters=model.parameters())
scaler = paddle.amp.GradScaler(init_loss_scaling=1024)
data = paddle.rand([10, 3, 32, 32])
......
......@@ -670,13 +670,13 @@ class Categorical(Distribution):
import paddle
from paddle.distribution import Categorical
paddle.manual_seed(100) # on CPU device
paddle.seed(100) # on CPU device
x = paddle.rand([6])
print(x.numpy())
# [0.5535528 0.20714243 0.01162981
# 0.51577556 0.36369765 0.2609165 ]
paddle.manual_seed(200) # on CPU device
paddle.seed(200) # on CPU device
y = paddle.rand([6])
print(y.numpy())
# [0.77663314 0.90824795 0.15685187
......@@ -685,7 +685,7 @@ class Categorical(Distribution):
cat = Categorical(x)
cat2 = Categorical(y)
paddle.manual_seed(1000) # on CPU device
paddle.seed(1000) # on CPU device
cat.sample([2,3])
# [[0, 0, 5],
# [3, 4, 5]]
......@@ -744,7 +744,7 @@ class Categorical(Distribution):
import paddle
from paddle.distribution import Categorical
paddle.manual_seed(100) # on CPU device
paddle.seed(100) # on CPU device
x = paddle.rand([6])
print(x.numpy())
# [0.5535528 0.20714243 0.01162981
......@@ -752,7 +752,7 @@ class Categorical(Distribution):
cat = Categorical(x)
paddle.manual_seed(1000) # on CPU device
paddle.seed(1000) # on CPU device
cat.sample([2,3])
# [[0, 0, 5],
# [3, 4, 5]]
......@@ -791,13 +791,13 @@ class Categorical(Distribution):
import paddle
from paddle.distribution import Categorical
paddle.manual_seed(100) # on CPU device
paddle.seed(100) # on CPU device
x = paddle.rand([6])
print(x.numpy())
# [0.5535528 0.20714243 0.01162981
# 0.51577556 0.36369765 0.2609165 ]
paddle.manual_seed(200) # on CPU device
paddle.seed(200) # on CPU device
y = paddle.rand([6])
print(y.numpy())
# [0.77663314 0.90824795 0.15685187
......@@ -842,7 +842,7 @@ class Categorical(Distribution):
import paddle
from paddle.distribution import Categorical
paddle.manual_seed(100) # on CPU device
paddle.seed(100) # on CPU device
x = paddle.rand([6])
print(x.numpy())
# [0.5535528 0.20714243 0.01162981
......@@ -887,7 +887,7 @@ class Categorical(Distribution):
import paddle
from paddle.distribution import Categorical
paddle.manual_seed(100) # on CPU device
paddle.seed(100) # on CPU device
x = paddle.rand([6])
print(x.numpy())
# [0.5535528 0.20714243 0.01162981
......@@ -953,7 +953,7 @@ class Categorical(Distribution):
import paddle
from paddle.distribution import Categorical
paddle.manual_seed(100) # on CPU device
paddle.seed(100) # on CPU device
x = paddle.rand([6])
print(x.numpy())
# [0.5535528 0.20714243 0.01162981
......
......@@ -114,7 +114,7 @@ class TestWeightDecay(unittest.TestCase):
return param_sum
def check_weight_decay(self, place, model):
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
main_prog = fluid.framework.Program()
startup_prog = fluid.framework.Program()
......@@ -137,7 +137,7 @@ class TestWeightDecay(unittest.TestCase):
return param_sum
def check_weight_decay2(self, place, model):
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
main_prog = fluid.framework.Program()
startup_prog = fluid.framework.Program()
......
......@@ -1058,7 +1058,7 @@ class Layer(core.Layer):
super(Mylayer, self).__init__()
self.linear1 = paddle.nn.Linear(10, 10)
self.linear2 = paddle.nn.Linear(5, 5)
self.conv2d = paddle.nn.Conv2d(3, 2, 3)
self.conv2d = paddle.nn.Conv2D(3, 2, 3)
self.embedding = paddle.nn.Embedding(128, 16)
self.h_0 = paddle.to_tensor(np.zeros([10, 10]).astype('float32'))
......
......@@ -110,7 +110,7 @@ class Conv2D(layers.Layer):
dilation (int or tuple, optional): The dilation size. If dilation is a tuple, it must
contain two integers, (dilation_H, dilation_W). Otherwise, the
dilation_H = dilation_W = dilation. Default: 1.
groups (int, optional): The groups number of the Conv2d Layer. According to grouped
groups (int, optional): The groups number of the Conv2D Layer. According to grouped
convolution in Alex Krizhevsky's Deep CNN paper: when group=2,
the first half of the filters is only connected to the first half
of the input channels, while the second half of the filters is only
......@@ -345,7 +345,7 @@ class Conv3D(layers.Layer):
dilation (int|tuple, optional): The dilation size. If dilation is a tuple, it must
contain three integers, (dilation_D, dilation_H, dilation_W). Otherwise, the
dilation_D = dilation_H = dilation_W = dilation. The default value is 1.
groups (int, optional): The groups number of the Conv3d Layer. According to grouped
groups (int, optional): The groups number of the Conv3D Layer. According to grouped
convolution in Alex Krizhevsky's Deep CNN paper: when group=2,
the first half of the filters is only connected to the first half
of the input channels, while the second half of the filters is only
......@@ -574,7 +574,7 @@ class Conv3DTranspose(layers.Layer):
dilation(int|tuple, optional): The dilation size. If dilation is a tuple, it must
contain three integers, (dilation_D, dilation_H, dilation_W). Otherwise, the
dilation_D = dilation_H = dilation_W = dilation. The default value is 1.
groups(int, optional): The groups number of the Conv3d transpose layer. Inspired by
groups(int, optional): The groups number of the Conv3D transpose layer. Inspired by
grouped convolution in Alex Krizhevsky's Deep CNN paper, in which
when group=2, the first half of the filters is only connected to the
first half of the input channels, while the second half of the
......@@ -2541,7 +2541,7 @@ class Conv2DTranspose(layers.Layer):
dilation(int or tuple, optional): The dilation size. If dilation is a tuple, it must
contain two integers, (dilation_H, dilation_W). Otherwise, the
dilation_H = dilation_W = dilation. Default: 1.
groups(int, optional): The groups number of the Conv2d transpose layer. Inspired by
groups(int, optional): The groups number of the Conv2D transpose layer. Inspired by
grouped convolution in Alex Krizhevsky's Deep CNN paper, in which
when group=2, the first half of the filters is only connected to the
first half of the input channels, while the second half of the
......
......@@ -749,7 +749,7 @@ class BilinearInitializer(Initializer):
regularizer=L2Decay(0.),
initializer=nn.initializer.Bilinear())
data = paddle.rand([B, 3, H, W], dtype='float32')
conv_up = nn.ConvTranspose2d(3,
conv_up = nn.Conv2DTranspose(3,
out_channels=C,
kernel_size=2 * factor - factor % 2,
padding=int(
......
......@@ -43,7 +43,7 @@ def simple_img_conv_pool(input,
act=None,
use_cudnn=True):
"""
:api_attr: Static Graph
:api_attr: Static Graph
The simple_img_conv_pool api is composed of :ref:`api_fluid_layers_conv2d` and :ref:`api_fluid_layers_pool2d` .
......@@ -106,6 +106,8 @@ def simple_img_conv_pool(input,
.. code-block:: python
import paddle.fluid as fluid
import paddle
paddle.enable_static()
img = fluid.data(name='img', shape=[100, 1, 28, 28], dtype='float32')
conv_pool = fluid.nets.simple_img_conv_pool(input=img,
filter_size=5,
......@@ -151,37 +153,37 @@ def img_conv_group(input,
pool_type="max",
use_cudnn=True):
"""
:api_attr: Static Graph
:api_attr: Static Graph
The Image Convolution Group is composed of Convolution2d, BatchNorm, DropOut,
and Pool2d. According to the input arguments, img_conv_group will do serials of
and Pool2D. According to the input arguments, img_conv_group will do serials of
computation for Input using Convolution2d, BatchNorm, DropOut, and pass the last
result to Pool2d.
result to Pool2D.
Args:
input (Variable): The input is 4-D Tensor with shape [N, C, H, W], the data type of input is float32 or float64.
conv_num_filter(list|tuple): Indicates the numbers of filter of this group.
pool_size (int|list|tuple): The pooling size of Pool2d Layer. If pool_size
pool_size (int|list|tuple): The pooling size of Pool2D Layer. If pool_size
is a list or tuple, it must contain two integers, (pool_size_height, pool_size_width).
Otherwise, the pool_size_height = pool_size_width = pool_size.
conv_padding (int|list|tuple): The padding size of the Conv2d Layer. If padding is
conv_padding (int|list|tuple): The padding size of the Conv2D Layer. If padding is
a list or tuple, its length must be equal to the length of conv_num_filter.
Otherwise the conv_padding of all Conv2d Layers are the same. Default 1.
Otherwise the conv_padding of all Conv2D Layers are the same. Default 1.
conv_filter_size (int|list|tuple): The filter size. If filter_size is a list or
tuple, its length must be equal to the length of conv_num_filter.
Otherwise the conv_filter_size of all Conv2d Layers are the same. Default 3.
conv_act (str): Activation type for Conv2d Layer that is not followed by BatchNorm.
Otherwise the conv_filter_size of all Conv2D Layers are the same. Default 3.
conv_act (str): Activation type for Conv2D Layer that is not followed by BatchNorm.
Default: None.
param_attr (ParamAttr): The parameters to the Conv2d Layer. Default: None
conv_with_batchnorm (bool|list): Indicates whether to use BatchNorm after Conv2d Layer.
param_attr (ParamAttr): The parameters to the Conv2D Layer. Default: None
conv_with_batchnorm (bool|list): Indicates whether to use BatchNorm after Conv2D Layer.
If conv_with_batchnorm is a list, its length must be equal to the length of
conv_num_filter. Otherwise, conv_with_batchnorm indicates whether all the
Conv2d Layer follows a BatchNorm. Default False.
Conv2D Layer follows a BatchNorm. Default False.
conv_batchnorm_drop_rate (float|list): Indicates the drop_rate of Dropout Layer
after BatchNorm. If conv_batchnorm_drop_rate is a list, its length must be
equal to the length of conv_num_filter. Otherwise, drop_rate of all Dropout
Layers is conv_batchnorm_drop_rate. Default 0.0.
pool_stride (int|list|tuple): The pooling stride of Pool2d layer. If pool_stride
pool_stride (int|list|tuple): The pooling stride of Pool2D layer. If pool_stride
is a list or tuple, it must contain two integers, (pooling_stride_H,
pooling_stride_W). Otherwise, the pooling_stride_H = pooling_stride_W = pool_stride.
Default 1.
......@@ -192,12 +194,15 @@ def img_conv_group(input,
Return:
A Variable holding Tensor representing the final result after serial computation using Convolution2d,
BatchNorm, DropOut, and Pool2d, whose data type is the same with input.
BatchNorm, DropOut, and Pool2D, whose data type is the same with input.
Examples:
.. code-block:: python
import paddle.fluid as fluid
import paddle
paddle.enable_static()
img = fluid.data(name='img', shape=[None, 1, 28, 28], dtype='float32')
conv_pool = fluid.nets.img_conv_group(input=img,
conv_padding=1,
......@@ -261,7 +266,7 @@ def sequence_conv_pool(input,
pool_type="max",
bias_attr=None):
"""
:api_attr: Static Graph
:api_attr: Static Graph
**This api takes input as an LoDTensor. If input is a Tensor, please use**
:ref:`api_fluid_nets_simple_img_conv_pool` **instead**
......@@ -300,6 +305,8 @@ def sequence_conv_pool(input,
.. code-block:: python
import paddle.fluid as fluid
import paddle
paddle.enable_static()
input_dim = 100 #len(word_dict)
emb_dim = 128
hid_dim = 512
......@@ -327,7 +334,7 @@ def sequence_conv_pool(input,
def glu(input, dim=-1):
"""
:api_attr: Static Graph
:api_attr: Static Graph
The Gated Linear Units(GLU) composed by :ref:`api_fluid_layers_split` ,
:ref:`api_fluid_layers_sigmoid` and :ref:`api_fluid_layers_elementwise_mul` .
......@@ -356,6 +363,9 @@ def glu(input, dim=-1):
.. code-block:: python
import paddle.fluid as fluid
import paddle
paddle.enable_static()
data = fluid.data(
name="words", shape=[-1, 6, 3, 9], dtype="float32")
# shape of output: [-1, 3, 3, 9]
......@@ -375,7 +385,7 @@ def scaled_dot_product_attention(queries,
num_heads=1,
dropout_rate=0.):
"""
:api_attr: Static Graph
:api_attr: Static Graph
This interface Multi-Head Attention using scaled dot product.
Attention mechanism can be seen as mapping a query and a set of key-value
......@@ -435,7 +445,9 @@ def scaled_dot_product_attention(queries,
.. code-block:: python
import paddle.fluid as fluid
import paddle
paddle.enable_static()
queries = fluid.data(name="queries", shape=[3, 5, 9], dtype="float32")
keys = fluid.data(name="keys", shape=[3, 6, 9], dtype="float32")
values = fluid.data(name="values", shape=[3, 6, 10], dtype="float32")
......
......@@ -564,7 +564,7 @@ def train_bmn(args, place, to_static):
loss_data = []
with fluid.dygraph.guard(place):
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
global local_random
local_random = np.random.RandomState(SEED)
......
......@@ -450,7 +450,7 @@ def do_train(args, to_static):
place = fluid.CUDAPlace(0) if fluid.is_compiled_with_cuda(
) else fluid.CPUPlace()
with fluid.dygraph.guard(place):
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
reader = get_random_input_data(args.batch_size, args.vocab_size,
......
......@@ -451,7 +451,7 @@ def train_mobilenet(args, to_static):
with fluid.dygraph.guard(args.place):
np.random.seed(SEED)
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
if args.model == "MobileNetV1":
......
......@@ -218,7 +218,7 @@ def train(place):
batch_num = 200
with fluid.dygraph.guard(place):
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
ptb_model = PtbModel(
hidden_size=hidden_size,
......
......@@ -210,7 +210,7 @@ def train(place):
batch_num = 200
paddle.disable_static(place)
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
ptb_model = PtbModel(
hidden_size=hidden_size,
......
......@@ -65,7 +65,7 @@ def train(args, place, to_static):
env.seed(SEED)
with fluid.dygraph.guard(place):
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
local_random = np.random.RandomState(SEED)
......
......@@ -219,7 +219,7 @@ def train(to_static):
"""
with fluid.dygraph.guard(place):
np.random.seed(SEED)
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
train_reader = paddle.batch(
......
......@@ -66,7 +66,7 @@ class ConvBNLayer(paddle.nn.Layer):
act=None):
super(ConvBNLayer, self).__init__()
self._conv = paddle.nn.Conv2d(
self._conv = paddle.nn.Conv2D(
in_channels=num_channels,
out_channels=num_filters,
kernel_size=filter_size,
......@@ -214,7 +214,7 @@ def train(to_static):
"""
paddle.disable_static(place)
np.random.seed(SEED)
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
train_reader = paddle.batch(
......
......@@ -334,7 +334,7 @@ def train(train_reader, to_static):
np.random.seed(SEED)
with fluid.dygraph.guard(place):
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
se_resnext = SeResNeXt()
optimizer = optimizer_setting(train_parameters, se_resnext.parameters())
......
......@@ -286,7 +286,7 @@ def train(args, to_static):
with fluid.dygraph.guard(place):
np.random.seed(SEED)
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
train_reader = fake_data_reader(args.class_num, args.vocab_size,
......
......@@ -108,7 +108,7 @@ def train(conf_dict, to_static):
place = fluid.CPUPlace()
with fluid.dygraph.guard(place):
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
conf_dict['dict_size'] = len(vocab)
......
......@@ -106,7 +106,7 @@ def train(conf_dict, to_static):
place = paddle.CPUPlace()
paddle.disable_static(place)
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
conf_dict['dict_size'] = len(vocab)
......
......@@ -33,7 +33,7 @@ STEP_NUM = 10
def train_static(args, batch_generator):
paddle.enable_static()
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
train_prog = fluid.Program()
startup_prog = fluid.Program()
......@@ -131,7 +131,7 @@ def train_static(args, batch_generator):
def train_dygraph(args, batch_generator):
with fluid.dygraph.guard(place):
if SEED is not None:
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
# define data loader
train_loader = fluid.io.DataLoader.from_generator(capacity=10)
......@@ -223,7 +223,7 @@ def train_dygraph(args, batch_generator):
def predict_dygraph(args, batch_generator):
with fluid.dygraph.guard(place):
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
# define data loader
......@@ -295,7 +295,7 @@ def predict_dygraph(args, batch_generator):
def predict_static(args, batch_generator):
test_prog = fluid.Program()
with fluid.program_guard(test_prog):
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
# define input and reader
......
......@@ -272,7 +272,7 @@ def train(args, fake_data_reader, to_static):
random.seed(0)
np.random.seed(0)
with fluid.dygraph.guard(place):
paddle.manual_seed(1000)
paddle.seed(1000)
paddle.framework.random._manual_program_seed(1000)
video_model = TSM_ResNet("TSM", train_config, 'Train')
......
......@@ -20,7 +20,7 @@ import struct
import paddle.fluid.core as core
from paddle.fluid.tests.unittests.op_test import OpTest, convert_float_to_uint16
from paddle.fluid.tests.unittests.test_conv2d_op import conv2d_forward_naive, TestConv2dOp
from paddle.fluid.tests.unittests.test_conv2d_op import conv2d_forward_naive, TestConv2DOp
def conv2d_residual_naive(out, residual):
......@@ -31,7 +31,7 @@ def conv2d_residual_naive(out, residual):
@unittest.skipIf(not core.supports_bfloat16(),
"place does not support BF16 evaluation")
class TestConv2dBf16Op(TestConv2dOp):
class TestConv2DBf16Op(TestConv2DOp):
def setUp(self):
self.op_type = "conv2d"
self.use_cudnn = False
......@@ -110,7 +110,7 @@ class TestConv2dBf16Op(TestConv2dOp):
pass
def init_test_case(self):
TestConv2dOp.init_test_case(self)
TestConv2DOp.init_test_case(self)
self.input_size = [1, 1, 5, 5] # NCHW
f_c = self.input_size[1] // self.groups
self.input_residual_size = [1, 2, 3, 3]
......@@ -130,7 +130,7 @@ class TestConv2dBf16Op(TestConv2dOp):
self.fuse_residual = True
class TestConv2d(TestConv2dBf16Op):
class TestConv2D(TestConv2DBf16Op):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -144,19 +144,19 @@ class TestConv2d(TestConv2dBf16Op):
self.input_type = np.uint16
class TestWithPad(TestConv2d):
class TestWithPad(TestConv2D):
def init_test_case(self):
TestConv2d.init_test_case(self)
TestConv2D.init_test_case(self)
self.pad = [1, 1]
self.input_residual_size = [2, 6, 5, 5]
class TestWithGroup(TestConv2d):
class TestWithGroup(TestConv2D):
def init_group(self):
self.groups = 3
class TestWithStride(TestConv2dBf16Op):
class TestWithStride(TestConv2DBf16Op):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -170,7 +170,7 @@ class TestWithStride(TestConv2dBf16Op):
self.input_type = np.uint16
class TestWithDilations(TestConv2dBf16Op):
class TestWithDilations(TestConv2DBf16Op):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -185,7 +185,7 @@ class TestWithDilations(TestConv2dBf16Op):
self.input_type = np.uint16
class TestWith1x1ForceFP32Output(TestConv2dBf16Op):
class TestWith1x1ForceFP32Output(TestConv2DBf16Op):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -201,7 +201,7 @@ class TestWith1x1ForceFP32Output(TestConv2dBf16Op):
self.fuse_residual = False
class TestWithInput1x1Filter1x1(TestConv2dBf16Op):
class TestWithInput1x1Filter1x1(TestConv2DBf16Op):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......
......@@ -19,7 +19,7 @@ import numpy as np
import paddle.fluid.core as core
from paddle.fluid.tests.unittests.op_test import OpTest
from paddle.fluid.tests.unittests.test_conv2d_op import conv2d_forward_naive, TestConv2dOp
from paddle.fluid.tests.unittests.test_conv2d_op import conv2d_forward_naive, TestConv2DOp
def conv2d_forward_refer(input, filter, group, conv_param):
......@@ -28,7 +28,7 @@ def conv2d_forward_refer(input, filter, group, conv_param):
return out
class TestConv2dInt8Op(TestConv2dOp):
class TestConv2DInt8Op(TestConv2DOp):
def setUp(self):
self.op_type = "conv2d"
self.use_cudnn = False
......@@ -162,7 +162,7 @@ class TestConv2dInt8Op(TestConv2dOp):
pass
def init_test_case(self):
TestConv2dOp.init_test_case(self)
TestConv2DOp.init_test_case(self)
self.input_size = [1, 1, 5, 5] # NCHW
f_c = self.input_size[1] // self.groups
self.input_residual_size = [1, 2, 3, 3]
......@@ -186,7 +186,7 @@ class TestConv2dInt8Op(TestConv2dOp):
#--------------------test conv2d u8 in and u8 out with residual fuse--------------------
class TestConv2d(TestConv2dInt8Op):
class TestConv2D(TestConv2DInt8Op):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -201,19 +201,19 @@ class TestConv2d(TestConv2dInt8Op):
self.scale_in_eltwise = 0.6
class TestWithPad(TestConv2d):
class TestWithPad(TestConv2D):
def init_test_case(self):
TestConv2d.init_test_case(self)
TestConv2D.init_test_case(self)
self.pad = [1, 1]
self.input_residual_size = [2, 6, 5, 5]
class TestWithGroup(TestConv2d):
class TestWithGroup(TestConv2D):
def init_group(self):
self.groups = 3
class TestWithStride(TestConv2dInt8Op):
class TestWithStride(TestConv2DInt8Op):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -228,7 +228,7 @@ class TestWithStride(TestConv2dInt8Op):
self.scale_in_eltwise = 0.5
class TestWithDilations(TestConv2dInt8Op):
class TestWithDilations(TestConv2DInt8Op):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -244,7 +244,7 @@ class TestWithDilations(TestConv2dInt8Op):
self.scale_in_eltwise = 0.5
class TestWith1x1(TestConv2dInt8Op):
class TestWith1x1(TestConv2DInt8Op):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -259,7 +259,7 @@ class TestWith1x1(TestConv2dInt8Op):
self.scale_in_eltwise = 0.5
class TestWithInput1x1Filter1x1(TestConv2dInt8Op):
class TestWithInput1x1Filter1x1(TestConv2DInt8Op):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -356,7 +356,7 @@ def create_test_int8_class(parent):
globals()[cls_name_u8s8_re_1] = TestU8S8ResCase
create_test_int8_class(TestConv2dInt8Op)
create_test_int8_class(TestConv2DInt8Op)
create_test_int8_class(TestWithPad)
create_test_int8_class(TestWithStride)
create_test_int8_class(TestWithDilations)
......@@ -365,7 +365,7 @@ create_test_int8_class(TestWith1x1)
create_test_int8_class(TestWithInput1x1Filter1x1)
class TestConv2dOp_AsyPadding_INT_MKLDNN(TestConv2dInt8Op):
class TestConv2DOp_AsyPadding_INT_MKLDNN(TestConv2DInt8Op):
def init_kernel_type(self):
self.use_mkldnn = True
......@@ -374,13 +374,13 @@ class TestConv2dOp_AsyPadding_INT_MKLDNN(TestConv2dInt8Op):
self.padding_algorithm = "EXPLICIT"
class TestConv2dOp_Same_INT_MKLDNN(TestConv2dOp_AsyPadding_INT_MKLDNN):
class TestConv2DOp_Same_INT_MKLDNN(TestConv2DOp_AsyPadding_INT_MKLDNN):
def init_paddings(self):
self.pad = [0, 0]
self.padding_algorithm = "SAME"
class TestConv2dOp_Valid_INT_MKLDNN(TestConv2dOp_AsyPadding_INT_MKLDNN):
class TestConv2DOp_Valid_INT_MKLDNN(TestConv2DOp_AsyPadding_INT_MKLDNN):
def init_paddings(self):
self.pad = [1, 1]
self.padding_algorithm = "VALID"
......
......@@ -19,7 +19,7 @@ import numpy as np
import paddle.fluid.core as core
from paddle.fluid.tests.unittests.op_test import OpTest, skip_check_grad_ci
from paddle.fluid.tests.unittests.test_conv2d_op import TestConv2dOp, TestConv2dOp_v2
from paddle.fluid.tests.unittests.test_conv2d_op import TestConv2DOp, TestConv2DOp_v2
def conv2d_bias_naive(out, bias):
......@@ -36,7 +36,7 @@ def conv2d_residual_naive(out, residual):
return out
class TestConv2dMKLDNNOp(TestConv2dOp):
class TestConv2DMKLDNNOp(TestConv2DOp):
def init_group(self):
self.groups = 1
......@@ -64,7 +64,7 @@ class TestConv2dMKLDNNOp(TestConv2dOp):
self.fuse_residual_connection = False
self.input_residual_size = None
TestConv2dOp.setUp(self)
TestConv2DOp.setUp(self)
output = self.outputs['Output']
......@@ -106,9 +106,9 @@ class TestConv2dMKLDNNOp(TestConv2dOp):
@skip_check_grad_ci(
reason="Fusion is for inference only, check_grad is not required.")
class TestWithbreluFusion(TestConv2dMKLDNNOp):
class TestWithbreluFusion(TestConv2DMKLDNNOp):
def init_test_case(self):
TestConv2dMKLDNNOp.init_test_case(self)
TestConv2DMKLDNNOp.init_test_case(self)
self.fuse_activation = "relu6"
self.fuse_alpha = 6.0
self.dsttype = np.float32
......@@ -116,9 +116,9 @@ class TestWithbreluFusion(TestConv2dMKLDNNOp):
@skip_check_grad_ci(
reason="Fusion is for inference only, check_grad is not required.")
class TestWithFuse(TestConv2dMKLDNNOp):
class TestWithFuse(TestConv2DMKLDNNOp):
def init_test_case(self):
TestConv2dMKLDNNOp.init_test_case(self)
TestConv2DMKLDNNOp.init_test_case(self)
self.pad = [1, 1]
self.fuse_bias = True
self.bias_size = [6]
......@@ -126,22 +126,22 @@ class TestWithFuse(TestConv2dMKLDNNOp):
self.input_residual_size = [2, 6, 5, 5]
class TestWithPadWithBias(TestConv2dMKLDNNOp):
class TestWithPadWithBias(TestConv2DMKLDNNOp):
def init_test_case(self):
TestConv2dMKLDNNOp.init_test_case(self)
TestConv2DMKLDNNOp.init_test_case(self)
self.pad = [1, 1]
self.input_size = [2, 3, 6, 6]
class TestWithStride(TestConv2dMKLDNNOp):
class TestWithStride(TestConv2DMKLDNNOp):
def init_test_case(self):
TestConv2dMKLDNNOp.init_test_case(self)
TestConv2DMKLDNNOp.init_test_case(self)
self.pad = [1, 1]
self.stride = [2, 2]
self.input_size = [2, 3, 6, 6]
class TestWithGroup(TestConv2dMKLDNNOp):
class TestWithGroup(TestConv2DMKLDNNOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -154,15 +154,15 @@ class TestWithGroup(TestConv2dMKLDNNOp):
self.groups = 3
class TestWith1x1(TestConv2dMKLDNNOp):
class TestWith1x1(TestConv2DMKLDNNOp):
def init_test_case(self):
TestConv2dMKLDNNOp.init_test_case(self)
TestConv2DMKLDNNOp.init_test_case(self)
self.filter_size = [40, 3, 1, 1]
class TestWithInput1x1Filter1x1(TestConv2dMKLDNNOp):
class TestWithInput1x1Filter1x1(TestConv2DMKLDNNOp):
def init_test_case(self):
TestConv2dMKLDNNOp.init_test_case(self)
TestConv2DMKLDNNOp.init_test_case(self)
self.input_size = [2, 60, 1, 1] # NCHW
assert np.mod(self.input_size[1], self.groups) == 0
f_c = self.input_size[1] // self.groups
......@@ -172,7 +172,7 @@ class TestWithInput1x1Filter1x1(TestConv2dMKLDNNOp):
self.groups = 3
class TestConv2dOp_AsyPadding_MKLDNN(TestConv2dOp_v2):
class TestConv2DOp_AsyPadding_MKLDNN(TestConv2DOp_v2):
def init_kernel_type(self):
self.use_mkldnn = True
self.dtype = np.float32
......@@ -182,19 +182,19 @@ class TestConv2dOp_AsyPadding_MKLDNN(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestConv2dOp_Same_MKLDNN(TestConv2dOp_AsyPadding_MKLDNN):
class TestConv2DOp_Same_MKLDNN(TestConv2DOp_AsyPadding_MKLDNN):
def init_paddings(self):
self.pad = [0, 0]
self.padding_algorithm = "SAME"
class TestConv2dOp_Valid_MKLDNN(TestConv2dOp_AsyPadding_MKLDNN):
class TestConv2DOp_Valid_MKLDNN(TestConv2DOp_AsyPadding_MKLDNN):
def init_paddings(self):
self.pad = [1, 1]
self.padding_algorithm = "VALID"
class TestConv2dOp_Valid_NHWC_MKLDNN(TestConv2dOp_Valid_MKLDNN):
class TestConv2DOp_Valid_NHWC_MKLDNN(TestConv2DOp_Valid_MKLDNN):
def init_data_format(self):
self.data_format = "NHWC"
......@@ -203,21 +203,21 @@ class TestConv2dOp_Valid_NHWC_MKLDNN(TestConv2dOp_Valid_MKLDNN):
self.input_size = [N, H, W, C]
class TestConv2dOp_Same_NHWC_MKLDNN(TestConv2dOp_Valid_NHWC_MKLDNN):
class TestConv2DOp_Same_NHWC_MKLDNN(TestConv2DOp_Valid_NHWC_MKLDNN):
def init_paddings(self):
self.pad = [0, 0]
self.padding_algorithm = "SAME"
class TestConv2dOp_AsyPadding_NHWC_MKLDNN(TestConv2dOp_Valid_NHWC_MKLDNN):
class TestConv2DOp_AsyPadding_NHWC_MKLDNN(TestConv2DOp_Valid_NHWC_MKLDNN):
def init_paddings(self):
self.pad = [0, 0, 1, 2]
self.padding_algorithm = "EXPLICIT"
class TestMKLDNNDilations(TestConv2dMKLDNNOp):
class TestMKLDNNDilations(TestConv2DMKLDNNOp):
def init_test_case(self):
TestConv2dMKLDNNOp.init_test_case(self)
TestConv2DMKLDNNOp.init_test_case(self)
self.pad = [0, 0]
self.stride = [1, 1]
self.input_size = [2, 3, 10, 10] # NCHW
......
......@@ -19,7 +19,7 @@ import numpy as np
import paddle.fluid.core as core
from paddle.fluid.tests.unittests.op_test import OpTest
from paddle.fluid.tests.unittests.test_conv2d_transpose_op import conv2dtranspose_forward_naive, TestConv2dTransposeOp
from paddle.fluid.tests.unittests.test_conv2d_transpose_op import conv2dtranspose_forward_naive, TestConv2DTransposeOp
def conv2d_bias_naive(out, bias):
......@@ -30,7 +30,7 @@ def conv2d_bias_naive(out, bias):
return out
class TestConv2dTransposeMKLDNNOp(TestConv2dTransposeOp):
class TestConv2DTransposeMKLDNNOp(TestConv2DTransposeOp):
def test_check_grad(self):
return
......@@ -64,7 +64,7 @@ class TestConv2dTransposeMKLDNNOp(TestConv2dTransposeOp):
def setUp(self):
TestConv2dTransposeOp.setUp(self)
TestConv2DTransposeOp.setUp(self)
output = self.outputs['Output']
......@@ -86,46 +86,46 @@ class TestConv2dTransposeMKLDNNOp(TestConv2dTransposeOp):
self.outputs['Output'] = output
class TestMKLDNNFuseBias(TestConv2dTransposeMKLDNNOp):
class TestMKLDNNFuseBias(TestConv2DTransposeMKLDNNOp):
def init_test_case(self):
TestConv2dTransposeMKLDNNOp.init_test_case(self)
TestConv2DTransposeMKLDNNOp.init_test_case(self)
self.pad = [1, 1]
self.fuse_bias = True
self.bias_size = [6]
class TestMKLDNNWithPad(TestConv2dTransposeMKLDNNOp):
class TestMKLDNNWithPad(TestConv2DTransposeMKLDNNOp):
def init_test_case(self):
TestConv2dTransposeMKLDNNOp.init_test_case(self)
TestConv2DTransposeMKLDNNOp.init_test_case(self)
self.pad = [1, 1]
self.input_size = [2, 3, 10, 10]
class TestMKLDNNWithStride(TestConv2dTransposeMKLDNNOp):
class TestMKLDNNWithStride(TestConv2DTransposeMKLDNNOp):
def init_test_case(self):
TestConv2dTransposeMKLDNNOp.init_test_case(self)
TestConv2DTransposeMKLDNNOp.init_test_case(self)
self.pad = [1, 1]
self.stride = [2, 2]
self.input_size = [2, 3, 6, 6] # NCHW
class TestMKLDNNWithAsymPad(TestConv2dTransposeMKLDNNOp):
class TestMKLDNNWithAsymPad(TestConv2DTransposeMKLDNNOp):
def init_test_case(self):
TestConv2dTransposeMKLDNNOp.init_test_case(self)
TestConv2DTransposeMKLDNNOp.init_test_case(self)
self.pad = [0, 0, 1, 2]
self.padding_algorithm = "EXPLICIT"
class TestMKLDNNWithSamePad(TestConv2dTransposeMKLDNNOp):
class TestMKLDNNWithSamePad(TestConv2DTransposeMKLDNNOp):
def init_test_case(self):
TestConv2dTransposeMKLDNNOp.init_test_case(self)
TestConv2DTransposeMKLDNNOp.init_test_case(self)
self.pad = [0, 0]
self.padding_algorithm = "SAME"
class TestMKLDNNWithValidPad(TestConv2dTransposeMKLDNNOp):
class TestMKLDNNWithValidPad(TestConv2DTransposeMKLDNNOp):
def init_test_case(self):
TestConv2dTransposeMKLDNNOp.init_test_case(self)
TestConv2DTransposeMKLDNNOp.init_test_case(self)
self.pad = [1, 1]
self.padding_algorithm = "VALID"
......@@ -138,10 +138,10 @@ class TestMKLDNNWithValidPad_NHWC(TestMKLDNNWithValidPad):
self.input_size = [N, H, W, C]
class TestConv2dTransposeMKLDNNWithDilationsExplicitPad(
TestConv2dTransposeMKLDNNOp):
class TestConv2DTransposeMKLDNNWithDilationsExplicitPad(
TestConv2DTransposeMKLDNNOp):
def init_test_case(self):
TestConv2dTransposeMKLDNNOp.init_test_case(self)
TestConv2DTransposeMKLDNNOp.init_test_case(self)
self.stride = [2, 1]
self.dilations = [1, 2]
self.groups = 1
......
......@@ -16,10 +16,10 @@ from __future__ import print_function
import unittest
import numpy as np
from paddle.fluid.tests.unittests.test_conv3d_op import TestConv3dOp, TestCase1, TestWithGroup1, TestWithGroup2, TestWith1x1, TestWithInput1x1Filter1x1, TestConv3dOp_2
from paddle.fluid.tests.unittests.test_conv3d_op import TestConv3DOp, TestCase1, TestWithGroup1, TestWithGroup2, TestWith1x1, TestWithInput1x1Filter1x1, TestConv3DOp_2
class TestMKLDNN(TestConv3dOp):
class TestMKLDNN(TestConv3DOp):
def init_kernel_type(self):
self.use_mkldnn = True
self.data_format = "NCHW"
......@@ -61,7 +61,7 @@ class TestMKLDNNWithInput1x1Filter1x1(TestWithInput1x1Filter1x1):
self.dtype = np.float32
class TestConv3dOp_AsyPadding_MKLDNN(TestConv3dOp):
class TestConv3DOp_AsyPadding_MKLDNN(TestConv3DOp):
def init_kernel_type(self):
self.use_mkldnn = True
self.data_format = "NCHW"
......@@ -72,7 +72,7 @@ class TestConv3dOp_AsyPadding_MKLDNN(TestConv3dOp):
self.padding_algorithm = "EXPLICIT"
class TestConv3dOp_Same_MKLDNN(TestConv3dOp_AsyPadding_MKLDNN):
class TestConv3DOp_Same_MKLDNN(TestConv3DOp_AsyPadding_MKLDNN):
def init_paddings(self):
self.pad = [0, 0, 0]
self.padding_algorithm = "SAME"
......@@ -83,7 +83,7 @@ class TestConv3dOp_Same_MKLDNN(TestConv3dOp_AsyPadding_MKLDNN):
self.dtype = np.float32
class TestConv3dOp_Valid_MKLDNN(TestConv3dOp_AsyPadding_MKLDNN):
class TestConv3DOp_Valid_MKLDNN(TestConv3DOp_AsyPadding_MKLDNN):
def init_paddings(self):
self.pad = [1, 1, 1]
self.padding_algorithm = "VALID"
......
......@@ -23,7 +23,7 @@ from paddle.fluid.tests.unittests.op_test import OpTest
from paddle.fluid.tests.unittests.test_pool2d_op import TestPool2D_Op, avg_pool2D_forward_naive, max_pool2D_forward_naive
class TestPool2dMKLDNNInt8_Op(TestPool2D_Op):
class TestPool2DMKLDNNInt8_Op(TestPool2D_Op):
def init_kernel_type(self):
self.use_mkldnn = True
......@@ -51,7 +51,7 @@ class TestPool2dMKLDNNInt8_Op(TestPool2D_Op):
pass
class TestCase1Avg(TestPool2dMKLDNNInt8_Op):
class TestCase1Avg(TestPool2DMKLDNNInt8_Op):
def init_test_case(self):
self.shape = [2, 3, 7, 7]
self.ksize = [3, 3]
......@@ -65,7 +65,7 @@ class TestCase1Avg(TestPool2dMKLDNNInt8_Op):
self.exclusive = True
class TestCase2Avg(TestPool2dMKLDNNInt8_Op):
class TestCase2Avg(TestPool2DMKLDNNInt8_Op):
def init_test_case(self):
self.shape = [2, 3, 7, 7]
self.ksize = [3, 3]
......@@ -79,7 +79,7 @@ class TestCase2Avg(TestPool2dMKLDNNInt8_Op):
self.exclusive = False
class TestCase0Max(TestPool2dMKLDNNInt8_Op):
class TestCase0Max(TestPool2DMKLDNNInt8_Op):
def init_pool_type(self):
self.pool_type = "max"
self.pool2D_forward_naive = max_pool2D_forward_naive
......@@ -114,7 +114,7 @@ def create_test_s8_u8_class(parent):
globals()[cls_name_u8] = TestU8Case
create_test_s8_u8_class(TestPool2dMKLDNNInt8_Op)
create_test_s8_u8_class(TestPool2DMKLDNNInt8_Op)
create_test_s8_u8_class(TestCase1Avg)
create_test_s8_u8_class(TestCase2Avg)
create_test_s8_u8_class(TestCase0Max)
......
......@@ -26,7 +26,7 @@ import paddle.fluid as fluid
import paddle.fluid.dygraph as dygraph
from paddle.fluid import core
from paddle.fluid.optimizer import SGDOptimizer
from paddle.nn import Conv2d, Linear, SyncBatchNorm
from paddle.nn import Conv2D, Linear, SyncBatchNorm
from paddle.fluid.dygraph.base import to_variable
from test_dist_base import runtime_main, TestParallelDyGraphRunnerBase
......@@ -42,7 +42,7 @@ class TestLayer(fluid.dygraph.Layer):
act=None):
super(TestLayer, self).__init__()
self._conv = Conv2d(
self._conv = Conv2D(
in_channels=num_channels,
out_channels=num_filters,
kernel_size=filter_size,
......@@ -53,7 +53,7 @@ class TestLayer(fluid.dygraph.Layer):
self._sync_batch_norm = SyncBatchNorm(num_filters)
self._conv2 = Conv2d(
self._conv2 = Conv2D(
in_channels=num_filters,
out_channels=num_filters,
kernel_size=filter_size,
......
......@@ -65,7 +65,7 @@ class TestParallelExecutorBase(unittest.TestCase):
feed_data_reader, FeedDataReader
), "feed_data_reader must be type of FeedDataReader"
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
main = fluid.Program()
startup = fluid.Program()
......
......@@ -259,7 +259,7 @@ class TestLSTM(unittest.TestCase):
def test_predict(self):
place = paddle.set_device(self.place)
paddle.manual_seed(123)
paddle.seed(123)
np.random.seed(123)
class Net(paddle.nn.Layer):
......
......@@ -72,7 +72,7 @@ def avg_pool1D_forward_naive(x,
return out
class TestPool1d_API(unittest.TestCase):
class TestPool1D_API(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.places = [fluid.CPUPlace()]
......@@ -89,7 +89,7 @@ class TestPool1d_API(unittest.TestCase):
self.assertTrue(np.allclose(result.numpy(), result_np))
ada_max_pool1d_dg = paddle.nn.layer.AdaptiveAvgPool1d(
ada_max_pool1d_dg = paddle.nn.layer.AdaptiveAvgPool1D(
output_size=16)
result = ada_max_pool1d_dg(input)
self.assertTrue(np.allclose(result.numpy(), result_np))
......
......@@ -84,7 +84,7 @@ def adaptive_pool2d_forward(x, output_size, data_format='NCHW',
return out
class TestAdaptiveAvgPool2dAPI(unittest.TestCase):
class TestAdaptiveAvgPool2DAPI(unittest.TestCase):
def setUp(self):
self.x_np = np.random.random([2, 3, 7, 7]).astype("float32")
self.res_1_np = adaptive_pool2d_forward(
......@@ -179,7 +179,7 @@ class TestAdaptiveAvgPool2dAPI(unittest.TestCase):
assert np.allclose(out_6.numpy(), self.res_3_np)
class TestAdaptiveAvgPool2dClassAPI(unittest.TestCase):
class TestAdaptiveAvgPool2DClassAPI(unittest.TestCase):
def setUp(self):
self.x_np = np.random.random([2, 3, 7, 7]).astype("float32")
self.res_1_np = adaptive_pool2d_forward(
......@@ -207,20 +207,20 @@ class TestAdaptiveAvgPool2dClassAPI(unittest.TestCase):
paddle.enable_static()
x = paddle.fluid.data(name="x", shape=[2, 3, 7, 7], dtype="float32")
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(output_size=[3, 3])
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(output_size=[3, 3])
out_1 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(output_size=5)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(output_size=5)
out_2 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(output_size=[2, 5])
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(output_size=[2, 5])
out_3 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(
output_size=[3, 3], data_format="NHWC")
out_4 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(
output_size=[None, 3])
out_5 = adaptive_avg_pool(x=x)
......@@ -247,20 +247,20 @@ class TestAdaptiveAvgPool2dClassAPI(unittest.TestCase):
paddle.disable_static(place=place)
x = paddle.to_tensor(self.x_np)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(output_size=[3, 3])
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(output_size=[3, 3])
out_1 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(output_size=5)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(output_size=5)
out_2 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(output_size=[2, 5])
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(output_size=[2, 5])
out_3 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(
output_size=[3, 3], data_format="NHWC")
out_4 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool2D(
output_size=[None, 3])
out_5 = adaptive_avg_pool(x=x)
......
......@@ -99,7 +99,7 @@ def adaptive_pool3d_forward(x,
return out
class TestAdaptiveAvgPool3dAPI(unittest.TestCase):
class TestAdaptiveAvgPool3DAPI(unittest.TestCase):
def setUp(self):
self.x_np = np.random.random([2, 3, 5, 7, 7]).astype("float32")
self.res_1_np = adaptive_pool3d_forward(
......@@ -125,7 +125,8 @@ class TestAdaptiveAvgPool3dAPI(unittest.TestCase):
if core.is_compiled_with_cuda() else [False]):
place = paddle.CUDAPlace(0) if use_cuda else paddle.CPUPlace()
paddle.enable_static()
x = paddle.fluid.data(name="x", shape=[2, 3, 5, 7, 7], dtype="float32")
x = paddle.fluid.data(
name="x", shape=[2, 3, 5, 7, 7], dtype="float32")
out_1 = paddle.nn.functional.adaptive_avg_pool3d(
x=x, output_size=[3, 3, 3])
......@@ -194,7 +195,7 @@ class TestAdaptiveAvgPool3dAPI(unittest.TestCase):
assert np.allclose(out_6.numpy(), self.res_3_np)
class TestAdaptiveAvgPool3dClassAPI(unittest.TestCase):
class TestAdaptiveAvgPool3DClassAPI(unittest.TestCase):
def setUp(self):
self.x_np = np.random.random([2, 3, 5, 7, 7]).astype("float32")
self.res_1_np = adaptive_pool3d_forward(
......@@ -220,24 +221,25 @@ class TestAdaptiveAvgPool3dClassAPI(unittest.TestCase):
if core.is_compiled_with_cuda() else [False]):
place = paddle.CUDAPlace(0) if use_cuda else paddle.CPUPlace()
paddle.enable_static()
x = paddle.fluid.data(name="x", shape=[2, 3, 5, 7, 7], dtype="float32")
x = paddle.fluid.data(
name="x", shape=[2, 3, 5, 7, 7], dtype="float32")
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(
output_size=[3, 3, 3])
out_1 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(output_size=5)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(output_size=5)
out_2 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(
output_size=[2, 3, 5])
out_3 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(
output_size=[3, 3, 3], data_format="NDHWC")
out_4 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(
output_size=[None, 3, None])
out_5 = adaptive_avg_pool(x=x)
......@@ -264,22 +266,22 @@ class TestAdaptiveAvgPool3dClassAPI(unittest.TestCase):
paddle.disable_static(place=place)
x = paddle.to_tensor(self.x_np)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(
output_size=[3, 3, 3])
out_1 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(output_size=5)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(output_size=5)
out_2 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(
output_size=[2, 3, 5])
out_3 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(
output_size=[3, 3, 3], data_format="NDHWC")
out_4 = adaptive_avg_pool(x=x)
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3d(
adaptive_avg_pool = paddle.nn.AdaptiveAvgPool3D(
output_size=[None, 3, None])
out_5 = adaptive_avg_pool(x=x)
......
......@@ -63,7 +63,7 @@ def max_pool1D_forward_naive(x,
return out
class TestPool1d_API(unittest.TestCase):
class TestPool1D_API(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.places = [fluid.CPUPlace()]
......@@ -80,7 +80,7 @@ class TestPool1d_API(unittest.TestCase):
input_np, ksize=[16], strides=[0], paddings=[0], adaptive=True)
self.assertTrue(np.allclose(result.numpy(), result_np))
ada_max_pool1d_dg = paddle.nn.layer.AdaptiveMaxPool1d(
ada_max_pool1d_dg = paddle.nn.layer.AdaptiveMaxPool1D(
output_size=16)
result = ada_max_pool1d_dg(input)
self.assertTrue(np.allclose(result.numpy(), result_np))
......
......@@ -84,7 +84,7 @@ def adaptive_pool2d_forward(x, output_size, data_format='NCHW',
return out
class TestAdaptiveMaxPool2dAPI(unittest.TestCase):
class TestAdaptiveMaxPool2DAPI(unittest.TestCase):
def setUp(self):
self.x_np = np.random.random([2, 3, 7, 7]).astype("float32")
self.res_1_np = adaptive_pool2d_forward(
......@@ -174,7 +174,7 @@ class TestAdaptiveMaxPool2dAPI(unittest.TestCase):
assert np.allclose(out_5.numpy(), self.res_5_np)
class TestAdaptiveMaxPool2dClassAPI(unittest.TestCase):
class TestAdaptiveMaxPool2DClassAPI(unittest.TestCase):
def setUp(self):
self.x_np = np.random.random([2, 3, 7, 7]).astype("float32")
self.res_1_np = adaptive_pool2d_forward(
......@@ -202,20 +202,20 @@ class TestAdaptiveMaxPool2dClassAPI(unittest.TestCase):
paddle.enable_static()
x = paddle.fluid.data(name="x", shape=[2, 3, 7, 7], dtype="float32")
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(output_size=[3, 3])
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(output_size=[3, 3])
out_1 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(output_size=5)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(output_size=5)
out_2 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(output_size=[2, 5])
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(output_size=[2, 5])
out_3 = adaptive_max_pool(x=x)
# adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(
# adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(
# output_size=[3, 3], data_format="NHWC")
# out_4 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(
output_size=[None, 3])
out_5 = adaptive_max_pool(x=x)
......@@ -242,20 +242,20 @@ class TestAdaptiveMaxPool2dClassAPI(unittest.TestCase):
paddle.disable_static(place=place)
x = paddle.to_tensor(self.x_np)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(output_size=[3, 3])
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(output_size=[3, 3])
out_1 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(output_size=5)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(output_size=5)
out_2 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(output_size=[2, 5])
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(output_size=[2, 5])
out_3 = adaptive_max_pool(x=x)
#adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(
#adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(
# output_size=[3, 3], data_format="NHWC")
#out_4 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2d(
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(
output_size=[None, 3])
out_5 = adaptive_max_pool(x=x)
......
......@@ -99,7 +99,7 @@ def adaptive_pool3d_forward(x,
return out
class TestAdaptiveMaxPool3dAPI(unittest.TestCase):
class TestAdaptiveMaxPool3DAPI(unittest.TestCase):
def setUp(self):
self.x_np = np.random.random([2, 3, 5, 7, 7]).astype("float32")
self.res_1_np = adaptive_pool3d_forward(
......@@ -125,7 +125,8 @@ class TestAdaptiveMaxPool3dAPI(unittest.TestCase):
if core.is_compiled_with_cuda() else [False]):
place = paddle.CUDAPlace(0) if use_cuda else paddle.CPUPlace()
paddle.enable_static()
x = paddle.fluid.data(name="x", shape=[2, 3, 5, 7, 7], dtype="float32")
x = paddle.fluid.data(
name="x", shape=[2, 3, 5, 7, 7], dtype="float32")
out_1 = paddle.nn.functional.adaptive_max_pool3d(
x=x, output_size=[3, 3, 3])
......@@ -189,7 +190,7 @@ class TestAdaptiveMaxPool3dAPI(unittest.TestCase):
assert np.allclose(out_5.numpy(), self.res_5_np)
class TestAdaptiveMaxPool3dClassAPI(unittest.TestCase):
class TestAdaptiveMaxPool3DClassAPI(unittest.TestCase):
def setUp(self):
self.x_np = np.random.random([2, 3, 5, 7, 7]).astype("float32")
self.res_1_np = adaptive_pool3d_forward(
......@@ -215,24 +216,25 @@ class TestAdaptiveMaxPool3dClassAPI(unittest.TestCase):
if core.is_compiled_with_cuda() else [False]):
place = paddle.CUDAPlace(0) if use_cuda else paddle.CPUPlace()
paddle.enable_static()
x = paddle.fluid.data(name="x", shape=[2, 3, 5, 7, 7], dtype="float32")
x = paddle.fluid.data(
name="x", shape=[2, 3, 5, 7, 7], dtype="float32")
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(
output_size=[3, 3, 3])
out_1 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(output_size=5)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(output_size=5)
out_2 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(
output_size=[2, 3, 5])
out_3 = adaptive_max_pool(x=x)
# adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(
# adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(
# output_size=[3, 3, 3], data_format="NDHWC")
# out_4 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(
output_size=[None, 3, None])
out_5 = adaptive_max_pool(x=x)
......@@ -259,22 +261,22 @@ class TestAdaptiveMaxPool3dClassAPI(unittest.TestCase):
paddle.disable_static(place=place)
x = paddle.to_tensor(self.x_np)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(
output_size=[3, 3, 3])
out_1 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(output_size=5)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(output_size=5)
out_2 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(
output_size=[2, 3, 5])
out_3 = adaptive_max_pool(x=x)
# adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(
# adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(
# output_size=[3, 3, 3], data_format="NDHWC")
# out_4 = adaptive_max_pool(x=x)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3d(
adaptive_max_pool = paddle.nn.AdaptiveMaxPool3D(
output_size=[None, 3, None])
out_5 = adaptive_max_pool(x=x)
......
......@@ -32,7 +32,7 @@ class TestBatchNorm(unittest.TestCase):
places.append(fluid.CUDAPlace(0))
for p in places:
with fluid.dygraph.guard(p):
batch_norm1d = paddle.nn.BatchNorm1d(1, name="test")
batch_norm1d = paddle.nn.BatchNorm1D(1, name="test")
def test_error(self):
places = [fluid.CPUPlace()]
......@@ -45,32 +45,32 @@ class TestBatchNorm(unittest.TestCase):
def error1d_dataformat():
x_data_4 = np.random.random(size=(2, 1, 3, 3)).astype('float32')
batch_norm1d = paddle.nn.BatchNorm1d(1, data_format='NCDHW')
batch_norm1d = paddle.nn.BatchNorm1D(1, data_format='NCDHW')
batch_norm1d(fluid.dygraph.to_variable(x_data_4))
def error2d_dataformat():
x_data_3 = np.random.random(size=(2, 1, 3)).astype('float32')
batch_norm2d = paddle.nn.BatchNorm2d(1, data_format='NCDHW')
batch_norm2d = paddle.nn.BatchNorm2D(1, data_format='NCDHW')
batch_norm2d(fluid.dygraph.to_variable(x_data_3))
def error3d_dataformat():
x_data_4 = np.random.random(size=(2, 1, 3, 3)).astype('float32')
batch_norm3d = paddle.nn.BatchNorm3d(1, data_format='NCL')
batch_norm3d = paddle.nn.BatchNorm3D(1, data_format='NCL')
batch_norm3d(fluid.dygraph.to_variable(x_data_4))
def error1d():
x_data_4 = np.random.random(size=(2, 1, 3, 3)).astype('float32')
batch_norm1d = paddle.nn.BatchNorm1d(1)
batch_norm1d = paddle.nn.BatchNorm1D(1)
batch_norm1d(fluid.dygraph.to_variable(x_data_4))
def error2d():
x_data_3 = np.random.random(size=(2, 1, 3)).astype('float32')
batch_norm2d = paddle.nn.BatchNorm2d(1)
batch_norm2d = paddle.nn.BatchNorm2D(1)
batch_norm2d(fluid.dygraph.to_variable(x_data_3))
def error3d():
x_data_4 = np.random.random(size=(2, 1, 3, 3)).astype('float32')
batch_norm3d = paddle.nn.BatchNorm3d(1)
batch_norm3d = paddle.nn.BatchNorm3D(1)
batch_norm3d(fluid.dygraph.to_variable(x_data_4))
with fluid.dygraph.guard(p):
......@@ -99,7 +99,7 @@ class TestBatchNorm(unittest.TestCase):
def compute_v2(x):
with fluid.dygraph.guard(p):
bn = paddle.nn.BatchNorm2d(shape[1])
bn = paddle.nn.BatchNorm2D(shape[1])
y = bn(fluid.dygraph.to_variable(x))
return y.numpy()
......@@ -120,7 +120,7 @@ class TestBatchNorm(unittest.TestCase):
def compute_v4(x):
with fluid.dygraph.guard(p):
bn = paddle.nn.BatchNorm2d(
bn = paddle.nn.BatchNorm2D(
shape[1], weight_attr=False, bias_attr=False)
y = bn(fluid.dygraph.to_variable(x))
return y.numpy()
......@@ -155,7 +155,7 @@ class TestBatchNorm(unittest.TestCase):
def compute_v2(x_np):
with program_guard(Program(), Program()):
bn = paddle.nn.BatchNorm2d(shape[1])
bn = paddle.nn.BatchNorm2D(shape[1])
x = fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
y = bn(x)
exe.run(fluid.default_startup_program())
......@@ -183,8 +183,8 @@ class TestBatchNormChannelLast(unittest.TestCase):
for p in self.places:
with fluid.dygraph.guard(p):
x = paddle.randn([2, 6, 4])
net1 = paddle.nn.BatchNorm1d(4, data_format="NLC")
net2 = paddle.nn.BatchNorm1d(4)
net1 = paddle.nn.BatchNorm1D(4, data_format="NLC")
net2 = paddle.nn.BatchNorm1D(4)
net2.weight = net1.weight
net2.bias = net1.bias
y1 = net1(x)
......@@ -197,8 +197,8 @@ class TestBatchNormChannelLast(unittest.TestCase):
for p in self.places:
with fluid.dygraph.guard(p):
x = paddle.randn([2, 6, 6, 4])
net1 = paddle.nn.BatchNorm2d(4, data_format="NHWC")
net2 = paddle.nn.BatchNorm2d(4)
net1 = paddle.nn.BatchNorm2D(4, data_format="NHWC")
net2 = paddle.nn.BatchNorm2D(4)
net2.weight = net1.weight
net2.bias = net1.bias
y1 = net1(x)
......@@ -211,8 +211,8 @@ class TestBatchNormChannelLast(unittest.TestCase):
for p in self.places:
with fluid.dygraph.guard(p):
x = paddle.randn([2, 6, 6, 6, 4])
net1 = paddle.nn.BatchNorm3d(4, data_format="NDHWC")
net2 = paddle.nn.BatchNorm3d(4)
net1 = paddle.nn.BatchNorm3D(4, data_format="NDHWC")
net2 = paddle.nn.BatchNorm3D(4)
net2.weight = net1.weight
net2.bias = net1.bias
y1 = net1(x)
......
......@@ -47,7 +47,7 @@ class InplaceTestBase(unittest.TestCase):
def build_program_and_scope(self):
self.place = fluid.CUDAPlace(0) if self.use_cuda else fluid.CPUPlace()
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
startup_program = fluid.Program()
main_program = fluid.Program()
......
......@@ -30,7 +30,7 @@ class TestCompiledProgram(unittest.TestCase):
self.label = np.random.randint(
low=0, high=10, size=[16, 1], dtype=np.int64)
with new_program_scope():
paddle.manual_seed(self.seed)
paddle.seed(self.seed)
paddle.framework.random._manual_program_seed(self.seed)
place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
) else fluid.CPUPlace()
......@@ -47,7 +47,7 @@ class TestCompiledProgram(unittest.TestCase):
def test_compiled_program_base(self):
with new_program_scope():
paddle.manual_seed(self.seed)
paddle.seed(self.seed)
paddle.framework.random._manual_program_seed(self.seed)
place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
) else fluid.CPUPlace()
......@@ -65,7 +65,7 @@ class TestCompiledProgram(unittest.TestCase):
def test_compiled_program_with_data_parallel(self):
with new_program_scope():
paddle.manual_seed(self.seed)
paddle.seed(self.seed)
paddle.framework.random._manual_program_seed(self.seed)
place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
) else fluid.CPUPlace()
......
......@@ -21,7 +21,7 @@ import paddle.fluid.initializer as I
import unittest
class Conv1dTestCase(unittest.TestCase):
class Conv1DTestCase(unittest.TestCase):
def __init__(self,
methodName='runTest',
batch_size=4,
......@@ -37,7 +37,7 @@ class Conv1dTestCase(unittest.TestCase):
no_bias=False,
dtype="float32",
data_format="NCL"):
super(Conv1dTestCase, self).__init__(methodName)
super(Conv1DTestCase, self).__init__(methodName)
self.batch_size = batch_size
self.num_channels = num_channels
self.num_filters = num_filters
......@@ -107,7 +107,7 @@ class Conv1dTestCase(unittest.TestCase):
def paddle_nn_layer(self):
x_var = paddle.to_tensor(self.input)
conv = nn.Conv1d(
conv = nn.Conv1D(
self.num_channels,
self.num_filters,
self.filter_size,
......@@ -139,7 +139,7 @@ class Conv1dTestCase(unittest.TestCase):
self._test_equivalence(place)
class Conv1dErrorTestCase(Conv1dTestCase):
class Conv1DErrorTestCase(Conv1DTestCase):
def runTest(self):
place = fluid.CPUPlace()
with dg.guard(place):
......@@ -147,7 +147,7 @@ class Conv1dErrorTestCase(Conv1dTestCase):
self.paddle_nn_layer()
class Conv1dTypeErrorTestCase(Conv1dTestCase):
class Conv1DTypeErrorTestCase(Conv1DTestCase):
def runTest(self):
place = fluid.CPUPlace()
with dg.guard(place):
......@@ -156,27 +156,27 @@ class Conv1dTypeErrorTestCase(Conv1dTestCase):
def add_cases(suite):
suite.addTest(Conv1dTestCase(methodName='runTest'))
suite.addTest(Conv1dTestCase(methodName='runTest', stride=[1], dilation=2))
suite.addTest(Conv1dTestCase(methodName='runTest', stride=2, dilation=(1)))
suite.addTest(Conv1DTestCase(methodName='runTest'))
suite.addTest(Conv1DTestCase(methodName='runTest', stride=[1], dilation=2))
suite.addTest(Conv1DTestCase(methodName='runTest', stride=2, dilation=(1)))
suite.addTest(
Conv1dTestCase(
Conv1DTestCase(
methodName='runTest', padding="same", no_bias=True))
suite.addTest(
Conv1dTestCase(
Conv1DTestCase(
methodName='runTest', filter_size=3, padding='valid'))
suite.addTest(
Conv1dTestCase(
Conv1DTestCase(
methodName='runTest', padding=2, data_format='NLC'))
suite.addTest(Conv1dTestCase(methodName='runTest', padding=[1]))
suite.addTest(Conv1dTestCase(methodName='runTest', padding=[1, 2]))
suite.addTest(Conv1dTestCase(methodName='runTest', padding=2))
suite.addTest(Conv1dTestCase(methodName='runTest'))
suite.addTest(Conv1DTestCase(methodName='runTest', padding=[1]))
suite.addTest(Conv1DTestCase(methodName='runTest', padding=[1, 2]))
suite.addTest(Conv1DTestCase(methodName='runTest', padding=2))
suite.addTest(Conv1DTestCase(methodName='runTest'))
suite.addTest(
Conv1dTestCase(
Conv1DTestCase(
methodName='runTest', groups=2, padding="valid"))
suite.addTest(
Conv1dTestCase(
Conv1DTestCase(
methodName='runTest',
num_filters=6,
num_channels=3,
......@@ -187,22 +187,22 @@ def add_cases(suite):
def add_error_cases(suite):
suite.addTest(
Conv1dTypeErrorTestCase(
Conv1DTypeErrorTestCase(
methodName='runTest', padding_mode="reflect", padding="valid"))
suite.addTest(
Conv1dErrorTestCase(
Conv1DErrorTestCase(
methodName='runTest', data_format="VALID"))
suite.addTest(
Conv1dErrorTestCase(
Conv1DErrorTestCase(
methodName='runTest', padding_mode="VALID"))
suite.addTest(
Conv1dErrorTestCase(
Conv1DErrorTestCase(
methodName='runTest', num_channels=5, groups=2))
suite.addTest(
Conv1dErrorTestCase(
Conv1DErrorTestCase(
methodName='runTest', num_filters=8, num_channels=15, groups=3))
suite.addTest(
Conv1dErrorTestCase(
Conv1DErrorTestCase(
methodName='runTest', padding=[1, 2, 3, 4, 5]))
......
......@@ -21,7 +21,7 @@ import paddle.fluid.initializer as I
import unittest
class ConvTranspose1dTestCase(unittest.TestCase):
class Conv1DTransposeTestCase(unittest.TestCase):
def __init__(self,
methodName='runTest',
batch_size=4,
......@@ -38,7 +38,7 @@ class ConvTranspose1dTestCase(unittest.TestCase):
no_bias=False,
data_format="NCL",
dtype="float32"):
super(ConvTranspose1dTestCase, self).__init__(methodName)
super(Conv1DTransposeTestCase, self).__init__(methodName)
self.batch_size = batch_size
self.in_channels = in_channels
self.out_channels = out_channels
......@@ -113,7 +113,7 @@ class ConvTranspose1dTestCase(unittest.TestCase):
def paddle_nn_layer(self):
x_var = paddle.to_tensor(self.input)
conv = nn.ConvTranspose1d(
conv = nn.Conv1DTranspose(
self.in_channels,
self.out_channels,
self.filter_size,
......@@ -145,7 +145,7 @@ class ConvTranspose1dTestCase(unittest.TestCase):
self._test_equivalence(place)
class ConvTranspose1dErrorTestCase(ConvTranspose1dTestCase):
class Conv1DTransposeErrorTestCase(Conv1DTransposeTestCase):
def runTest(self):
place = fluid.CPUPlace()
with dg.guard(place):
......@@ -154,68 +154,68 @@ class ConvTranspose1dErrorTestCase(ConvTranspose1dTestCase):
def add_cases(suite):
suite.addTest(ConvTranspose1dTestCase(methodName='runTest'))
suite.addTest(Conv1DTransposeTestCase(methodName='runTest'))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest', stride=[2], no_bias=True, dilation=2))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest',
filter_size=(3),
output_size=[36],
stride=[2],
dilation=2))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest', stride=2, dilation=(2)))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest', padding="valid"))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest', padding='valid'))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest', filter_size=1, padding=3))
suite.addTest(ConvTranspose1dTestCase(methodName='runTest', padding=[2]))
suite.addTest(Conv1DTransposeTestCase(methodName='runTest', padding=[2]))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest', data_format="NLC"))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest', groups=2, padding="valid"))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest',
out_channels=6,
in_channels=3,
groups=3,
padding="valid"))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest',
data_format="NLC",
spartial_shape=16,
output_size=18))
suite.addTest(
ConvTranspose1dTestCase(
Conv1DTransposeTestCase(
methodName='runTest', data_format="NLC", stride=3,
output_padding=2))
suite.addTest(ConvTranspose1dTestCase(methodName='runTest', padding=[1, 2]))
suite.addTest(Conv1DTransposeTestCase(methodName='runTest', padding=[1, 2]))
def add_error_cases(suite):
suite.addTest(
ConvTranspose1dErrorTestCase(
Conv1DTransposeErrorTestCase(
methodName='runTest', data_format="not_valid"))
suite.addTest(
ConvTranspose1dErrorTestCase(
Conv1DTransposeErrorTestCase(
methodName='runTest', in_channels=5, groups=2))
suite.addTest(
ConvTranspose1dErrorTestCase(
Conv1DTransposeErrorTestCase(
methodName='runTest', stride=2, output_padding=3))
suite.addTest(
ConvTranspose1dErrorTestCase(
Conv1DTransposeErrorTestCase(
methodName='runTest', output_size="not_valid"))
......
......@@ -45,7 +45,7 @@ def create_test_padding_VALID_class(parent):
globals()[cls_name] = TestPaddingVALIDCase
class TestConv2dFusionOp(OpTest):
class TestConv2DFusionOp(OpTest):
def setUp(self):
self.op_type = "conv2d_fusion"
self.exhaustive_search = False
......@@ -157,28 +157,28 @@ class TestConv2dFusionOp(OpTest):
self.padding_algorithm = "EXPLICIT"
class TestWithoutResidual(TestConv2dFusionOp):
class TestWithoutResidual(TestConv2DFusionOp):
def init_residual(self):
self.add_residual_data = False
class TestIdentityActivation(TestConv2dFusionOp):
class TestIdentityActivation(TestConv2DFusionOp):
def init_activation(self):
self.activation = 'identity'
class TestIdentityActivation(TestConv2dFusionOp):
class TestIdentityActivation(TestConv2DFusionOp):
def init_activation(self):
self.activation = 'identity'
self.add_residual_data = False
class TestWithGroup(TestConv2dFusionOp):
class TestWithGroup(TestConv2DFusionOp):
def init_group(self):
self.groups = 3
class TestWithDilation(TestConv2dFusionOp):
class TestWithDilation(TestConv2DFusionOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -194,12 +194,12 @@ class TestWithDilation(TestConv2dFusionOp):
self.groups = 3
class TestCUDNNExhaustiveSearch(TestConv2dFusionOp):
class TestCUDNNExhaustiveSearch(TestConv2DFusionOp):
def set_search_method(self):
self.exhaustive_search = True
class TestMultipleOutputs(TestConv2dFusionOp):
class TestMultipleOutputs(TestConv2DFusionOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -215,13 +215,13 @@ class TestMultipleOutputs(TestConv2dFusionOp):
self.outputs['Outputs'] = [('out1', out1), ('out2', out2)]
class TestAsyPadding(TestConv2dFusionOp):
class TestAsyPadding(TestConv2DFusionOp):
def init_paddings(self):
self.pad = [0, 0, 1, 2]
self.padding_algorithm = "EXPLICIT"
class TestWithPad_AsyPadding(TestConv2dFusionOp):
class TestWithPad_AsyPadding(TestConv2DFusionOp):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 3, 10, 10] # NCHW
......@@ -234,7 +234,7 @@ class TestWithPad_AsyPadding(TestConv2dFusionOp):
self.padding_algorithm = "EXPLICIT"
class TestWithStride_AsyPadding(TestConv2dFusionOp):
class TestWithStride_AsyPadding(TestConv2DFusionOp):
def init_test_case(self):
self.stride = [2, 2]
self.input_size = [2, 3, 6, 6] # NCHW
......@@ -247,7 +247,7 @@ class TestWithStride_AsyPadding(TestConv2dFusionOp):
self.padding_algorithm = "EXPLICIT"
class TestWith1x1_AsyPadding(TestConv2dFusionOp):
class TestWith1x1_AsyPadding(TestConv2DFusionOp):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 3, 5, 5] # NCHW
......@@ -263,12 +263,12 @@ class TestWith1x1_AsyPadding(TestConv2dFusionOp):
self.padding_algorithm = "EXPLICIT"
class TestWithGroup_AsyPadding(TestConv2dFusionOp):
class TestWithGroup_AsyPadding(TestConv2DFusionOp):
def init_group(self):
self.groups = 3
class TestWithDepthWise3x3_AsyPadding(TestConv2dFusionOp):
class TestWithDepthWise3x3_AsyPadding(TestConv2DFusionOp):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [3, 4, 10, 10] # NCHW
......@@ -287,7 +287,7 @@ class TestWithDepthWise3x3_AsyPadding(TestConv2dFusionOp):
self.padding_algorithm = "EXPLICIT"
class TestWithDepthWise5x5_AsyPadding(TestConv2dFusionOp):
class TestWithDepthWise5x5_AsyPadding(TestConv2DFusionOp):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 4, 10, 10] # NCHW
......@@ -303,7 +303,7 @@ class TestWithDepthWise5x5_AsyPadding(TestConv2dFusionOp):
self.padding_algorithm = "EXPLICIT"
class TestWithDepthWise7x7_AsyPadding(TestConv2dFusionOp):
class TestWithDepthWise7x7_AsyPadding(TestConv2DFusionOp):
def init_test_case(self):
self.stride = [2, 2]
self.input_size = [2, 8, 10, 10] # NCHW
......@@ -319,7 +319,7 @@ class TestWithDepthWise7x7_AsyPadding(TestConv2dFusionOp):
self.padding_algorithm = "EXPLICIT"
class TestWithDilation_AsyPadding(TestConv2dFusionOp):
class TestWithDilation_AsyPadding(TestConv2DFusionOp):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 3, 10, 10] # NCHW
......@@ -338,7 +338,7 @@ class TestWithDilation_AsyPadding(TestConv2dFusionOp):
self.padding_algorithm = "EXPLICIT"
class TestWithInput1x1Filter1x1_AsyPadding(TestConv2dFusionOp):
class TestWithInput1x1Filter1x1_AsyPadding(TestConv2DFusionOp):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 3, 1, 1] # NCHW
......
......@@ -166,7 +166,7 @@ class Conv2DTestCase(unittest.TestCase):
def paddle_nn_layer(self):
x_var = dg.to_variable(self.input)
conv = nn.Conv2d(
conv = nn.Conv2D(
self.num_channels,
self.num_filters,
self.filter_size,
......
......@@ -289,7 +289,7 @@ def create_test_cudnn_padding_VALID_class(parent):
globals()[cls_name] = TestCUDNNPaddingVALIDCase
class TestConv2dOp(OpTest):
class TestConv2DOp(OpTest):
def setUp(self):
self.op_type = "conv2d"
self.use_cudnn = False
......@@ -412,7 +412,7 @@ class TestConv2dOp(OpTest):
pass
class TestWithPad(TestConv2dOp):
class TestWithPad(TestConv2DOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -422,7 +422,7 @@ class TestWithPad(TestConv2dOp):
self.filter_size = [6, f_c, 3, 3]
class TestWithStride(TestConv2dOp):
class TestWithStride(TestConv2DOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -432,7 +432,7 @@ class TestWithStride(TestConv2dOp):
self.filter_size = [6, f_c, 3, 3]
class TestWithGroup(TestConv2dOp):
class TestWithGroup(TestConv2DOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -443,7 +443,7 @@ class TestWithGroup(TestConv2dOp):
self.filter_size = [18, f_c, 3, 3]
class TestWith1x1(TestConv2dOp):
class TestWith1x1(TestConv2DOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -456,7 +456,7 @@ class TestWith1x1(TestConv2dOp):
self.groups = 3
class TestWithDepthWise3x3(TestConv2dOp):
class TestWithDepthWise3x3(TestConv2DOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -472,7 +472,7 @@ class TestWithDepthWise3x3(TestConv2dOp):
self.groups = 4
class TestWithDepthWise5x5(TestConv2dOp):
class TestWithDepthWise5x5(TestConv2DOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -485,7 +485,7 @@ class TestWithDepthWise5x5(TestConv2dOp):
self.groups = 4
class TestWithDepthWise7x7(TestConv2dOp):
class TestWithDepthWise7x7(TestConv2DOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -498,7 +498,7 @@ class TestWithDepthWise7x7(TestConv2dOp):
self.groups = 8
class TestWithDilation(TestConv2dOp):
class TestWithDilation(TestConv2DOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -514,7 +514,7 @@ class TestWithDilation(TestConv2dOp):
self.groups = 3
class TestWithInput1x1Filter1x1(TestConv2dOp):
class TestWithInput1x1Filter1x1(TestConv2DOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -527,18 +527,18 @@ class TestWithInput1x1Filter1x1(TestConv2dOp):
self.groups = 3
#----------------Conv2dCUDNN----------------
#----------------Conv2DCUDNN----------------
create_test_cudnn_class(TestConv2dOp)
create_test_cudnn_class(TestConv2DOp)
create_test_cudnn_class(TestWithPad)
create_test_cudnn_class(TestWithStride)
create_test_cudnn_class(TestWithGroup)
create_test_cudnn_class(TestWith1x1)
create_test_cudnn_class(TestWithInput1x1Filter1x1)
#----------------Conv2dCUDNN fp16----------------
#----------------Conv2DCUDNN fp16----------------
create_test_cudnn_fp16_class(TestConv2dOp, grad_check=False)
create_test_cudnn_fp16_class(TestConv2DOp, grad_check=False)
create_test_cudnn_fp16_class(TestWithPad, grad_check=False)
create_test_cudnn_fp16_class(TestWithStride, grad_check=False)
create_test_cudnn_fp16_class(TestWithGroup, grad_check=False)
......@@ -548,7 +548,7 @@ create_test_cudnn_fp16_class(TestWithInput1x1Filter1x1, grad_check=False)
#----------------TestDepthwiseConv -----
class TestDepthwiseConv(TestConv2dOp):
class TestDepthwiseConv(TestConv2DOp):
def init_test_case(self):
self.use_cuda = True
self.pad = [1, 1]
......@@ -561,7 +561,7 @@ class TestDepthwiseConv(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConv2(TestConv2dOp):
class TestDepthwiseConv2(TestConv2DOp):
def init_test_case(self):
self.use_cuda = True
self.pad = [1, 1]
......@@ -574,7 +574,7 @@ class TestDepthwiseConv2(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConv3(TestConv2dOp):
class TestDepthwiseConv3(TestConv2DOp):
def init_test_case(self):
self.use_cuda = True
self.pad = [1, 1]
......@@ -587,7 +587,7 @@ class TestDepthwiseConv3(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConvWithDilation(TestConv2dOp):
class TestDepthwiseConvWithDilation(TestConv2DOp):
def init_test_case(self):
self.use_cuda = True
self.pad = [1, 1]
......@@ -601,7 +601,7 @@ class TestDepthwiseConvWithDilation(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConvWithDilation2(TestConv2dOp):
class TestDepthwiseConvWithDilation2(TestConv2DOp):
def init_test_case(self):
self.use_cuda = True
self.pad = [1, 1]
......@@ -615,7 +615,7 @@ class TestDepthwiseConvWithDilation2(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConvandFuse(TestConv2dOp):
class TestDepthwiseConvandFuse(TestConv2DOp):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -629,7 +629,7 @@ class TestDepthwiseConvandFuse(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConv2andFuse(TestConv2dOp):
class TestDepthwiseConv2andFuse(TestConv2DOp):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -643,7 +643,7 @@ class TestDepthwiseConv2andFuse(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConv3andFuse(TestConv2dOp):
class TestDepthwiseConv3andFuse(TestConv2DOp):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -657,7 +657,7 @@ class TestDepthwiseConv3andFuse(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConvWithDilationandFuse(TestConv2dOp):
class TestDepthwiseConvWithDilationandFuse(TestConv2DOp):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -672,7 +672,7 @@ class TestDepthwiseConvWithDilationandFuse(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestDepthwiseConvWithDilation2andFuse(TestConv2dOp):
class TestDepthwiseConvWithDilation2andFuse(TestConv2DOp):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -687,13 +687,13 @@ class TestDepthwiseConvWithDilation2andFuse(TestConv2dOp):
self.op_type = "depthwise_conv2d"
class TestCUDNNExhaustiveSearch(TestConv2dOp):
class TestCUDNNExhaustiveSearch(TestConv2DOp):
def init_kernel_type(self):
self.use_cudnn = True
self.exhaustive_search = True
class TestConv2dOpError(unittest.TestCase):
class TestConv2DOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
......@@ -724,7 +724,7 @@ class TestConv2dOpError(unittest.TestCase):
# ---- test asymmetric padding ----
class TestConv2dOp_v2(OpTest):
class TestConv2DOp_v2(OpTest):
def setUp(self):
self.op_type = "conv2d"
self.use_cudnn = False
......@@ -854,13 +854,13 @@ class TestConv2dOp_v2(OpTest):
pass
class TestConv2dOp_AsyPadding(TestConv2dOp_v2):
class TestConv2DOp_AsyPadding(TestConv2DOp_v2):
def init_paddings(self):
self.pad = [0, 0, 1, 2]
self.padding_algorithm = "EXPLICIT"
class TestWithPad_AsyPadding(TestConv2dOp_v2):
class TestWithPad_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 3, 5, 5] # NCHW
......@@ -873,7 +873,7 @@ class TestWithPad_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestWithStride_AsyPadding(TestConv2dOp_v2):
class TestWithStride_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.stride = [2, 2]
self.input_size = [2, 3, 6, 6] # NCHW
......@@ -886,7 +886,7 @@ class TestWithStride_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestWithGroup_AsyPadding(TestConv2dOp_v2):
class TestWithGroup_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 2]
......@@ -897,7 +897,7 @@ class TestWithGroup_AsyPadding(TestConv2dOp_v2):
self.filter_size = [24, f_c, 4, 3]
class TestWith1x1_AsyPadding(TestConv2dOp_v2):
class TestWith1x1_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 3, 5, 5] # NCHW
......@@ -913,7 +913,7 @@ class TestWith1x1_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestWithDepthWise3x3_AsyPadding(TestConv2dOp_v2):
class TestWithDepthWise3x3_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [3, 4, 10, 10] # NCHW
......@@ -932,7 +932,7 @@ class TestWithDepthWise3x3_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestWithDepthWise5x5_AsyPadding(TestConv2dOp_v2):
class TestWithDepthWise5x5_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 4, 10, 10] # NCHW
......@@ -948,7 +948,7 @@ class TestWithDepthWise5x5_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestWithDepthWise7x7_AsyPadding(TestConv2dOp_v2):
class TestWithDepthWise7x7_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.stride = [2, 2]
self.input_size = [2, 8, 10, 10] # NCHW
......@@ -964,7 +964,7 @@ class TestWithDepthWise7x7_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestWithDilation_AsyPadding(TestConv2dOp_v2):
class TestWithDilation_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [2, 3, 10, 10] # NCHW
......@@ -983,7 +983,7 @@ class TestWithDilation_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestWithInput1x1Filter1x1_AsyPadding(TestConv2dOp_v2):
class TestWithInput1x1Filter1x1_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.stride = [1, 1]
self.input_size = [40, 3, 1, 1] # NCHW
......@@ -999,7 +999,7 @@ class TestWithInput1x1Filter1x1_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
create_test_cudnn_class(TestConv2dOp_AsyPadding)
create_test_cudnn_class(TestConv2DOp_AsyPadding)
create_test_cudnn_class(TestWithPad_AsyPadding)
create_test_cudnn_class(TestWithStride_AsyPadding)
create_test_cudnn_class(TestWithGroup_AsyPadding)
......@@ -1007,7 +1007,7 @@ create_test_cudnn_class(TestWith1x1_AsyPadding)
create_test_cudnn_class(TestWithInput1x1Filter1x1_AsyPadding)
class TestDepthwiseConv_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConv_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.use_cuda = True
self.stride = [2, 2]
......@@ -1023,7 +1023,7 @@ class TestDepthwiseConv_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConv2_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConv2_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.use_cuda = True
self.stride = [1, 1]
......@@ -1039,7 +1039,7 @@ class TestDepthwiseConv2_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConv3_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConv3_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.use_cuda = True
self.stride = [1, 1]
......@@ -1055,7 +1055,7 @@ class TestDepthwiseConv3_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConvWithDilation_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConvWithDilation_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.use_cuda = True
self.pad = [1, 1]
......@@ -1073,7 +1073,7 @@ class TestDepthwiseConvWithDilation_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConvWithDilation2_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConvWithDilation2_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.use_cuda = True
self.pad = [1, 1]
......@@ -1091,7 +1091,7 @@ class TestDepthwiseConvWithDilation2_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConvandFuse_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConvandFuse_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -1109,7 +1109,7 @@ class TestDepthwiseConvandFuse_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConv2andFuse_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConv2andFuse_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -1127,7 +1127,7 @@ class TestDepthwiseConv2andFuse_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConv3andFuse_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConv3andFuse_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -1145,7 +1145,7 @@ class TestDepthwiseConv3andFuse_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConvWithDilationandFuse_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConvWithDilationandFuse_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -1164,7 +1164,7 @@ class TestDepthwiseConvWithDilationandFuse_AsyPadding(TestConv2dOp_v2):
self.padding_algorithm = "EXPLICIT"
class TestDepthwiseConvWithDilation2andFuse_AsyPadding(TestConv2dOp_v2):
class TestDepthwiseConvWithDilation2andFuse_AsyPadding(TestConv2DOp_v2):
def init_test_case(self):
self.fuse_relu_before_depthwise_conv = True
self.use_cuda = True
......@@ -1184,25 +1184,25 @@ class TestDepthwiseConvWithDilation2andFuse_AsyPadding(TestConv2dOp_v2):
#---------- test SAME VALID -----------
create_test_padding_SAME_class(TestConv2dOp_AsyPadding)
create_test_padding_SAME_class(TestConv2DOp_AsyPadding)
create_test_padding_SAME_class(TestWithPad_AsyPadding)
create_test_padding_SAME_class(TestWithStride_AsyPadding)
create_test_padding_SAME_class(TestWithGroup_AsyPadding)
create_test_padding_SAME_class(TestWithInput1x1Filter1x1_AsyPadding)
create_test_padding_VALID_class(TestConv2dOp_AsyPadding)
create_test_padding_VALID_class(TestConv2DOp_AsyPadding)
create_test_padding_VALID_class(TestWithPad_AsyPadding)
create_test_padding_VALID_class(TestWithStride_AsyPadding)
create_test_padding_VALID_class(TestWithGroup_AsyPadding)
create_test_padding_VALID_class(TestWithInput1x1Filter1x1_AsyPadding)
create_test_cudnn_padding_SAME_class(TestConv2dOp_AsyPadding)
create_test_cudnn_padding_SAME_class(TestConv2DOp_AsyPadding)
create_test_cudnn_padding_SAME_class(TestWithPad_AsyPadding)
create_test_cudnn_padding_SAME_class(TestWithStride_AsyPadding)
create_test_cudnn_padding_SAME_class(TestWithGroup_AsyPadding)
create_test_cudnn_padding_SAME_class(TestWithInput1x1Filter1x1_AsyPadding)
create_test_cudnn_padding_VALID_class(TestConv2dOp_AsyPadding)
create_test_cudnn_padding_VALID_class(TestConv2DOp_AsyPadding)
create_test_cudnn_padding_VALID_class(TestWithPad_AsyPadding)
create_test_cudnn_padding_VALID_class(TestWithStride_AsyPadding)
create_test_cudnn_padding_VALID_class(TestWithGroup_AsyPadding)
......@@ -1221,7 +1221,7 @@ create_test_padding_VALID_class(TestDepthwiseConvandFuse_AsyPadding)
create_test_padding_VALID_class(TestDepthwiseConvWithDilationandFuse_AsyPadding)
# ------------ test channel last ---------
create_test_channel_last_class(TestConv2dOp_AsyPadding)
create_test_channel_last_class(TestConv2DOp_AsyPadding)
create_test_channel_last_class(TestWithPad_AsyPadding)
create_test_channel_last_class(TestWithGroup_AsyPadding)
create_test_channel_last_class(TestWith1x1_AsyPadding)
......@@ -1232,14 +1232,14 @@ create_test_channel_last_class(TestDepthwiseConvWithDilation2_AsyPadding)
create_test_channel_last_class(TestDepthwiseConvandFuse_AsyPadding)
create_test_channel_last_class(TestDepthwiseConvWithDilationandFuse_AsyPadding)
create_test_cudnn_channel_last_class(TestConv2dOp_AsyPadding)
create_test_cudnn_channel_last_class(TestConv2DOp_AsyPadding)
create_test_cudnn_channel_last_class(TestWithPad_AsyPadding)
create_test_cudnn_channel_last_class(TestWithStride_AsyPadding)
create_test_cudnn_channel_last_class(TestWithGroup_AsyPadding)
create_test_cudnn_channel_last_class(TestWithDilation_AsyPadding)
create_test_cudnn_channel_last_fp16_class(
TestConv2dOp_AsyPadding, grad_check=False)
TestConv2DOp_AsyPadding, grad_check=False)
create_test_cudnn_channel_last_fp16_class(
TestWithPad_AsyPadding, grad_check=False)
create_test_cudnn_channel_last_fp16_class(
......@@ -1251,7 +1251,7 @@ create_test_cudnn_channel_last_fp16_class(
# --------- test python API ---------------
class TestConv2dAPI(unittest.TestCase):
class TestConv2DAPI(unittest.TestCase):
def test_api(self):
input_NHWC = fluid.layers.data(
......@@ -1327,7 +1327,7 @@ class TestConv2dAPI(unittest.TestCase):
data_format="NCHW")
class TestConv2dAPI_Error(unittest.TestCase):
class TestConv2DAPI_Error(unittest.TestCase):
def test_api(self):
input = fluid.layers.data(
name="input",
......
......@@ -155,7 +155,7 @@ class Conv2DTransposeTestCase(unittest.TestCase):
else:
output_size = self.output_size
conv = nn.ConvTranspose2d(
conv = nn.Conv2DTranspose(
self.num_channels,
self.num_filters,
self.filter_size,
......
......@@ -111,7 +111,7 @@ def conv2dtranspose_forward_naive(input_, filter_, attrs):
return out
class TestConv2dTransposeOp(OpTest):
class TestConv2DTransposeOp(OpTest):
def setUp(self):
# init as conv transpose
self.dtype = np.float64
......@@ -211,7 +211,7 @@ class TestConv2dTransposeOp(OpTest):
self.op_type = "conv2d_transpose"
class TestWithSymmetricPad(TestConv2dTransposeOp):
class TestWithSymmetricPad(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -222,7 +222,7 @@ class TestWithSymmetricPad(TestConv2dTransposeOp):
self.filter_size = [f_c, 6, 3, 3]
class TestWithAsymmetricPad(TestConv2dTransposeOp):
class TestWithAsymmetricPad(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 0, 1, 2]
self.stride = [1, 1]
......@@ -233,7 +233,7 @@ class TestWithAsymmetricPad(TestConv2dTransposeOp):
self.filter_size = [f_c, 6, 3, 3]
class TestWithSAMEPad(TestConv2dTransposeOp):
class TestWithSAMEPad(TestConv2DTransposeOp):
def init_test_case(self):
self.stride = [2, 1]
self.dilations = [1, 2]
......@@ -244,7 +244,7 @@ class TestWithSAMEPad(TestConv2dTransposeOp):
self.padding_algorithm = 'SAME'
class TestWithVALIDPad(TestConv2dTransposeOp):
class TestWithVALIDPad(TestConv2DTransposeOp):
def init_test_case(self):
self.stride = [1, 1]
self.dilations = [1, 1]
......@@ -255,7 +255,7 @@ class TestWithVALIDPad(TestConv2dTransposeOp):
self.padding_algorithm = 'VALID'
class TestWithGroups(TestConv2dTransposeOp):
class TestWithGroups(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -266,7 +266,7 @@ class TestWithGroups(TestConv2dTransposeOp):
self.filter_size = [f_c, 3, 3, 3]
class TestWithStride(TestConv2dTransposeOp):
class TestWithStride(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -277,7 +277,7 @@ class TestWithStride(TestConv2dTransposeOp):
self.filter_size = [f_c, 6, 3, 3]
class TestWithDilation(TestConv2dTransposeOp):
class TestWithDilation(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -288,7 +288,7 @@ class TestWithDilation(TestConv2dTransposeOp):
self.filter_size = [f_c, 6, 3, 3]
class TestWithEvenUpsample(TestConv2dTransposeOp):
class TestWithEvenUpsample(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [2, 2]
self.stride = [2, 2]
......@@ -300,7 +300,7 @@ class TestWithEvenUpsample(TestConv2dTransposeOp):
self.filter_size = [f_c, 6, 5, 5]
class TestWithEvenUpsampleOutputPadding(TestConv2dTransposeOp):
class TestWithEvenUpsampleOutputPadding(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [2, 2]
self.stride = [2, 2]
......@@ -312,7 +312,7 @@ class TestWithEvenUpsampleOutputPadding(TestConv2dTransposeOp):
self.filter_size = [f_c, 6, 5, 5]
class Test_NHWC(TestConv2dTransposeOp):
class Test_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -324,7 +324,7 @@ class Test_NHWC(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestWithSymmetricPad_NHWC(TestConv2dTransposeOp):
class TestWithSymmetricPad_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -336,7 +336,7 @@ class TestWithSymmetricPad_NHWC(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestWithAsymmetricPad_NHWC(TestConv2dTransposeOp):
class TestWithAsymmetricPad_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 0, 1, 2]
self.stride = [1, 1]
......@@ -348,7 +348,7 @@ class TestWithAsymmetricPad_NHWC(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestWithGroups_NHWC(TestConv2dTransposeOp):
class TestWithGroups_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -360,7 +360,7 @@ class TestWithGroups_NHWC(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestWithStride_NHWC(TestConv2dTransposeOp):
class TestWithStride_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -372,7 +372,7 @@ class TestWithStride_NHWC(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestWithDilation_NHWC(TestConv2dTransposeOp):
class TestWithDilation_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [1, 1]
......@@ -384,7 +384,7 @@ class TestWithDilation_NHWC(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestWithEvenUpsample_NHWC(TestConv2dTransposeOp):
class TestWithEvenUpsample_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [2, 2]
self.stride = [2, 2]
......@@ -397,7 +397,7 @@ class TestWithEvenUpsample_NHWC(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestWithEvenUpsample_NHWC_output_padding(TestConv2dTransposeOp):
class TestWithEvenUpsample_NHWC_output_padding(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [2, 2]
self.stride = [2, 2]
......@@ -413,7 +413,7 @@ class TestWithEvenUpsample_NHWC_output_padding(TestConv2dTransposeOp):
# ------------ test_cudnn ------------
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestCUDNN(TestConv2dTransposeOp):
class TestCUDNN(TestConv2DTransposeOp):
def init_op_type(self):
self.use_cudnn = True
self.op_type = "conv2d_transpose"
......@@ -547,7 +547,7 @@ class TestCUDNNWithEvenUpsample(TestWithEvenUpsample):
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestCUDNN_NHWC(TestConv2dTransposeOp):
class TestCUDNN_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [0, 0]
self.stride = [1, 1]
......@@ -654,7 +654,7 @@ class TestCUDNNWithEvenUpsample_NHWC(TestWithEvenUpsample):
self.op_type = "conv2d_transpose"
class TestDepthwiseConvTranspose(TestConv2dTransposeOp):
class TestDepthwiseConvTranspose(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -667,7 +667,7 @@ class TestDepthwiseConvTranspose(TestConv2dTransposeOp):
self.op_type = "depthwise_conv2d_transpose"
class TestDepthwiseConvTransposeAsymmetricPad(TestConv2dTransposeOp):
class TestDepthwiseConvTransposeAsymmetricPad(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 0, 1, 2]
self.stride = [2, 2]
......@@ -681,7 +681,7 @@ class TestDepthwiseConvTransposeAsymmetricPad(TestConv2dTransposeOp):
self.data_format = 'NCHW'
class TestDepthwiseConvTransposeSAMEPad(TestConv2dTransposeOp):
class TestDepthwiseConvTransposeSAMEPad(TestConv2DTransposeOp):
def init_test_case(self):
self.stride = [2, 2]
self.dilations = [1, 1]
......@@ -694,7 +694,7 @@ class TestDepthwiseConvTransposeSAMEPad(TestConv2dTransposeOp):
self.padding_algorithm = 'SAME'
class TestDepthwiseConvTransposeVALIDPad(TestConv2dTransposeOp):
class TestDepthwiseConvTransposeVALIDPad(TestConv2DTransposeOp):
def init_test_case(self):
self.stride = [2, 2]
self.dilations = [1, 1]
......@@ -707,7 +707,7 @@ class TestDepthwiseConvTransposeVALIDPad(TestConv2dTransposeOp):
self.padding_algorithm = 'VALID'
class TestDepthwiseConvTranspose_NHWC_4x4kernel(TestConv2dTransposeOp):
class TestDepthwiseConvTranspose_NHWC_4x4kernel(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -721,7 +721,7 @@ class TestDepthwiseConvTranspose_NHWC_4x4kernel(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestDepthwiseConvTranspose_NHWC_3x3kernel(TestConv2dTransposeOp):
class TestDepthwiseConvTranspose_NHWC_3x3kernel(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 1]
self.stride = [2, 2]
......@@ -735,7 +735,7 @@ class TestDepthwiseConvTranspose_NHWC_3x3kernel(TestConv2dTransposeOp):
self.data_format = 'NHWC'
class TestDepthwiseConvTransposeAsymmetricPad_NHWC(TestConv2dTransposeOp):
class TestDepthwiseConvTransposeAsymmetricPad_NHWC(TestConv2DTransposeOp):
def init_test_case(self):
self.pad = [1, 0, 1, 2]
self.stride = [2, 2]
......@@ -751,7 +751,7 @@ class TestDepthwiseConvTransposeAsymmetricPad_NHWC(TestConv2dTransposeOp):
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestCUDNN_FP16(TestConv2dTransposeOp):
class TestCUDNN_FP16(TestConv2DTransposeOp):
def init_test_case(self):
self.dtype = np.float16
self.pad = [1, 1]
......@@ -867,7 +867,7 @@ class TestCUDNNWithEvenUpsample_NHWC_FP16(TestCUDNN_FP16):
self.data_format = 'NHWC'
class TestConv2dTransposeAPI(unittest.TestCase):
class TestConv2DTransposeAPI(unittest.TestCase):
def test_case1(self):
data1 = fluid.layers.data(
name='data1', shape=[3, 5, 5], dtype='float32')
......@@ -945,7 +945,7 @@ class TestConv2dTransposeAPI(unittest.TestCase):
self.assertIsNotNone(results[6])
class TestConv2dTransposeOpException(unittest.TestCase):
class TestConv2DTransposeOpException(unittest.TestCase):
def test_exception(self):
data = fluid.layers.data(name='data', shape=[3, 5, 5], dtype="float32")
......
......@@ -135,7 +135,7 @@ class Conv3DTestCase(unittest.TestCase):
def paddle_nn_layer(self):
x_var = dg.to_variable(self.input)
conv = nn.Conv3d(
conv = nn.Conv3D(
self.num_channels,
self.num_filters,
self.filter_size,
......
......@@ -228,7 +228,7 @@ def create_test_cudnn_channel_last_class(parent):
globals()[cls_name] = TestCudnnChannelLastCase
class TestConv3dOp(OpTest):
class TestConv3DOp(OpTest):
def setUp(self):
self.op_type = "conv3d"
self.use_cudnn = False
......@@ -334,7 +334,7 @@ class TestConv3dOp(OpTest):
pass
class TestCase1(TestConv3dOp):
class TestCase1(TestConv3DOp):
def init_test_case(self):
self.pad = [1, 1, 1]
self.stride = [1, 1, 1]
......@@ -344,7 +344,7 @@ class TestCase1(TestConv3dOp):
self.filter_size = [6, f_c, 3, 3, 3]
class TestWithGroup1(TestConv3dOp):
class TestWithGroup1(TestConv3DOp):
def init_group(self):
self.groups = 3
......@@ -354,7 +354,7 @@ class TestWithGroup2(TestCase1):
self.groups = 3
class TestWith1x1(TestConv3dOp):
class TestWith1x1(TestConv3DOp):
def init_test_case(self):
self.pad = [0, 0, 0]
self.stride = [1, 1, 1]
......@@ -370,7 +370,7 @@ class TestWith1x1(TestConv3dOp):
self.groups = 3
class TestWithInput1x1Filter1x1(TestConv3dOp):
class TestWithInput1x1Filter1x1(TestConv3DOp):
def init_test_case(self):
self.pad = [0, 0, 0]
self.stride = [1, 1, 1]
......@@ -386,7 +386,7 @@ class TestWithInput1x1Filter1x1(TestConv3dOp):
self.groups = 3
class TestWithDilation(TestConv3dOp):
class TestWithDilation(TestConv3DOp):
def init_test_case(self):
self.pad = [0, 0, 0]
self.stride = [1, 1, 1]
......@@ -402,19 +402,19 @@ class TestWithDilation(TestConv3dOp):
self.groups = 3
#---------------- Conv3dCUDNN ----------------
#---------------- Conv3DCUDNN ----------------
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestCUDNN(TestConv3dOp):
class TestCUDNN(TestConv3DOp):
def init_kernel_type(self):
self.use_cudnn = True
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestFP16CUDNN(TestConv3dOp):
class TestFP16CUDNN(TestConv3DOp):
def init_kernel_type(self):
self.use_cudnn = True
self.dtype = np.float16
......@@ -519,7 +519,7 @@ class TestCUDNNExhaustiveSearch(TestCUDNN):
# ---- test asymmetric padding ----
class TestConv3dOp_2(OpTest):
class TestConv3DOp_2(OpTest):
def setUp(self):
self.op_type = "conv3d"
self.use_cudnn = False
......@@ -624,7 +624,7 @@ class TestConv3dOp_2(OpTest):
self.data_format = "NCDHW"
class TestConv3dOp_AsyPadding(TestConv3dOp_2):
class TestConv3DOp_AsyPadding(TestConv3DOp_2):
def init_test_case(self):
self.stride = [1, 1, 2]
self.input_size = [2, 3, 4, 4, 4] # NCDHW
......@@ -637,7 +637,7 @@ class TestConv3dOp_AsyPadding(TestConv3dOp_2):
self.padding_algorithm = "EXPLICIT"
class TestConv3dOp_DiffDataInDiffDim(TestConv3dOp_2):
class TestConv3DOp_DiffDataInDiffDim(TestConv3DOp_2):
def init_test_case(self):
self.stride = [1, 1, 2]
self.input_size = [2, 3, 4, 5, 5] # NCDHW
......@@ -650,12 +650,12 @@ class TestConv3dOp_DiffDataInDiffDim(TestConv3dOp_2):
self.padding_algorithm = "EXPLICIT"
create_test_padding_SAME_class(TestConv3dOp_DiffDataInDiffDim)
create_test_padding_VALID_class(TestConv3dOp_DiffDataInDiffDim)
create_test_channel_last_class(TestConv3dOp_DiffDataInDiffDim)
create_test_padding_SAME_class(TestConv3DOp_DiffDataInDiffDim)
create_test_padding_VALID_class(TestConv3DOp_DiffDataInDiffDim)
create_test_channel_last_class(TestConv3DOp_DiffDataInDiffDim)
class TestCase1_AsyPadding(TestConv3dOp_2):
class TestCase1_AsyPadding(TestConv3DOp_2):
def init_test_case(self):
self.stride = [1, 1, 1]
self.input_size = [2, 3, 4, 4, 4] # NCDHW
......@@ -668,7 +668,7 @@ class TestCase1_AsyPadding(TestConv3dOp_2):
self.padding_algorithm = "EXPLICIT"
class TestWithGroup1_AsyPadding(TestConv3dOp_2):
class TestWithGroup1_AsyPadding(TestConv3DOp_2):
def init_group(self):
self.groups = 3
......@@ -677,7 +677,7 @@ class TestWithGroup1_AsyPadding(TestConv3dOp_2):
self.padding_algorithm = "EXPLICIT"
class TestWithGroup2_AsyPadding(TestConv3dOp_2):
class TestWithGroup2_AsyPadding(TestConv3DOp_2):
def init_test_case(self):
self.stride = [1, 1, 1]
self.input_size = [2, 3, 4, 4, 4] # NCDHW
......@@ -693,7 +693,7 @@ class TestWithGroup2_AsyPadding(TestConv3dOp_2):
self.padding_algorithm = "EXPLICIT"
class TestWith1x1_AsyPadding(TestConv3dOp_2):
class TestWith1x1_AsyPadding(TestConv3DOp_2):
def init_test_case(self):
self.stride = [1, 1, 1]
self.input_size = [2, 3, 4, 4, 4]
......@@ -712,7 +712,7 @@ class TestWith1x1_AsyPadding(TestConv3dOp_2):
self.padding_algorithm = "EXPLICIT"
class TestWithDilation_AsyPadding(TestConv3dOp_2):
class TestWithDilation_AsyPadding(TestConv3DOp_2):
def init_test_case(self):
self.stride = [1, 1, 1]
self.input_size = [2, 3, 6, 6, 6]
......@@ -731,41 +731,41 @@ class TestWithDilation_AsyPadding(TestConv3dOp_2):
self.padding_algorithm = "EXPLICIT"
create_test_cudnn_class(TestConv3dOp_AsyPadding)
create_test_cudnn_class(TestConv3DOp_AsyPadding)
create_test_cudnn_class(TestWithGroup1_AsyPadding)
create_test_cudnn_class(TestWithGroup2_AsyPadding)
create_test_cudnn_class(TestWith1x1_AsyPadding)
create_test_cudnn_class(TestWithDilation_AsyPadding)
create_test_padding_SAME_class(TestConv3dOp_AsyPadding)
create_test_padding_SAME_class(TestConv3DOp_AsyPadding)
create_test_padding_SAME_class(TestWithGroup1_AsyPadding)
create_test_padding_SAME_class(TestWith1x1_AsyPadding)
create_test_padding_VALID_class(TestConv3dOp_AsyPadding)
create_test_padding_VALID_class(TestConv3DOp_AsyPadding)
create_test_padding_VALID_class(TestWithGroup1_AsyPadding)
create_test_padding_VALID_class(TestWith1x1_AsyPadding)
create_test_cudnn_padding_SAME_class(TestConv3dOp_AsyPadding)
create_test_cudnn_padding_SAME_class(TestConv3DOp_AsyPadding)
create_test_cudnn_padding_SAME_class(TestWithGroup1_AsyPadding)
create_test_cudnn_padding_SAME_class(TestWith1x1_AsyPadding)
create_test_cudnn_padding_VALID_class(TestConv3dOp_AsyPadding)
create_test_cudnn_padding_VALID_class(TestConv3DOp_AsyPadding)
create_test_cudnn_padding_VALID_class(TestWithGroup1_AsyPadding)
create_test_cudnn_padding_VALID_class(TestWith1x1_AsyPadding)
create_test_channel_last_class(TestConv3dOp_AsyPadding)
create_test_channel_last_class(TestConv3DOp_AsyPadding)
create_test_channel_last_class(TestWithGroup1_AsyPadding)
create_test_channel_last_class(TestWith1x1_AsyPadding)
create_test_channel_last_class(TestConv3dOp_AsyPadding)
create_test_channel_last_class(TestConv3DOp_AsyPadding)
create_test_channel_last_class(TestWithGroup1_AsyPadding)
create_test_channel_last_class(TestWith1x1_AsyPadding)
create_test_cudnn_channel_last_class(TestConv3dOp_AsyPadding)
create_test_cudnn_channel_last_class(TestConv3DOp_AsyPadding)
create_test_cudnn_channel_last_class(TestWithGroup1_AsyPadding)
create_test_cudnn_channel_last_class(TestWith1x1_AsyPadding)
create_test_cudnn_channel_last_class(TestConv3dOp_AsyPadding)
create_test_cudnn_channel_last_class(TestConv3DOp_AsyPadding)
create_test_cudnn_channel_last_class(TestWithGroup1_AsyPadding)
create_test_cudnn_channel_last_class(TestWith1x1_AsyPadding)
......@@ -777,7 +777,7 @@ create_test_cudnn_channel_last_class(TestWith1x1_AsyPadding)
# --------- test python API ---------------
class TestConv3dAPI(unittest.TestCase):
class TestConv3DAPI(unittest.TestCase):
def test_api(self):
input_NDHWC = fluid.layers.data(
......@@ -853,7 +853,7 @@ class TestConv3dAPI(unittest.TestCase):
data_format="NCDHW")
class TestConv3dAPI_Error(unittest.TestCase):
class TestConv3DAPI_Error(unittest.TestCase):
def test_api(self):
input = fluid.layers.data(
name="input",
......
......@@ -139,7 +139,7 @@ class Conv3DTransposeTestCase(unittest.TestCase):
def paddle_nn_layer(self):
x_var = dg.to_variable(self.input)
conv = nn.ConvTranspose3d(
conv = nn.Conv3DTranspose(
self.num_channels,
self.num_filters,
self.filter_size,
......
......@@ -107,7 +107,7 @@ def conv3dtranspose_forward_naive(input_, filter_, attrs):
return out
class TestConv3dTransposeOp(OpTest):
class TestConv3DTransposeOp(OpTest):
def setUp(self):
# init as conv transpose
self.use_cudnn = False
......@@ -200,7 +200,7 @@ class TestConv3dTransposeOp(OpTest):
self.op_type = "conv3d_transpose"
class TestWithSymmetricPad(TestConv3dTransposeOp):
class TestWithSymmetricPad(TestConv3DTransposeOp):
def init_test_case(self):
self.check_no_input = True
self.pad = [1, 1, 1]
......@@ -212,7 +212,7 @@ class TestWithSymmetricPad(TestConv3dTransposeOp):
self.filter_size = [f_c, 6, 3, 3, 3]
class TestWithAsymmetricPad(TestConv3dTransposeOp):
class TestWithAsymmetricPad(TestConv3DTransposeOp):
def init_test_case(self):
self.pad = [1, 0, 1, 0, 1, 2]
self.stride = [1, 1, 1]
......@@ -223,7 +223,7 @@ class TestWithAsymmetricPad(TestConv3dTransposeOp):
self.filter_size = [f_c, 6, 3, 3, 3]
class TestWithSAMEPad(TestConv3dTransposeOp):
class TestWithSAMEPad(TestConv3DTransposeOp):
def init_test_case(self):
self.stride = [1, 1, 2]
self.dilations = [1, 2, 1]
......@@ -234,7 +234,7 @@ class TestWithSAMEPad(TestConv3dTransposeOp):
self.padding_algorithm = 'SAME'
class TestWithVALIDPad(TestConv3dTransposeOp):
class TestWithVALIDPad(TestConv3DTransposeOp):
def init_test_case(self):
self.stride = [2, 1, 1]
self.dilations = [1, 1, 1]
......@@ -245,7 +245,7 @@ class TestWithVALIDPad(TestConv3dTransposeOp):
self.padding_algorithm = 'VALID'
class TestWithStride(TestConv3dTransposeOp):
class TestWithStride(TestConv3DTransposeOp):
def init_test_case(self):
self.check_no_filter = True
self.pad = [1, 1, 1]
......@@ -257,7 +257,7 @@ class TestWithStride(TestConv3dTransposeOp):
self.filter_size = [f_c, 6, 3, 3, 3]
class TestWithGroups(TestConv3dTransposeOp):
class TestWithGroups(TestConv3DTransposeOp):
def init_test_case(self):
self.pad = [1, 1, 1]
self.stride = [1, 1, 1]
......@@ -268,7 +268,7 @@ class TestWithGroups(TestConv3dTransposeOp):
self.filter_size = [f_c, 3, 3, 3, 3]
class TestWithDilation(TestConv3dTransposeOp):
class TestWithDilation(TestConv3DTransposeOp):
def init_test_case(self):
self.pad = [1, 1, 1]
self.stride = [1, 1, 1]
......@@ -279,7 +279,7 @@ class TestWithDilation(TestConv3dTransposeOp):
self.filter_size = [f_c, 6, 3, 3, 3]
class Test_NHWC(TestConv3dTransposeOp):
class Test_NHWC(TestConv3DTransposeOp):
def init_test_case(self):
self.pad = [0, 0, 0]
self.stride = [1, 1, 1]
......@@ -294,7 +294,7 @@ class Test_NHWC(TestConv3dTransposeOp):
# ------------ test_cudnn ------------
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestCUDNN(TestConv3dTransposeOp):
class TestCUDNN(TestConv3DTransposeOp):
def init_op_type(self):
self.use_cudnn = True
self.op_type = "conv3d_transpose"
......@@ -419,7 +419,7 @@ class TestCUDNNWithGroups(TestWithGroups):
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestCUDNN_NHWC(TestConv3dTransposeOp):
class TestCUDNN_NHWC(TestConv3DTransposeOp):
def init_test_case(self):
self.pad = [0, 0, 0]
self.stride = [1, 1, 1]
......
......@@ -20,10 +20,10 @@ import numpy as np
import paddle.fluid.core as core
import paddle.fluid as fluid
from op_test import OpTest
from test_conv3d_transpose_op import conv3dtranspose_forward_naive, TestConv3dTransposeOp
from test_conv3d_transpose_op import TestConv3DTransposeOp
class TestWithSymmetricPad_NHWC(TestConv3dTransposeOp):
class TestWithSymmetricPad_NHWC(TestConv3DTransposeOp):
def init_test_case(self):
self.pad = [1, 1, 1]
self.stride = [1, 1, 1]
......@@ -35,7 +35,7 @@ class TestWithSymmetricPad_NHWC(TestConv3dTransposeOp):
self.data_format = 'NHWC'
class TestWithAsymmetricPad_NHWC(TestConv3dTransposeOp):
class TestWithAsymmetricPad_NHWC(TestConv3DTransposeOp):
def init_test_case(self):
self.pad = [1, 0, 1, 0, 1, 2]
self.stride = [1, 1, 1]
......@@ -47,7 +47,7 @@ class TestWithAsymmetricPad_NHWC(TestConv3dTransposeOp):
self.data_format = 'NHWC'
class TestWithGroups_NHWC(TestConv3dTransposeOp):
class TestWithGroups_NHWC(TestConv3DTransposeOp):
def init_test_case(self):
self.check_no_filter = True
self.pad = [1, 1, 1]
......@@ -60,7 +60,7 @@ class TestWithGroups_NHWC(TestConv3dTransposeOp):
self.data_format = 'NHWC'
class TestWithStride_NHWC(TestConv3dTransposeOp):
class TestWithStride_NHWC(TestConv3DTransposeOp):
def init_test_case(self):
self.pad = [1, 1, 1]
self.stride = [2, 2, 2]
......@@ -72,7 +72,7 @@ class TestWithStride_NHWC(TestConv3dTransposeOp):
self.data_format = 'NHWC'
class TestWithDilation_NHWC(TestConv3dTransposeOp):
class TestWithDilation_NHWC(TestConv3DTransposeOp):
def init_test_case(self):
self.check_no_input = True
self.pad = [1, 1, 1]
......@@ -85,7 +85,7 @@ class TestWithDilation_NHWC(TestConv3dTransposeOp):
self.data_format = 'NHWC'
class TestConv3dTransposeAPI(unittest.TestCase):
class TestConv3DTransposeAPI(unittest.TestCase):
def test_case1(self):
data1 = fluid.layers.data(
name='data1', shape=[3, 5, 5, 5], dtype='float32')
......@@ -164,7 +164,7 @@ class TestConv3dTransposeAPI(unittest.TestCase):
self.assertIsNotNone(results[6])
class TestConv3dTransposeOpException(unittest.TestCase):
class TestConv3DTransposeOpException(unittest.TestCase):
def test_exception(self):
data = fluid.layers.data(
name='data', shape=[3, 5, 5, 5], dtype="float32")
......
......@@ -438,7 +438,7 @@ class TestConv3DDoubleGradCheck_ChannelLast(unittest.TestCase):
self.func(p)
class TestConv3dDoubleGradCheck_ChannelLast_AsyPadding(unittest.TestCase):
class TestConv3DDoubleGradCheck_ChannelLast_AsyPadding(unittest.TestCase):
@prog_scope()
def func(self, place):
shape = [2, 2, 2, 2, 3]
......
......@@ -31,7 +31,7 @@ class TestGeneratorSeed(unittest.TestCase):
"""
def test_gen_dropout_dygraph(self):
gen = paddle.manual_seed(12343)
gen = paddle.seed(12343)
fluid.enable_dygraph()
......@@ -70,13 +70,13 @@ class TestGeneratorSeed(unittest.TestCase):
"""Test Generator seed."""
fluid.enable_dygraph()
paddle.manual_seed(12312321111)
paddle.seed(12312321111)
x = fluid.layers.gaussian_random([120], dtype="float32")
st1 = paddle.get_cuda_rng_state()
x1 = fluid.layers.gaussian_random([120], dtype="float32")
paddle.set_cuda_rng_state(st1)
x2 = fluid.layers.gaussian_random([120], dtype="float32")
paddle.manual_seed(12312321111)
paddle.seed(12312321111)
x3 = fluid.layers.gaussian_random([120], dtype="float32")
x_np = x.numpy()
x1_np = x1.numpy()
......@@ -93,13 +93,13 @@ class TestGeneratorSeed(unittest.TestCase):
fluid.enable_dygraph()
gen = paddle.manual_seed(12312321111)
gen = paddle.seed(12312321111)
x = paddle.randint(low=10, shape=[10], dtype="int32")
st1 = gen.get_state()
x1 = paddle.randint(low=10, shape=[10], dtype="int32")
gen.set_state(st1)
x2 = paddle.randint(low=10, shape=[10], dtype="int32")
paddle.manual_seed(12312321111)
paddle.seed(12312321111)
x3 = paddle.randint(low=10, shape=[10], dtype="int32")
x_np = x.numpy()
x1_np = x1.numpy()
......@@ -114,7 +114,7 @@ class TestGeneratorSeed(unittest.TestCase):
def test_gen_TruncatedNormal_initializer(self):
fluid.disable_dygraph()
gen = paddle.manual_seed(123123143)
gen = paddle.seed(123123143)
cur_state = paddle.get_cuda_rng_state()
startup_program = fluid.Program()
......@@ -140,7 +140,7 @@ class TestGeneratorSeed(unittest.TestCase):
feed={},
fetch_list=[result_1, result_2])
paddle.manual_seed(123123143)
paddle.seed(123123143)
with fluid.program_guard(train_program, startup_program):
exe.run(startup_program)
out2 = exe.run(train_program,
......
......@@ -34,7 +34,7 @@ def random_reader():
def simple_fc_net(places, use_legacy_py_reader, use_double_buffer):
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
startup_prog = fluid.Program()
main_prog = fluid.Program()
......
......@@ -286,7 +286,7 @@ class TestModulatedDeformableConvInvalidInput(unittest.TestCase):
self.assertRaises(TypeError, test_invalid_offset)
class TestDeformConv2dAPI(unittest.TestCase):
class TestDeformConv2DAPI(unittest.TestCase):
def test_api(self):
def test_deform_conv2d_v1():
paddle.enable_static()
......
......@@ -487,7 +487,7 @@ class TestDropoutCAPI(unittest.TestCase):
self.assertTrue(np.allclose(result.numpy(), result_np))
class TestDropout2dFAPI(unittest.TestCase):
class TestDropout2DFAPI(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.places = [fluid.CPUPlace()]
......@@ -535,7 +535,7 @@ class TestDropout2dFAPI(unittest.TestCase):
self.assertTrue(np.allclose(res.numpy(), res_np))
class TestDropout2dFAPIError(unittest.TestCase):
class TestDropout2DFAPIError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
......@@ -554,7 +554,7 @@ class TestDropout2dFAPIError(unittest.TestCase):
self.assertRaises(ValueError, test_dataformat)
class TestDropout2dCAPI(unittest.TestCase):
class TestDropout2DCAPI(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.places = [fluid.CPUPlace()]
......@@ -567,13 +567,13 @@ class TestDropout2dCAPI(unittest.TestCase):
input_np = np.random.random([2, 3, 4, 5]).astype("float32")
result_np = input_np
input = fluid.dygraph.to_variable(input_np)
m = paddle.nn.Dropout2d(p=0.)
m = paddle.nn.Dropout2D(p=0.)
m.eval()
result = m(input)
self.assertTrue(np.allclose(result.numpy(), result_np))
class TestDropout3dFAPI(unittest.TestCase):
class TestDropout3DFAPI(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.places = [fluid.CPUPlace()]
......@@ -621,7 +621,7 @@ class TestDropout3dFAPI(unittest.TestCase):
self.assertTrue(np.allclose(res.numpy(), res_np))
class TestDropout3dFAPIError(unittest.TestCase):
class TestDropout3DFAPIError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
......@@ -640,7 +640,7 @@ class TestDropout3dFAPIError(unittest.TestCase):
self.assertRaises(ValueError, test_dataformat)
class TestDropout3dCAPI(unittest.TestCase):
class TestDropout3DCAPI(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.places = [fluid.CPUPlace()]
......@@ -653,7 +653,7 @@ class TestDropout3dCAPI(unittest.TestCase):
input_np = np.random.random([2, 3, 4, 5, 6]).astype("float32")
result_np = input_np
input = fluid.dygraph.to_variable(input_np)
m = paddle.nn.Dropout3d(p=0.)
m = paddle.nn.Dropout3D(p=0.)
m.eval()
result = m(input)
self.assertTrue(np.allclose(result.numpy(), result_np))
......
......@@ -110,7 +110,7 @@ class TestDygraphMultiForward(unittest.TestCase):
epoch_num = 1
with fluid.dygraph.guard():
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
mnist = MNIST()
sgd = SGDOptimizer(
......@@ -143,7 +143,7 @@ class TestDygraphMultiForward(unittest.TestCase):
dy_param_init_value[param.name] = param.numpy()
with new_program_scope():
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
exe = fluid.Executor(fluid.CPUPlace(
) if not core.is_compiled_with_cuda() else fluid.CUDAPlace(0))
......
......@@ -117,7 +117,7 @@ class TestDygraphWeightNorm(unittest.TestCase):
def test_check_output(self):
fluid.enable_imperative()
linear = paddle.nn.Conv2d(2, 3, 3)
linear = paddle.nn.Conv2D(2, 3, 3)
before_weight = linear.weight.numpy()
if self.dim == None:
self.dim = -1
......@@ -179,7 +179,7 @@ class TestDygraphRemoveWeightNorm(unittest.TestCase):
def test_check_output(self):
fluid.enable_imperative()
linear = paddle.nn.Conv2d(2, 3, 3)
linear = paddle.nn.Conv2D(2, 3, 3)
before_weight = linear.weight
wn = weight_norm(linear, dim=self.dim)
rwn = remove_weight_norm(linear)
......
......@@ -466,7 +466,7 @@ class PaddingRNNTestBase(unittest.TestCase):
pass
def _prepare_program(self, config, parallel=True):
paddle.manual_seed(config.random_seed)
paddle.seed(config.random_seed)
self.main_program = fluid.Program()
self.startup_program = fluid.Program()
with fluid.program_guard(self.main_program, self.startup_program):
......
......@@ -39,7 +39,7 @@ class TestEmbeddingIdStopGradientBase(unittest.TestCase):
def run_program(self, place, stop_gradient=False):
np.random.seed(1)
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
startup_program = fluid.Program()
......
......@@ -137,7 +137,7 @@ class TestFCOpWithPadding(TestFCOp):
class TestFcOp_NumFlattenDims_NegOne(unittest.TestCase):
def test_api(self):
def run_program(num_flatten_dims):
paddle.manual_seed(SEED)
paddle.seed(SEED)
startup_program = Program()
main_program = Program()
......
......@@ -57,7 +57,7 @@ class TestFuseBatchNormActPass(unittest.TestCase):
return x, y, loss
def check(self, place, use_cuda):
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
main_program = fluid.Program()
startup_program = fluid.Program()
......
......@@ -158,7 +158,7 @@ class TestFusedBnAddActAPI(unittest.TestCase):
return x, y, loss
def check(self, place, use_cuda):
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
iters = 5
batch_size = 16
......
......@@ -38,7 +38,7 @@ class TestGaussianRandomOp(OpTest):
"seed": 10,
"use_mkldnn": self.use_mkldnn
}
paddle.manual_seed(10)
paddle.seed(10)
self.outputs = {'Out': np.zeros((123, 92), dtype='float32')}
......
......@@ -30,8 +30,6 @@ class TestGenerator(unittest.TestCase):
"""Test basic generator."""
gen = generator.Generator()
gen.manual_seed(123123143)
s = gen.initial_seed()
s = gen.seed()
st = gen.get_state()
gen.set_state(st)
gen.random()
......
......@@ -35,7 +35,7 @@ def random_reader():
def simple_fc_net(places, use_legacy_py_reader, use_double_buffer):
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
startup_prog = fluid.Program()
main_prog = fluid.Program()
......
......@@ -269,7 +269,7 @@ class TestHSigmoidOpWithSparseGrad(unittest.TestCase):
def training_test(self, is_sparse):
with fluid.program_guard(fluid.Program(), fluid.Program()):
paddle.manual_seed(1)
paddle.seed(1)
start_up = fluid.default_startup_program()
x = np.arange(6).reshape(6)
path_table = np.array([(1, 2, -1), (1, 2, -1)]).astype('int64')
......
......@@ -120,7 +120,7 @@ class TestAmpScaler(unittest.TestCase):
inp_np = np.random.random(size=[1, 3, 128, 128]).astype(np.float32)
def run_simple_conv(inp_np, use_scaler=True):
paddle.manual_seed(10)
paddle.seed(10)
paddle.framework.random._manual_program_seed(10)
with fluid.dygraph.guard():
model = SimpleConv(
......@@ -205,7 +205,7 @@ class TestResnet2(unittest.TestCase):
paddle.disable_static()
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
resnet = ResNet(use_cudnn=True)
......@@ -282,7 +282,7 @@ class TestResnet(unittest.TestCase):
batch_num = 1
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
resnet = ResNet(use_cudnn=True)
......
......@@ -206,7 +206,7 @@ class TestDygraphDeepCF(unittest.TestCase):
else:
(users_np, items_np, labels_np, num_users, num_items,
matrix) = get_data()
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
startup = fluid.Program()
main = fluid.Program()
......@@ -243,7 +243,7 @@ class TestDygraphDeepCF(unittest.TestCase):
sys.stderr.write('static loss %s\n' % static_loss)
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
deepcf = DeepCF(num_users, num_items, matrix)
......@@ -268,7 +268,7 @@ class TestDygraphDeepCF(unittest.TestCase):
sys.stderr.write('dynamic loss: %s %s\n' % (slice, dy_loss))
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
deepcf2 = DeepCF(num_users, num_items, matrix)
......
......@@ -311,7 +311,7 @@ class TestDygraphDoubleGradVisitedUniq(TestCase):
fluid.set_flags({'FLAGS_sort_sum_gradient': True})
with fluid.dygraph.guard():
paddle.manual_seed(123)
paddle.seed(123)
paddle.framework.random._manual_program_seed(123)
a = fluid.dygraph.to_variable(value)
a.stop_gradient = False
......@@ -328,7 +328,7 @@ class TestDygraphDoubleGradVisitedUniq(TestCase):
grad_1 = dx[0].numpy()
with fluid.dygraph.guard():
paddle.manual_seed(123)
paddle.seed(123)
paddle.framework.random._manual_program_seed(123)
a = fluid.dygraph.to_variable(value)
a.stop_gradient = False
......
......@@ -56,7 +56,7 @@ class Generator(fluid.Layer):
class TestDygraphGAN(unittest.TestCase):
def test_gan_float32(self):
seed = 90
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
startup = fluid.Program()
discriminate_p = fluid.Program()
......@@ -131,7 +131,7 @@ class TestDygraphGAN(unittest.TestCase):
dy_params = dict()
with fluid.dygraph.guard():
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
discriminator = Discriminator()
......@@ -176,7 +176,7 @@ class TestDygraphGAN(unittest.TestCase):
dy_params2 = dict()
with fluid.dygraph.guard():
fluid.set_flags({'FLAGS_sort_sum_gradient': True})
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
discriminator2 = Discriminator()
generator2 = Generator()
......
......@@ -61,7 +61,7 @@ class GCN(fluid.Layer):
class TestDygraphGNN(unittest.TestCase):
def test_gnn_float32(self):
paddle.manual_seed(90)
paddle.seed(90)
paddle.framework.random._manual_program_seed(90)
startup = fluid.Program()
main = fluid.Program()
......@@ -112,7 +112,7 @@ class TestDygraphGNN(unittest.TestCase):
scope.find_var(model.gc.weight.name).get_tensor())
with fluid.dygraph.guard():
paddle.manual_seed(90)
paddle.seed(90)
paddle.framework.random._manual_program_seed(90)
features = np.ones([1, 100, 50], dtype=np.float32)
......@@ -138,7 +138,7 @@ class TestDygraphGNN(unittest.TestCase):
model_gc_weight_value = model.gc.weight.numpy()
with fluid.dygraph.guard():
paddle.manual_seed(90)
paddle.seed(90)
paddle.framework.random._manual_program_seed(90)
features2 = np.ones([1, 100, 50], dtype=np.float32)
......
......@@ -28,11 +28,11 @@ class LeNetDygraph(fluid.dygraph.Layer):
super(LeNetDygraph, self).__init__()
self.num_classes = num_classes
self.features = nn.Sequential(
nn.Conv2d(
nn.Conv2D(
1, 6, 3, stride=1, padding=1),
nn.ReLU(),
paddle.fluid.dygraph.Pool2D(2, 'max', 2),
nn.Conv2d(
nn.Conv2D(
6, 16, 5, stride=1, padding=0),
nn.ReLU(),
paddle.fluid.dygraph.Pool2D(2, 'max', 2))
......@@ -60,7 +60,7 @@ def init_weights(layer):
new_bias = paddle.fluid.layers.fill_constant(
layer.bias.shape, layer.bias.dtype, value=-0.1)
layer.bias.set_value(new_bias)
elif type(layer) == nn.Conv2d:
elif type(layer) == nn.Conv2D:
new_weight = paddle.fluid.layers.fill_constant(
layer.weight.shape, layer.weight.dtype, value=0.7)
layer.weight.set_value(new_weight)
......@@ -80,7 +80,7 @@ class TestLayerApply(unittest.TestCase):
if type(layer) == nn.Linear:
np.testing.assert_allclose(layer.weight.numpy(), 0.9)
np.testing.assert_allclose(layer.bias.numpy(), -0.1)
elif type(layer) == nn.Conv2d:
elif type(layer) == nn.Conv2D:
np.testing.assert_allclose(layer.weight.numpy(), 0.7)
np.testing.assert_allclose(layer.bias.numpy(), -0.2)
......
......@@ -27,11 +27,11 @@ class LeNetDygraph(fluid.dygraph.Layer):
def __init__(self):
super(LeNetDygraph, self).__init__()
self.features = nn.Sequential(
nn.Conv2d(
nn.Conv2D(
1, 6, 3, stride=1, padding=1),
nn.ReLU(),
paddle.fluid.dygraph.Pool2D(2, 'max', 2),
nn.Conv2d(
nn.Conv2D(
6, 16, 5, stride=1, padding=0),
nn.ReLU(),
paddle.fluid.dygraph.Pool2D(2, 'max', 2))
......
......@@ -95,7 +95,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
for is_sort_sum_gradient in [True, False]:
with fluid.dygraph.guard(place):
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
simple_net = SimpleNet(
......@@ -140,7 +140,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
dy_loss_value = dy_loss.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
simple_net = SimpleNet(
......
......@@ -403,7 +403,7 @@ class TestDygraphOCRAttention(unittest.TestCase):
with fluid.dygraph.guard():
fluid.set_flags({'FLAGS_sort_sum_gradient': True})
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
ocr_attention = OCRAttention()
......@@ -454,7 +454,7 @@ class TestDygraphOCRAttention(unittest.TestCase):
dy_param_value[param.name] = param.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
exe = fluid.Executor(fluid.CPUPlace(
) if not core.is_compiled_with_cuda() else fluid.CUDAPlace(0))
......
......@@ -74,7 +74,7 @@ class TestImperativeOptimizerBase(unittest.TestCase):
with fluid.dygraph.guard(place):
try:
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
mlp = MLP()
optimizer = self.get_optimizer_dygraph(
......@@ -91,7 +91,7 @@ class TestImperativeOptimizerBase(unittest.TestCase):
) else fluid.CUDAPlace(0)
with fluid.dygraph.guard(place):
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
mlp = MLP()
......@@ -132,7 +132,7 @@ class TestImperativeOptimizerBase(unittest.TestCase):
dy_param_value[param.name] = param.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
if place == None:
......
......@@ -74,7 +74,7 @@ class TestImperativeOptimizerBase(unittest.TestCase):
try:
paddle.disable_static()
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
mlp = MLP()
optimizer = self.get_optimizer_dygraph(
......@@ -93,7 +93,7 @@ class TestImperativeOptimizerBase(unittest.TestCase):
) else fluid.CUDAPlace(0)
paddle.disable_static(place)
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
mlp = MLP()
......@@ -142,7 +142,7 @@ class TestImperativeOptimizerBase(unittest.TestCase):
paddle.enable_static()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
if place == None:
......
......@@ -226,7 +226,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
traced_layer = None
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -294,7 +294,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
dy_last_hidden_value = last_hidden.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
ptb_model = PtbModel(
hidden_size=hidden_size,
......
......@@ -45,7 +45,7 @@ class TestDygraphPtbRnnSortGradient(unittest.TestCase):
with fluid.dygraph.guard():
fluid.set_flags({'FLAGS_sort_sum_gradient': True})
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
......@@ -95,7 +95,7 @@ class TestDygraphPtbRnnSortGradient(unittest.TestCase):
dy_last_hidden_value = last_hidden.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
ptb_model = PtbModel(
......
......@@ -64,7 +64,7 @@ class TestImperativeMnist(unittest.TestCase):
mask = np.array(mask_list).astype("float32")
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
policy = Policy(input_size=4)
......@@ -105,7 +105,7 @@ class TestImperativeMnist(unittest.TestCase):
dy_param_value[param.name] = param.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
exe = fluid.Executor(fluid.CPUPlace(
......
......@@ -251,7 +251,7 @@ class TestDygraphResnet(unittest.TestCase):
traced_layer = None
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
resnet = ResNet()
......@@ -334,7 +334,7 @@ class TestDygraphResnet(unittest.TestCase):
dy_param_value[param.name] = param.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
exe = fluid.Executor(fluid.CPUPlace(
......
......@@ -78,7 +78,7 @@ class TestDygraphResnetSortGradient(unittest.TestCase):
batch_num = 10
with fluid.dygraph.guard():
fluid.set_flags({'FLAGS_sort_sum_gradient': True})
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
resnet = ResNet()
......@@ -137,7 +137,7 @@ class TestDygraphResnetSortGradient(unittest.TestCase):
dy_param_value[param.name] = param.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
exe = fluid.Executor(fluid.CPUPlace(
......
......@@ -219,7 +219,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -305,7 +305,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -414,7 +414,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -521,7 +521,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -711,7 +711,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -802,7 +802,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
......
......@@ -219,7 +219,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -308,7 +308,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -416,7 +416,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -524,7 +524,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -638,7 +638,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -717,7 +717,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......@@ -808,7 +808,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
batch_num = 200
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
# TODO: marsyang1993 Change seed to
ptb_model = PtbModel(
......
......@@ -311,7 +311,7 @@ class TestImperativeResneXt(unittest.TestCase):
batch_num = 1
epoch_num = 1
with fluid.dygraph.guard():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
se_resnext = SeResNeXt()
......@@ -372,7 +372,7 @@ class TestImperativeResneXt(unittest.TestCase):
dy_param_value[param.name] = param.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
exe = fluid.Executor(fluid.CPUPlace(
......
......@@ -102,7 +102,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
for is_sort_sum_gradient in [True, False]:
traced_layer = None
with fluid.dygraph.guard(place):
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
simple_net = SimpleNet(
......@@ -146,7 +146,7 @@ class TestDygraphSimpleNet(unittest.TestCase):
dy_loss_value = dy_loss.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
simple_net = SimpleNet(
......
......@@ -468,7 +468,7 @@ def build_optimizer(layer, cfg, loss=None):
class DyGraphTrainModel(object):
def __init__(self, cfg):
paddle.manual_seed(1)
paddle.seed(1)
paddle.framework.random._manual_program_seed(1)
self.generator = Generator(cfg)
......@@ -529,7 +529,7 @@ class StaticGraphTrainModel(object):
shape=[None, cfg.c_dim], dtype='float32', name='label_trg')
return image_real, label_org, label_trg
paddle.manual_seed(cfg.seed)
paddle.seed(cfg.seed)
paddle.framework.random._manual_program_seed(cfg.seed)
self.gen_program = fluid.Program()
gen_startup_program = fluid.Program()
......
......@@ -951,7 +951,7 @@ class TestDygraphTransformerSortGradient(unittest.TestCase):
with guard():
fluid.set_flags({'FLAGS_sort_sum_gradient': True})
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
transformer = TransFormer(
ModelHyperParams.src_vocab_size,
......@@ -1035,7 +1035,7 @@ class TestDygraphTransformerSortGradient(unittest.TestCase):
dy_token_num_value = dy_token_num.numpy()
with new_program_scope():
paddle.manual_seed(seed)
paddle.seed(seed)
paddle.framework.random._manual_program_seed(seed)
transformer = TransFormer(
ModelHyperParams.src_vocab_size,
......
......@@ -80,7 +80,7 @@ class TestInplaceAddto(unittest.TestCase):
def test_result(self):
def run_program(enable_addto):
np.random.seed(10)
paddle.manual_seed(10)
paddle.seed(10)
paddle.framework.random._manual_program_seed(10)
if fluid.core.is_compiled_with_cuda():
fluid.set_flags({"FLAGS_cudnn_deterministic": True})
......
......@@ -35,22 +35,22 @@ class TestInstanceNorm(unittest.TestCase):
def error1d():
x_data_4 = np.random.random(size=(2, 1, 3, 3)).astype('float32')
instance_norm1d = paddle.nn.InstanceNorm1d(1)
instance_norm1d = paddle.nn.InstanceNorm1D(1)
instance_norm1d(fluid.dygraph.to_variable(x_data_4))
def error2d():
x_data_3 = np.random.random(size=(2, 1, 3)).astype('float32')
instance_norm2d = paddle.nn.InstanceNorm2d(1)
instance_norm2d = paddle.nn.InstanceNorm2D(1)
instance_norm2d(fluid.dygraph.to_variable(x_data_3))
def error3d():
x_data_4 = np.random.random(size=(2, 1, 3, 3)).astype('float32')
instance_norm3d = paddle.nn.BatchNorm3d(1)
instance_norm3d = paddle.nn.BatchNorm3D(1)
instance_norm3d(fluid.dygraph.to_variable(x_data_4))
def weight_bias_false():
x_data_4 = np.random.random(size=(2, 1, 3, 3)).astype('float32')
instance_norm3d = paddle.nn.BatchNorm3d(
instance_norm3d = paddle.nn.BatchNorm3D(
1, weight_attr=False, bias_attr=False)
with fluid.dygraph.guard(p):
......@@ -75,7 +75,7 @@ class TestInstanceNorm(unittest.TestCase):
def compute_v2(x):
with fluid.dygraph.guard(p):
bn = paddle.nn.InstanceNorm2d(shape[1])
bn = paddle.nn.InstanceNorm2D(shape[1])
y = bn(fluid.dygraph.to_variable(x))
return y.numpy()
......@@ -104,7 +104,7 @@ class TestInstanceNorm(unittest.TestCase):
def compute_v2(x_np):
with program_guard(Program(), Program()):
ins = paddle.nn.InstanceNorm2d(shape[1])
ins = paddle.nn.InstanceNorm2D(shape[1])
x = fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
y = ins(x)
exe.run(fluid.default_startup_program())
......
......@@ -37,7 +37,7 @@ class TestIrMemoryOptimizeIfElseOp(unittest.TestCase):
use_cuda=True,
use_mem_opt=False,
iter_num=5):
paddle.manual_seed(100)
paddle.seed(100)
paddle.framework.random._manual_program_seed(100)
prog = Program()
startup_prog = Program()
......
......@@ -222,7 +222,7 @@ class TestJitSaveLoad(unittest.TestCase):
# enable dygraph mode
fluid.enable_dygraph()
# config seed
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
def train_and_save_model(self, model_path=None):
......@@ -370,7 +370,7 @@ class TestJitSaveLoadConfig(unittest.TestCase):
# enable dygraph mode
fluid.enable_dygraph()
# config seed
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
def test_output_spec(self):
......@@ -429,7 +429,7 @@ class TestJitMultipleLoading(unittest.TestCase):
# enable dygraph mode
fluid.enable_dygraph()
# config seed
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
# train and save base model
self.train_and_save_orig_model()
......@@ -457,7 +457,7 @@ class TestJitPruneModelAndLoad(unittest.TestCase):
# enable dygraph mode
fluid.enable_dygraph()
# config seed
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
def train_and_save(self):
......@@ -512,7 +512,7 @@ class TestJitSaveMultiCases(unittest.TestCase):
# enable dygraph mode
fluid.enable_dygraph()
# config seed
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
def verify_inference_correctness(self, layer, model_path, with_label=False):
......
......@@ -57,7 +57,7 @@ class LayerTest(unittest.TestCase):
@contextlib.contextmanager
def static_graph(self):
with new_program_scope():
paddle.manual_seed(self.seed)
paddle.seed(self.seed)
paddle.framework.random._manual_program_seed(self.seed)
yield
......@@ -77,7 +77,7 @@ class LayerTest(unittest.TestCase):
def dynamic_graph(self, force_to_use_cpu=False):
with fluid.dygraph.guard(
self._get_place(force_to_use_cpu=force_to_use_cpu)):
paddle.manual_seed(self.seed)
paddle.seed(self.seed)
paddle.framework.random._manual_program_seed(self.seed)
yield
......
......@@ -17,16 +17,16 @@ import unittest
import paddle
import paddle.fluid as fluid
from paddle.framework import manual_seed
from paddle.framework import seed
from paddle.fluid.framework import Program, default_main_program, default_startup_program
import numpy as np
class TestManualSeed(unittest.TestCase):
def test_manual_seed(self):
def test_seed(self):
fluid.enable_dygraph()
gen = paddle.manual_seed(12312321111)
gen = paddle.seed(12312321111)
x = fluid.layers.gaussian_random([10], dtype="float32")
st1 = gen.get_state()
x1 = fluid.layers.gaussian_random([10], dtype="float32")
......
......@@ -18,7 +18,7 @@ import paddle
import copy
np.random.seed(10)
paddle.manual_seed(10)
paddle.seed(10)
class TestNormalAPI(unittest.TestCase):
......@@ -61,7 +61,8 @@ class TestNormalAPI(unittest.TestCase):
if isinstance(self.mean, np.ndarray) \
and isinstance(self.std, np.ndarray):
with paddle.static.program_guard(paddle.static.Program()):
mean = paddle.fluid.data('Mean', self.mean.shape, self.mean.dtype)
mean = paddle.fluid.data('Mean', self.mean.shape,
self.mean.dtype)
std = paddle.fluid.data('Std', self.std.shape, self.std.dtype)
out = paddle.normal(mean, std, self.shape)
......@@ -76,7 +77,8 @@ class TestNormalAPI(unittest.TestCase):
return ret_all
elif isinstance(self.mean, np.ndarray):
with paddle.static.program_guard(paddle.static.Program()):
mean = paddle.fluid.data('Mean', self.mean.shape, self.mean.dtype)
mean = paddle.fluid.data('Mean', self.mean.shape,
self.mean.dtype)
out = paddle.normal(mean, self.std, self.shape)
exe = paddle.static.Executor(self.place)
......
......@@ -73,7 +73,7 @@ class TestSaveLoad(unittest.TestCase):
paddle.disable_static()
# config seed
paddle.manual_seed(SEED)
paddle.seed(SEED)
paddle.framework.random._manual_program_seed(SEED)
def build_and_train_model(self):
......
......@@ -105,7 +105,7 @@ def avg_pool1D_forward_naive(x,
return out
class TestPool1d_API(unittest.TestCase):
class TestPool1D_API(unittest.TestCase):
def setUp(self):
np.random.seed(123)
self.places = [fluid.CPUPlace()]
......@@ -138,7 +138,7 @@ class TestPool1d_API(unittest.TestCase):
self.assertTrue(np.allclose(result.numpy(), result_np))
avg_pool1d_dg = paddle.nn.layer.AvgPool1d(
avg_pool1d_dg = paddle.nn.layer.AvgPool1D(
kernel_size=2, stride=None, padding=0)
result = avg_pool1d_dg(input)
self.assertTrue(np.allclose(result.numpy(), result_np))
......@@ -159,7 +159,7 @@ class TestPool1d_API(unittest.TestCase):
self.assertTrue(np.allclose(result.numpy(), result_np))
avg_pool1d_dg = paddle.nn.AvgPool1d(
avg_pool1d_dg = paddle.nn.AvgPool1D(
kernel_size=2, stride=None, padding=1, count_include_pad=True)
result = avg_pool1d_dg(input)
self.assertTrue(np.allclose(result.numpy(), result_np))
......@@ -190,7 +190,7 @@ class TestPool1d_API(unittest.TestCase):
self.assertTrue(np.allclose(result.numpy(), result_np))
max_pool1d_dg = paddle.nn.layer.MaxPool1d(
max_pool1d_dg = paddle.nn.layer.MaxPool1D(
kernel_size=2, stride=None, padding=0)
result = max_pool1d_dg(input)
self.assertTrue(np.allclose(result.numpy(), result_np))
......@@ -207,7 +207,7 @@ class TestPool1d_API(unittest.TestCase):
self.assertTrue(np.allclose(result.numpy(), result_np))
max_pool1d_dg = paddle.nn.layer.MaxPool1d(
max_pool1d_dg = paddle.nn.layer.MaxPool1D(
kernel_size=2, stride=None, padding=0)
result = max_pool1d_dg(input)
self.assertTrue(np.allclose(result.numpy(), result_np))
......@@ -248,7 +248,7 @@ class TestPool1d_API(unittest.TestCase):
self.check_max_dygraph_return_index_results(place)
class TestPool2dError_API(unittest.TestCase):
class TestPool2DError_API(unittest.TestCase):
def test_error_api(self):
def run1():
with fluid.dygraph.guard():
......
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