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Update 2.0 convolution api (#26491)

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* update Conv2d Conv3d conv2d conv3d api
test_feature_precision_test_c
LielinJiang 5 years ago committed by GitHub
parent 7c42f056e2
commit 3a9417f4f7
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GPG Key ID: 4AEE18F83AFDEB23
17 changed files with 351 additions and 434 deletions
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20
python/paddle/fluid/tests/unittests/parallel_dygraph_sync_batch_norm.py
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@ -26,7 +26,7 @@ import paddle.fluid as fluid
import paddle.fluid.dygraph as dygraph import paddle.fluid.dygraph as dygraph
from paddle.fluid import core from paddle.fluid import core
from paddle.fluid.optimizer import SGDOptimizer from paddle.fluid.optimizer import SGDOptimizer
from paddle.nn import Conv2D, Pool2D, Linear, SyncBatchNorm from paddle.nn import Conv2d, Pool2D, Linear, SyncBatchNorm
from paddle.fluid.dygraph.base import to_variable from paddle.fluid.dygraph.base import to_variable
from test_dist_base import runtime_main, TestParallelDyGraphRunnerBase from test_dist_base import runtime_main, TestParallelDyGraphRunnerBase
@ -42,26 +42,24 @@ class TestLayer(fluid.dygraph.Layer):
act=None): act=None):
super(TestLayer, self).__init__() super(TestLayer, self).__init__()
self._conv = Conv2D( self._conv = Conv2d(
num_channels=num_channels, in_channels=num_channels,
num_filters=num_filters, out_channels=num_filters,
filter_size=filter_size, kernel_size=filter_size,
stride=stride, stride=stride,
padding=(filter_size - 1) // 2, padding=(filter_size - 1) // 2,
groups=groups, groups=groups,
act=None,
bias_attr=False) bias_attr=False)
self._sync_batch_norm = SyncBatchNorm(num_filters) self._sync_batch_norm = SyncBatchNorm(num_filters)
self._conv2 = Conv2D( self._conv2 = Conv2d(
num_channels=num_filters, in_channels=num_filters,
num_filters=num_filters, out_channels=num_filters,
filter_size=filter_size, kernel_size=filter_size,
stride=stride, stride=stride,
padding=(filter_size - 1) // 2, padding=(filter_size - 1) // 2,
groups=groups, groups=groups,
act=None,
bias_attr=False) bias_attr=False)
self._sync_batch_norm2 = SyncBatchNorm( self._sync_batch_norm2 = SyncBatchNorm(

76
python/paddle/fluid/tests/unittests/test_conv2d_layer.py
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@ -20,6 +20,10 @@ import paddle.fluid.initializer as I
import unittest import unittest
def _reverse_repeat_list(t, n):
return list(x for x in reversed(t) for _ in range(n))
class Conv2DTestCase(unittest.TestCase): class Conv2DTestCase(unittest.TestCase):
def __init__(self, def __init__(self,
methodName='runTest', methodName='runTest',
@ -29,12 +33,11 @@ class Conv2DTestCase(unittest.TestCase):
num_filters=8, num_filters=8,
filter_size=3, filter_size=3,
padding=0, padding=0,
padding_mode='zeros',
stride=1, stride=1,
dilation=1, dilation=1,
groups=1, groups=1,
act=None,
no_bias=False, no_bias=False,
use_cudnn=True,
data_format="NCHW", data_format="NCHW",
dtype="float32"): dtype="float32"):
super(Conv2DTestCase, self).__init__(methodName) super(Conv2DTestCase, self).__init__(methodName)
@ -45,12 +48,16 @@ class Conv2DTestCase(unittest.TestCase):
self.filter_size = filter_size self.filter_size = filter_size
self.padding = padding self.padding = padding
if padding_mode in {'reflect', 'replicate', 'circular'}:
_paired_padding = fluid.layers.utils.convert_to_list(padding, 2,
'padding')
self._reversed_padding_repeated_twice = _reverse_repeat_list(
_paired_padding, 2)
self.padding_mode = padding_mode
self.stride = stride self.stride = stride
self.dilation = dilation self.dilation = dilation
self.groups = groups self.groups = groups
self.act = act
self.no_bias = no_bias self.no_bias = no_bias
self.use_cudnn = use_cudnn
self.data_format = data_format self.data_format = data_format
self.dtype = dtype self.dtype = dtype
@ -91,19 +98,27 @@ class Conv2DTestCase(unittest.TestCase):
bias_attr = False bias_attr = False
else: else:
bias_attr = I.NumpyArrayInitializer(self.bias) bias_attr = I.NumpyArrayInitializer(self.bias)
if self.padding_mode != 'zeros':
x_var = F.pad(x_var,
self._reversed_padding_repeated_twice,
mode=self.padding_mode,
data_format=self.data_format)
padding = 0
else:
padding = self.padding
y_var = fluid.layers.conv2d( y_var = fluid.layers.conv2d(
x_var, x_var,
self.num_filters, self.num_filters,
self.filter_size, self.filter_size,
padding=self.padding, padding=padding,
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
param_attr=weight_attr, param_attr=weight_attr,
bias_attr=bias_attr, bias_attr=bias_attr,
use_cudnn=self.use_cudnn,
act=self.act,
data_format=self.data_format) data_format=self.data_format)
feed_dict = {"input": self.input} feed_dict = {"input": self.input}
exe = fluid.Executor(place) exe = fluid.Executor(place)
exe.run(start) exe.run(start)
@ -122,16 +137,24 @@ class Conv2DTestCase(unittest.TestCase):
"weight", self.weight_shape, dtype=self.dtype) "weight", self.weight_shape, dtype=self.dtype)
b_var = fluid.data( b_var = fluid.data(
"bias", (self.num_filters, ), dtype=self.dtype) "bias", (self.num_filters, ), dtype=self.dtype)
if self.padding_mode != 'zeros':
x_var = F.pad(x_var,
self._reversed_padding_repeated_twice,
mode=self.padding_mode,
data_format=self.data_format)
padding = 0
else:
padding = self.padding
y_var = F.conv2d( y_var = F.conv2d(
x_var, x_var,
w_var, w_var,
b_var if not self.no_bias else None, b_var if not self.no_bias else None,
padding=self.padding, padding=padding,
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
act=self.act,
use_cudnn=self.use_cudnn,
data_format=self.data_format) data_format=self.data_format)
feed_dict = {"input": self.input, "weight": self.weight} feed_dict = {"input": self.input, "weight": self.weight}
if self.bias is not None: if self.bias is not None:
@ -143,18 +166,16 @@ class Conv2DTestCase(unittest.TestCase):
def paddle_nn_layer(self): def paddle_nn_layer(self):
x_var = dg.to_variable(self.input) x_var = dg.to_variable(self.input)
conv = nn.Conv2D( conv = nn.Conv2d(
self.num_channels, self.num_channels,
self.num_filters, self.num_filters,
self.filter_size, self.filter_size,
padding=self.padding, padding=self.padding,
padding_mode=self.padding_mode,
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
act=self.act, data_format=self.data_format)
use_cudnn=self.use_cudnn,
data_format=self.data_format,
dtype=self.dtype)
conv.weight.set_value(self.weight) conv.weight.set_value(self.weight)
if not self.no_bias: if not self.no_bias:
conv.bias.set_value(self.bias) conv.bias.set_value(self.bias)
@ -198,7 +219,7 @@ def add_cases(suite):
methodName='runTest', stride=2, dilation=(2, 1))) methodName='runTest', stride=2, dilation=(2, 1)))
suite.addTest( suite.addTest(
Conv2DTestCase( Conv2DTestCase(
methodName='runTest', padding="same", no_bias=True, act="sigmoid")) methodName='runTest', padding="same", no_bias=True))
suite.addTest( suite.addTest(
Conv2DTestCase( Conv2DTestCase(
methodName='runTest', filter_size=(3, 3), padding='valid')) methodName='runTest', filter_size=(3, 3), padding='valid'))
@ -222,15 +243,28 @@ def add_cases(suite):
num_filters=6, num_filters=6,
num_channels=3, num_channels=3,
groups=3, groups=3,
use_cudnn=False,
act="sigmoid",
padding="valid")) padding="valid"))
suite.addTest(
Conv2DTestCase(
methodName='runTest',
filter_size=(3, 3),
padding=1,
padding_mode='reflect'))
suite.addTest(
Conv2DTestCase(
methodName='runTest',
filter_size=(3, 3),
padding=1,
padding_mode='replicate'))
suite.addTest(
Conv2DTestCase(
methodName='runTest',
filter_size=(3, 3),
padding=1,
padding_mode='circular'))
def add_error_cases(suite): def add_error_cases(suite):
suite.addTest(
Conv2DErrorTestCase(
methodName='runTest', use_cudnn="not_valid"))
suite.addTest( suite.addTest(
Conv2DErrorTestCase( Conv2DErrorTestCase(
methodName='runTest', num_channels=5, groups=2)) methodName='runTest', num_channels=5, groups=2))

20
python/paddle/fluid/tests/unittests/test_conv3d_layer.py
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@ -32,9 +32,7 @@ class Conv3DTestCase(unittest.TestCase):
stride=1, stride=1,
dilation=1, dilation=1,
groups=1, groups=1,
act=None,
no_bias=False, no_bias=False,
use_cudnn=True,
data_format="NCDHW", data_format="NCDHW",
dtype="float32"): dtype="float32"):
super(Conv3DTestCase, self).__init__(methodName) super(Conv3DTestCase, self).__init__(methodName)
@ -48,9 +46,7 @@ class Conv3DTestCase(unittest.TestCase):
self.stride = stride self.stride = stride
self.dilation = dilation self.dilation = dilation
self.groups = groups self.groups = groups
self.act = act
self.no_bias = no_bias self.no_bias = no_bias
self.use_cudnn = use_cudnn
self.data_format = data_format self.data_format = data_format
self.dtype = dtype self.dtype = dtype
@ -101,8 +97,6 @@ class Conv3DTestCase(unittest.TestCase):
groups=self.groups, groups=self.groups,
param_attr=weight_attr, param_attr=weight_attr,
bias_attr=bias_attr, bias_attr=bias_attr,
use_cudnn=self.use_cudnn,
act=self.act,
data_format=self.data_format) data_format=self.data_format)
feed_dict = {"input": self.input} feed_dict = {"input": self.input}
exe = fluid.Executor(place) exe = fluid.Executor(place)
@ -130,8 +124,6 @@ class Conv3DTestCase(unittest.TestCase):
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
act=self.act,
use_cudnn=self.use_cudnn,
data_format=self.data_format) data_format=self.data_format)
feed_dict = {"input": self.input, "weight": self.weight} feed_dict = {"input": self.input, "weight": self.weight}
if self.bias is not None: if self.bias is not None:
@ -143,7 +135,7 @@ class Conv3DTestCase(unittest.TestCase):
def paddle_nn_layer(self): def paddle_nn_layer(self):
x_var = dg.to_variable(self.input) x_var = dg.to_variable(self.input)
conv = nn.Conv3D( conv = nn.Conv3d(
self.num_channels, self.num_channels,
self.num_filters, self.num_filters,
self.filter_size, self.filter_size,
@ -151,10 +143,7 @@ class Conv3DTestCase(unittest.TestCase):
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
act=self.act, data_format=self.data_format)
use_cudnn=self.use_cudnn,
data_format=self.data_format,
dtype=self.dtype)
conv.weight.set_value(self.weight) conv.weight.set_value(self.weight)
if not self.no_bias: if not self.no_bias:
conv.bias.set_value(self.bias) conv.bias.set_value(self.bias)
@ -225,15 +214,10 @@ def add_cases(suite):
num_filters=6, num_filters=6,
num_channels=3, num_channels=3,
groups=3, groups=3,
use_cudnn=False,
act="sigmoid",
padding="valid")) padding="valid"))
def add_error_cases(suite): def add_error_cases(suite):
suite.addTest(
Conv3DErrorTestCase(
methodName='runTest', use_cudnn="not_valid"))
suite.addTest( suite.addTest(
Conv3DErrorTestCase( Conv3DErrorTestCase(
methodName='runTest', num_channels=5, groups=2)) methodName='runTest', num_channels=5, groups=2))

4
python/paddle/fluid/tests/unittests/test_dygraph_weight_norm.py
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@ -117,7 +117,7 @@ class TestDygraphWeightNorm(unittest.TestCase):
def test_check_output(self): def test_check_output(self):
fluid.enable_imperative() fluid.enable_imperative()
linear = paddle.nn.Conv2D(2, 3, 3) linear = paddle.nn.Conv2d(2, 3, 3)
before_weight = linear.weight.numpy() before_weight = linear.weight.numpy()
if self.dim == None: if self.dim == None:
self.dim = -1 self.dim = -1
@ -169,7 +169,7 @@ class TestDygraphRemoveWeightNorm(unittest.TestCase):
def test_check_output(self): def test_check_output(self):
fluid.enable_imperative() fluid.enable_imperative()
linear = paddle.nn.Conv2D(2, 3, 3) linear = paddle.nn.Conv2d(2, 3, 3)
before_weight = linear.weight before_weight = linear.weight
wn = weight_norm(linear, dim=self.dim) wn = weight_norm(linear, dim=self.dim)
rwn = remove_weight_norm(linear) rwn = remove_weight_norm(linear)

38
python/paddle/fluid/tests/unittests/test_functional_conv2d.py
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@ -37,7 +37,6 @@ class TestFunctionalConv2D(TestCase):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NHWC" self.data_format = "NHWC"
def prepare(self): def prepare(self):
@ -88,7 +87,6 @@ class TestFunctionalConv2D(TestCase):
param_attr=I.NumpyArrayInitializer(self.weight), param_attr=I.NumpyArrayInitializer(self.weight),
bias_attr=False bias_attr=False
if self.no_bias else I.NumpyArrayInitializer(self.bias), if self.no_bias else I.NumpyArrayInitializer(self.bias),
use_cudnn=self.use_cudnn,
act=self.act, act=self.act,
data_format=self.data_format) data_format=self.data_format)
exe = fluid.Executor(self.place) exe = fluid.Executor(self.place)
@ -121,9 +119,11 @@ class TestFunctionalConv2D(TestCase):
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
act=self.act, data_format=self.data_format)
data_format=self.data_format,
use_cudnn=self.use_cudnn) if self.act == 'sigmoid':
y = F.sigmoid(y)
exe = fluid.Executor(self.place) exe = fluid.Executor(self.place)
exe.run(start) exe.run(start)
feed_dict = {"input": self.input, "weight": self.weight} feed_dict = {"input": self.input, "weight": self.weight}
@ -144,10 +144,12 @@ class TestFunctionalConv2D(TestCase):
padding=self.padding, padding=self.padding,
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
act=self.act,
groups=self.groups, groups=self.groups,
data_format=self.data_format, data_format=self.data_format)
use_cudnn=self.use_cudnn)
if self.act == 'sigmoid':
y = F.sigmoid(y)
out = y.numpy() out = y.numpy()
return out return out
@ -185,7 +187,6 @@ class TestFunctionalConv2DError(TestCase):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NHWC" self.data_format = "NHWC"
def test_exception(self): def test_exception(self):
@ -228,9 +229,7 @@ class TestFunctionalConv2DError(TestCase):
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
act=self.act, data_format=self.data_format)
data_format=self.data_format,
use_cudnn=self.use_cudnn)
class TestFunctionalConv2DCase2(TestFunctionalConv2D): class TestFunctionalConv2DCase2(TestFunctionalConv2D):
@ -383,21 +382,6 @@ class TestFunctionalConv2DErrorCase4(TestFunctionalConv2DError):
self.data_format = "NCHW" self.data_format = "NCHW"
class TestFunctionalConv2DErrorCase6(TestFunctionalConv2DError):
def setUp(self):
self.in_channels = 3
self.out_channels = 5
self.filter_shape = 3
self.padding = "same"
self.stride = 1
self.dilation = 1
self.groups = 1
self.no_bias = False
self.act = "sigmoid"
self.use_cudnn = "not_valid"
self.data_format = "NCHW"
class TestFunctionalConv2DErrorCase7(TestFunctionalConv2DError): class TestFunctionalConv2DErrorCase7(TestFunctionalConv2DError):
def setUp(self): def setUp(self):
self.in_channels = 3 self.in_channels = 3

54
python/paddle/fluid/tests/unittests/test_functional_conv3d.py
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@ -37,7 +37,6 @@ class TestFunctionalConv3D(TestCase):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NDHWC" self.data_format = "NDHWC"
def prepare(self): def prepare(self):
@ -88,7 +87,6 @@ class TestFunctionalConv3D(TestCase):
param_attr=I.NumpyArrayInitializer(self.weight), param_attr=I.NumpyArrayInitializer(self.weight),
bias_attr=False bias_attr=False
if self.no_bias else I.NumpyArrayInitializer(self.bias), if self.no_bias else I.NumpyArrayInitializer(self.bias),
use_cudnn=self.use_cudnn,
act=self.act, act=self.act,
data_format=self.data_format) data_format=self.data_format)
exe = fluid.Executor(self.place) exe = fluid.Executor(self.place)
@ -121,9 +119,11 @@ class TestFunctionalConv3D(TestCase):
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
act=self.act, data_format=self.data_format)
data_format=self.data_format,
use_cudnn=self.use_cudnn) if self.act == 'sigmoid':
y = F.sigmoid(y)
exe = fluid.Executor(self.place) exe = fluid.Executor(self.place)
exe.run(start) exe.run(start)
feed_dict = {"input": self.input, "weight": self.weight} feed_dict = {"input": self.input, "weight": self.weight}
@ -144,10 +144,12 @@ class TestFunctionalConv3D(TestCase):
padding=self.padding, padding=self.padding,
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
act=self.act,
groups=self.groups, groups=self.groups,
data_format=self.data_format, data_format=self.data_format)
use_cudnn=self.use_cudnn)
if self.act == 'sigmoid':
y = F.sigmoid(y)
out = y.numpy() out = y.numpy()
return out return out
@ -185,7 +187,6 @@ class TestFunctionalConv3DError(TestCase):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NDHWC" self.data_format = "NDHWC"
def test_exception(self): def test_exception(self):
@ -228,9 +229,10 @@ class TestFunctionalConv3DError(TestCase):
stride=self.stride, stride=self.stride,
dilation=self.dilation, dilation=self.dilation,
groups=self.groups, groups=self.groups,
act=self.act, data_format=self.data_format)
data_format=self.data_format,
use_cudnn=self.use_cudnn) if self.act == 'sigmoid':
y = F.sigmoid(y)
class TestFunctionalConv3DCase2(TestFunctionalConv3D): class TestFunctionalConv3DCase2(TestFunctionalConv3D):
@ -244,7 +246,6 @@ class TestFunctionalConv3DCase2(TestFunctionalConv3D):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NDHWC" self.data_format = "NDHWC"
@ -259,7 +260,6 @@ class TestFunctionalConv3DCase3(TestFunctionalConv3D):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NDHWC" self.data_format = "NDHWC"
@ -274,7 +274,6 @@ class TestFunctionalConv3DCase4(TestFunctionalConv3D):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NDHWC" self.data_format = "NDHWC"
@ -289,7 +288,6 @@ class TestFunctionalConv3DCase5(TestFunctionalConv3D):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NDHWC" self.data_format = "NDHWC"
@ -304,7 +302,6 @@ class TestFunctionalConv3DCase6(TestFunctionalConv3D):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NCDHW" self.data_format = "NCDHW"
@ -319,7 +316,6 @@ class TestFunctionalConv3DCase7(TestFunctionalConv3D):
self.groups = 2 self.groups = 2
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NCDHW" self.data_format = "NCDHW"
@ -349,7 +345,6 @@ class TestFunctionalConv3DErrorCase2(TestFunctionalConv3DError):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = False
self.data_format = "NCDHW" self.data_format = "NCDHW"
@ -364,7 +359,6 @@ class TestFunctionalConv3DErrorCase3(TestFunctionalConv3DError):
self.groups = 2 self.groups = 2
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = False
self.data_format = "not_valid" self.data_format = "not_valid"
@ -379,22 +373,6 @@ class TestFunctionalConv3DErrorCase4(TestFunctionalConv3DError):
self.groups = 2 self.groups = 2
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = False
self.data_format = "NCDHW"
class TestFunctionalConv3DErrorCase6(TestFunctionalConv3DError):
def setUp(self):
self.in_channels = 3
self.out_channels = 5
self.filter_shape = 3
self.padding = "same"
self.stride = 1
self.dilation = 1
self.groups = 1
self.no_bias = False
self.act = "sigmoid"
self.use_cudnn = "not_valid"
self.data_format = "NCDHW" self.data_format = "NCDHW"
@ -409,7 +387,6 @@ class TestFunctionalConv3DErrorCase7(TestFunctionalConv3DError):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "not_valid" self.data_format = "not_valid"
@ -424,7 +401,6 @@ class TestFunctionalConv3DErrorCase8(TestFunctionalConv3DError):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = True
self.data_format = "NCDHW" self.data_format = "NCDHW"
@ -439,7 +415,6 @@ class TestFunctionalConv3DErrorCase9(TestFunctionalConv3DError):
self.groups = 1 self.groups = 1
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = False
self.data_format = "NCDHW" self.data_format = "NCDHW"
@ -454,7 +429,6 @@ class TestFunctionalConv3DErrorCase10(TestFunctionalConv3DError):
self.groups = 2 self.groups = 2
self.no_bias = False self.no_bias = False
self.act = "sigmoid" self.act = "sigmoid"
self.use_cudnn = False
self.data_format = "NDHWC" self.data_format = "NDHWC"

8
python/paddle/fluid/tests/unittests/test_imperative_layer_apply.py
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@ -28,11 +28,11 @@ class LeNetDygraph(fluid.dygraph.Layer):
super(LeNetDygraph, self).__init__() super(LeNetDygraph, self).__init__()
self.num_classes = num_classes self.num_classes = num_classes
self.features = nn.Sequential( self.features = nn.Sequential(
nn.Conv2D( nn.Conv2d(
1, 6, 3, stride=1, padding=1), 1, 6, 3, stride=1, padding=1),
nn.ReLU(), nn.ReLU(),
nn.Pool2D(2, 'max', 2), nn.Pool2D(2, 'max', 2),
nn.Conv2D( nn.Conv2d(
6, 16, 5, stride=1, padding=0), 6, 16, 5, stride=1, padding=0),
nn.ReLU(), nn.ReLU(),
nn.Pool2D(2, 'max', 2)) nn.Pool2D(2, 'max', 2))
@ -61,7 +61,7 @@ def init_weights(layer):
new_bias = paddle.fill_constant( new_bias = paddle.fill_constant(
layer.bias.shape, layer.bias.dtype, value=-0.1) layer.bias.shape, layer.bias.dtype, value=-0.1)
layer.bias.set_value(new_bias) layer.bias.set_value(new_bias)
elif type(layer) == nn.Conv2D: elif type(layer) == nn.Conv2d:
new_weight = paddle.fill_constant( new_weight = paddle.fill_constant(
layer.weight.shape, layer.weight.dtype, value=0.7) layer.weight.shape, layer.weight.dtype, value=0.7)
layer.weight.set_value(new_weight) layer.weight.set_value(new_weight)
@ -81,7 +81,7 @@ class TestLayerApply(unittest.TestCase):
if type(layer) == nn.Linear: if type(layer) == nn.Linear:
np.testing.assert_allclose(layer.weight.numpy(), 0.9) np.testing.assert_allclose(layer.weight.numpy(), 0.9)
np.testing.assert_allclose(layer.bias.numpy(), -0.1) 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.weight.numpy(), 0.7)
np.testing.assert_allclose(layer.bias.numpy(), -0.2) np.testing.assert_allclose(layer.bias.numpy(), -0.2)

4
python/paddle/fluid/tests/unittests/test_imperative_layer_children.py
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@ -27,11 +27,11 @@ class LeNetDygraph(fluid.dygraph.Layer):
def __init__(self): def __init__(self):
super(LeNetDygraph, self).__init__() super(LeNetDygraph, self).__init__()
self.features = nn.Sequential( self.features = nn.Sequential(
nn.Conv2D( nn.Conv2d(
1, 6, 3, stride=1, padding=1), 1, 6, 3, stride=1, padding=1),
nn.ReLU(), nn.ReLU(),
nn.Pool2D(2, 'max', 2), nn.Pool2D(2, 'max', 2),
nn.Conv2D( nn.Conv2d(
6, 16, 5, stride=1, padding=0), 6, 16, 5, stride=1, padding=0),
nn.ReLU(), nn.ReLU(),
nn.Pool2D(2, 'max', 2)) nn.Pool2D(2, 'max', 2))

4
python/paddle/fluid/tests/unittests/test_retain_graph.py
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@ -26,7 +26,7 @@ paddle.manual_seed(SEED)
class Generator(fluid.dygraph.Layer): class Generator(fluid.dygraph.Layer):
def __init__(self): def __init__(self):
super(Generator, self).__init__() super(Generator, self).__init__()
self.conv1 = paddle.nn.Conv2D(3, 3, 3, 1) self.conv1 = paddle.nn.Conv2d(3, 3, 3, padding=1)
def forward(self, x): def forward(self, x):
x = self.conv1(x) x = self.conv1(x)
@ -37,7 +37,7 @@ class Generator(fluid.dygraph.Layer):
class Discriminator(fluid.dygraph.Layer): class Discriminator(fluid.dygraph.Layer):
def __init__(self): def __init__(self):
super(Discriminator, self).__init__() super(Discriminator, self).__init__()
self.convd = paddle.nn.Conv2D(6, 3, 1) self.convd = paddle.nn.Conv2d(6, 3, 1)
def forward(self, x): def forward(self, x):
x = self.convd(x) x = self.convd(x)

6
python/paddle/incubate/hapi/tests/test_model.py
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@ -23,7 +23,7 @@ import shutil
import tempfile import tempfile
from paddle import fluid from paddle import fluid
from paddle.nn import Conv2D, Pool2D, Linear, ReLU, Sequential from paddle.nn import Conv2d, Pool2D, Linear, ReLU, Sequential
from paddle.fluid.dygraph.base import to_variable from paddle.fluid.dygraph.base import to_variable
import paddle.incubate.hapi as hapi import paddle.incubate.hapi as hapi
@ -40,11 +40,11 @@ class LeNetDygraph(fluid.dygraph.Layer):
super(LeNetDygraph, self).__init__() super(LeNetDygraph, self).__init__()
self.num_classes = num_classes self.num_classes = num_classes
self.features = Sequential( self.features = Sequential(
Conv2D( Conv2d(
1, 6, 3, stride=1, padding=1), 1, 6, 3, stride=1, padding=1),
ReLU(), ReLU(),
Pool2D(2, 'max', 2), Pool2D(2, 'max', 2),
Conv2D( Conv2d(
6, 16, 5, stride=1, padding=0), 6, 16, 5, stride=1, padding=0),
ReLU(), ReLU(),
Pool2D(2, 'max', 2)) Pool2D(2, 'max', 2))

6
python/paddle/incubate/hapi/tests/test_uncombined_weight2state_dict.py
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@ -22,7 +22,7 @@ import shutil
import tempfile import tempfile
from paddle import fluid from paddle import fluid
from paddle.nn import Conv2D, Pool2D, Linear, ReLU, Sequential from paddle.nn import Conv2d, Pool2D, Linear, ReLU, Sequential
from paddle.incubate.hapi.utils import uncombined_weight_to_state_dict from paddle.incubate.hapi.utils import uncombined_weight_to_state_dict
@ -32,11 +32,11 @@ class LeNetDygraph(fluid.dygraph.Layer):
super(LeNetDygraph, self).__init__() super(LeNetDygraph, self).__init__()
self.num_classes = num_classes self.num_classes = num_classes
self.features = Sequential( self.features = Sequential(
Conv2D( Conv2d(
1, 6, 3, stride=1, padding=1), 1, 6, 3, stride=1, padding=1),
ReLU(), ReLU(),
Pool2D(2, 'max', 2), Pool2D(2, 'max', 2),
Conv2D( Conv2d(
6, 16, 5, stride=1, padding=0), 6, 16, 5, stride=1, padding=0),
ReLU(), ReLU(),
Pool2D(2, 'max', 2)) Pool2D(2, 'max', 2))

6
python/paddle/incubate/hapi/vision/models/lenet.py
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@ -13,7 +13,7 @@
#limitations under the License. #limitations under the License.
import paddle.fluid as fluid import paddle.fluid as fluid
from paddle.nn import Conv2D, Pool2D, Linear, ReLU, Sequential from paddle.nn import Conv2d, Pool2D, Linear, ReLU, Sequential
__all__ = ['LeNet'] __all__ = ['LeNet']
@ -39,11 +39,11 @@ class LeNet(fluid.dygraph.Layer):
super(LeNet, self).__init__() super(LeNet, self).__init__()
self.num_classes = num_classes self.num_classes = num_classes
self.features = Sequential( self.features = Sequential(
Conv2D( Conv2d(
1, 6, 3, stride=1, padding=1), 1, 6, 3, stride=1, padding=1),
ReLU(), ReLU(),
Pool2D(2, 'max', 2), Pool2D(2, 'max', 2),
Conv2D( Conv2d(
6, 16, 5, stride=1, padding=0), 6, 16, 5, stride=1, padding=0),
ReLU(), ReLU(),
Pool2D(2, 'max', 2)) Pool2D(2, 'max', 2))

11
python/paddle/incubate/hapi/vision/models/vgg.py
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@ -13,7 +13,7 @@
# limitations under the License. # limitations under the License.
import paddle.fluid as fluid import paddle.fluid as fluid
from paddle.fluid.dygraph.nn import Conv2D, Pool2D, BatchNorm, Linear from paddle.nn import Conv2d, Pool2D, BatchNorm, Linear, ReLU
from paddle.fluid.dygraph.container import Sequential from paddle.fluid.dygraph.container import Sequential
from ...download import get_weights_path_from_url from ...download import get_weights_path_from_url
@ -105,12 +105,11 @@ def make_layers(cfg, batch_norm=False):
layers += [Pool2D(pool_size=2, pool_stride=2)] layers += [Pool2D(pool_size=2, pool_stride=2)]
else: else:
if batch_norm: if batch_norm:
conv2d = Conv2D(in_channels, v, filter_size=3, padding=1) conv2d = Conv2d(in_channels, v, kernel_size=3, padding=1)
layers += [conv2d, BatchNorm(v, act='relu')] layers += [conv2d, BatchNorm(v), ReLU()]
else: else:
conv2d = Conv2D( conv2d = Conv2d(in_channels, v, kernel_size=3, padding=1)
in_channels, v, filter_size=3, padding=1, act='relu') layers += [conv2d, ReLU()]
layers += [conv2d]
in_channels = v in_channels = v
return Sequential(*layers) return Sequential(*layers)

4
python/paddle/nn/__init__.py
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@ -93,9 +93,9 @@ from .layer.common import Dropout2D #DEFINE_ALIAS
from .layer.common import Dropout3D #DEFINE_ALIAS from .layer.common import Dropout3D #DEFINE_ALIAS
from .layer.pooling import AdaptiveAvgPool2d #DEFINE_ALIAS from .layer.pooling import AdaptiveAvgPool2d #DEFINE_ALIAS
from .layer.pooling import AdaptiveAvgPool3d #DEFINE_ALIAS from .layer.pooling import AdaptiveAvgPool3d #DEFINE_ALIAS
from .layer.conv import Conv2D #DEFINE_ALIAS from .layer.conv import Conv2d #DEFINE_ALIAS
from .layer.conv import Conv3d #DEFINE_ALIAS
from .layer.conv import ConvTranspose2d #DEFINE_ALIAS from .layer.conv import ConvTranspose2d #DEFINE_ALIAS
from .layer.conv import Conv3D #DEFINE_ALIAS
from .layer.conv import ConvTranspose3d #DEFINE_ALIAS from .layer.conv import ConvTranspose3d #DEFINE_ALIAS
# from .layer.conv import TreeConv #DEFINE_ALIAS # from .layer.conv import TreeConv #DEFINE_ALIAS
# from .layer.conv import Conv1D #DEFINE_ALIAS # from .layer.conv import Conv1D #DEFINE_ALIAS

143
python/paddle/nn/functional/conv.py
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4
python/paddle/nn/layer/__init__.py
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@ -57,9 +57,9 @@ from .common import Dropout2D #DEFINE_ALIAS
from .common import Dropout3D #DEFINE_ALIAS from .common import Dropout3D #DEFINE_ALIAS
from .pooling import AdaptiveAvgPool2d #DEFINE_ALIAS from .pooling import AdaptiveAvgPool2d #DEFINE_ALIAS
from .pooling import AdaptiveAvgPool3d #DEFINE_ALIAS from .pooling import AdaptiveAvgPool3d #DEFINE_ALIAS
from .conv import Conv2D #DEFINE_ALIAS from .conv import Conv2d #DEFINE_ALIAS
from .conv import Conv3d #DEFINE_ALIAS
from .conv import ConvTranspose2d #DEFINE_ALIAS from .conv import ConvTranspose2d #DEFINE_ALIAS
from .conv import Conv3D #DEFINE_ALIAS
from .conv import ConvTranspose3d #DEFINE_ALIAS from .conv import ConvTranspose3d #DEFINE_ALIAS
# from .conv import TreeConv #DEFINE_ALIAS # from .conv import TreeConv #DEFINE_ALIAS
# from .conv import Conv1D #DEFINE_ALIAS # from .conv import Conv1D #DEFINE_ALIAS

377
python/paddle/nn/layer/conv.py
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