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wenyuanbo
tic
Commits
d626eab8
Commit
d626eab8
authored
Jan 16, 2018
by
Yuwei Hu
Committed by
Tianqi Chen
May 29, 2018
Browse files
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[CI] turn on keras frontend test (#309)
* [CI] turn on keras frontend test * fix * using tensorflow cpu version
parent
2374852e
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Showing
3 changed files
with
32 additions
and
22 deletions
+32
-22
nnvm/python/nnvm/frontend/keras.py
+0
-2
nnvm/tests/python/frontend/keras/test_forward.py
+29
-20
nnvm/tests/scripts/task_frontend_test.sh
+3
-0
No files found.
nnvm/python/nnvm/frontend/keras.py
View file @
d626eab8
...
...
@@ -273,7 +273,6 @@ def _convert_pooling(insym, keras_layer, symtab):
def
_convert_upsample
(
insym
,
keras_layer
,
_
):
_check_data_format
(
keras_layer
)
upsample_type
=
type
(
keras_layer
)
.
__name__
if
upsample_type
==
"UpSampling1D"
:
h
=
keras_layer
.
size
params
=
{
'scale'
:
h
}
...
...
@@ -291,7 +290,6 @@ def _convert_upsample(insym, keras_layer, _):
params
=
{
'scale'
:
h
}
else
:
raise
TypeError
(
"Unsupported upsampling type : {}"
.
format
(
upsample_type
))
return
_sym
.
upsampling
(
insym
,
**
params
)
...
...
nnvm/tests/python/frontend/keras/test_forward.py
View file @
d626eab8
...
...
@@ -39,7 +39,7 @@ def verify_keras_frontend(keras_model):
np
.
testing
.
assert_allclose
(
keras_out
,
tvm_out
,
rtol
=
1e-5
,
atol
=
1e-5
)
def
verify
_forward_softrelu
():
def
test
_forward_softrelu
():
data
=
keras
.
layers
.
Input
(
shape
=
(
32
,
32
,
3
))
x
=
keras
.
layers
.
Activation
(
'softplus'
)(
data
)
x
=
keras
.
layers
.
Concatenate
()([
x
,
x
])
...
...
@@ -48,7 +48,7 @@ def verify_forward_softrelu():
verify_keras_frontend
(
keras_model
)
def
verify
_forward_leaky_relu
():
def
test
_forward_leaky_relu
():
data
=
keras
.
layers
.
Input
(
shape
=
(
32
,
32
,
3
))
x
=
keras
.
layers
.
LeakyReLU
(
alpha
=
0.3
)(
data
)
x
=
keras
.
layers
.
Add
()([
x
,
x
])
...
...
@@ -57,7 +57,7 @@ def verify_forward_leaky_relu():
verify_keras_frontend
(
keras_model
)
def
verify
_forward_dense
():
def
test
_forward_dense
():
data
=
keras
.
layers
.
Input
(
shape
=
(
32
,
32
,
3
))
x
=
keras
.
layers
.
MaxPooling2D
(
pool_size
=
(
2
,
2
))(
data
)
x
=
keras
.
layers
.
Flatten
()(
x
)
...
...
@@ -66,7 +66,7 @@ def verify_forward_dense():
verify_keras_frontend
(
keras_model
)
def
verify
_forward_transpose_conv
():
def
test
_forward_transpose_conv
():
data
=
keras
.
layers
.
Input
(
shape
=
(
32
,
32
,
3
))
x
=
keras
.
layers
.
Conv2D
(
filters
=
10
,
kernel_size
=
(
3
,
3
),
strides
=
(
2
,
2
),
padding
=
'same'
)(
data
)
x
=
keras
.
applications
.
mobilenet
.
DepthwiseConv2D
(
kernel_size
=
(
3
,
3
),
padding
=
'same'
)(
x
)
...
...
@@ -76,7 +76,7 @@ def verify_forward_transpose_conv():
verify_keras_frontend
(
keras_model
)
def
verify
_forward_separable_conv
():
def
test
_forward_separable_conv
():
data
=
keras
.
layers
.
Input
(
shape
=
(
32
,
32
,
3
))
x
=
keras
.
layers
.
SeparableConv2D
(
filters
=
10
,
kernel_size
=
(
3
,
3
),
padding
=
'same'
,
activation
=
'relu'
)(
data
)
...
...
@@ -87,31 +87,40 @@ def verify_forward_separable_conv():
verify_keras_frontend
(
keras_model
)
def
verify_forward_vgg16
():
keras_model
=
keras
.
applications
.
vgg16
.
VGG16
(
include_top
=
True
,
weights
=
'imagenet'
,
def
test_forward_upsample
():
data
=
keras
.
layers
.
Input
(
shape
=
(
32
,
32
,
3
))
x
=
keras
.
layers
.
UpSampling2D
(
size
=
(
3
,
3
))(
data
)
x
=
keras
.
layers
.
GlobalAveragePooling2D
()(
x
)
keras_model
=
keras
.
models
.
Model
(
data
,
x
)
verify_keras_frontend
(
keras_model
)
def
test_forward_vgg16
():
keras_model
=
keras
.
applications
.
vgg16
.
VGG16
(
include_top
=
True
,
weights
=
None
,
input_shape
=
(
224
,
224
,
3
),
classes
=
1000
)
verify_keras_frontend
(
keras_model
)
def
verify
_forward_xception
():
keras_model
=
keras
.
applications
.
xception
.
Xception
(
include_top
=
True
,
weights
=
'imagenet'
,
def
test
_forward_xception
():
keras_model
=
keras
.
applications
.
xception
.
Xception
(
include_top
=
True
,
weights
=
None
,
input_shape
=
(
299
,
299
,
3
),
classes
=
1000
)
verify_keras_frontend
(
keras_model
)
def
verify
_forward_resnet50
():
keras_model
=
keras
.
applications
.
resnet50
.
ResNet50
(
include_top
=
True
,
weights
=
'imagenet'
,
def
test
_forward_resnet50
():
keras_model
=
keras
.
applications
.
resnet50
.
ResNet50
(
include_top
=
True
,
weights
=
None
,
input_shape
=
(
224
,
224
,
3
),
classes
=
1000
)
verify_keras_frontend
(
keras_model
)
if
__name__
==
'__main__'
:
verify_forward_softrelu
()
verify_forward_leaky_relu
()
verify_forward_dense
()
verify_forward_transpose_conv
()
verify_forward_separable_conv
()
verify_forward_vgg16
()
verify_forward_xception
()
verify_forward_resnet50
()
test_forward_softrelu
()
test_forward_leaky_relu
()
test_forward_dense
()
test_forward_transpose_conv
()
test_forward_separable_conv
()
test_forward_upsample
()
test_forward_vgg16
()
test_forward_xception
()
test_forward_resnet50
()
nnvm/tests/scripts/task_frontend_test.sh
View file @
d626eab8
...
...
@@ -7,3 +7,6 @@ python -m nose -v tests/python/frontend/onnx || exit -1
echo
"Running MXNet frontend test..."
python
-m
nose
-v
tests/python/frontend/mxnet
||
exit
-1
echo
"Running Keras frontend test..."
python
-m
nose
-v
tests/python/frontend/keras
||
exit
-1
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