Skip to content

Commit

Permalink
Expose clip to frontend mxnet (apache#512)
Browse files Browse the repository at this point in the history
  • Loading branch information
ehsanmok authored and tqchen committed May 26, 2018
1 parent 38ca07d commit 8a573bf
Show file tree
Hide file tree
Showing 3 changed files with 55 additions and 18 deletions.
7 changes: 7 additions & 0 deletions nnvm/python/nnvm/frontend/mxnet.py
Original file line number Diff line number Diff line change
Expand Up @@ -205,6 +205,12 @@ def _upsampling(inputs, attrs):
new_attrs = {'scale':int(scale)}
return _get_nnvm_op('upsampling')(inputs[0], **new_attrs)

def _clip(inputs, attrs):
op_name, new_attrs = "clip", {}
new_attrs['a_min'] = _required_attr(attrs, 'a_min')
new_attrs['a_max'] = _required_attr(attrs, 'a_max')
return _get_nnvm_op(op_name)(*inputs, **new_attrs)


_identity_list = ['__add_scalar__', '__add_symbol__', '__div_scalar__',
'__div_symbol__', '__mul_scalar__', '__mul_symbol__',
Expand Down Expand Up @@ -248,6 +254,7 @@ def _upsampling(inputs, attrs):
'reshape' : _reshape,
'sum_axis' : _rename('sum'),
'UpSampling' : _upsampling,
'clip' : _clip
}

def _convert_symbol(op_name, inputs, attrs,
Expand Down
2 changes: 1 addition & 1 deletion nnvm/tests/python/frontend/mxnet/model_zoo/vgg.py
Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ def get_symbol(num_classes, num_layers=11, batch_norm=False, dtype='float32', **
13: ([2, 2, 2, 2, 2], [64, 128, 256, 512, 512]),
16: ([2, 2, 3, 3, 3], [64, 128, 256, 512, 512]),
19: ([2, 2, 4, 4, 4], [64, 128, 256, 512, 512])}
if not vgg_spec.has_key(num_layers):
if num_layers not in vgg_spec:
raise ValueError("Invalide num_layers {}. Possible choices are 11,13,16,19.".format(num_layers))
layers, filters = vgg_spec[num_layers]
data = mx.sym.Variable(name="data")
Expand Down
64 changes: 47 additions & 17 deletions nnvm/tests/python/frontend/mxnet/test_forward.py
Original file line number Diff line number Diff line change
Expand Up @@ -8,24 +8,41 @@
from nnvm.testing.config import ctx_list
from nnvm import frontend
import mxnet as mx
from mxnet import gluon
from mxnet.gluon.model_zoo import vision
import model_zoo


def verify_mxnet_frontend_impl(mx_symbol, data_shape=(1, 3, 224, 224), out_shape=(1, 1000)):
def verify_mxnet_frontend_impl(mx_symbol, data_shape=(1, 3, 224, 224), out_shape=(1, 1000),
gluon_impl=False, name=None):
"""Use name different from test to avoid let nose pick it up"""
def get_mxnet_output(symbol, x, dtype='float32'):
from collections import namedtuple
Batch = namedtuple('Batch', ['data'])
mod = mx.mod.Module(symbol, label_names=None)
mod.bind(data_shapes=[('data', x.shape)], for_training=False)
mod.init_params()
mod.forward(Batch([mx.nd.array(x.astype(dtype))]))
out = mod.get_outputs()[0].asnumpy()
args, auxs = mod.get_params()
return out, args, auxs
if gluon_impl:
def get_gluon_output(name, x):
net = vision.get_model(name)
net.collect_params().initialize(mx.init.Xavier())
net_sym = gluon.nn.SymbolBlock(outputs=net(mx.sym.var('data')),
inputs=mx.sym.var('data'),
params=net.collect_params())
out = net_sym(mx.nd.array(x.astype(dtype))).asnumpy()
return out, net_sym
else:
def get_mxnet_output(symbol, x, dtype='float32'):
from collections import namedtuple
Batch = namedtuple('Batch', ['data'])
mod = mx.mod.Module(symbol, label_names=None)
mod.bind(data_shapes=[('data', x.shape)], for_training=False)
mod.init_params()
mod.forward(Batch([mx.nd.array(x.astype(dtype))]))
out = mod.get_outputs()[0].asnumpy()
args, auxs = mod.get_params()
return out, args, auxs

def get_tvm_output(symbol, x, args, auxs, target, ctx, dtype='float32'):
new_sym, params = frontend.from_mxnet(symbol, args, auxs)
if gluon_impl:
new_sym, params = frontend.from_mxnet(symbol)
else:
new_sym, params = frontend.from_mxnet(symbol, args, auxs)

dshape = x.shape
shape_dict = {'data': dshape}
with nnvm.compiler.build_config(opt_level=3):
Expand All @@ -42,11 +59,17 @@ def get_tvm_output(symbol, x, args, auxs, target, ctx, dtype='float32'):
# random input
dtype = 'float32'
x = np.random.uniform(size=data_shape)
mx_out, args, auxs = get_mxnet_output(mx_symbol, x, dtype)
assert "data" not in args
for target, ctx in ctx_list():
tvm_out = get_tvm_output(mx_symbol, x, args, auxs, target, ctx, dtype)
np.testing.assert_allclose(mx_out, tvm_out, rtol=1e-5, atol=1e-5)
if gluon_impl:
gluon_out, gluon_sym = get_gluon_output(name, x)
for target, ctx in ctx_list():
tvm_out = get_tvm_output(gluon_sym, x, None, None, target, ctx, dtype)
np.testing.assert_allclose(gluon_out, tvm_out, rtol=1e-5, atol=1e-5)
else:
mx_out, args, auxs = get_mxnet_output(mx_symbol, x, dtype)
assert "data" not in args
for target, ctx in ctx_list():
tvm_out = get_tvm_output(mx_symbol, x, args, auxs, target, ctx, dtype)
np.testing.assert_allclose(mx_out, tvm_out, rtol=1e-5, atol=1e-5)

def test_forward_mlp():
mlp = model_zoo.mx_mlp
Expand Down Expand Up @@ -91,6 +114,12 @@ def test_forward_fc_flatten():
except:
pass

def test_forward_clip():
data = mx.sym.var('data')
data = mx.sym.concat(data, -data, dim=1) # negative part explicity
mx_sym = mx.sym.clip(data, a_min=0, a_max=1)
verify_mxnet_frontend_impl(mx_sym, (1, 3, 100, 100), (1, 6, 100, 100))

if __name__ == '__main__':
test_forward_mlp()
test_forward_vgg()
Expand All @@ -99,3 +128,4 @@ def test_forward_fc_flatten():
test_forward_rrelu()
test_forward_softrelu()
test_forward_fc_flatten()
test_forward_clip()

0 comments on commit 8a573bf

Please sign in to comment.