From 31edf3f7eb4c7c2473cc13cbe74d534c70788f62 Mon Sep 17 00:00:00 2001
From: "Ehsan M. Kermani" <ehsanmo1367@gmail.com>
Date: Fri, 25 May 2018 09:26:23 -0700
Subject: [PATCH] Expose clip to frontend mxnet (#512)
---
nnvm/python/nnvm/frontend/mxnet.py | 7 ++
.../python/frontend/mxnet/model_zoo/vgg.py | 2 +-
.../python/frontend/mxnet/test_forward.py | 64 ++++++++++++++-----
3 files changed, 55 insertions(+), 18 deletions(-)
diff --git a/nnvm/python/nnvm/frontend/mxnet.py b/nnvm/python/nnvm/frontend/mxnet.py
index e671acbe7..3fc3ca851 100644
--- a/nnvm/python/nnvm/frontend/mxnet.py
+++ b/nnvm/python/nnvm/frontend/mxnet.py
@@ -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__',
@@ -248,6 +254,7 @@ _convert_map = {
'reshape' : _reshape,
'sum_axis' : _rename('sum'),
'UpSampling' : _upsampling,
+ 'clip' : _clip
}
def _convert_symbol(op_name, inputs, attrs,
diff --git a/nnvm/tests/python/frontend/mxnet/model_zoo/vgg.py b/nnvm/tests/python/frontend/mxnet/model_zoo/vgg.py
index c9243d361..68215bb80 100644
--- a/nnvm/tests/python/frontend/mxnet/model_zoo/vgg.py
+++ b/nnvm/tests/python/frontend/mxnet/model_zoo/vgg.py
@@ -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")
diff --git a/nnvm/tests/python/frontend/mxnet/test_forward.py b/nnvm/tests/python/frontend/mxnet/test_forward.py
index 0f9747538..fca19a693 100644
--- a/nnvm/tests/python/frontend/mxnet/test_forward.py
+++ b/nnvm/tests/python/frontend/mxnet/test_forward.py
@@ -8,24 +8,41 @@ import nnvm.compiler
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):
@@ -42,11 +59,17 @@ def verify_mxnet_frontend_impl(mx_symbol, data_shape=(1, 3, 224, 224), out_shape
# 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
@@ -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()
@@ -99,3 +128,4 @@ if __name__ == '__main__':
test_forward_rrelu()
test_forward_softrelu()
test_forward_fc_flatten()
+ test_forward_clip()
--
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