Skip to content

Commit a7f63e9

Browse files
piiswrongsergei-mironov
piiswrong
authored and
sergei-mironov
committed
add level2 ops (#6)
1 parent 89c5205 commit a7f63e9

File tree

2 files changed

+369
-9
lines changed

2 files changed

+369
-9
lines changed

‎nnvm/include/nnvm/top/nn.h

Lines changed: 153 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -12,6 +12,20 @@
1212
namespace nnvm {
1313
namespace top {
1414

15+
enum LayoutFlag {
16+
kNCHW = 0,
17+
kNHWC,
18+
kCHWN,
19+
20+
kNCW = 1 << 3,
21+
kNWC,
22+
kCWN,
23+
24+
kNCDHW = 1 << 5,
25+
kNDHWC,
26+
kCDHWN
27+
};
28+
1529
struct DenseParam : public dmlc::Parameter<DenseParam> {
1630
int units;
1731
bool use_bias;
@@ -85,6 +99,145 @@ struct LogSoftmaxParam : public dmlc::Parameter<LogSoftmaxParam> {
8599
}
86100
};
87101

102+
struct Conv2DParam : public dmlc::Parameter<Conv2DParam> {
103+
int channels;
104+
TShape kernel_size;
105+
TShape strides;
106+
TShape padding;
107+
TShape dilation;
108+
int groups;
109+
int layout;
110+
bool use_bias;
111+
112+
DMLC_DECLARE_PARAMETER(Conv2DParam) {
113+
DMLC_DECLARE_FIELD(channels)
114+
.describe("The dimensionality of the output space"
115+
"i.e. the number of output channels in the convolution.");
116+
DMLC_DECLARE_FIELD(kernel_size)
117+
.describe("Specifies the dimensions of the convolution window.");
118+
DMLC_DECLARE_FIELD(strides).set_default(TShape({1, 1}))
119+
.describe("Specifies the strides of the convolution.");
120+
DMLC_DECLARE_FIELD(padding).set_default(TShape({0, 0}))
121+
.describe("If padding is non-zero, then the input is implicitly zero-padded"
122+
"on both sides for padding number of points");
123+
DMLC_DECLARE_FIELD(dilation).set_default(TShape({1, 1}))
124+
.describe("Specifies the dilation rate to use for dilated convolution.");
125+
DMLC_DECLARE_FIELD(groups).set_default(1)
126+
.describe("Controls the connections between inputs and outputs."
127+
"At groups=1, all inputs are convolved to all outputs."
128+
"At groups=2, the operation becomes equivalent to having two convolution"
129+
"layers side by side, each seeing half the input channels, and producing"
130+
"half the output channels, and both subsequently concatenated.");
131+
DMLC_DECLARE_FIELD(layout)
132+
.add_enum("NCHW", kNCHW)
133+
.add_enum("NHWC", kNHWC)
134+
.set_default(kNCHW)
135+
.describe("Dimension ordering of data and weight. Can be 'NCHW', 'NHWC', etc."
136+
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
137+
"dimensions respectively. Convolution is applied on the 'H' and"
138+
"'W' dimensions.");
139+
DMLC_DECLARE_FIELD(use_bias).set_default(true)
140+
.describe("Whether the layer uses a bias vector.");
141+
}
142+
};
143+
144+
145+
struct Conv2DTransposeParam : public dmlc::Parameter<Conv2DTransposeParam> {
146+
int channels;
147+
TShape kernel_size;
148+
TShape strides;
149+
TShape padding;
150+
TShape output_padding;
151+
TShape dilation;
152+
int groups;
153+
int layout;
154+
bool use_bias;
155+
156+
DMLC_DECLARE_PARAMETER(Conv2DTransposeParam) {
157+
DMLC_DECLARE_FIELD(channels)
158+
.describe("The dimensionality of the output space"
159+
"i.e. the number of output channels in the convolution.");
160+
DMLC_DECLARE_FIELD(kernel_size)
161+
.describe("Specifies the dimensions of the convolution window.");
162+
DMLC_DECLARE_FIELD(strides).set_default(TShape({1, 1}))
163+
.describe("Specifies the strides of the convolution.");
164+
DMLC_DECLARE_FIELD(output_padding).set_default(TShape({0, 0}))
165+
.describe("Zero-padding added to one side of the output.");
166+
DMLC_DECLARE_FIELD(padding).set_default(TShape({0, 0}))
167+
.describe("If padding is non-zero, then the input is implicitly zero-padded"
168+
"on both sides for padding number of points");
169+
DMLC_DECLARE_FIELD(dilation).set_default(TShape({1, 1}))
170+
.describe("Specifies the dilation rate to use for dilated convolution.");
171+
DMLC_DECLARE_FIELD(groups).set_default(1)
172+
.describe("Controls the connections between inputs and outputs."
173+
"At groups=1, all inputs are convolved to all outputs."
174+
"At groups=2, the operation becomes equivalent to having two convolution"
175+
"layers side by side, each seeing half the input channels, and producing"
176+
"half the output channels, and both subsequently concatenated.");
177+
DMLC_DECLARE_FIELD(layout)
178+
.add_enum("NCHW", kNCHW)
179+
.add_enum("NHWC", kNHWC)
180+
.set_default(kNCHW)
181+
.describe("Dimension ordering of data and weight. Can be 'NCHW', 'NHWC', etc."
182+
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
183+
"dimensions respectively. Convolution is applied on the 'H' and"
184+
"'W' dimensions.");
185+
DMLC_DECLARE_FIELD(use_bias).set_default(true)
186+
.describe("Whether the layer uses a bias vector.");
187+
}
188+
};
189+
190+
struct Pool2DParam : public dmlc::Parameter<Pool2DParam> {
191+
TShape pool_size;
192+
TShape strides;
193+
TShape padding;
194+
int groups;
195+
int layout;
196+
bool ceil_mode;
197+
198+
DMLC_DECLARE_PARAMETER(Pool2DParam) {
199+
DMLC_DECLARE_FIELD(pool_size)
200+
.describe("Size of the pooling windows..");
201+
DMLC_DECLARE_FIELD(strides).set_default(TShape({1, 1}))
202+
.describe("Specifies the strides of the convolution.");
203+
DMLC_DECLARE_FIELD(padding).set_default(TShape({0, 0}))
204+
.describe("If padding is non-zero, then the input is implicitly zero-padded"
205+
"on both sides for padding number of points");
206+
DMLC_DECLARE_FIELD(groups).set_default(1)
207+
.describe("Controls the connections between inputs and outputs."
208+
"At groups=1, all inputs are convolved to all outputs."
209+
"At groups=2, the operation becomes equivalent to having two convolution"
210+
"layers side by side, each seeing half the input channels, and producing"
211+
"half the output channels, and both subsequently concatenated.");
212+
DMLC_DECLARE_FIELD(layout)
213+
.add_enum("NCHW", kNCHW)
214+
.add_enum("NHWC", kNHWC)
215+
.set_default(kNCHW)
216+
.describe("Dimension ordering of data and weight. Can be 'NCHW', 'NHWC', etc."
217+
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
218+
"dimensions respectively. Convolution is applied on the 'H' and"
219+
"'W' dimensions.");
220+
DMLC_DECLARE_FIELD(ceil_mode).set_default(false)
221+
.describe("When true, will use ceil instead of floor to compute the output shape.");
222+
}
223+
};
224+
225+
226+
struct GlobalPool2DParam : public dmlc::Parameter<GlobalPool2DParam> {
227+
int layout;
228+
229+
DMLC_DECLARE_PARAMETER(GlobalPool2DParam) {
230+
DMLC_DECLARE_FIELD(layout)
231+
.add_enum("NCHW", kNCHW)
232+
.add_enum("NHWC", kNHWC)
233+
.set_default(kNCHW)
234+
.describe("Dimension ordering of data and weight. Can be 'NCHW', 'NHWC', etc."
235+
"'N', 'C', 'H', 'W' stands for batch, channel, height, and width"
236+
"dimensions respectively. Convolution is applied on the 'H' and"
237+
"'W' dimensions.");
238+
}
239+
};
240+
88241
} // namespace top
89242
} // namespace nnvm
90243

0 commit comments

Comments
 (0)