1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
use ndarray::{Array, ArrayD, ArrayViewD};
use nodes::*;
use std::collections::BTreeMap;
use std::fmt;
use optimizers::Optimizer;
use xavier_initialize;
#[derive(Debug, Clone, Copy, Serialize, Deserialize, Hash, PartialEq, Eq)]
pub struct Idx {
idx: usize,
}
#[derive(DebugStub, Serialize, Deserialize)]
pub struct Graph {
nodes: BTreeMap<usize, Node>,
values: BTreeMap<usize, ArrayD<f32>>,
losses: BTreeMap<usize, ArrayD<f32>>,
num_inserted: usize,
#[debug_stub = "Initializer function"]
#[serde(skip)]
initializer: Initializer,
pub optimizer: Optimizer,
pub named_idxs: BTreeMap<String, Idx>,
}
struct Initializer(Box<(Fn(&[usize]) -> ArrayD<f32>)>);
impl Default for Initializer {
fn default() -> Self {
Initializer(Box::new(xavier_initialize))
}
}
impl fmt::Display for Graph {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
writeln!(f, "Computation Graph with Optimizer:\n\t{}", self.optimizer)?;
for (i, node) in self.nodes.iter() {
writeln!(
f,
"\n{}\t{:?}\n\tvalue shape: {:?}\tloss shape: {:?}",
i,
node,
self.values[&i].shape(),
self.losses[&i].shape(),
)?
}
Ok(())
}
}
impl Default for Graph {
fn default() -> Self {
Graph::new(Box::new(xavier_initialize), Optimizer::default())
}
}
impl Graph {
pub fn new(initializer: Box<(Fn(&[usize]) -> ArrayD<f32>)>, optimizer: Optimizer) -> Self {
Graph {
nodes: BTreeMap::new(),
values: BTreeMap::new(),
losses: BTreeMap::new(),
named_idxs: BTreeMap::new(),
num_inserted: 0,
initializer: Initializer(initializer),
optimizer,
}
}
pub fn register(&mut self, node: Node) -> Idx {
let idx = self.num_inserted;
if let Node::Parameter(ref shape) = node {
self.optimizer.register(Idx { idx }, shape)
}
self.nodes.insert(idx, node);
self.values.insert(idx, Array::zeros(()).into_dyn());
self.losses.insert(idx, Array::zeros(()).into_dyn());
self.num_inserted += 1;
Idx { idx }
}
pub fn param(&mut self, shape: &[usize]) -> Idx {
let idx = self.register(Node::Parameter(shape.to_vec().into_boxed_slice()));
self.values.insert(idx.idx, (self.initializer.0)(shape));
self.losses.insert(idx.idx, Array::zeros(shape));
self.num_inserted += 1;
idx
}
pub fn input(&mut self, it: Option<Box<Iterator<Item = ArrayD<f32>>>>) -> Idx {
self.register(Node::Input { it })
}
pub fn op(&mut self, op: impl Operation + 'static, inputs: &[Idx]) -> Idx {
let o = Node::Operation {
operation: Box::new(op),
inputs: inputs.to_vec().into_boxed_slice(),
};
self.register(o)
}
pub fn constant(&mut self, c: ArrayD<f32>) -> Idx {
let idx = self.register(Node::Constant);
self.set_value(idx, c);
idx
}
fn _forward1(&mut self, i: usize) {
if let Some(n) = self.nodes.get_mut(&i) {
let inps = n.inputs();
if let Some(v) = n.forward(&view_at_idxs(&inps, &self.values)) {
self.values.insert(i, v);
}
}
self.losses.insert(i, Array::zeros(self.values[&i].shape()));
}
fn _backward1(&mut self, i: usize) {
if let Some(n) = self.nodes.get_mut(&i) {
if let Node::Parameter(..) = n {
self.optimizer.apply_gradient(
Idx { idx: i },
self.values.get_mut(&i).unwrap().view_mut(),
&self.losses[&i],
);
} else {
let inps = n.inputs();
let gradients = n.backward(&view_at_idxs(&inps, &self.values), &self.losses[&i]);
for (grad, j) in gradients.iter().zip(inps.iter()) {
if let Some(x) = self.losses.get_mut(&j.idx) {
*x += grad;
}
}
}
}
}
pub fn forward(&mut self) {
let keys: Vec<usize> = self.nodes.keys().cloned().collect();
for i in keys.into_iter() {
self._forward1(i);
}
}
pub fn backward(&mut self) {
let keys: Vec<usize> = self.nodes.keys().rev().cloned().collect();
for i in keys.into_iter() {
self._backward1(i);
}
}
pub fn forward1(&mut self, i: Idx) {
self._forward1(i.idx);
}
pub fn backward1(&mut self, i: Idx) {
self._backward1(i.idx);
}
pub fn remove(&mut self, idx: Idx) {
self.nodes.remove(&idx.idx);
self.values.remove(&idx.idx);
self.losses.remove(&idx.idx);
}
pub fn clear_non_parameters(&mut self) {
let mut keys = Vec::new();
for (i, n) in self.nodes.iter() {
if let Node::Parameter(_) = n {
} else {
keys.push(*i);
}
}
for k in keys.into_iter() {
self.nodes.remove(&k);
self.values.remove(&k);
self.losses.remove(&k);
}
}
pub fn set_value(&mut self, idx: Idx, val: ArrayD<f32>) {
if self.values.insert(idx.idx, val).is_none() {
panic!("Tried to set value at a removed index")
}
}
pub fn get_value(&self, idx: Idx) -> &ArrayD<f32> {
&self.values[&idx.idx]
}
pub fn set_loss(&mut self, idx: Idx, loss: ArrayD<f32>) {
if self.losses.insert(idx.idx, loss).is_none() {
panic!("Tried to set loss at a removed index")
}
}
pub fn get_loss(&self, idx: Idx) -> &ArrayD<f32> {
&self.losses[&idx.idx]
}
pub fn replace_input_iterator(
&mut self,
idx: Idx,
new: Box<Iterator<Item = ArrayD<f32>>>,
) -> Result<(), String> {
if let Some(n) = self.nodes.get_mut(&idx.idx) {
match n {
Node::Input { it } => *it = Some(new),
Node::Constant => *n = Node::Input { it: Some(new) },
_ => {
return Err("Tried to replace input iter at non Input/Constant node.".to_string())
}
}
Ok(())
} else {
Err("Tried to replace input iterator at invalid index.".to_string())
}
}
pub fn add(&mut self, inputs: &[Idx]) -> Idx {
self.register(Node::Add {
xs: inputs.to_vec(),
})
}
pub fn mult(&mut self, inputs: &[Idx]) -> Idx {
self.register(Node::Mult {
xs: inputs.to_vec(),
})
}
pub fn conv(&mut self, kernel: Idx, img: Idx, padding: Padding, stride: usize) -> Idx {
self.register(Node::Conv {
kernel,
img,
conv: Conv::new(padding, stride),
})
}
pub fn global_pool(&mut self, x: Idx, pool: GlobalPool) -> Idx {
self.register(Node::GlobalPool { x, pool })
}
pub fn relu(&mut self, x: Idx) -> Idx {
self.register(Node::Activation {
x,
a: Activation::Relu { leak: 0.0 },
})
}
pub fn sigmoid(&mut self, x: Idx) -> Idx {
self.register(Node::Activation {
x,
a: Activation::Sigmoid,
})
}
pub fn tanh(&mut self, x: Idx) -> Idx {
self.register(Node::Activation {
x,
a: Activation::Tanh,
})
}
pub fn matmul(&mut self, mat: Idx, v: Idx) -> Idx {
self.register(Node::MatMul { mat, v })
}
pub fn embedding(&mut self, emb: Idx, code: Idx) -> Idx {
self.register(Node::Embedding { emb, code })
}
}
fn view_at_idxs<'a>(
indices: &[Idx],
nodes: &'a BTreeMap<usize, ArrayD<f32>>,
) -> Box<[ArrayViewD<'a, f32>]> {
let mut vals = Vec::new();
for i in indices.iter() {
vals.push(nodes[&i.idx].view());
}
vals.into_boxed_slice()
}