Update model.py
Browse files
model.py
CHANGED
@@ -89,6 +89,7 @@ class PatchEmbedding(nnx.Module):
|
|
89 |
padding=config.padding,
|
90 |
use_bias=config.use_bias,
|
91 |
rngs=rngs,
|
|
|
92 |
)
|
93 |
|
94 |
def __call__(self, x):
|
@@ -103,10 +104,10 @@ class TimeEmbedding(nnx.Module):
|
|
103 |
self.freq_dim = config.time_freq_dim
|
104 |
self.max_period = config.time_max_period
|
105 |
self.fc1 = nnx.Linear(
|
106 |
-
self.freq_dim, config.hidden_dim, use_bias=config.use_bias, rngs=rngs
|
107 |
)
|
108 |
self.fc2 = nnx.Linear(
|
109 |
-
config.hidden_dim, config.hidden_dim, use_bias=config.use_bias, rngs=rngs
|
110 |
)
|
111 |
|
112 |
@staticmethod
|
@@ -140,12 +141,14 @@ class MLP(nnx.Module):
|
|
140 |
config.hidden_dim * config.mlp_ratio,
|
141 |
use_bias=config.use_bias,
|
142 |
rngs=rngs,
|
|
|
143 |
)
|
144 |
self.fc2 = nnx.Linear(
|
145 |
config.hidden_dim * config.mlp_ratio,
|
146 |
config.hidden_dim,
|
147 |
use_bias=config.use_bias,
|
148 |
rngs=rngs,
|
|
|
149 |
)
|
150 |
|
151 |
def __call__(self, x):
|
@@ -165,6 +168,7 @@ class SelfAttention(nnx.Module):
|
|
165 |
3 * config.hidden_dim,
|
166 |
use_bias=config.use_bias,
|
167 |
rngs=rngs,
|
|
|
168 |
)
|
169 |
self.heads = config.num_heads
|
170 |
self.head_dim = config.hidden_dim // config.num_heads
|
@@ -209,6 +213,7 @@ class TransformerBlock(nnx.Module):
|
|
209 |
6 * config.hidden_dim,
|
210 |
use_bias=config.use_bias,
|
211 |
rngs=rngs,
|
|
|
212 |
),
|
213 |
)
|
214 |
|
@@ -241,6 +246,7 @@ class FinalLayer(nnx.Module):
|
|
241 |
padding=config.padding,
|
242 |
use_bias=config.use_bias,
|
243 |
rngs=rngs,
|
|
|
244 |
)
|
245 |
self.adalm_modulation = nnx.Sequential(
|
246 |
nnx.silu,
|
@@ -249,6 +255,7 @@ class FinalLayer(nnx.Module):
|
|
249 |
2 * config.hidden_dim,
|
250 |
use_bias=config.use_bias,
|
251 |
rngs=rngs,
|
|
|
252 |
),
|
253 |
)
|
254 |
|
|
|
89 |
padding=config.padding,
|
90 |
use_bias=config.use_bias,
|
91 |
rngs=rngs,
|
92 |
+
dtype=jnp.bfloat16,
|
93 |
)
|
94 |
|
95 |
def __call__(self, x):
|
|
|
104 |
self.freq_dim = config.time_freq_dim
|
105 |
self.max_period = config.time_max_period
|
106 |
self.fc1 = nnx.Linear(
|
107 |
+
self.freq_dim, config.hidden_dim, use_bias=config.use_bias, rngs=rngs, dtype=jnp.bfloat16
|
108 |
)
|
109 |
self.fc2 = nnx.Linear(
|
110 |
+
config.hidden_dim, config.hidden_dim, use_bias=config.use_bias, rngs=rngs, dtype=jnp.bfloat16
|
111 |
)
|
112 |
|
113 |
@staticmethod
|
|
|
141 |
config.hidden_dim * config.mlp_ratio,
|
142 |
use_bias=config.use_bias,
|
143 |
rngs=rngs,
|
144 |
+
dtype=jnp.bfloat16,
|
145 |
)
|
146 |
self.fc2 = nnx.Linear(
|
147 |
config.hidden_dim * config.mlp_ratio,
|
148 |
config.hidden_dim,
|
149 |
use_bias=config.use_bias,
|
150 |
rngs=rngs,
|
151 |
+
dtype=jnp.bfloat16,
|
152 |
)
|
153 |
|
154 |
def __call__(self, x):
|
|
|
168 |
3 * config.hidden_dim,
|
169 |
use_bias=config.use_bias,
|
170 |
rngs=rngs,
|
171 |
+
dtype=jnp.bfloat16,
|
172 |
)
|
173 |
self.heads = config.num_heads
|
174 |
self.head_dim = config.hidden_dim // config.num_heads
|
|
|
213 |
6 * config.hidden_dim,
|
214 |
use_bias=config.use_bias,
|
215 |
rngs=rngs,
|
216 |
+
dtype=jnp.bfloat16,
|
217 |
),
|
218 |
)
|
219 |
|
|
|
246 |
padding=config.padding,
|
247 |
use_bias=config.use_bias,
|
248 |
rngs=rngs,
|
249 |
+
dtype=jnp.bfloat16,
|
250 |
)
|
251 |
self.adalm_modulation = nnx.Sequential(
|
252 |
nnx.silu,
|
|
|
255 |
2 * config.hidden_dim,
|
256 |
use_bias=config.use_bias,
|
257 |
rngs=rngs,
|
258 |
+
dtype=jnp.bfloat16,
|
259 |
),
|
260 |
)
|
261 |
|