| /external/tensorflow/tensorflow/contrib/optimizer_v2/ |
| momentum.py | 81 mom = state.get_slot(var, "momentum")
84 mom,
92 mom = state.get_slot(var, "momentum")
95 mom.handle,
103 mom = state.get_slot(var, "momentum")
106 mom,
115 mom = state.get_slot(var, "momentum")
118 mom.handle,
|
| rmsprop.py | 25 mom = momentum * mom{t-1} + learning_rate * g_t / sqrt(mean_square)
26 delta = - mom
35 mom = momentum * mom{t-1} + learning_rate * g_t /
37 delta = - mom
120 mom = state.get_slot(var, "momentum")
127 mom,
140 mom,
150 mom = state.get_slot(var, "momentum"
[all...] |
| rmsprop_test.py | 57 def _rmsprop_update_numpy(self, var, g, mg, rms, mom, lr, decay, momentum,
66 mom_t = momentum * mom + lr * g / np.sqrt(denom_t, dtype=denom_t.dtype)
70 def _sparse_rmsprop_update_numpy(self, var, gindexs, gvalues, mg, rms, mom,
74 mom_t = copy.deepcopy(mom)
84 mom_t[gindex] = momentum * mom[gindex] + lr * gvalue / np.sqrt(denom_t)
381 # Step 1: rms = 1, mom = 0. So we should see a normal
|
| /external/tensorflow/tensorflow/python/training/ |
| momentum.py | 96 mom = self.get_slot(var, "momentum")
98 var, mom,
106 mom = self.get_slot(var, "momentum")
108 var.handle, mom.handle,
116 mom = self.get_slot(var, "momentum")
118 var, mom,
126 mom = self.get_slot(var, "momentum")
128 var.handle, mom.handle,
|
| rmsprop.py | 25 mom = momentum * mom{t-1} + learning_rate * g_t / sqrt(mean_square + epsilon)
26 delta = - mom
35 mom = momentum * mom{t-1} + learning_rate * g_t /
37 delta = - mom
142 mom = self.get_slot(var, "momentum")
149 mom,
160 mom,
170 mom = self.get_slot(var, "momentum"
[all...] |
| rmsprop_test.py | 61 def _rmsprop_update_numpy(self, var, g, mg, rms, mom, lr, decay, momentum,
70 mom_t = momentum * mom + lr * g / np.sqrt(denom_t, dtype=denom_t.dtype)
74 def _sparse_rmsprop_update_numpy(self, var, gindexs, gvalues, mg, rms, mom,
78 mom_t = copy.deepcopy(mom)
88 mom_t[gindex] = momentum * mom[gindex] + lr * gvalue / np.sqrt(denom_t)
388 # Step 1: rms = 1, mom = 0. So we should see a normal
|
| /external/guice/extensions/assistedinject/test/com/google/inject/assistedinject/ |
| ManyConstructorsTest.java | 275 assertEquals(null, pops.mom);
276 Farm moms = factory.momsFarm("Mom");
278 assertEquals("Mom", moms.mom);
279 Farm momAndPop = factory.momAndPopsFarm("Mom", "Pop");
281 assertEquals("Mom", momAndPop.mom);
287 Farm momsFarm(@Assisted("mom") String mom);
289 Farm momAndPopsFarm(@Assisted("mom") String mom, @Assisted("pop") String pop)
294 String mom; field in class:ManyConstructorsTest.Farm
[all...] |
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| lars_optimizer.py | 120 mom = self.get_slot(var, "momentum")
123 mom,
132 mom = self.get_slot(var, "momentum")
135 mom.handle,
144 mom = self.get_slot(var, "momentum")
147 mom,
156 mom = self.get_slot(var, "momentum")
159 mom.handle,
|
| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| rmsprop.py | 141 mom = self.get_slot(var, "momentum")
148 mom.handle,
159 mom.handle,
186 mom = self.get_slot(var, "momentum")
193 mom.handle,
205 mom.handle,
|
| rmsprop_test.py | 60 def _rmsprop_update_numpy(self, var, g, mg, rms, mom, lr, rho, momentum,
70 mom_t = momentum * mom + lr * g / (np.sqrt(denom_t + epsilon))
73 mom_t = mom
77 def _sparse_rmsprop_update_numpy(self, var, gindexs, gvalues, mg, rms, mom,
81 mom_t = copy.deepcopy(mom)
93 mom_t[gindex] = momentum * mom[gindex] + lr * gvalue / np.sqrt(denom_t +
97 mom_t[gindex] = mom[gindex]
|
| /build/make/tools/droiddoc/templates-pdk/assets/ |
| android-developer-reference.js | 117 function new_node(me, mom, text, link, children_data, api_level)
122 node.depth = mom.depth + 1;
125 mom.get_children_ul().appendChild(node.li);
215 function get_node(me, mom)
217 mom.children_visited = true;
218 for (var i in mom.children_data) {
219 var node_data = mom.children_data[i];
220 mom.children[i] = new_node(me, mom, node_data[0], node_data[1],
306 var mom = me.node
[all...] |
| /external/doclava/res/assets/templates/assets/ |
| doclava-developer-reference.js | 98 function new_node(me, mom, text, link, children_data, api_level)
103 node.depth = mom.depth + 1;
106 mom.get_children_ul().appendChild(node.li);
196 function get_node(me, mom)
198 mom.children_visited = true;
199 for (var i in mom.children_data) {
200 var node_data = mom.children_data[i];
201 mom.children[i] = new_node(me, mom, node_data[0], node_data[1],
287 var mom = me.node
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| training_ops_test.cc | 137 auto mom = Scalar(g, 0.01); local
138 test::graph::Multi(g, "ApplyMomentum", {var, accum, lr, grad, mom});
203 auto mom = Var(g, n); local
207 test::graph::Assign(g, mom, zero);
214 auto mom = Var(g, n); local
221 {var, ms, mom, lr, rho, momentum, epsilon, grad});
|
| training_ops_gpu.cu.cc | 230 typename TTypes<T>::Flat ms, typename TTypes<T>::Flat mom,
243 mom.device(d) =
244 mom * momentum.reshape(single).broadcast(bcast) +
247 var.device(d) -= mom;
255 typename TTypes<T>::Flat mom,
270 mom.device(d) = mom * momentum.reshape(single).broadcast(bcast) +
272 var.device(d) -= mom;
|
| training_ops.cc | 396 typename TTypes<T>::Flat ms, typename TTypes<T>::Flat mom,
403 mom.device(d) =
404 mom * momentum() + (grad * lr()) / ((ms + epsilon()).sqrt());
405 var.device(d) -= mom;
413 typename TTypes<T>::Flat mom,
422 mom.device(d) = mom * momentum() + (grad * lr()) / denom.sqrt();
423 var.device(d) -= mom;
3353 Tensor mom; variable
3439 Tensor mom; variable
3596 Tensor mom; variable
3729 Tensor mom; variable
[all...] |
| training_ops.h | 180 typename TTypes<T>::Flat ms, typename TTypes<T>::Flat mom,
192 typename TTypes<T>::Flat mom,
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| rmsprop_test.py | 38 mom,
51 mom_t = momentum * mom + lr * g / np.sqrt(denom_t, dtype=denom_t.dtype)
|
| /build/make/tools/droiddoc/templates-ndk/assets/js/ |
| docs.js | [all...] |
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| training_ops.cc | 569 xla::XlaOp var, ms, mom, mg; variable
577 ctx->ReadVariableInput("mom", dtype_, &mom_shape, &mom));
597 // var should be the same shape as mom and ms.
604 "var and mom do not have the same shape",
618 // mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)
619 // var <- var - mom
643 xla::XlaOp new_mom = mom * momentum + grad * lr * xla::Rsqrt(denominator);
651 OP_REQUIRES_OK(ctx, ctx->AssignVariable("mom", dtype_, new_mom));
[all...] |
| /external/doclava/res/assets/templates-sdk/assets/js/ |
| docs.js | 960 function new_google_node(me, mom, text, link, children_data, api_level) {
965 node.depth = mom.depth + 1;
976 mom.get_children_ul().appendChild(node.li);
[all...] |
| /external/tensorflow/tensorflow/go/op/ |
| wrappers.go | [all...] |
