| /external/tensorflow/tensorflow/compiler/tests/ |
| ftrl_test.py | 38 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
41 return var0, var1, grads0, grads1
44 var0, var1, grads0, grads1 = self.initVariableAndGradient(dtype)
51 ftrl_update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
64 var0, var1, grads0, grads1 = self.initVariableAndGradient(dtype)
66 adagrad_update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
79 var0, var1, grads0, grads1 = self.initVariableAndGradient(dtype)
86 ftrl_update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
99 var0, var1, grads0, grads1 = self.initVariableAndGradient(dtype)
101 sgd_update = opt.apply_gradients(zip([grads0, grads1], [var0, var1])
[all...] |
| adam_test.py | 67 grads0 = array_ops.placeholder(dtype)
70 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
83 update.run(feed_dict={grads0: grads0_np, grads1: grads1_np})
106 grads0 = array_ops.placeholder(dtype)
109 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
122 update.run(feed_dict={grads0: grads0_np, grads1: grads1_np})
145 grads0 = array_ops.placeholder(dtype)
148 update1 = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
149 update2 = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
163 update1.run(feed_dict={grads0: grads0_np, grads1: grads1_np}
[all...] |
| adagrad_test.py | 38 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
42 zip([grads0, grads1], [var0, var1]))
63 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
68 zip([grads0, grads1], [var0, var1]))
89 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
95 zip([grads0, grads1], [var0, var1]))
97 zip([grads0, grads1], [var0, var1]))
|
| rmsprop_test.py | 38 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
42 zip([grads0, grads1], [var0, var1]))
|
| momentum_test.py | 47 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
52 zip([grads0, grads1], [var0, var1]))
126 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
132 zip([grads0, grads1], [var0, var1]))
|
| /external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
| variational_sgd_optimizer_test.py | 36 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
46 zip([grads0, grads1], [var0, var1]))
63 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
79 zip([grads0, grads1], [var0, var1]))
120 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
132 zip([grads0, grads1], [var0, var1]))
150 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
163 sgd_op = optimizer.apply_gradients(zip([grads0, grads1], [var0, var1]))
205 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
217 zip([grads0, grads1], [var0, var1]), global_step=global_step
[all...] |
| sgld_optimizer_test.py | 36 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
41 zip([grads0, grads1], [var0, var1]))
64 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
73 zip([grads0, grads1], [var0, var1]))
114 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
121 zip([grads0, grads1], [var0, var1]))
155 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
160 zip([grads0, grads1], [var0, var1]), global_step=global_step)
184 grads0 = ops.IndexedSlices(
193 zip([grads0, grads1], [var0, var1])
[all...] |
| /external/tensorflow/tensorflow/python/training/ |
| proximal_adagrad_test.py | 41 grads0 = constant_op.constant([0.1, 0.2])
48 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
77 grads0 = constant_op.constant([0.1, 0.2])
85 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
120 grads0 = constant_op.constant([0.1, 0.2])
128 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
146 grads0 = constant_op.constant([0.1, 0.2])
154 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
173 grads0 = ops.IndexedSlices(
186 grads0 = constant_op.constant([0.1, 0.2]
[all...] |
| adagrad_da_test.py | 45 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
54 zip([grads0, grads1], [var0, var1]), global_step=global_step)
108 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
118 zip([grads0, grads1], [var0, var1]), global_step=global_step)
140 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
150 zip([grads0, grads1], [var0, var1]), global_step=global_step)
172 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
182 zip([grads0, grads1], [var0, var1]), global_step=global_step)
|
| gradient_descent_test.py | 40 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
44 zip([grads0, grads1], [var0, var1]))
63 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
66 zip([grads0, grads1], [var0, var1]))
141 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
145 lrate).apply_gradients(zip([grads0, grads1], [var0, var1]))
175 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
178 zip([grads0, grads1], [var0, var1]), global_step=global_step)
197 grads0 = ops.IndexedSlices(
208 zip([grads0, grads1], [var0, var1])
[all...] |
| ftrl_test.py | 47 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
54 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
82 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
90 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
128 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
136 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
157 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
165 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
193 grads0 = constant_op.constant([0.1, 0.2], dtype=dtype)
202 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1])
[all...] |
| proximal_gradient_descent_test.py | 46 grads0 = constant_op.constant([0.1, 0.2])
50 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
75 grads0 = constant_op.constant([0.1, 0.2])
80 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
117 grads0 = constant_op.constant([0.1, 0.2])
122 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
141 grads0 = ops.IndexedSlices(
154 grads0 = constant_op.constant([0.1, 0.2])
157 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
|
| adagrad_test.py | 46 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
51 zip([grads0, grads1], [var0, var1]))
98 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
103 zip([grads0, grads1], [var0, var1]))
122 grads0 = ops.IndexedSlices(
134 zip([grads0, grads1], [var0, var1]))
212 grads0 = ops.IndexedSlices(
223 ada_update = ada_opt.apply_gradients(zip([grads0], [var0]))
243 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
249 zip([grads0, grads1], [var0, var1])
[all...] |
| adam_test.py | 74 grads0 = ops.IndexedSlices(
82 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
171 grads0 = constant_op.constant(grads0_np)
175 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
200 opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
237 grads0 = constant_op.constant(grads0_np)
240 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
274 grads0 = constant_op.constant(grads0_np)
277 update1 = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
278 update2 = opt.apply_gradients(zip([grads0, grads1], [var0, var1])
[all...] |
| momentum_test.py | 57 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
67 zip([grads0, grads1], [var0, var1]))
105 mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
275 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
281 zip([grads0, grads1], [var0, var1]))
429 grads0 = constant_op.constant([0.0] * num_samples)
431 mom_update = mom_opt.apply_gradients(zip([grads0], [var0]))
434 mom_update.run(feed_dict={grads0: db_grad[i]})
442 grads0 = ops.IndexedSlices(
455 zip([grads0, grads1], [var0, var1])
[all...] |
| rmsprop_test.py | 107 grads0 = constant_op.constant(grads0_np)
116 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
223 grads0 = ops.IndexedSlices(
236 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
290 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
294 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
356 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
361 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
|
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| addsign_test.py | 87 grads0 = constant_op.constant(grads0_np)
96 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]),
98 neg_update = opt.apply_gradients(zip([-grads0, -grads1], [var0, var1]),
114 opt.apply_gradients(zip([grads0, grads1], [var0, var1]),
120 opt.apply_gradients(zip([-grads0, -grads1], [var0, var1]),
191 grads0 = ops.IndexedSlices(
204 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]),
206 neg_update = opt.apply_gradients(zip([-grads0, -grads1], [var0, var1]),
|
| powersign_test.py | 88 grads0 = constant_op.constant(grads0_np)
97 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]),
99 neg_update = opt.apply_gradients(zip([-grads0, -grads1], [var0, var1]),
116 opt.apply_gradients(zip([grads0, grads1], [var0, var1]),
122 opt.apply_gradients(zip([-grads0, -grads1], [var0, var1]),
196 grads0 = ops.IndexedSlices(
209 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]),
211 neg_update = opt.apply_gradients(zip([-grads0, -grads1], [var0, var1]),
|
| multitask_optimizer_wrapper_test.py | 40 grads0 = constant_op.constant([0.1, 0.1], dtype=dtypes.float32)
46 mom_update = mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
100 grads0 = constant_op.constant([10.0, 15.0], dtype=dtypes.float32)
105 gradients = [grads0, grads1, grads2, grads3]
|
| nadam_optimizer_test.py | 71 grads0 = ops.IndexedSlices(
79 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
123 grads0 = constant_op.constant(grads0_np)
126 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
|
| lazy_adam_optimizer_test.py | 67 grads0 = ops.IndexedSlices(
75 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
|
| variable_clipping_optimizer_test.py | 72 grads0 = constant_op.constant([[0.1, 0.1], [0.1, 0.1]], dtype=dtype)
79 list(zip([grads0, grads1], [var0, var1])))
|
| moving_average_optimizer_test.py | 60 grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
71 list(six.moves.zip([grads0, grads1], [var0, var1])))
|
