| /external/tensorflow/tensorflow/compiler/tests/ |
| ftrl_test.py | 39 grads1 = constant_op.constant([0.02, 0.04], 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 | 68 grads1 = 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})
107 grads1 = 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})
146 grads1 = 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 | 39 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
42 zip([grads0, grads1], [var0, var1]))
64 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
68 zip([grads0, grads1], [var0, var1]))
90 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
95 zip([grads0, grads1], [var0, var1]))
97 zip([grads0, grads1], [var0, var1]))
|
| rmsprop_test.py | 39 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
42 zip([grads0, grads1], [var0, var1]))
|
| momentum_test.py | 48 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
52 zip([grads0, grads1], [var0, var1]))
127 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
132 zip([grads0, grads1], [var0, var1]))
|
| /external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
| variational_sgd_optimizer_test.py | 37 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
46 zip([grads0, grads1], [var0, var1]))
64 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
79 zip([grads0, grads1], [var0, var1]))
121 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
132 zip([grads0, grads1], [var0, var1]))
151 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
163 sgd_op = optimizer.apply_gradients(zip([grads0, grads1], [var0, var1]))
206 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
217 zip([grads0, grads1], [var0, var1]), global_step=global_step
[all...] |
| sgld_optimizer_test.py | 37 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
41 zip([grads0, grads1], [var0, var1]))
65 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
73 zip([grads0, grads1], [var0, var1]))
115 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
121 zip([grads0, grads1], [var0, var1]))
156 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
160 zip([grads0, grads1], [var0, var1]), global_step=global_step)
187 grads1 = ops.IndexedSlices(
193 zip([grads0, grads1], [var0, var1])
[all...] |
| /external/tensorflow/tensorflow/python/training/ |
| proximal_adagrad_test.py | 42 grads1 = constant_op.constant([0.01, 0.02])
48 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
78 grads1 = constant_op.constant([0.01, 0.02])
85 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
121 grads1 = constant_op.constant([0.01, 0.02])
128 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
147 grads1 = constant_op.constant([0.01, 0.02])
154 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
178 grads1 = ops.IndexedSlices(
187 grads1 = constant_op.constant([0.01, 0.02]
[all...] |
| adagrad_da_test.py | 46 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
54 zip([grads0, grads1], [var0, var1]), global_step=global_step)
109 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
118 zip([grads0, grads1], [var0, var1]), global_step=global_step)
141 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
150 zip([grads0, grads1], [var0, var1]), global_step=global_step)
173 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
182 zip([grads0, grads1], [var0, var1]), global_step=global_step)
|
| gradient_descent_test.py | 41 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
44 zip([grads0, grads1], [var0, var1]))
64 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
66 zip([grads0, grads1], [var0, var1]))
142 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
145 lrate).apply_gradients(zip([grads0, grads1], [var0, var1]))
176 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
178 zip([grads0, grads1], [var0, var1]), global_step=global_step)
202 grads1 = ops.IndexedSlices(
208 zip([grads0, grads1], [var0, var1])
[all...] |
| ftrl_test.py | 48 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
54 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
83 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
90 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
129 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
136 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
158 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
165 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
194 grads1 = constant_op.constant([0.01, 0.02], dtype=dtype)
202 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1])
[all...] |
| proximal_gradient_descent_test.py | 47 grads1 = constant_op.constant([0.01, 0.02])
50 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
76 grads1 = constant_op.constant([0.01, 0.02])
80 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
118 grads1 = constant_op.constant([0.01, 0.02])
122 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
146 grads1 = ops.IndexedSlices(
155 grads1 = constant_op.constant([0.01, 0.02])
157 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
|
| adagrad_test.py | 47 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
51 zip([grads0, grads1], [var0, var1]))
99 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
103 zip([grads0, grads1], [var0, var1]))
127 grads1 = ops.IndexedSlices(
134 zip([grads0, grads1], [var0, var1]))
244 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
249 zip([grads0, grads1], [var0, var1]))
251 zip([grads0, grads1], [var0, var1]))
|
| adam_test.py | 78 grads1 = ops.IndexedSlices(
82 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
172 grads1 = constant_op.constant(grads1_np)
175 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
200 opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
238 grads1 = constant_op.constant(grads1_np)
240 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
275 grads1 = constant_op.constant(grads1_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 | 58 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
67 zip([grads0, grads1], [var0, var1]))
105 mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
276 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
281 zip([grads0, grads1], [var0, var1]))
447 grads1 = ops.IndexedSlices(
455 zip([grads0, grads1], [var0, var1]))
512 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
516 zip([grads0, grads1], [var0, var1]))
518 zip([grads0, grads1], [var0, var1])
[all...] |
| rmsprop_test.py | 108 grads1 = constant_op.constant(grads1_np)
116 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
227 grads1 = ops.IndexedSlices(
236 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
291 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
294 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
357 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
361 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
|
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| addsign_test.py | 88 grads1 = constant_op.constant(grads1_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]),
195 grads1 = 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 | 89 grads1 = constant_op.constant(grads1_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]),
200 grads1 = 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 | 41 grads1 = constant_op.constant([0.01, 0.01], dtype=dtypes.float32)
46 mom_update = mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
48 zip([grads_allzero, grads1], [var0, var1]))
101 grads1 = constant_op.constant([0.0, 5.0], dtype=dtypes.float32)
105 gradients = [grads0, grads1, grads2, grads3]
|
| nadam_optimizer_test.py | 75 grads1 = ops.IndexedSlices(
79 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
124 grads1 = constant_op.constant(grads1_np)
126 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
|
| lazy_adam_optimizer_test.py | 71 grads1 = ops.IndexedSlices(
75 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
|
| variable_clipping_optimizer_test.py | 73 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
79 list(zip([grads0, grads1], [var0, var1])))
|
| moving_average_optimizer_test.py | 61 grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
71 list(six.moves.zip([grads0, grads1], [var0, var1])))
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| rev_block_lib.py | 104 grads1 = gradients_impl.gradients(gy1, g_vars + g_side_input, grad_y2)
105 grad_g_vars, grad_g_side = grads1[:len(g_vars)], grads1[len(g_vars):]
|
