| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| D | moving_stats.py | 84 base_dtype = mean_var.dtype.base_dtype
85 if not base_dtype.is_floating:
88 "`dtype`.".format(base_dtype.name))
89 if base_dtype != variance_var.dtype.base_dtype:
92 base_dtype.name,
93 variance_var.dtype.base_dtype.name))
94 value = ops.convert_to_tensor(value, dtype=base_dtype, name="value")
95 decay = ops.convert_to_tensor(decay, dtype=base_dtype, name="decay")
159 base_dtype = log_mean_exp_var.dtype.base_dtype
160 if not base_dtype.is_floating:
[all …]
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| /external/tensorflow/tensorflow/contrib/optimizer_v2/ |
| D | rmsprop.py | 111 v.dtype.base_dtype) * array_ops.ones_like(v)
113 v.dtype.base_dtype, "rms")
128 state.get_hyper("learning_rate", var.dtype.base_dtype),
129 state.get_hyper("decay", var.dtype.base_dtype),
130 state.get_hyper("momentum", var.dtype.base_dtype),
141 state.get_hyper("learning_rate", var.dtype.base_dtype),
142 state.get_hyper("decay", var.dtype.base_dtype),
143 state.get_hyper("momentum", var.dtype.base_dtype),
158 state.get_hyper("learning_rate", var.dtype.base_dtype),
159 state.get_hyper("decay", var.dtype.base_dtype),
[all …]
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| D | adam.py | 123 math_ops.cast(beta1_power, var.dtype.base_dtype),
124 math_ops.cast(beta2_power, var.dtype.base_dtype),
125 state.get_hyper("learning_rate", var.dtype.base_dtype),
126 state.get_hyper("beta1", var.dtype.base_dtype),
127 state.get_hyper("beta2", var.dtype.base_dtype),
128 state.get_hyper("epsilon", var.dtype.base_dtype),
140 math_ops.cast(beta1_power, grad.dtype.base_dtype),
141 math_ops.cast(beta2_power, grad.dtype.base_dtype),
142 state.get_hyper("learning_rate", grad.dtype.base_dtype),
143 state.get_hyper("beta1", grad.dtype.base_dtype),
[all …]
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| D | adadelta.py | 68 state.get_hyper("learning_rate", var.dtype.base_dtype),
69 state.get_hyper("rho", var.dtype.base_dtype),
70 state.get_hyper("epsilon", var.dtype.base_dtype),
81 state.get_hyper("learning_rate", var.dtype.base_dtype),
82 state.get_hyper("rho", var.dtype.base_dtype),
83 state.get_hyper("epsilon", var.dtype.base_dtype),
94 state.get_hyper("learning_rate", var.dtype.base_dtype),
95 state.get_hyper("rho", var.dtype.base_dtype),
96 state.get_hyper("epsilon", var.dtype.base_dtype),
108 state.get_hyper("learning_rate", var.dtype.base_dtype),
[all …]
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| D | momentum.py | 85 state.get_hyper("learning_rate", var.dtype.base_dtype),
87 state.get_hyper("momentum", var.dtype.base_dtype),
96 state.get_hyper("learning_rate", var.dtype.base_dtype),
98 state.get_hyper("momentum", var.dtype.base_dtype),
107 state.get_hyper("learning_rate", var.dtype.base_dtype),
110 state.get_hyper("momentum", var.dtype.base_dtype),
119 state.get_hyper("learning_rate", var.dtype.base_dtype),
122 state.get_hyper("momentum", var.dtype.base_dtype),
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| D | adagrad.py | 67 dtype = v.dtype.base_dtype
88 state.get_hyper("learning_rate", var.dtype.base_dtype),
97 state.get_hyper("learning_rate", var.dtype.base_dtype),
106 state.get_hyper("learning_rate", var.dtype.base_dtype),
116 state.get_hyper("learning_rate", var.dtype.base_dtype),
|
| D | gradient_descent.py | 50 state.get_hyper("learning_rate", var.dtype.base_dtype),
55 lr = state.get_hyper("learning_rate", grad.dtype.base_dtype)
61 lr = state.get_hyper("learning_rate", grad.dtype.base_dtype)
67 grad.values * state.get_hyper("learning_rate", var.dtype.base_dtype),
|
| /external/tensorflow/tensorflow/python/training/ |
| D | ftrl.py | 156 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
158 var.dtype.base_dtype),
160 var.dtype.base_dtype),
161 math_ops.cast(self._learning_rate_power_tensor, var.dtype.base_dtype),
169 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
171 var.dtype.base_dtype),
173 var.dtype.base_dtype),
175 var.dtype.base_dtype),
176 math_ops.cast(self._learning_rate_power_tensor, var.dtype.base_dtype),
188 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
[all …]
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| D | rmsprop.py | 119 init_rms = init_ops.ones_initializer(dtype=v.dtype.base_dtype)
123 v.dtype.base_dtype, "rms",
150 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
151 math_ops.cast(self._decay_tensor, var.dtype.base_dtype),
152 math_ops.cast(self._momentum_tensor, var.dtype.base_dtype),
153 math_ops.cast(self._epsilon_tensor, var.dtype.base_dtype),
161 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
162 math_ops.cast(self._decay_tensor, var.dtype.base_dtype),
163 math_ops.cast(self._momentum_tensor, var.dtype.base_dtype),
164 math_ops.cast(self._epsilon_tensor, var.dtype.base_dtype),
[all …]
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| D | adam.py | 153 math_ops.cast(beta1_power, var.dtype.base_dtype),
154 math_ops.cast(beta2_power, var.dtype.base_dtype),
155 math_ops.cast(self._lr_t, var.dtype.base_dtype),
156 math_ops.cast(self._beta1_t, var.dtype.base_dtype),
157 math_ops.cast(self._beta2_t, var.dtype.base_dtype),
158 math_ops.cast(self._epsilon_t, var.dtype.base_dtype),
170 math_ops.cast(beta1_power, grad.dtype.base_dtype),
171 math_ops.cast(beta2_power, grad.dtype.base_dtype),
172 math_ops.cast(self._lr_t, grad.dtype.base_dtype),
173 math_ops.cast(self._beta1_t, grad.dtype.base_dtype),
[all …]
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| D | adagrad_da.py | 91 0.0, shape=v.get_shape(), dtype=v.dtype.base_dtype)
95 dtype=v.dtype.base_dtype)
118 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
119 math_ops.cast(self._l1_regularization_strength, var.dtype.base_dtype),
120 math_ops.cast(self._l2_regularization_strength, var.dtype.base_dtype),
134 math_ops.cast(self._learning_rate_tensor, grad.dtype.base_dtype),
135 math_ops.cast(self._l1_regularization_strength, grad.dtype.base_dtype),
136 math_ops.cast(self._l2_regularization_strength, grad.dtype.base_dtype),
151 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
152 math_ops.cast(self._l1_regularization_strength, var.dtype.base_dtype),
[all …]
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| D | adadelta.py | 88 math_ops.cast(self._lr_t, var.dtype.base_dtype),
89 math_ops.cast(self._rho_t, var.dtype.base_dtype),
90 math_ops.cast(self._epsilon_t, var.dtype.base_dtype),
101 math_ops.cast(self._lr_t, grad.dtype.base_dtype),
102 math_ops.cast(self._rho_t, grad.dtype.base_dtype),
103 math_ops.cast(self._epsilon_t, grad.dtype.base_dtype),
114 math_ops.cast(self._lr_t, var.dtype.base_dtype),
115 math_ops.cast(self._rho_t, var.dtype.base_dtype),
116 math_ops.cast(self._epsilon_t, var.dtype.base_dtype),
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| D | momentum.py | 99 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
101 math_ops.cast(self._momentum_tensor, var.dtype.base_dtype),
109 math_ops.cast(self._learning_rate_tensor, grad.dtype.base_dtype),
111 math_ops.cast(self._momentum_tensor, grad.dtype.base_dtype),
119 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
121 math_ops.cast(self._momentum_tensor, var.dtype.base_dtype),
|
| D | slot_creator_test.py | 45 self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
58 self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
73 self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
95 self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
109 self.assertEqual(dtypes.float32, slot.dtype.base_dtype)
125 self.assertEqual(dtypes.float64, slot.dtype.base_dtype)
|
| D | adagrad.py | 73 dtype = v.dtype.base_dtype
101 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
110 math_ops.cast(self._learning_rate_tensor, grad.dtype.base_dtype),
119 math_ops.cast(self._learning_rate_tensor, var.dtype.base_dtype),
|
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| D | nadam_optimizer.py | 43 math_ops.cast(beta1_power, var.dtype.base_dtype),
44 math_ops.cast(beta2_power, var.dtype.base_dtype),
45 math_ops.cast(self._lr_t, var.dtype.base_dtype),
46 math_ops.cast(self._beta1_t, var.dtype.base_dtype),
47 math_ops.cast(self._beta2_t, var.dtype.base_dtype),
48 math_ops.cast(self._epsilon_t, var.dtype.base_dtype),
61 math_ops.cast(beta1_power, grad.dtype.base_dtype),
62 math_ops.cast(beta2_power, grad.dtype.base_dtype),
63 math_ops.cast(self._lr_t, grad.dtype.base_dtype),
64 math_ops.cast(self._beta1_t, grad.dtype.base_dtype),
[all …]
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| D | adam_gs_optimizer.py | 153 math_ops.cast(beta1_power, var.dtype.base_dtype),
154 math_ops.cast(beta2_power, var.dtype.base_dtype),
155 math_ops.cast(self._lr_t, var.dtype.base_dtype),
156 math_ops.cast(self._beta1_t, var.dtype.base_dtype),
157 math_ops.cast(self._beta2_t, var.dtype.base_dtype),
158 math_ops.cast(self._epsilon_t, var.dtype.base_dtype),
170 math_ops.cast(beta1_power, grad.dtype.base_dtype),
171 math_ops.cast(beta2_power, grad.dtype.base_dtype),
172 math_ops.cast(self._lr_t, grad.dtype.base_dtype),
173 math_ops.cast(self._beta1_t, grad.dtype.base_dtype),
[all …]
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| D | adamax.py | 117 math_ops.cast(beta1_power, var.dtype.base_dtype),
118 math_ops.cast(self._lr_t, var.dtype.base_dtype),
119 math_ops.cast(self._beta1_t, var.dtype.base_dtype),
120 math_ops.cast(self._beta2_t, var.dtype.base_dtype),
121 math_ops.cast(self._epsilon_t, var.dtype.base_dtype),
130 math_ops.cast(beta1_power, grad.dtype.base_dtype),
131 math_ops.cast(self._lr_t, grad.dtype.base_dtype),
132 math_ops.cast(self._beta1_t, grad.dtype.base_dtype),
133 math_ops.cast(self._beta2_t, grad.dtype.base_dtype),
134 math_ops.cast(self._epsilon_t, grad.dtype.base_dtype),
[all …]
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| D | lazy_adam_optimizer.py | 52 beta1_power = math_ops.cast(beta1_power, var.dtype.base_dtype)
53 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
54 lr_t = math_ops.cast(self._lr_t, var.dtype.base_dtype)
55 beta1_t = math_ops.cast(self._beta1_t, var.dtype.base_dtype)
56 beta2_t = math_ops.cast(self._beta2_t, var.dtype.base_dtype)
57 epsilon_t = math_ops.cast(self._epsilon_t, var.dtype.base_dtype)
85 beta1_power = math_ops.cast(beta1_power, var.dtype.base_dtype)
86 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
87 lr_t = math_ops.cast(self._lr_t, var.dtype.base_dtype)
88 beta1_t = math_ops.cast(self._beta1_t, var.dtype.base_dtype)
[all …]
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| D | lazy_adam_gs_optimizer.py | 52 beta1_power = math_ops.cast(beta1_power, var.dtype.base_dtype)
53 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
54 lr_t = math_ops.cast(self._lr_t, var.dtype.base_dtype)
55 beta1_t = math_ops.cast(self._beta1_t, var.dtype.base_dtype)
56 beta2_t = math_ops.cast(self._beta2_t, var.dtype.base_dtype)
57 epsilon_t = math_ops.cast(self._epsilon_t, var.dtype.base_dtype)
85 beta1_power = math_ops.cast(beta1_power, var.dtype.base_dtype)
86 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
87 lr_t = math_ops.cast(self._lr_t, var.dtype.base_dtype)
88 beta1_t = math_ops.cast(self._beta1_t, var.dtype.base_dtype)
[all …]
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| D | powersign.py | 118 math_ops.cast(self._lr_t, var.dtype.base_dtype),
119 math_ops.cast(self._logbase_t, var.dtype.base_dtype),
120 math_ops.cast(self._sign_decay_t, var.dtype.base_dtype),
121 math_ops.cast(self._beta_t, var.dtype.base_dtype),
130 math_ops.cast(self._lr_t, var.dtype.base_dtype),
131 math_ops.cast(self._logbase_t, var.dtype.base_dtype),
132 math_ops.cast(self._sign_decay_t, var.dtype.base_dtype),
133 math_ops.cast(self._beta_t, var.dtype.base_dtype),
138 lr_t = math_ops.cast(self._lr_t, var.dtype.base_dtype)
139 beta_t = math_ops.cast(self._beta_t, var.dtype.base_dtype)
[all …]
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| D | addsign.py | 116 math_ops.cast(self._lr_t, var.dtype.base_dtype),
117 math_ops.cast(self._alpha_t, var.dtype.base_dtype),
118 math_ops.cast(self._sign_decay_t, var.dtype.base_dtype),
119 math_ops.cast(self._beta_t, var.dtype.base_dtype),
128 math_ops.cast(self._lr_t, var.dtype.base_dtype),
129 math_ops.cast(self._alpha_t, var.dtype.base_dtype),
130 math_ops.cast(self._sign_decay_t, var.dtype.base_dtype),
131 math_ops.cast(self._beta_t, var.dtype.base_dtype),
136 lr_t = math_ops.cast(self._lr_t, var.dtype.base_dtype)
137 alpha_t = math_ops.cast(self._alpha_t, var.dtype.base_dtype)
[all …]
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| D | affine_linear_operator.py | 131 dtype = shift.dtype.base_dtype
136 shift.dtype.base_dtype != scale.dtype.base_dtype):
151 dtype = scale.dtype.base_dtype
209 return constant_op.constant(0., dtype=x.dtype.base_dtype)
|
| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| D | learning_rate_schedule.py | 249 if b.dtype.base_dtype != x_recomp.dtype.base_dtype:
253 if (b.dtype.base_dtype == dtypes.int32 and
254 x_recomp.dtype.base_dtype == dtypes.int64):
255 b = math_ops.cast(b, x_recomp.dtype.base_dtype)
260 (b.dtype.base_dtype, x_recomp.dtype.base_dtype))
263 if v.dtype.base_dtype != values[0].dtype.base_dtype:
266 (values[0].dtype.base_dtype, v.dtype.base_dtype))
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| /external/tensorflow/tensorflow/python/tpu/ |
| D | bfloat16_test.py | 43 self.assertEqual(v1.dtype.base_dtype, dtypes.float32)
45 self.assertEqual(v2.dtype.base_dtype, dtypes.bfloat16)
47 [v.dtype.base_dtype for v in scope.global_variables()])
|