| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| D | gradient_descent.py | 127 def _prepare_local(self, var_device, var_dtype, apply_state): argument
128 super(SGD, self)._prepare_local(var_device, var_dtype, apply_state)
129 apply_state[(var_device, var_dtype)]["momentum"] = array_ops.identity(
133 var_device, var_dtype = var.device, var.dtype.base_dtype
134 coefficients = ((apply_state or {}).get((var_device, var_dtype))
135 or self._fallback_apply_state(var_device, var_dtype))
160 var_device, var_dtype = var.device, var.dtype.base_dtype
161 coefficients = (kwargs.get("apply_state", {}).get((var_device, var_dtype))
162 or self._fallback_apply_state(var_device, var_dtype))
171 var_device, var_dtype = var.device, var.dtype.base_dtype
[all …]
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| D | adagrad.py | 86 def _prepare_local(self, var_device, var_dtype, apply_state): argument
87 super(Adagrad, self)._prepare_local(var_device, var_dtype, apply_state)
88 apply_state[(var_device, var_dtype)].update(
92 neg_lr_t=-apply_state[(var_device, var_dtype)]['lr_t'],
128 var_device, var_dtype = var.device, var.dtype.base_dtype
129 coefficients = ((apply_state or {}).get((var_device, var_dtype))
130 or self._fallback_apply_state(var_device, var_dtype))
142 var_device, var_dtype = var.device, var.dtype.base_dtype
143 coefficients = ((apply_state or {}).get((var_device, var_dtype))
144 or self._fallback_apply_state(var_device, var_dtype))
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| D | adam.py | 134 def _prepare_local(self, var_device, var_dtype, apply_state): argument
135 super(Adam, self)._prepare_local(var_device, var_dtype, apply_state)
142 lr = (apply_state[(var_device, var_dtype)]['lr_t'] *
144 apply_state[(var_device, var_dtype)].update(
167 var_device, var_dtype = var.device, var.dtype.base_dtype
168 coefficients = ((apply_state or {}).get((var_device, var_dtype))
169 or self._fallback_apply_state(var_device, var_dtype))
204 var_device, var_dtype = var.device, var.dtype.base_dtype
205 coefficients = ((apply_state or {}).get((var_device, var_dtype))
206 or self._fallback_apply_state(var_device, var_dtype))
[all …]
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| D | adadelta.py | 100 def _prepare_local(self, var_device, var_dtype, apply_state): argument
101 super(Adadelta, self)._prepare_local(var_device, var_dtype, apply_state)
102 apply_state[(var_device, var_dtype)].update(
118 var_device, var_dtype = var.device, var.dtype.base_dtype
119 coefficients = ((apply_state or {}).get((var_device, var_dtype))
120 or self._fallback_apply_state(var_device, var_dtype))
135 var_device, var_dtype = var.device, var.dtype.base_dtype
136 coefficients = ((apply_state or {}).get((var_device, var_dtype))
137 or self._fallback_apply_state(var_device, var_dtype))
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| D | adamax.py | 113 def _prepare_local(self, var_device, var_dtype, apply_state): argument
114 super(Adamax, self)._prepare_local(var_device, var_dtype, apply_state)
120 lr_t = apply_state[(var_device, var_dtype)]['lr_t']
122 apply_state[(var_device, var_dtype)].update(
134 var_device, var_dtype = var.device, var.dtype.base_dtype
135 coefficients = ((apply_state or {}).get((var_device, var_dtype))
136 or self._fallback_apply_state(var_device, var_dtype))
153 var_device, var_dtype = var.device, var.dtype.base_dtype
154 coefficients = ((apply_state or {}).get((var_device, var_dtype))
155 or self._fallback_apply_state(var_device, var_dtype))
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| D | ftrl.py | 139 def _prepare_local(self, var_device, var_dtype, apply_state): argument
140 super(Ftrl, self)._prepare_local(var_device, var_dtype, apply_state)
141 apply_state[(var_device, var_dtype)].update(
154 var_device, var_dtype = var.device, var.dtype.base_dtype
155 coefficients = ((apply_state or {}).get((var_device, var_dtype))
156 or self._fallback_apply_state(var_device, var_dtype))
192 var_device, var_dtype = var.device, var.dtype.base_dtype
193 coefficients = ((apply_state or {}).get((var_device, var_dtype))
194 or self._fallback_apply_state(var_device, var_dtype))
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| D | rmsprop.py | 163 def _prepare_local(self, var_device, var_dtype, apply_state): argument
164 super(RMSprop, self)._prepare_local(var_device, var_dtype, apply_state)
167 apply_state[(var_device, var_dtype)].update(
169 neg_lr_t=-apply_state[(var_device, var_dtype)]["lr_t"],
177 var_device, var_dtype = var.device, var.dtype.base_dtype
178 coefficients = ((apply_state or {}).get((var_device, var_dtype))
179 or self._fallback_apply_state(var_device, var_dtype))
223 var_device, var_dtype = var.device, var.dtype.base_dtype
224 coefficients = ((apply_state or {}).get((var_device, var_dtype))
225 or self._fallback_apply_state(var_device, var_dtype))
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| D | nadam.py | 109 def _prepare_local(self, var_device, var_dtype, apply_state): argument
129 apply_state[(var_device, var_dtype)] = dict(
151 var_device, var_dtype = var.device, var.dtype.base_dtype
152 coefficients = ((apply_state or {}).get((var_device, var_dtype))
153 or self._fallback_apply_state(var_device, var_dtype))
174 var_device, var_dtype = var.device, var.dtype.base_dtype
175 coefficients = ((apply_state or {}).get((var_device, var_dtype))
176 or self._fallback_apply_state(var_device, var_dtype))
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| D | optimizer_v2.py | 934 for var_device in var_devices:
935 keys.add((var_device, var_dtype))
938 for var_device, var_dtype in keys:
939 apply_state[(var_device, var_dtype)] = {}
940 with ops.device(var_device):
941 self._prepare_local(var_device, var_dtype, apply_state)
945 def _prepare_local(self, var_device, var_dtype, apply_state): argument
948 apply_state[(var_device, var_dtype)]["lr_t"] = lr_t
950 def _fallback_apply_state(self, var_device, var_dtype): argument
952 apply_state = {(var_device, var_dtype): {}}
[all …]
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| /external/tensorflow/tensorflow/core/tpu/graph_rewrite/ |
| D | distributed_tpu_rewrite_pass.cc | 2488 DeviceNameUtils::ParsedName var_device; in FindVariableInputs() local
2490 &var_device)); in FindVariableInputs()
2491 if (var_device.has_job && var_device.has_replica && var_device.has_task && in FindVariableInputs()
2492 var_device.has_type && var_device.has_id) { in FindVariableInputs()
|