Python resource_apply_ada_max 예제들

예제 #1

파일: adamax.py 프로젝트: Ajaycs99/tensorflow

 def _resource_apply_dense(self, grad, var):
   m = self.get_slot(var, "m")
   v = self.get_slot(var, "v")
   beta1_power = self._get_beta_accumulators()
   return training_ops.resource_apply_ada_max(
       var.handle, m.handle, v.handle,
       math_ops.cast(beta1_power, grad.dtype.base_dtype),
       math_ops.cast(self._lr_t, grad.dtype.base_dtype),
       math_ops.cast(self._beta1_t, grad.dtype.base_dtype),
       math_ops.cast(self._beta2_t, grad.dtype.base_dtype),
       math_ops.cast(self._epsilon_t, grad.dtype.base_dtype),
       grad, use_locking=self._use_locking)

예제 #2

파일: adamax.py 프로젝트: neuroph12/CNNDDDD

 def _resource_apply_dense(self, grad, var):
   m = self.get_slot(var, "m")
   v = self.get_slot(var, "v")
   beta1_power = self._get_beta_accumulators()
   return training_ops.resource_apply_ada_max(
       var.handle, m.handle, v.handle,
       math_ops.cast(beta1_power, grad.dtype.base_dtype),
       math_ops.cast(self._lr_t, grad.dtype.base_dtype),
       math_ops.cast(self._beta1_t, grad.dtype.base_dtype),
       math_ops.cast(self._beta2_t, grad.dtype.base_dtype),
       math_ops.cast(self._epsilon_t, grad.dtype.base_dtype),
       grad, use_locking=self._use_locking)

예제 #3

파일: adamax.py 프로젝트: warofthewrens/retrosheetsetl

    def _resource_apply_dense(self, grad, var, apply_state=None):
        var_device, var_dtype = var.device, var.dtype.base_dtype
        coefficients = ((apply_state or {}).get((var_device, var_dtype))
                        or self._fallback_apply_state(var_device, var_dtype))

        m = self.get_slot(var, 'm')
        v = self.get_slot(var, 'v')

        return training_ops.resource_apply_ada_max(
            var.handle,
            m.handle,
            v.handle,
            coefficients['beta_1_power'],
            coefficients['lr_t'],
            coefficients['beta_1_t'],
            coefficients['beta_2_t'],
            coefficients['epsilon'],
            grad,
            use_locking=self._use_locking)

예제 #4

 def _resource_apply_dense(self, grad, var):
     grad_dtype = grad.dtype.base_dtype
     m = self.get_slot(var, 'm')
     v = self.get_slot(var, 'v')
     local_step = math_ops.cast(self.iterations + 1, grad_dtype)
     beta_1_t = math_ops.cast(self._get_hyper('beta_1'), grad_dtype)
     beta_2_t = math_ops.cast(self._get_hyper('beta_2'), grad_dtype)
     beta_1_power = math_ops.pow(beta_1_t, local_step)
     return training_ops.resource_apply_ada_max(
         var.handle,
         m.handle,
         v.handle,
         beta_1_power,
         math_ops.cast(self._get_hyper('learning_rate'), grad_dtype),
         beta_1_t,
         beta_2_t,
         math_ops.cast(self._get_hyper('epsilon'), grad_dtype),
         grad,
         use_locking=self._use_locking)

예제 #5

파일: adamax.py 프로젝트: zhaoyongke/tensorflow

 def _resource_apply_dense(self, grad, var):
   grad_dtype = grad.dtype.base_dtype
   m = self.get_slot(var, 'm')
   v = self.get_slot(var, 'v')
   local_step = math_ops.cast(self.iterations + 1, grad_dtype)
   beta_1_t = math_ops.cast(self._get_hyper('beta_1'), grad_dtype)
   beta_2_t = math_ops.cast(self._get_hyper('beta_2'), grad_dtype)
   beta_1_power = math_ops.pow(beta_1_t, local_step)
   return training_ops.resource_apply_ada_max(
       var.handle,
       m.handle,
       v.handle,
       beta_1_power,
       math_ops.cast(self._get_hyper('learning_rate'), grad_dtype),
       beta_1_t,
       beta_2_t,
       math_ops.cast(self._get_hyper('epsilon'), grad_dtype),
       grad,
       use_locking=self._use_locking)

예제 #6

 def _resource_apply_dense(self, grad, var):
     var_dtype = var.dtype.base_dtype
     lr_t = self._decayed_lr(var_dtype)
     m = self.get_slot(var, 'm')
     v = self.get_slot(var, 'v')
     beta_1_t = self._get_hyper('beta_1', var_dtype)
     beta_2_t = self._get_hyper('beta_2', var_dtype)
     local_step = math_ops.cast(self.iterations + 1, var_dtype)
     beta_1_power = math_ops.pow(beta_1_t, local_step)
     return training_ops.resource_apply_ada_max(
         var.handle,
         m.handle,
         v.handle,
         beta_1_power,
         lr_t,
         beta_1_t,
         beta_2_t,
         self._get_hyper('epsilon', var_dtype),
         grad,
         use_locking=self._use_locking)

예제 #7

파일: adamax.py 프로젝트: aeverall/tensorflow

 def _resource_apply_dense(self, grad, var):
   var_dtype = var.dtype.base_dtype
   lr_t = self._decayed_lr(var_dtype)
   m = self.get_slot(var, 'm')
   v = self.get_slot(var, 'v')
   beta_1_t = self._get_hyper('beta_1', var_dtype)
   beta_2_t = self._get_hyper('beta_2', var_dtype)
   local_step = math_ops.cast(self.iterations + 1, var_dtype)
   beta_1_power = math_ops.pow(beta_1_t, local_step)
   return training_ops.resource_apply_ada_max(
       var.handle,
       m.handle,
       v.handle,
       beta_1_power,
       lr_t,
       beta_1_t,
       beta_2_t,
       self._get_hyper('epsilon', var_dtype),
       grad,
       use_locking=self._use_locking)