Comments (3)
Dear Sir,
Amazing work ! Congratulation!!
please , I have a question.can you kindly provide me with the full path I should insert of checkpoint the trained large scale training model to be able to use it as a pre-trained to meta transfer training?
I'm waiting for your reply.
Thanks in advance
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Please @wuguolil I'm facing a problem when i load the pretrained model , specially when it reads the checkpoint
this is the error .. how did you kindly solve it please ??
NotFoundError (see above for traceback): Key MODEL/conv7/kernel/Adam_3 not found in checkpoint
[[Node: save/RestoreV2_69 = RestoreV2[dtypes=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_save/Const_0_0, save/RestoreV2_69/tensor_names, save/RestoreV2_69/shape_and_slices)]]
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Please can you kindly explain me how to calculate this weight loss ?
def get_loss_weights(self):
loss_weights = tf.ones(shape=[self.TASK_ITER]) * (1.0/self.TASK_ITER)
decay_rate = 1.0 / self.TASK_ITER / (10000 / 3)
min_value= 0.03 / self.TASK_ITER
loss_weights_pre = tf.maximum(loss_weights[:-1] - (tf.multiply(tf.to_float(self.global_step), decay_rate)), min_value)
loss_weight_cur= tf.minimum(loss_weights[-1] + (tf.multiply(tf.to_float(self.global_step),(self.TASK_ITER- 1) * decay_rate)), 1.0 - ((self.TASK_ITER - 1) * min_value))
loss_weights = tf.concat([[loss_weights_pre], [[loss_weight_cur]]], axis=1)
return loss_weights
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Related Issues (20)
- Variable dimensions are incompatible while calculating l1_loss(during Large-Scale_Training) HOT 1
- about the high_resolution image HOT 3
- How to obtain X3 experimental results HOT 2
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- Reproduction with the given model HOT 5
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- Where is the path I should insert of checkpoint the trained large scale training model ? HOT 1
- Error during Large Scale Training HOT 1
- Problem when i load the pretrained model , specially when it reads the checkpoint HOT 1
- I do not understand how to calculate the weight loss ?
- Error during large scale training
- AlreadyExistsError during Meta-training
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