tf estimator input_fn reuse dataset
I want to split a tensorflow Dataset into a train and validation set to use it in an estimator. To do that I have to create the dataset in advance and then pass it to my input_fn.
dataset = dataset.shuffle(10000)
train_dataset = dataset.take(train_lines).repeat()
valid_dataset = dataset.skip(train_lines).repeat()
def train_input_fn():
return train_dataset
However, that throws an error because the dataset is from the wrong graph:
Tensor("IteratorV2:0", shape=(), dtype=resource) must be from the same graph as Tensor("MapDataset_1:0", shape=(), dtype=variant).
Tensorflow obviously needs to have everything in the same graph. How can I reuse a dataset to keep my random split?
python tensorflow tensorflow-datasets tensorflow-estimator
asked Nov 22 '18 at 8:41
user9491841user9491841
63
add a comment |
I want to split a tensorflow Dataset into a train and validation set to use it in an estimator. To do that I have to create the dataset in advance and then pass it to my input_fn.
dataset = dataset.shuffle(10000)
train_dataset = dataset.take(train_lines).repeat()
valid_dataset = dataset.skip(train_lines).repeat()
def train_input_fn():
return train_dataset
However, that throws an error because the dataset is from the wrong graph:
Tensor("IteratorV2:0", shape=(), dtype=resource) must be from the same graph as Tensor("MapDataset_1:0", shape=(), dtype=variant).
Tensorflow obviously needs to have everything in the same graph. How can I reuse a dataset to keep my random split?
python tensorflow tensorflow-datasets tensorflow-estimator
asked Nov 22 '18 at 8:41
user9491841user9491841
63
add a comment |
I want to split a tensorflow Dataset into a train and validation set to use it in an estimator. To do that I have to create the dataset in advance and then pass it to my input_fn.
dataset = dataset.shuffle(10000)
train_dataset = dataset.take(train_lines).repeat()
valid_dataset = dataset.skip(train_lines).repeat()
def train_input_fn():
return train_dataset
However, that throws an error because the dataset is from the wrong graph:
Tensor("IteratorV2:0", shape=(), dtype=resource) must be from the same graph as Tensor("MapDataset_1:0", shape=(), dtype=variant).
Tensorflow obviously needs to have everything in the same graph. How can I reuse a dataset to keep my random split?
python tensorflow tensorflow-datasets tensorflow-estimator
asked Nov 22 '18 at 8:41
user9491841user9491841
63
I want to split a tensorflow Dataset into a train and validation set to use it in an estimator. To do that I have to create the dataset in advance and then pass it to my input_fn.
dataset = dataset.shuffle(10000)
train_dataset = dataset.take(train_lines).repeat()
valid_dataset = dataset.skip(train_lines).repeat()
def train_input_fn():
return train_dataset
However, that throws an error because the dataset is from the wrong graph:
Tensor("IteratorV2:0", shape=(), dtype=resource) must be from the same graph as Tensor("MapDataset_1:0", shape=(), dtype=variant).
Tensorflow obviously needs to have everything in the same graph. How can I reuse a dataset to keep my random split?
python tensorflow tensorflow-datasets tensorflow-estimator
python tensorflow tensorflow-datasets tensorflow-estimator
asked Nov 22 '18 at 8:41
user9491841user9491841
63
asked Nov 22 '18 at 8:41
user9491841user9491841
63
asked Nov 22 '18 at 8:41
user9491841user9491841
63
asked Nov 22 '18 at 8:41
user9491841user9491841
63
asked Nov 22 '18 at 8:41
user9491841user9491841
63
63
add a comment |
add a comment |
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