How to extract weights and other variable values from tensorflow checkpoint without restoring the graph?
Provided a checkpoint file but no meta graph or code that produced the network, I want to extract the stored values of the variables in the checkpoint file.
So without restoring the graph, how do I extract the values stored in thr checkpoint. I could potentially convert everything from the checkpoint to a dictionary of numpy arrays or something similar.
python tensorflow checkpoint
edited Nov 20 '18 at 10:48
D Manokhin
584219
asked Nov 20 '18 at 10:43
dsalaj
6291026
add a comment |
Provided a checkpoint file but no meta graph or code that produced the network, I want to extract the stored values of the variables in the checkpoint file.
So without restoring the graph, how do I extract the values stored in thr checkpoint. I could potentially convert everything from the checkpoint to a dictionary of numpy arrays or something similar.
python tensorflow checkpoint
edited Nov 20 '18 at 10:48
D Manokhin
584219
asked Nov 20 '18 at 10:43
dsalaj
6291026
add a comment |
Provided a checkpoint file but no meta graph or code that produced the network, I want to extract the stored values of the variables in the checkpoint file.
So without restoring the graph, how do I extract the values stored in thr checkpoint. I could potentially convert everything from the checkpoint to a dictionary of numpy arrays or something similar.
python tensorflow checkpoint
edited Nov 20 '18 at 10:48
D Manokhin
584219
asked Nov 20 '18 at 10:43
dsalaj
6291026
Provided a checkpoint file but no meta graph or code that produced the network, I want to extract the stored values of the variables in the checkpoint file.
So without restoring the graph, how do I extract the values stored in thr checkpoint. I could potentially convert everything from the checkpoint to a dictionary of numpy arrays or something similar.
python tensorflow checkpoint
python tensorflow checkpoint
edited Nov 20 '18 at 10:48
D Manokhin
584219
asked Nov 20 '18 at 10:43
dsalaj
6291026
edited Nov 20 '18 at 10:48
D Manokhin
584219
asked Nov 20 '18 at 10:43
dsalaj
6291026
edited Nov 20 '18 at 10:48
D Manokhin
584219
edited Nov 20 '18 at 10:48
D Manokhin
584219
edited Nov 20 '18 at 10:48
D Manokhin
584219
584219
asked Nov 20 '18 at 10:43
dsalaj
6291026
asked Nov 20 '18 at 10:43
dsalaj
6291026
asked Nov 20 '18 at 10:43
dsalaj
6291026
6291026
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Found the solution:
reader = tf.train.NewCheckpointReader("/path/to/checkpoint")
shapes_dict = reader.get_variable_to_shape_map() # use it to get the variable names
extracted_values = reader.get_tensor(shapes_dict.keys()[0])
# array([[ 0. , -1.8053141],
# [-1.5647348, 0. ]], dtype=float32)
The tf.train.NewCheckpointReader is not really documented in current documentation of API r1.12.
But you can see the usage example in the source code here.
answered Nov 20 '18 at 10:56
dsalaj
6291026
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Found the solution:
reader = tf.train.NewCheckpointReader("/path/to/checkpoint")
shapes_dict = reader.get_variable_to_shape_map() # use it to get the variable names
extracted_values = reader.get_tensor(shapes_dict.keys()[0])
# array([[ 0. , -1.8053141],
# [-1.5647348, 0. ]], dtype=float32)
The tf.train.NewCheckpointReader is not really documented in current documentation of API r1.12.
But you can see the usage example in the source code here.
answered Nov 20 '18 at 10:56
dsalaj
6291026
add a comment |
Found the solution:
reader = tf.train.NewCheckpointReader("/path/to/checkpoint")
shapes_dict = reader.get_variable_to_shape_map() # use it to get the variable names
extracted_values = reader.get_tensor(shapes_dict.keys()[0])
# array([[ 0. , -1.8053141],
# [-1.5647348, 0. ]], dtype=float32)
The tf.train.NewCheckpointReader is not really documented in current documentation of API r1.12.
But you can see the usage example in the source code here.
answered Nov 20 '18 at 10:56
dsalaj
6291026
add a comment |
Found the solution:
reader = tf.train.NewCheckpointReader("/path/to/checkpoint")
shapes_dict = reader.get_variable_to_shape_map() # use it to get the variable names
extracted_values = reader.get_tensor(shapes_dict.keys()[0])
# array([[ 0. , -1.8053141],
# [-1.5647348, 0. ]], dtype=float32)
The tf.train.NewCheckpointReader is not really documented in current documentation of API r1.12.
But you can see the usage example in the source code here.
answered Nov 20 '18 at 10:56
dsalaj
6291026
Found the solution:
reader = tf.train.NewCheckpointReader("/path/to/checkpoint")
shapes_dict = reader.get_variable_to_shape_map() # use it to get the variable names
extracted_values = reader.get_tensor(shapes_dict.keys()[0])
# array([[ 0. , -1.8053141],
# [-1.5647348, 0. ]], dtype=float32)
The tf.train.NewCheckpointReader is not really documented in current documentation of API r1.12.
But you can see the usage example in the source code here.
answered Nov 20 '18 at 10:56
dsalaj
6291026
answered Nov 20 '18 at 10:56
dsalaj
6291026
answered Nov 20 '18 at 10:56
dsalaj
6291026
answered Nov 20 '18 at 10:56
dsalaj
6291026
6291026
add a comment |
add a comment |
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