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How do I find the variable names and values that are saved in a checkpoint?

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tensorflow

I want to see the variables that are saved in a TensorFlow checkpoint along with their values. How can I find the variable names that are saved in a TensorFlow checkpoint?

I used tf.train.NewCheckpointReader which is explained here. But, it is not given in the documentation of TensorFlow. Is there any other way?

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Tavakoli Avatar asked Jul 06 '16 07:07

Tavakoli


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What is model Ckpt?

ModelCheckpoint callback is used in conjunction with training using model. fit() to save a model or weights (in a checkpoint file) at some interval, so the model or weights can be loaded later to continue the training from the state saved.


1 Answers

Example usage:

from tensorflow.python.tools.inspect_checkpoint import print_tensors_in_checkpoint_file import os checkpoint_path = os.path.join(model_dir, "model.ckpt")  # List ALL tensors example output: v0/Adam (DT_FLOAT) [3,3,1,80] print_tensors_in_checkpoint_file(file_name=checkpoint_path, tensor_name='')  # List contents of v0 tensor. # Example output: tensor_name:  v0 [[[[  9.27958265e-02   7.40226209e-02   4.52989563e-02   3.15700471e-02 print_tensors_in_checkpoint_file(file_name=checkpoint_path, tensor_name='v0')  # List contents of v1 tensor. print_tensors_in_checkpoint_file(file_name=checkpoint_path, tensor_name='v1') 

Update: all_tensors argument was added to print_tensors_in_checkpoint_file since Tensorflow 0.12.0-rc0 so you may need to add all_tensors=False or all_tensors=True if required.

Alternative method:

from tensorflow.python import pywrap_tensorflow import os  checkpoint_path = os.path.join(model_dir, "model.ckpt") reader = pywrap_tensorflow.NewCheckpointReader(checkpoint_path) var_to_shape_map = reader.get_variable_to_shape_map()  for key in var_to_shape_map:     print("tensor_name: ", key)     print(reader.get_tensor(key)) # Remove this is you want to print only variable names 

Hope it helps.

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sagunms Avatar answered Sep 21 '22 05:09

sagunms