Merge pull request #1 from CamiloPosso/py_37_tensorflow_2.0.0

Updating denovo to tensorflow 2.0.0

.gitignore

@@ -155,3 +155,14 @@ dmypy.json
 docker log.txt
 next steps from yuri.txt
 cProfile.ipynb
+
+
+## More ignores
+.vscode/launch.json
+Kaiko_denovo/src/kaiko_main_debugging.py
+Kaiko_denovo/tf2.0.0_variable_names.txt
+Kaiko_denovo_tf1.15.0
+
+
+tf2.0.0_variable_names.txt
+tf_updgrade_report.txt

Kaiko_denovo/VERSION INFO.txt

@@ -0,0 +1 @@
+this is the denovo piece of Kaiko, being tested with tensorflow 2.0.0

Kaiko_denovo/src/deepnovo_config.py

@@ -11,7 +11,8 @@
 from six.moves import xrange
 
 import numpy as np
-import tensorflow as tf
+# import tensorflow as tf
+import tensorflow.compat.v1 as tf
 
 
 # ==============================================================================
@@ -20,7 +21,7 @@
 
 
 tf.app.flags.DEFINE_string("train_dir", # flag_name
-                           "train", # default_value
+                           "Kaiko_denovo/model/", # default_value
                            "Training directory.") # docstring
 
 tf.app.flags.DEFINE_integer("direction",
@@ -63,7 +64,7 @@
                            "Knapsack input directory.")
 
 tf.app.flags.DEFINE_boolean("multi_decode",
-                            False,
+                            True,
                             "Set to True for decoding multiple files.")
 
 tf.app.flags.DEFINE_boolean("topk",
@@ -151,15 +152,15 @@
                             False,
                             "Set to True to search decoy database.")
 
+tf.app.flags.DEFINE_boolean("profile",
+                             False,
+                             "Set to True to profile the denovo model")
+
 FLAGS = tf.app.flags.FLAGS
 """
 Kaiko cProfile addition
 """
 
-tf.app.flags.DEFINE_boolean("profile",
-                             False,
-                             "Set to True to profile the denovo model")
-
 
 # ==============================================================================
 # GLOBAL VARIABLES for VOCABULARY

Kaiko_denovo/src/deepnovo_main_modules.py

@@ -1978,14 +1978,14 @@ def create_model(session, training_mode):
 
   # folder of training state
   ckpt = tf.train.get_checkpoint_state(deepnovo_config.FLAGS.train_dir)
-  if ckpt and tf.gfile.Exists(ckpt.model_checkpoint_path+".index"):
+  if ckpt and tf.io.gfile.exists(ckpt.model_checkpoint_path+".index"):
     print("Reading model parameters from %s" % ckpt.model_checkpoint_path)
     model.saver.restore(session, ckpt.model_checkpoint_path)
   else:
     print("Created model with fresh parameters.")
     #~ train_writer = tf.train.SummaryWriter("train_log", session.graph)
     #~ train_writer.close()
-    session.run(tf.global_variables_initializer())
+    session.run(tf.compat.v1.global_variables_initializer())
   return model
 
 
@@ -2893,7 +2893,7 @@ def decode_beam_search(sess,
 def decode(input_file=deepnovo_config.decode_test_file):
   """TODO(nh2tran): docstring."""
 
-  with tf.Session() as sess:
+  with tf.compat.v1.Session() as sess:
 
     # DECODING MODEL
     print("DECODING MODEL")
@@ -3034,7 +3034,7 @@ def decode(input_file=deepnovo_config.decode_test_file):
 def multi_decode(input_dir=deepnovo_config.input_mgf_dir):
   """TODO(nh2tran): docstring."""
 
-  with tf.Session() as sess:
+  with tf.compat.v1.Session() as sess:
 
     # DECODING MODEL
     print("DECODING MODEL")
@@ -3580,7 +3580,7 @@ def train():
         #~ resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / 1000)
 
   # TRAINING on train_set
-  with tf.Session() as sess:
+  with tf.compat.v1.Session() as sess:
   #~ print("RESOURCE-sess: ",
           #~ resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / 1000)
 
@@ -3691,7 +3691,7 @@ def test_true_feeding():
                                spectra_file_location_test)
 
   # Testing
-  with tf.Session() as sess:
+  with tf.compat.v1.Session() as sess:
 
     print("Create model for testing")
     model = create_model(sess, training_mode=False)
@@ -3809,8 +3809,8 @@ def multi_train_for_sigopt(hyperparams,
   valid_bucket_pos_id = np.nonzero(valid_bucket_len)[0]
 
   # TRAINING on train_set
-  tf.reset_default_graph()
-  with tf.Session() as sess:
+  tf.compat.v1.reset_default_graph()
+  with tf.compat.v1.Session() as sess:
     print("Create model for training")
     model = create_model(sess, training_mode=True)
 
@@ -3931,7 +3931,7 @@ def multi_train():
   valid_bucket_pos_id = np.nonzero(valid_bucket_len)[0]
 
   # TRAINING on train_set
-  with tf.Session() as sess:
+  with tf.compat.v1.Session() as sess:
     print("Create model for training")
     model = create_model(sess, training_mode=True)
 
@@ -4328,7 +4328,7 @@ def multi_train_pickles():
   valid_bucket_pos_id = np.nonzero(valid_bucket_len)[0]
 
   # TRAINING on train_set
-  with tf.Session() as sess:
+  with tf.compat.v1.Session() as sess:
     print("Create model for training")
     model = create_model(sess, training_mode=True)