more testing

infer_qcds_01.py

@@ -16,7 +16,6 @@ import qcstereo_functions as qsf
 import tensorflow as tf
 from tensorflow.python.ops import resource_variable_ops
 
-
 tf.ResourceVariable = resource_variable_ops.ResourceVariable
 
 qsf.TIME_START = time.time()
@@ -146,6 +145,18 @@ rv_stage1_out = tf.Variable(
     collections = [GraphKeys.LOCAL_VARIABLES],# Works, available with tf.local_variables()
     dtype=np.float32,
     name = 'rv_stage1_out')
+
+'''
+rv_stage1_out = tf.get_variable("rv_stage1_out",
+                                shape=[HEIGHT * WIDTH, NN_LAYOUT1[-1]],
+                                dtype=tf.float32,
+                                initializer=tf.zeros_initializer,
+                                collections = [GraphKeys.LOCAL_VARIABLES], trainable=False)
+'''
+
+#rv_stageX_out_init_placeholder = tf.placeholder(tf.float32, shape=[HEIGHT * WIDTH, NN_LAYOUT1[-1]])
+#rv_stageX_out_init_op = rv_stageX_out.assign(rv_stageX_out_init_placeholder)
+
 ##stage1_tiled = tf.reshape(rv_stage1_out.read_value(),[HEIGHT, WIDTH, -1], name = 'stage1_tiled') 
 stage1_tiled = tf.reshape(rv_stage1_out, [HEIGHT, WIDTH, -1], name = 'stage1_tiled') # no need to synchronize here?
 
@@ -220,7 +231,7 @@ tf.add_to_collection(collection_io, stage2_out_sparse)
 """
 ##saver=tf.train.Saver()
 saver  =tf.train.Saver(tf.global_variables())
-#saver2 =tf.train.Saver(tf.global_variables()+tf.local_variables())
+#saver = tf.train.Saver(tf.global_variables()+tf.local_variables())
 
 saver_def = saver.as_saver_def()
 
@@ -250,10 +261,14 @@ except:
 
 
 with tf.Session()  as sess:
+        
     sess.run(tf.global_variables_initializer())
     sess.run(tf.local_variables_initializer())
+    
     saver.restore(sess, files["checkpoints"])
     
+    #tf.add_to_collection(GraphKeys.GLOBAL_VARIABLES,rv_stage1_out)
+    
     saver.save(sess, files["inference"])  #TODO: move to different subdir
     #saver2.save(sess, files["inference"]+"_2")  #TODO: move to different subdir
       
@@ -263,6 +278,8 @@ with tf.Session()  as sess:
     if LOGPATH:
         lf=open(LOGPATH,"w") #overwrite previous (or make it "a"?
 
+    #_ = sess.run([rv_stageX_out_init_op],feed_dict={rv_stageX_out_init_placeholder: np.zeros((HEIGHT * WIDTH, NN_LAYOUT1[-1]))})
+
     for nimg,_ in enumerate(image_data):
         dataset_img = qsf.readImageData(
             image_data =     image_data,

infer_qcds_graph_01.py

@@ -129,6 +129,8 @@ try:
 except:
     pass
 
+from tensorflow.python.framework.ops import GraphKeys
+
 with tf.Session()  as sess:
     
     # default option
@@ -162,10 +164,23 @@ with tf.Session()  as sess:
     if not USE_SPARSE_ONLY: #Does it reduce the graph size?
         stage2_out_full = graph.get_tensor_by_name('Disparity_net/stage2_out_full:0') 
 
+    '''
+    if not use_saved_model:
+        rv_stage1_out = tf.get_variable("rv_stage1_out",
+                                        shape=[78408, 32],
+                                        dtype=tf.float32,
+                                        initializer=tf.zeros_initializer)
+                                        #collections = [GraphKeys.LOCAL_VARIABLES],trainable=False)
+    '''
+
     sess.run(tf.global_variables_initializer())
     sess.run(tf.local_variables_initializer())
 
+    if not use_saved_model:
         infer_saver.restore(sess, files["inference"]) # after initializers, of course
+    else:
+        infer_saver.restore(sess, dirs['exportdir']+"/variables/variables.data-00000-of-00001")
+
     #infer_saver.restore(sess, files["inference"]+"_2") # after initializers, of course
     
     merged = tf.summary.merge_all()
@@ -222,8 +237,8 @@ with tf.Session()  as sess:
     if not use_saved_model:
         #builder.add_meta_graph_and_variables(sess,PB_TAGS)
         builder.add_meta_graph_and_variables(sess,[tf.saved_model.tag_constants.SERVING])
-        #builder.save(True)
-        builder.save(False)
+        builder.save(True)
+        #builder.save(False)
     
     if lf:
         lf.close()