Hacked a hook. Still to be fixed

bob/learn/tensorflow/utils/hooks.py

@@ -33,3 +33,34 @@ class LoggerHook(tf.train.SessionRunHook):
                           'sec/batch)')
             print(format_str % (datetime.now(), self._step, loss_value,
                                 examples_per_sec, sec_per_batch))
+                                
+class LoggerHookEstimator(tf.train.SessionRunHook):
+    """Logs loss and runtime."""
+
+    def __init__(self, estimator, batch_size, log_frequency):
+        self.estimator = estimator
+        self.batch_size = batch_size
+        self.log_frequency = log_frequency
+
+    def begin(self):
+        self._step = -1
+        self._start_time = time.time()
+
+    def before_run(self, run_context):
+        self._step += 1
+        return tf.train.SessionRunArgs(self.estimator.loss)  # Asks for loss value.
+
+    def after_run(self, run_context, run_values):
+        if self._step % self.log_frequency == 0:
+            current_time = time.time()
+            duration = current_time - self._start_time
+            self._start_time = current_time
+
+            loss_value = run_values.results
+            examples_per_sec = self.log_frequency * self.batch_size / duration
+            sec_per_batch = float(duration / self.log_frequency)
+
+            format_str = ('%s: step %d, loss = %.2f (%.1f examples/sec; %.3f '
+                          'sec/batch)')
+            print(format_str % (datetime.now(), self._step, loss_value,
+                                examples_per_sec, sec_per_batch))