factor_analysis for BEAT

factor_analyser.py

@@ -572,10 +572,15 @@ class FactorAnalyser:
         gmm_covariance = "diag" if ubm.invcov.ndim == 2 else "full"
 
         # Set useful variables
-        with h5py.File(stat_server_filename[0], 'r') as fh:  # open the first StatServer to get size
-            _, sv_size = fh['stat1'].shape
-            feature_size = fh['stat1'].shape[1] // fh['stat0'].shape[1]
-            distrib_nb = fh['stat0'].shape[1]
+        if not isinstance(stat_server_filename[0], h5py._hl.files.File):
+            with h5py.File(stat_server_filename[0], 'r') as fh:  # open the first StatServer to get size
+                _, sv_size = fh['stat1'].shape
+                feature_size = fh['stat1'].shape[1] // fh['stat0'].shape[1]
+                distrib_nb = fh['stat0'].shape[1]
+        else:
+            _, sv_size = stat_server_filename[0]['stat1'].shape
+            feature_size = stat_server_filename[0]['stat1'].shape[1] // stat_server_filename[0]['stat0'].shape[1]
+            distrib_nb = stat_server_filename[0]['stat0'].shape[1]
 
         upper_triangle_indices = numpy.triu_indices(tv_rank)
 
@@ -611,7 +616,11 @@ class FactorAnalyser:
             for stat_server_file in stat_server_filename:
 
                 # get info from the current StatServer
-                with h5py.File(stat_server_file, 'r') as fh:
+                if not isinstance(stat_server_file, h5py._hl.files.File):
+                    fh = h5py.File(stat_server_file, 'r')
+                else:
+                    fh = stat_server_file
+
                     nb_sessions = fh["modelset"].shape[0]
                     total_session_nb += nb_sessions
                     batch_nb = int(numpy.floor(nb_sessions / float(batch_size) + 0.999))
@@ -644,6 +653,9 @@ class FactorAnalyser:
 
                     _A, _C, _R = watcher.get()
 
+                if not isinstance(stat_server_file, h5py._hl.files.File):
+                    fh.close()
+
             _R /= total_session_nb
 
             # M-step