!11263 remove the max_file_size limitation for export files

From: @jiang-shuqiang
Reviewed-by: @yelihua,@ouwenchang
Signed-off-by: @ouwenchang

mindspore/train/callback/_summary_collector.py

@@ -129,6 +129,7 @@ class SummaryCollector(Callback):
             specify `max_file_size=4 * 1024**3`.
         export_options (Union[None, dict]): Perform custom operations on the export data.
             Default: None, it means there is no export data.
+            Note that the size of export files is not limited by the max_file_size.
             You can customize the export data with a dictionary. For example, you can set {'tensor_format': 'npy'}
             to export tensor as npy file. The data that supports control is shown below.
 

mindspore/train/summary/_summary_adapter.py

@@ -36,14 +36,14 @@ EVENT_FILE_INIT_VERSION = 1
 F32_MIN, F32_MAX = np.finfo(np.float32).min, np.finfo(np.float32).max
 
 
-def get_event_file_name(prefix, suffix, seconds=None):
+def get_event_file_name(prefix, suffix, time_second):
     """
     Create file name: file_prefix + EVENT_FILE_NAME_MARK + time(seconds) + "." + Hostname + file_suffix.
 
     Args:
         prefix (str): The prefix of file name.
         suffix (str): The suffix of file name.
-        seconds (str): The time stamp of file name.
+        time_second (str): The time stamp of file name.
 
     Returns:
         String, the name of event log file.
@@ -51,9 +51,6 @@ def get_event_file_name(prefix, suffix, seconds=None):
     Validator.check_str_by_regular(prefix)
     Validator.check_str_by_regular(suffix)
     file_name = ""
-    time_second = str(int(time.time()))
-    if seconds is not None:
-        time_second = seconds
     hostname = platform.node()
 
     if prefix is not None:

mindspore/train/summary/summary_record.py

@@ -108,6 +108,7 @@ class SummaryRecord:
             in recording data. Default: False, this means that error logs are printed and no exception is thrown.
         export_options (Union[None, dict]): Perform custom operations on the export data.
             Default: None, it means there is no export data.
+            Note that the size of export files is not limited by the max_file_size.
             You can customize the export data with a dictionary. For example, you can set {'tensor_format': 'npy'}
             to export tensor as npy file. The data that supports control is shown below.
 
@@ -158,19 +159,19 @@ class SummaryRecord:
         self.network = network
         self.has_graph = False
 
-        seconds = str(int(time.time()))
+        time_second = str(int(time.time()))
         # create the summary writer file
-        self.event_file_name = get_event_file_name(self.prefix, self.suffix, seconds)
+        self.event_file_name = get_event_file_name(self.prefix, self.suffix, time_second)
         self.full_file_name = os.path.join(self.log_path, self.event_file_name)
 
         self._export_options = process_export_options(export_options)
         export_dir = ''
         if self._export_options is not None:
-            export_dir = "export_{}".format(seconds)
+            export_dir = "export_{}".format(time_second)
 
         filename_dict = dict(summary=self.full_file_name,
-                             lineage=get_event_file_name(self.prefix, '_lineage'),
-                             explainer=get_event_file_name(self.prefix, '_explain'),
+                             lineage=get_event_file_name(self.prefix, '_lineage', time_second),
+                             explainer=get_event_file_name(self.prefix, '_explain', time_second),
                              exporter=export_dir)
         self._event_writer = WriterPool(log_dir,
                                         max_file_size,

mindspore/train/summary/writer.py

@@ -163,10 +163,6 @@ class ExportWriter(BaseWriter):
         if disk_usage(path).free < required_length * FREE_DISK_SPACE_TIMES:
             raise RuntimeError(f"The disk space may be soon exhausted by the '{path}'.")
 
-        if max_file_size is not None and max_file_size < required_length:
-            raise RuntimeWarning(f"'max_file_size' reached: There are {max_file_size} bytes remaining, "
-                                 f"but the '{path}' requires to write {required_length} bytes.")
-
         np_path = "{}/{}_{}.npy".format(path, tag, step)
         np.save(np_path, np_value)
         os.chmod(np_path, FILE_MODE)