Loading raps/dataloaders/frontier.py +17 −8 Original line number Diff line number Diff line Loading @@ -65,7 +65,8 @@ def load_data_from_df(jobs_df: pd.DataFrame, jobprofile_df: pd.DataFrame, **kwar validate = kwargs.get('validate') jid = kwargs.get('jid', '*') if fastforward: print(f"fast-forwarding {fastforward} seconds") if fastforward: print(f"fast-forwarding {fastforward} seconds") min_time = kwargs.get('min_time', None) Loading Loading @@ -102,7 +103,8 @@ def load_data_from_df(jobs_df: pd.DataFrame, jobprofile_df: pd.DataFrame, **kwar nodes_required = jobs_df.loc[jidx, 'node_count'] end_state = jobs_df.loc[jidx, 'state_current'] name = jobs_df.loc[jidx, 'name'] if encrypt_bool: name = encrypt(name) if encrypt_bool: name = encrypt(name) if validate: cpu_power = jobprofile_df[jobprofile_df['allocation_id'] Loading Loading @@ -138,7 +140,8 @@ def load_data_from_df(jobs_df: pd.DataFrame, jobprofile_df: pd.DataFrame, **kwar diff = time_start - time_zero time_offset = max(diff.total_seconds(), 0) if fastforward: time_offset -= fastforward if fastforward: time_offset -= fastforward xnames = jobs_df.loc[jidx, 'xnames'] # Don't replay any job with an empty set of xnames Loading @@ -151,7 +154,12 @@ def load_data_from_df(jobs_df: pd.DataFrame, jobprofile_df: pd.DataFrame, **kwar priority = aging_boost(nodes_required) elif reschedule == 'submit-time': raise NotImplementedError scheduled_nodes = None time_submit = jobs_df.loc[jidx, 'time_submission'] diff = time_submit - time_zero time_offset = max(diff.total_seconds(), 0) priority = 0 # SIC #raise NotImplementedError else: # Prescribed replay scheduled_nodes = [] Loading Loading @@ -228,6 +236,7 @@ CDU_NAMES = [ 'x2609c1', ] def cdu_index_to_name(index: int, config: dict): return CDU_NAMES[index - 1] Loading Loading
raps/dataloaders/frontier.py +17 −8 Original line number Diff line number Diff line Loading @@ -65,7 +65,8 @@ def load_data_from_df(jobs_df: pd.DataFrame, jobprofile_df: pd.DataFrame, **kwar validate = kwargs.get('validate') jid = kwargs.get('jid', '*') if fastforward: print(f"fast-forwarding {fastforward} seconds") if fastforward: print(f"fast-forwarding {fastforward} seconds") min_time = kwargs.get('min_time', None) Loading Loading @@ -102,7 +103,8 @@ def load_data_from_df(jobs_df: pd.DataFrame, jobprofile_df: pd.DataFrame, **kwar nodes_required = jobs_df.loc[jidx, 'node_count'] end_state = jobs_df.loc[jidx, 'state_current'] name = jobs_df.loc[jidx, 'name'] if encrypt_bool: name = encrypt(name) if encrypt_bool: name = encrypt(name) if validate: cpu_power = jobprofile_df[jobprofile_df['allocation_id'] Loading Loading @@ -138,7 +140,8 @@ def load_data_from_df(jobs_df: pd.DataFrame, jobprofile_df: pd.DataFrame, **kwar diff = time_start - time_zero time_offset = max(diff.total_seconds(), 0) if fastforward: time_offset -= fastforward if fastforward: time_offset -= fastforward xnames = jobs_df.loc[jidx, 'xnames'] # Don't replay any job with an empty set of xnames Loading @@ -151,7 +154,12 @@ def load_data_from_df(jobs_df: pd.DataFrame, jobprofile_df: pd.DataFrame, **kwar priority = aging_boost(nodes_required) elif reschedule == 'submit-time': raise NotImplementedError scheduled_nodes = None time_submit = jobs_df.loc[jidx, 'time_submission'] diff = time_submit - time_zero time_offset = max(diff.total_seconds(), 0) priority = 0 # SIC #raise NotImplementedError else: # Prescribed replay scheduled_nodes = [] Loading Loading @@ -228,6 +236,7 @@ CDU_NAMES = [ 'x2609c1', ] def cdu_index_to_name(index: int, config: dict): return CDU_NAMES[index - 1] Loading