print selene_sdk version, add config and model file to output, add ra…

selene_sdk/utils/config_utils.py

@@ -9,13 +9,16 @@
 from time import strftime
 import types
 import random
+import shutil, yaml
 
 import numpy as np
 import torch
 
 from . import _is_lua_trained_model
 from . import instantiate
+from . import load_path
 
+from selene_sdk import version
 
 def class_instantiate(classobj):
     """Not used currently, but might be useful later for recursive
@@ -111,6 +114,7 @@ def initialize_model(model_configs, train=True, lr=None):
 
     module = None
     if os.path.isdir(import_model_from):
+        import_model_from = import_model_from.rstrip(os.sep)
         module = module_from_dir(import_model_from)
     else:
         module = module_from_file(import_model_from)
@@ -260,9 +264,11 @@ def parse_configs_and_run(configs,
 
     Parameters
     ----------
-    configs : dict
-        The dictionary of nested configuration parameters. Will look
-        for the following top-level parameters:
+    configs : str or dict
+        If it is a str,  then configs is the name of the configuration YAML file, from which we will read 
+                         nested configuration parameters.
+        If it is a dict, then configs is a dict storing nested configuration parameters.
+        Will look for the following top-level parameters:
 
             * `ops`: A list of 1 or more of the values \
             {"train", "evaluate", "analyze"}. The operations specified\
@@ -305,8 +311,19 @@ def parse_configs_and_run(configs,
         to the dirs specified in each operation's configuration.
 
     """
+    if isinstance(configs, str):
+        configs_file = configs
+        if not os.path.isfile(configs_file):
+            print("The configuration YAML file {} does not exist!".format(configs_file))
+            return
+        configs = load_path(configs_file, instantiate=False)
     operations = configs["ops"]
 
+    #print selene_sdk version
+    if "selene_sdk_version" not in configs:
+        configs["selene_sdk_version"] = version.__version__ 
+        print("Running with selene_sdk version {0}".format(version.__version__))
+
     if "train" in operations and "lr" not in configs and lr != None:
         configs["lr"] = float(lr)
     elif "train" in operations and "lr" in configs and lr != None:
@@ -331,8 +348,9 @@ def parse_configs_and_run(configs,
         if "create_subdirectory" in configs:
             create_subdirectory = configs["create_subdirectory"]
         if create_subdirectory:
+            rand_str = str(random.random())[2:]
             current_run_output_dir = os.path.join(
-                current_run_output_dir, strftime("%Y-%m-%d-%H-%M-%S"))
+                current_run_output_dir, '{}-{}'.format(strftime("%Y-%m-%d-%H-%M-%S"), rand_str))
             os.makedirs(current_run_output_dir)
         print("Outputs and logs saved to {0}".format(
             current_run_output_dir))
@@ -343,9 +361,25 @@ def parse_configs_and_run(configs,
         np.random.seed(seed)
         torch.manual_seed(seed)
         torch.cuda.manual_seed_all(seed)
+        #torch.backends.cudnn.deterministic = True
+        #torch.backends.cudnn.benchmark = False
         print("Setting random seed = {0}".format(seed))
     else:
         print("Warning: no random seed specified in config file. "
               "Using a random seed ensures results are reproducible.")
 
+    if current_run_output_dir:
+        # write configs to output directory
+        with open('{}/{}'.format(current_run_output_dir,'configs.yaml'), 'w') as f:
+             yaml.dump(configs, f, default_flow_style=None)
+        # copy model file or directory to output
+        model_input = configs['model']['path']
+        if os.path.isdir(model_input): # copy the directory
+            shutil.copytree (model_input, 
+                             os.path.join(current_run_output_dir, os.path.basename(import_model_from)), 
+                             dirs_exist_ok=True)
+        else: 
+            shutil.copy     (model_input, current_run_output_dir)
+
+
     execute(operations, configs, current_run_output_dir)

setup.py

@@ -63,7 +63,7 @@
         "scipy",
         "seaborn",
         "statsmodels",
-        "torch>=0.4.1, <=1.9",
+        "torch>=0.4.1, <=1.11",
     ],
     entry_points={
         'console_scripts': [

tutorials/getting_started_with_selene/simple_train.yml

@@ -47,6 +47,6 @@ train_model: !obj:selene_sdk.TrainModel {
 }
 random_seed: 1447
 output_dir: ./training_outputs
-create_subdirectory: False
+create_subdirectory: True
 load_test_set: False
 ...