Merge pull request #177 from microsoft/v0.8

merge V0.8

docs/en_US/GeneralNasInterfaces.md

@@ -90,7 +90,7 @@ NNI's annotation compiler transforms the annotated trial code to the code that c
 
 ![](../img/nas_on_nni.png)
 
-The above figure shows how the trial code runs on NNI. `nnictl` processes user trial code to generate a search space file and compiled trial code. The former is fed to tuner, and the latter is used to run trilas. 
+The above figure shows how the trial code runs on NNI. `nnictl` processes user trial code to generate a search space file and compiled trial code. The former is fed to tuner, and the latter is used to run trials. 
 
 [__TODO__] Simple example of NAS on NNI.
 

src/nni_manager/rest_server/restHandler.ts

@@ -203,7 +203,7 @@ class NNIRestHandler {
                 res.send();
             } catch (err) {
                 // setClusterMetata is a step of initialization, so any exception thrown is a fatal
-                this.handle_error(err, res, true);
+                this.handle_error(NNIError.FromError(err), res, true);
             }
         });
     }

src/sdk/pynni/nni/smartparam.py

@@ -149,7 +149,7 @@ else:
         chosen_layer = mutable_block[mutable_layer_id]["chosen_layer"]
         chosen_inputs = mutable_block[mutable_layer_id]["chosen_inputs"]
         real_chosen_inputs = [optional_inputs[input_name] for input_name in chosen_inputs]
-        layer_out = funcs[chosen_layer]([fixed_inputs, real_chosen_inputs], *funcs_args[chosen_layer])
+        layer_out = funcs[chosen_layer]([fixed_inputs, real_chosen_inputs], **funcs_args[chosen_layer])
         
         return layer_out
 

tools/nni_annotation/code_generator.py

@@ -60,7 +60,7 @@ def parse_annotation_mutable_layers(code, lineno):
                     kw_args = []
                     kw_values = []
                     for kw in call.keywords:
-                        kw_args.append(kw.arg)
+                        kw_args.append(ast.Str(s=kw.arg))
                         kw_values.append(kw.value)
                     call_kwargs_values.append(ast.Dict(keys=kw_args, values=kw_values))
                 call_funcs = ast.Dict(keys=call_funcs_keys, values=call_funcs_values)
@@ -314,20 +314,20 @@ class Transformer(ast.NodeTransformer):
         else:
             return node  # not an annotation, ignore it
 
-        if string.startswith('@nni.get_next_parameter('):
+        if string.startswith('@nni.get_next_parameter'):
             deprecated_message = "'@nni.get_next_parameter' is deprecated in annotation due to inconvenience. Please remove this line in the trial code."
             print_warning(deprecated_message)
 
-        if string.startswith('@nni.report_intermediate_result(')  \
-                or string.startswith('@nni.report_final_result(') \
-                or string.startswith('@nni.get_next_parameter('):
+        if string.startswith('@nni.report_intermediate_result')  \
+                or string.startswith('@nni.report_final_result') \
+                or string.startswith('@nni.get_next_parameter'):
             return parse_annotation(string[1:])  # expand annotation string to code
 
-        if string.startswith('@nni.mutable_layers('):
+        if string.startswith('@nni.mutable_layers'):
             return parse_annotation_mutable_layers(string[1:], node.lineno)
 
-        if string.startswith('@nni.variable(') \
-                or string.startswith('@nni.function_choice('):
+        if string.startswith('@nni.variable') \
+                or string.startswith('@nni.function_choice'):
             self.stack[-1] = string[1:]  # mark that the next expression is annotated
             return None