[Fit API] update estimator

python/mxnet/gluon/contrib/estimator/estimator.py

@@ -88,24 +88,36 @@ def _check_metrics(self, metrics):
  return metrics
 
  def _check_context(self, context):
- # handle context
- if isinstance(context, Context):
- context = [context]
- elif isinstance(context, list) and all([isinstance(c, Context) for c in context]):
- context = context
- elif not context:
- if num_gpus() > 0:
+ # infer available context
+ gpus = num_gpus()
+ available_gpus = [gpu(i) for i in range(gpus)]
+
+ if context:
+ # check context values, only accept Context or a list of Context
+ if isinstance(context, Context):
+ context = [context]
+ elif isinstance(context, list) and all([isinstance(c, Context) for c in context]):
+ context = context
+ else:
+ raise ValueError("context must be a Context or a list of Context, "
+ "for example mx.cpu() or [mx.gpu(0), mx.gpu(1)], "
+ "refer to mxnet.Context:{}".format(context))
+ for ctx in context:
+ assert ctx in available_gpus or str(ctx).startswith('cpu'), \
+ "%s is not available, please make sure " \
+ "your context is in one of: mx.cpu(), %s" % \
+ (ctx, ", ".join([str(ctx) for ctx in available_gpus]))
+ else:
+ # provide default context
+ if gpus > 0:
  # only use 1 GPU by default
- if num_gpus() > 1:
+ if gpus > 1:
  warnings.warn("You have multiple GPUs, gpu(0) will be used by default."
  "To utilize all your GPUs, specify context as a list of gpus, "
  "e.g. context=[mx.gpu(0), mx.gpu(1)] ")
  context = [gpu(0)]
  else:
  context = [cpu()]
- else:
- raise ValueError("context must be a Context or a list of Context, "
- "refer to mxnet.Context:{}".format(context))
  return context
 
  def _initialize(self, initializer):
@@ -167,7 +179,8 @@ def prepare_loss_and_metrics(self):
  self.train_metrics = [Accuracy()]
  self.val_metrics = []
  for loss in self.loss:
- self.train_metrics.append(Loss(''.join([i for i in loss.name if not i.isdigit()])))
+ # remove trailing numbers from loss name to avoid confusion
+ self.train_metrics.append(Loss(loss.name.rstrip('1234567890')))
  for metric in self.train_metrics:
  val_metric = copy.deepcopy(metric)
  metric.name = "Train " + metric.name

tests/python/unittest/test_gluon_estimator.py

@@ -258,6 +258,12 @@ def test_context():
  metrics=metrics,
  context='cpu')
 
+ with assert_raises(AssertionError):
+ est = Estimator(net=net,
+ loss=loss,
+ metrics=metrics,
+ context=[mx.gpu(0), mx.gpu(100)])
+
 
 def test_categorize_handlers():
  class CustomHandler1(TrainBegin):