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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/03/31 06:28:23 UTC
[GitHub] piiswrong closed pull request #10333: Fix error messages
piiswrong closed pull request #10333: Fix error messages
URL: https://github.com/apache/incubator-mxnet/pull/10333
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):
diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 3571b15ee06..fd95641274d 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -226,7 +226,7 @@ def _find_block_in_container(data):
'registered automatically. Make sure to register them using '
'register_child() or switching to '
'nn.Sequential/nn.HybridSequential instead. '
- .format(name=self.__class__.__name__ + "." + k))
+ .format(name=self.__class__.__name__ + "." + k), stacklevel=3)
def _alias(self):
return self.__class__.__name__.lower()
@@ -447,11 +447,11 @@ def _build_cache(self, *args):
for name, i in input_idx.items():
if name not in expected_inputs:
warnings.warn("The %d-th input to HybridBlock is not used by any "
- "computation. Is this intended?"%i)
+ "computation. Is this intended?"%i, stacklevel=4)
for name in params:
if name not in expected_inputs:
warnings.warn("Parameter %s is not used by any computation. "
- "Is this intended?"%name)
+ "Is this intended?"%name, stacklevel=4)
self._cached_op_args = [(False, params[name]) if name in params
else (True, input_idx[name])
diff --git a/python/mxnet/gluon/data/vision/transforms.py b/python/mxnet/gluon/data/vision/transforms.py
index a0734676a8d..5e65715e1b2 100644
--- a/python/mxnet/gluon/data/vision/transforms.py
+++ b/python/mxnet/gluon/data/vision/transforms.py
@@ -59,14 +59,17 @@ def __init__(self, transforms):
continue
elif len(hybrid) == 1:
self.add(hybrid[0])
+ hybrid = []
elif len(hybrid) > 1:
hblock = HybridSequential()
for j in hybrid:
hblock.add(j)
+ hblock.hybridize()
self.add(hblock)
+ hybrid = []
+
if i is not None:
self.add(i)
- self.hybridize()
class Cast(HybridBlock):
diff --git a/python/mxnet/gluon/model_zoo/vision/resnet.py b/python/mxnet/gluon/model_zoo/vision/resnet.py
index 37eb2cc19b4..5ee67b510a8 100644
--- a/python/mxnet/gluon/model_zoo/vision/resnet.py
+++ b/python/mxnet/gluon/model_zoo/vision/resnet.py
@@ -375,7 +375,12 @@ def get_resnet(version, num_layers, pretrained=False, ctx=cpu(),
root : str, default '~/.mxnet/models'
Location for keeping the model parameters.
"""
+ assert num_layers in resnet_spec, \
+ "Invalid number of layers: %d. Options are %s"%(
+ num_layers, str(resnet_spec.keys()))
block_type, layers, channels = resnet_spec[num_layers]
+ assert version >= 1 and version <= 2, \
+ "Invalid resnet version: %d. Options are 1 and 2."%version
resnet_class = resnet_net_versions[version-1]
block_class = resnet_block_versions[version-1][block_type]
net = resnet_class(block_class, layers, channels, **kwargs)
diff --git a/python/mxnet/gluon/nn/basic_layers.py b/python/mxnet/gluon/nn/basic_layers.py
index 3801c84b56f..f6113cc52b4 100644
--- a/python/mxnet/gluon/nn/basic_layers.py
+++ b/python/mxnet/gluon/nn/basic_layers.py
@@ -81,7 +81,7 @@ def hybridize(self, active=True, **kwargs):
"""
if self._children and all(isinstance(c, HybridBlock) for c in self._children):
warnings.warn('All children of this Sequential layer are HybridBlocks. Consider ' \
- 'using HybridSequential for the best performance.')
+ 'using HybridSequential for the best performance.', stacklevel=2)
super(Sequential, self).hybridize(active, **kwargs)
diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index 5a9277b2d63..ab511ab6e42 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -127,7 +127,7 @@ def grad_req(self):
@grad_req.setter
def grad_req(self, req):
assert req in ['write', 'add', 'null'], \
- "grad_req must be one of write, add, or null, but got %s"%req
+ "grad_req must be one of 'write', 'add', or 'null', but got '%s'"%req
if not self._differentiable:
req = 'null'
if self._grad_req == req:
@@ -165,25 +165,24 @@ def _check_and_get(self, arr_list, ctx):
return arr_list[0]
else:
ctx = context.current_context()
- if ctx.device_typeid < len(self._ctx_map):
- ctx_list = self._ctx_map[ctx.device_typeid]
- if ctx.device_id < len(ctx_list):
- idx = ctx_list[ctx.device_id]
- if idx is not None:
- return arr_list[idx]
+ ctx_list = self._ctx_map[ctx.device_typeid&1]
+ if ctx.device_id < len(ctx_list):
+ idx = ctx_list[ctx.device_id]
+ if idx is not None:
+ return arr_list[idx]
raise RuntimeError(
- "Parameter %s was not initialized on context %s. "
+ "Parameter '%s' was not initialized on context %s. "
"It was only initialized on %s."%(
self.name, str(ctx), str(self._ctx_list)))
if self._deferred_init:
raise DeferredInitializationError(
- "Parameter %s has not been initialized yet because initialization was " \
+ "Parameter '%s' has not been initialized yet because initialization was " \
"deferred. Actual initialization happens during the first forward pass. " \
"Please pass one batch of data through the network before accessing Parameters. " \
"You can also avoid deferred initialization by specifying in_units, " \
"num_features, etc., for network layers."%(self.name))
raise RuntimeError(
- "Parameter %s has not been initialized. Note that " \
+ "Parameter '%s' has not been initialized. Note that " \
"you should initialize parameters and create Trainer " \
"with Block.collect_params() instead of Block.params " \
"because the later does not include Parameters of " \
@@ -194,13 +193,13 @@ def _load_init(self, data, ctx):
if self.shape:
for self_dim, data_dim in zip(self.shape, data.shape):
assert self_dim == 0 or self_dim == data_dim, \
- "Failed loading Parameter %s from saved params: " \
+ "Failed loading Parameter '%s' from saved params: " \
"shape incompatible expacted %s vs saved %s"%(
self.name, str(self.shape), str(data.shape))
self.shape = tuple(i if i != 0 else j for i, j in zip(self.shape, data.shape))
if self.dtype:
assert np.dtype(self.dtype).type == data.dtype, \
- "Failed loading Parameter %s from saved params: " \
+ "Failed loading Parameter '%s' from saved params: " \
"dtype incompatible expacted %s vs saved %s"%(
self.name, str(self.dtype), str(data.dtype))
if isinstance(ctx, Context):
@@ -208,13 +207,13 @@ def _load_init(self, data, ctx):
if self._data is None:
if self._deferred_init:
assert set(ctx) == set(self._deferred_init[1]), \
- "Failed to load Parameter %s on %s because it was " \
+ "Failed to load Parameter '%s' on %s because it was " \
"previous initialized on %s."%(
self.name, str(ctx), str(self.list_ctx()))
self._init_impl(data, ctx)
else:
assert set(ctx) == set(self.list_ctx()), \
- "Failed to load Parameter %s on %s because it was " \
+ "Failed to load Parameter '%s' on %s because it was " \
"previous initialized on %s."%(
self.name, str(ctx), str(self.list_ctx()))
self.set_data(data)
@@ -227,7 +226,7 @@ def _finish_deferred_init(self):
init, ctx, default_init, data = self._deferred_init
self._deferred_init = ()
assert self.shape is not None and np.prod(self.shape) > 0, \
- "Cannot initialize Parameter %s because it has " \
+ "Cannot initialize Parameter '%s' because it has " \
"invalid shape: %s. Please specify in_units, " \
"in_channels, etc for `Block`s."%(
self.name, str(self.shape))
@@ -244,11 +243,9 @@ def _finish_deferred_init(self):
def _init_impl(self, data, ctx_list):
"""Sets data and grad."""
self._ctx_list = list(ctx_list)
- self._ctx_map = []
+ self._ctx_map = [[], []]
for i, ctx in enumerate(self._ctx_list):
- while len(self._ctx_map) <= ctx.device_typeid:
- self._ctx_map.append([])
- dev_list = self._ctx_map[ctx.device_typeid]
+ dev_list = self._ctx_map[ctx.device_typeid&1]
while len(dev_list) <= ctx.device_id:
dev_list.append(None)
dev_list[ctx.device_id] = i
@@ -317,8 +314,9 @@ def initialize(self, init=None, ctx=None, default_init=initializer.Uniform(),
<NDArray 2x2 @gpu(1)>
"""
if self._data is not None and not force_reinit:
- warnings.warn("Parameter %s is already initialized, ignoring. " \
- "Set force_reinit=True to re-initialize."%self.name)
+ warnings.warn("Parameter '%s' is already initialized, ignoring. " \
+ "Set force_reinit=True to re-initialize."%self.name,
+ stacklevel=2)
return
self._data = self._grad = None
@@ -332,7 +330,7 @@ def initialize(self, init=None, ctx=None, default_init=initializer.Uniform(),
if self._allow_deferred_init:
self._deferred_init = (init, ctx, default_init, None)
return
- raise ValueError("Cannot initialize Parameter %s because it has " \
+ raise ValueError("Cannot initialize Parameter '%s' because it has " \
"invalid shape: %s."%(self.name, str(self.shape)))
self._deferred_init = (init, ctx, default_init, None)
@@ -357,7 +355,7 @@ def reset_ctx(self, ctx):
init, _, default_init, data = self._deferred_init
self._deferred_init = (init, ctx, default_init, data)
else:
- raise ValueError("Cannot reset context for Parameter %s because it "
+ raise ValueError("Cannot reset context for Parameter '%s' because it "
"has not been initialized."%self.name)
@@ -367,7 +365,7 @@ def set_data(self, data):
if self._data is None:
assert self._deferred_init is not None, \
- "Parameter %s has not been initialized"%self.name
+ "Parameter '%s' has not been initialized"%self.name
self._deferred_init = self._deferred_init[:3] + (data,)
return
@@ -404,7 +402,7 @@ def grad(self, ctx=None):
"""
if self._data is not None and self._grad is None:
raise RuntimeError(
- "Cannot get gradient array for Parameter %s " \
+ "Cannot get gradient array for Parameter '%s' " \
"because grad_req='null'"%(self.name))
return self._check_and_get(self._grad, ctx)
@@ -413,7 +411,7 @@ def list_grad(self):
as :py:meth:`values`."""
if self._data is not None and self._grad is None:
raise RuntimeError(
- "Cannot get gradient array for Parameter %s " \
+ "Cannot get gradient array for Parameter '%s' " \
"because grad_req='null'"%(self.name))
return self._check_and_get(self._grad, list)
@@ -422,7 +420,7 @@ def list_ctx(self):
if self._data is None:
if self._deferred_init:
return self._deferred_init[1]
- raise RuntimeError("Parameter %s has not been initialized"%self.name)
+ raise RuntimeError("Parameter '%s' has not been initialized"%self.name)
return self._ctx_list
def zero_grad(self):
@@ -500,6 +498,14 @@ def _init_weight(self, _, arr):
init=init_name)
+def _brief_print_list(lst, limit=7):
+ """Print at most `limit` elements of list."""
+ if len(lst) > limit:
+ return _brief_print_list(lst[:limit//2], limit) + ', ..., ' + \
+ _brief_print_list(lst[-limit//2:], limit)
+ return ', '.join(["'%s'"%str(i) for i in lst])
+
+
class ParameterDict(object):
"""A dictionary managing a set of parameters.
@@ -600,9 +606,9 @@ def get(self, name, **kwargs):
continue
assert v is None or v == existing, \
- "Cannot retrieve Parameter %s because desired attribute " \
- "does not match with stored for attribute %s: " \
- "desired %s vs stored %s."%(
+ "Cannot retrieve Parameter '%s' because desired attribute " \
+ "does not match with stored for attribute '%s': " \
+ "desired '%s' vs stored '%s'."%(
name, k, str(v), str(getattr(param, k)))
else:
setattr(param, k, v)
@@ -631,20 +637,21 @@ def get_constant(self, name, value=None):
param = self._get_impl(name)
if param is None:
if value is None:
- raise KeyError("No constant named {}. Please specify value " \
+ raise KeyError("No constant named '{}'. Please specify value " \
"if you want to create a new constant.".format(
name))
param = Constant(name, value)
self._params[name] = param
elif value is not None:
assert isinstance(param, Constant), \
- "Parameter {} already exists but it is not a constant.".format(
+ "Parameter '{}' already exists but it is not a constant.".format(
name)
if isinstance(value, nd.NDArray):
value = value.asnumpy()
assert param.shape == value.shape and \
(param.value.asnumpy() == value).all(), \
- "Constant {} already exists but it's value doesn't match new value"
+ "Constant '{}' already exists but it's value doesn't match new " \
+ "value".format(name)
return param
def update(self, other):
@@ -653,7 +660,7 @@ def update(self, other):
if k in self._params:
assert self._params[k] is v, \
"Cannot update self with other because they have different " \
- "Parameters with the same name %s"%k
+ "Parameters with the same name '%s'"%k
else:
self._params[k] = v
@@ -727,8 +734,8 @@ def save(self, filename, strip_prefix=''):
weight = param._reduce()
if not param.name.startswith(strip_prefix):
raise ValueError(
- "Prefix %s is to be striped before saving, but Parameter " \
- "%s does not start with %s. If you are using Block.save_params, " \
+ "Prefix '%s' is to be striped before saving, but Parameter " \
+ "'%s' does not start with '%s'. If you are using Block.save_params, " \
"This may be due to your Block shares parameters from other " \
"Blocks or you forgot to use ``with name_scope()`` during init. " \
"Consider switching to Block.collect_params.save and " \
@@ -756,8 +763,8 @@ def load(self, filename, ctx, allow_missing=False,
if restore_prefix:
for name in self.keys():
assert name.startswith(restore_prefix), \
- "restore_prefix is %s but Parameters name %s does not start " \
- "with %s"%(restore_prefix, name, restore_prefix)
+ "restore_prefix is '%s' but Parameters name '%s' does not start " \
+ "with '%s'"%(restore_prefix, name, restore_prefix)
lprefix = len(restore_prefix)
loaded = [(k[4:] if k.startswith('arg:') or k.startswith('aux:') else k, v) \
for k, v in ndarray.load(filename).items()]
@@ -765,11 +772,15 @@ def load(self, filename, ctx, allow_missing=False,
if not allow_missing:
for name in self.keys():
assert name in arg_dict, \
- "Parameter %s is missing in file %s"%(name[lprefix:], filename)
+ "Parameter '%s' is missing in file '%s', which contains parameters: %s. " \
+ "Please make sure source and target networks have the same prefix."%(
+ name[lprefix:], filename, _brief_print_list(arg_dict.keys()))
for name in arg_dict:
if name not in self._params:
assert ignore_extra, \
- "Parameter %s loaded from file %s is not present in ParameterDict"%(
- name[lprefix:], filename)
+ "Parameter '%s' loaded from file '%s' is not present in ParameterDict, " \
+ "choices are: %s. Set ignore_extra to True to ignore. " \
+ "Please make sure source and target networks have the same prefix."%(
+ name[lprefix:], filename, _brief_print_list(self._params.keys()))
continue
self[name]._load_init(arg_dict[name], ctx)
diff --git a/src/imperative/imperative.cc b/src/imperative/imperative.cc
index fbbaf82d177..c5a47407c0c 100644
--- a/src/imperative/imperative.cc
+++ b/src/imperative/imperative.cc
@@ -193,7 +193,8 @@ void Imperative::RecordOp(
<< "Assigning to NDArrays that are already in a computational graph "
<< "will cause undefined behavior when evaluating gradients. "
<< "Please call backward first to clear the graph or do this out side of "
- << "a record section. ";
+ << "a record section. Also note that you cannot use inplace operations "
+ << "like +=, *=, relu(x, out=x), etc inside a record section.";
}
bool need_grad = false;
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