wassname/ray
1
0
Fork 0
mirror of https://github.com/wassname/ray.git synced 2026-07-03 05:45:24 +08:00
Code Issues Packages Projects Releases Wiki Activity

[RLlib] Add informative error message when bad Conv2D stack is used with fixed num_outputs (no flattening at end). (#9966)

Browse Source
This commit is contained in:
Sven Mika
2020-08-07 12:04:17 +02:00
committed by GitHub
parent 84b7240c4b
commit 5d5643e633
2 changed files with 34 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files
rllib/models/tf/visionnet.py
+18 -6
View File
@@ -11,15 +11,17 @@ class VisionNetwork(TFModelV2):
def __init__(self, obs_space, action_space, num_outputs, model_config,
name):
if not model_config.get("conv_filters"):
model_config["conv_filters"] = _get_filter_config(obs_space.shape)
super(VisionNetwork, self).__init__(obs_space, action_space,
num_outputs, model_config, name)
activation = get_activation_fn(model_config.get("conv_activation"))
filters = model_config.get("conv_filters")
if not filters:
filters = _get_filter_config(obs_space.shape)
no_final_linear = model_config.get("no_final_linear")
vf_share_layers = model_config.get("vf_share_layers")
activation = get_activation_fn(
self.model_config.get("conv_activation"), framework="tf")
filters = self.model_config["conv_filters"]
no_final_linear = self.model_config.get("no_final_linear")
vf_share_layers = self.model_config.get("vf_share_layers")
inputs = tf.keras.layers.Input(
shape=obs_space.shape, name="observations")
@@ -73,6 +75,16 @@ class VisionNetwork(TFModelV2):
padding="same",
data_format="channels_last",
name="conv_out")(last_layer)
if conv_out.shape[1] != 1 or conv_out.shape[2] != 1:
raise ValueError(
"Given `conv_filters` ({}) do not result in a [B, 1, "
"1, {} (`num_outputs`)] shape (but in {})! Please "
"adjust your Conv2D stack such that the dims 1 and 2 "
"are both 1.".format(
self.model_config["conv_filters"],
self.num_outputs, list(conv_out.shape)))
# num_outputs not known -> Flatten, then set self.num_outputs
# to the resulting number of nodes.
else:
rllib/models/torch/visionnet.py
+16 -6
View File
@@ -15,17 +15,18 @@ class VisionNetwork(TorchModelV2, nn.Module):
def __init__(self, obs_space, action_space, num_outputs, model_config,
name):
if not model_config.get("conv_filters"):
model_config["conv_filters"] = _get_filter_config(obs_space.shape)
TorchModelV2.__init__(self, obs_space, action_space, num_outputs,
model_config, name)
nn.Module.__init__(self)
activation = get_activation_fn(
model_config.get("conv_activation"), framework="torch")
filters = model_config.get("conv_filters")
if not filters:
filters = _get_filter_config(obs_space.shape)
no_final_linear = model_config.get("no_final_linear")
vf_share_layers = model_config.get("vf_share_layers")
self.model_config.get("conv_activation"), framework="torch")
filters = self.model_config["conv_filters"]
no_final_linear = self.model_config.get("no_final_linear")
vf_share_layers = self.model_config.get("vf_share_layers")
# Whether the last layer is the output of a Flattened (rather than
# a n x (1,1) Conv2D).
@@ -152,8 +153,17 @@ class VisionNetwork(TorchModelV2, nn.Module):
if not self.last_layer_is_flattened:
if self._logits:
conv_out = self._logits(conv_out)
if conv_out.shape[2] != 1 or conv_out.shape[3] != 1:
raise ValueError(
"Given `conv_filters` ({}) do not result in a [B, {} "
"(`num_outputs`), 1, 1] shape (but in {})! Please adjust "
"your Conv2D stack such that the last 2 dims are both "
"1.".format(
self.model_config["conv_filters"], self.num_outputs,
list(conv_out.shape)))
logits = conv_out.squeeze(3)
logits = logits.squeeze(2)
return logits, state
else:
return conv_out, state