gryf/coach
1
0
Fork 0
mirror of https://github.com/gryf/coach.git synced 2025-12-18 03:30:19 +01:00
Code Issues Projects Releases Wiki Activity

Enable creating custom tensorflow heads, embedders, and middleware. (#135)

Browse Source 
Allowing components to have a path property.
This commit is contained in:
Ryan Peach
2018-12-05 04:40:06 -05:00
committed by Gal Leibovich
parent 3c58ed740b
commit 9e66bb653e
4 changed files with 16 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
rl_coach/architectures/embedder_parameters.py
View File

@@ -18,6 +18,7 @@ from typing import List, Union
from rl_coach.base_parameters import EmbedderScheme, NetworkComponentParameters
MOD_NAMES = {'image': 'ImageEmbedder', 'vector': 'VectorEmbedder', 'tensor': 'TensorEmbedder'}
class InputEmbedderParameters(NetworkComponentParameters):
def __init__(self, activation_function: str='relu', scheme: Union[List, EmbedderScheme]=EmbedderScheme.Medium,
@@ -39,3 +40,6 @@ class InputEmbedderParameters(NetworkComponentParameters):
self.input_clipping = input_clipping
self.name = name
self.is_training = is_training
def path(self, emb_type):
return 'rl_coach.architectures.tensorflow_components.embedders:' + MOD_NAMES[emb_type]

5
rl_coach/architectures/head_parameters.py
View File

@@ -31,6 +31,11 @@ class HeadParameters(NetworkComponentParameters):
self.loss_weight = loss_weight
self.parameterized_class_name = parameterized_class_name
@property
def path(self):
return 'rl_coach.architectures.tensorflow_components.heads:' + self.parameterized_class_name
class PPOHeadParameters(HeadParameters):
def __init__(self, activation_function: str ='tanh', name: str='ppo_head_params',

4
rl_coach/architectures/middleware_parameters.py
View File

@@ -32,6 +32,10 @@ class MiddlewareParameters(NetworkComponentParameters):
self.is_training = is_training
self.parameterized_class_name = parameterized_class_name
@property
def path(self):
return 'rl_coach.architectures.tensorflow_components.middlewares:' + self.parameterized_class_name
class FCMiddlewareParameters(MiddlewareParameters):
def __init__(self, activation_function='relu',

8
rl_coach/architectures/tensorflow_components/general_network.py
View File

@@ -174,15 +174,13 @@ class GeneralTensorFlowNetwork(TensorFlowArchitecture):
raise ValueError("The key for the input embedder ({}) must match one of the following keys: {}"
.format(input_name, allowed_inputs.keys()))
mod_names = {'image': 'ImageEmbedder', 'vector': 'VectorEmbedder', 'tensor': 'TensorEmbedder'}
emb_type = "vector"
if isinstance(allowed_inputs[input_name], TensorObservationSpace):
emb_type = "tensor"
elif isinstance(allowed_inputs[input_name], PlanarMapsObservationSpace):
emb_type = "image"
embedder_path = 'rl_coach.architectures.tensorflow_components.embedders:' + mod_names[emb_type]
embedder_path = embedder_params.path(emb_type)
embedder_params_copy = copy.copy(embedder_params)
embedder_params_copy.activation_function = utils.get_activation_function(embedder_params.activation_function)
embedder_params_copy.input_rescaling = embedder_params_copy.input_rescaling[emb_type]
@@ -200,7 +198,7 @@ class GeneralTensorFlowNetwork(TensorFlowArchitecture):
:return: the middleware instance
"""
mod_name = middleware_params.parameterized_class_name
middleware_path = 'rl_coach.architectures.tensorflow_components.middlewares:' + mod_name
middleware_path = middleware_params.path
middleware_params_copy = copy.copy(middleware_params)
middleware_params_copy.activation_function = utils.get_activation_function(middleware_params.activation_function)
module = dynamic_import_and_instantiate_module_from_params(middleware_params_copy, path=middleware_path)
@@ -214,7 +212,7 @@ class GeneralTensorFlowNetwork(TensorFlowArchitecture):
:return: the head
"""
mod_name = head_params.parameterized_class_name
head_path = 'rl_coach.architectures.tensorflow_components.heads:' + mod_name
head_path = head_params.path
head_params_copy = copy.copy(head_params)
head_params_copy.activation_function = utils.get_activation_function(head_params_copy.activation_function)
return dynamic_import_and_instantiate_module_from_params(head_params_copy, path=head_path, extra_kwargs={