Skip to content
GitLab
Projects
Groups
Snippets
Help
Loading...
Help
Help
Support
Community forum
Keyboard shortcuts
?
Submit feedback
Sign in
Toggle navigation
E
EMADL2CPP
Project overview
Project overview
Details
Activity
Releases
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Locked Files
Issues
2
Issues
2
List
Boards
Labels
Service Desk
Milestones
Iterations
Merge Requests
0
Merge Requests
0
Requirements
Requirements
List
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Test Cases
Security & Compliance
Security & Compliance
Dependency List
License Compliance
Operations
Operations
Incidents
Environments
Packages & Registries
Packages & Registries
Container Registry
Analytics
Analytics
CI / CD
Code Review
Insights
Issue
Repository
Value Stream
Wiki
Wiki
Snippets
Snippets
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
monticore
EmbeddedMontiArc
generators
EMADL2CPP
Commits
d3c1bc00
Commit
d3c1bc00
authored
Aug 11, 2019
by
Nicola Gatto
Browse files
Options
Browse Files
Download
Plain Diff
Merge branch 'integrate-buffer-fix' into develop
parents
3cfe0efd
91a3d3e4
Pipeline
#170364
failed with stages
in 9 minutes and 46 seconds
Changes
8
Pipelines
2
Hide whitespace changes
Inline
Side-by-side
Showing
8 changed files
with
31 additions
and
7 deletions
+31
-7
pom.xml
pom.xml
+2
-2
src/test/resources/target_code/gluon/reinforcementModel/cartpole/CNNTrainer_cartpole_master_dqn.py
...forcementModel/cartpole/CNNTrainer_cartpole_master_dqn.py
+1
-1
src/test/resources/target_code/gluon/reinforcementModel/cartpole/reinforcement_learning/agent.py
...inforcementModel/cartpole/reinforcement_learning/agent.py
+9
-1
src/test/resources/target_code/gluon/reinforcementModel/mountaincar/reinforcement_learning/CNNCreator_mountaincar_agent_mountaincarCritic.py
...earning/CNNCreator_mountaincar_agent_mountaincarCritic.py
+0
-0
src/test/resources/target_code/gluon/reinforcementModel/mountaincar/reinforcement_learning/CNNNet_mountaincar_agent_mountaincarCritic.py
...nt_learning/CNNNet_mountaincar_agent_mountaincarCritic.py
+0
-0
src/test/resources/target_code/gluon/reinforcementModel/mountaincar/reinforcement_learning/agent.py
...orcementModel/mountaincar/reinforcement_learning/agent.py
+9
-1
src/test/resources/target_code/gluon/reinforcementModel/torcs/CNNTrainer_torcs_agent_torcsAgent_dqn.py
...ementModel/torcs/CNNTrainer_torcs_agent_torcsAgent_dqn.py
+1
-1
src/test/resources/target_code/gluon/reinforcementModel/torcs/reinforcement_learning/agent.py
.../reinforcementModel/torcs/reinforcement_learning/agent.py
+9
-1
No files found.
pom.xml
View file @
d3c1bc00
...
...
@@ -8,7 +8,7 @@
<groupId>
de.monticore.lang.monticar
</groupId>
<artifactId>
embedded-montiarc-emadl-generator
</artifactId>
<version>
0.3.
4
-SNAPSHOT
</version>
<version>
0.3.
5
-SNAPSHOT
</version>
<!-- == PROJECT DEPENDENCIES ============================================= -->
...
...
@@ -20,7 +20,7 @@
<cnnarch-generator.version>
0.0.2-SNAPSHOT
</cnnarch-generator.version>
<cnnarch-mxnet-generator.version>
0.2.16-SNAPSHOT
</cnnarch-mxnet-generator.version>
<cnnarch-caffe2-generator.version>
0.2.12-SNAPSHOT
</cnnarch-caffe2-generator.version>
<cnnarch-gluon-generator.version>
0.2.
5
-SNAPSHOT
</cnnarch-gluon-generator.version>
<cnnarch-gluon-generator.version>
0.2.
6
-SNAPSHOT
</cnnarch-gluon-generator.version>
<embedded-montiarc-math-opt-generator>
0.1.4
</embedded-montiarc-math-opt-generator>
<!-- .. Libraries .................................................. -->
...
...
src/test/resources/target_code/gluon/reinforcementModel/cartpole/CNNTrainer_cartpole_master_dqn.py
View file @
d3c1bc00
...
...
@@ -56,7 +56,7 @@ if __name__ == "__main__":
'memory_size'
:
10000
,
'sample_size'
:
32
,
'state_dtype'
:
'float32'
,
'action_dtype'
:
'
float32
'
,
'action_dtype'
:
'
uint8
'
,
'rewards_dtype'
:
'float32'
},
'strategy_params'
:
{
...
...
src/test/resources/target_code/gluon/reinforcementModel/cartpole/reinforcement_learning/agent.py
View file @
d3c1bc00
...
...
@@ -1043,6 +1043,14 @@ class DqnAgent(Agent):
self
.
_double_dqn
=
double_dqn
self
.
_use_fix_target
=
use_fix_target
# Build memory buffer for discrete actions
replay_memory_params
[
'state_dim'
]
=
state_dim
replay_memory_params
[
'action_dim'
]
=
(
1
,)
self
.
_replay_memory_params
=
replay_memory_params
rm_builder
=
ReplayMemoryBuilder
()
self
.
_memory
=
rm_builder
.
build_by_params
(
**
replay_memory_params
)
self
.
_minibatch_size
=
self
.
_memory
.
sample_size
# Initialize best network
self
.
_best_net
=
copy_net
(
self
.
_qnet
,
self
.
_state_dim
,
self
.
_ctx
)
self
.
_best_avg_score
=
-
np
.
infty
...
...
@@ -1199,7 +1207,7 @@ class DqnAgent(Agent):
# 3. Store transition in replay memory
self
.
_memory
.
append
(
state
,
action
,
reward
,
next_state
,
terminal
)
state
,
[
action
]
,
reward
,
next_state
,
terminal
)
# 4. Train the network if in interval
if
self
.
_do_training
():
...
...
src/test/resources/target_code/gluon/reinforcementModel/mountaincar/reinforcement_learning/CNNCreator_mountaincar_agent_
M
ountaincarCritic.py
→
src/test/resources/target_code/gluon/reinforcementModel/mountaincar/reinforcement_learning/CNNCreator_mountaincar_agent_
m
ountaincarCritic.py
View file @
d3c1bc00
File moved
src/test/resources/target_code/gluon/reinforcementModel/mountaincar/reinforcement_learning/CNNNet_mountaincar_agent_
M
ountaincarCritic.py
→
src/test/resources/target_code/gluon/reinforcementModel/mountaincar/reinforcement_learning/CNNNet_mountaincar_agent_
m
ountaincarCritic.py
View file @
d3c1bc00
File moved
src/test/resources/target_code/gluon/reinforcementModel/mountaincar/reinforcement_learning/agent.py
View file @
d3c1bc00
...
...
@@ -1043,6 +1043,14 @@ class DqnAgent(Agent):
self
.
_double_dqn
=
double_dqn
self
.
_use_fix_target
=
use_fix_target
# Build memory buffer for discrete actions
replay_memory_params
[
'state_dim'
]
=
state_dim
replay_memory_params
[
'action_dim'
]
=
(
1
,)
self
.
_replay_memory_params
=
replay_memory_params
rm_builder
=
ReplayMemoryBuilder
()
self
.
_memory
=
rm_builder
.
build_by_params
(
**
replay_memory_params
)
self
.
_minibatch_size
=
self
.
_memory
.
sample_size
# Initialize best network
self
.
_best_net
=
copy_net
(
self
.
_qnet
,
self
.
_state_dim
,
self
.
_ctx
)
self
.
_best_avg_score
=
-
np
.
infty
...
...
@@ -1199,7 +1207,7 @@ class DqnAgent(Agent):
# 3. Store transition in replay memory
self
.
_memory
.
append
(
state
,
action
,
reward
,
next_state
,
terminal
)
state
,
[
action
]
,
reward
,
next_state
,
terminal
)
# 4. Train the network if in interval
if
self
.
_do_training
():
...
...
src/test/resources/target_code/gluon/reinforcementModel/torcs/CNNTrainer_torcs_agent_torcsAgent_dqn.py
View file @
d3c1bc00
...
...
@@ -63,7 +63,7 @@ if __name__ == "__main__":
'memory_size'
:
1000000
,
'sample_size'
:
32
,
'state_dtype'
:
'float32'
,
'action_dtype'
:
'
float32
'
,
'action_dtype'
:
'
uint8
'
,
'rewards_dtype'
:
'float32'
},
'strategy_params'
:
{
...
...
src/test/resources/target_code/gluon/reinforcementModel/torcs/reinforcement_learning/agent.py
View file @
d3c1bc00
...
...
@@ -1043,6 +1043,14 @@ class DqnAgent(Agent):
self
.
_double_dqn
=
double_dqn
self
.
_use_fix_target
=
use_fix_target
# Build memory buffer for discrete actions
replay_memory_params
[
'state_dim'
]
=
state_dim
replay_memory_params
[
'action_dim'
]
=
(
1
,)
self
.
_replay_memory_params
=
replay_memory_params
rm_builder
=
ReplayMemoryBuilder
()
self
.
_memory
=
rm_builder
.
build_by_params
(
**
replay_memory_params
)
self
.
_minibatch_size
=
self
.
_memory
.
sample_size
# Initialize best network
self
.
_best_net
=
copy_net
(
self
.
_qnet
,
self
.
_state_dim
,
self
.
_ctx
)
self
.
_best_avg_score
=
-
np
.
infty
...
...
@@ -1199,7 +1207,7 @@ class DqnAgent(Agent):
# 3. Store transition in replay memory
self
.
_memory
.
append
(
state
,
action
,
reward
,
next_state
,
terminal
)
state
,
[
action
]
,
reward
,
next_state
,
terminal
)
# 4. Train the network if in interval
if
self
.
_do_training
():
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
.
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment