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lvzhengyang
REST
Commits
c01b9271
Commit
c01b9271
authored
Sep 07, 2022
by
lvzhengyang
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fix bug in getting ws_probs
parent
35ab999f
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4 changed files
with
34 additions
and
18 deletions
+34
-18
__pycache__/agent.cpython-38.pyc
+0
-0
__pycache__/model.cpython-38.pyc
+0
-0
agent.py
+20
-9
model.py
+14
-9
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__pycache__/agent.cpython-38.pyc
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agent.py
View file @
c01b9271
...
@@ -36,10 +36,16 @@ class Actor(nn.Module):
...
@@ -36,10 +36,16 @@ class Actor(nn.Module):
u0_probs
=
self
.
decoder
.
_get_u0_probs
(
e
)
u0_probs
=
self
.
decoder
.
_get_u0_probs
(
e
)
return
u0_probs
return
u0_probs
def
forward
(
self
,
nodes
,
mask_visited
=
None
,
mask_unvisited
=
None
):
def
get_u_probs
(
self
,
nodes
,
mask_visited
=
None
,
mask_unvisited
=
None
):
e
=
self
.
encoder
(
nodes
)
e
=
self
.
encoder
(
nodes
)
u_probs
,
ws_probs
=
self
.
decoder
(
e
,
mask_visited
,
mask_unvisited
)
u_probs
=
self
.
decoder
.
get_u_probs
(
e
,
mask_visited
,
mask_unvisited
)
return
u_probs
,
ws_probs
return
u_probs
def
get_ws_probs
(
self
,
nodes
,
mask_visited
=
None
,
mask_unvisited
=
None
):
e
=
self
.
encoder
(
nodes
)
ws_probs
=
self
.
decoder
.
get_ws_probs
(
e
,
self
.
decoder
.
_last_Eu
,
mask_visited
,
mask_unvisited
)
return
ws_probs
class
Critic
(
nn
.
Module
):
class
Critic
(
nn
.
Module
):
def
__init__
(
self
,
dim_e
=
D
,
dim_c
=
256
)
->
None
:
def
__init__
(
self
,
dim_e
=
D
,
dim_c
=
256
)
->
None
:
...
@@ -137,11 +143,20 @@ class Policy(nn.Module):
...
@@ -137,11 +143,20 @@ class Policy(nn.Module):
mask_unvisited
=
~
mask_visited
mask_unvisited
=
~
mask_visited
num_nodes
=
nodes
.
shape
[
1
]
num_nodes
=
nodes
.
shape
[
1
]
u_probs
,
ws_probs
=
self
.
actor
(
nodes
,
u_probs
=
self
.
actor
.
get_u_probs
(
nodes
,
mask_visited
=
mask_visited
,
mask_unvisited
=
mask_unvisited
)
mask_visited
=
mask_visited
,
mask_unvisited
=
mask_unvisited
)
u_dist
=
Categorical
(
u_probs
)
u_dist
=
Categorical
(
u_probs
)
ws_dist
=
Categorical
(
ws_probs
)
u
=
u_dist
.
sample
()
u
=
u_dist
.
sample
()
batch_size
=
u
.
shape
[
0
]
_last_Eu
=
[]
for
i
in
range
(
batch_size
):
_last_Eu
.
append
(
self
.
actor
.
_node_e
[
i
,
u
[
i
]])
self
.
actor
.
decoder
.
_last_Eu
=
torch
.
stack
(
_last_Eu
)
ws_probs
=
self
.
actor
.
get_ws_probs
(
nodes
,
mask_visited
=
mask_visited
,
mask_unvisited
=
mask_unvisited
)
ws_dist
=
Categorical
(
ws_probs
)
_w
=
ws_dist
.
sample
()
_w
=
ws_dist
.
sample
()
self
.
log_probs_buf
[
'u'
]
.
append
(
u_dist
.
log_prob
(
u
))
self
.
log_probs_buf
[
'u'
]
.
append
(
u_dist
.
log_prob
(
u
))
...
@@ -150,15 +165,12 @@ class Policy(nn.Module):
...
@@ -150,15 +165,12 @@ class Policy(nn.Module):
s
=
torch
.
where
(
_w
<
num_nodes
,
int
(
0
),
int
(
1
))
.
to
(
_w
.
device
)
s
=
torch
.
where
(
_w
<
num_nodes
,
int
(
0
),
int
(
1
))
.
to
(
_w
.
device
)
w
=
torch
.
where
(
_w
<
num_nodes
,
_w
,
_w
-
num_nodes
)
w
=
torch
.
where
(
_w
<
num_nodes
,
_w
,
_w
-
num_nodes
)
batch_size
=
u
.
shape
[
0
]
_last_Eu
=
[]
_last_Ew
=
[]
_last_Ew
=
[]
_last_Ev
=
[]
_last_Ev
=
[]
_last_Eh
=
[]
_last_Eh
=
[]
v
=
[]
v
=
[]
h
=
[]
h
=
[]
for
i
in
range
(
batch_size
):
for
i
in
range
(
batch_size
):
_last_Eu
.
append
(
self
.
actor
.
_node_e
[
i
,
u
[
i
]])
_last_Ew
.
append
(
self
.
actor
.
_node_e
[
i
,
w
[
i
]])
_last_Ew
.
append
(
self
.
actor
.
_node_e
[
i
,
w
[
i
]])
if
s
[
i
]
==
0
:
if
s
[
i
]
==
0
:
_last_Ev
.
append
(
self
.
actor
.
_node_e
[
i
,
u
[
i
]])
_last_Ev
.
append
(
self
.
actor
.
_node_e
[
i
,
u
[
i
]])
...
@@ -170,7 +182,6 @@ class Policy(nn.Module):
...
@@ -170,7 +182,6 @@ class Policy(nn.Module):
_last_Eh
.
append
(
self
.
actor
.
_node_e
[
i
,
u
[
i
]])
_last_Eh
.
append
(
self
.
actor
.
_node_e
[
i
,
u
[
i
]])
v
.
append
(
w
[
i
])
v
.
append
(
w
[
i
])
h
.
append
(
u
[
i
])
h
.
append
(
u
[
i
])
self
.
actor
.
decoder
.
_last_Eu
=
torch
.
stack
(
_last_Eu
)
self
.
actor
.
decoder
.
_last_Ew
=
torch
.
stack
(
_last_Ew
)
self
.
actor
.
decoder
.
_last_Ew
=
torch
.
stack
(
_last_Ew
)
self
.
actor
.
decoder
.
_last_Ev
=
torch
.
stack
(
_last_Ev
)
self
.
actor
.
decoder
.
_last_Ev
=
torch
.
stack
(
_last_Ev
)
self
.
actor
.
decoder
.
_last_Eh
=
torch
.
stack
(
_last_Eh
)
self
.
actor
.
decoder
.
_last_Eh
=
torch
.
stack
(
_last_Eh
)
...
...
model.py
View file @
c01b9271
...
@@ -182,7 +182,9 @@ class QGen(nn.Module):
...
@@ -182,7 +182,9 @@ class QGen(nn.Module):
if
cur_u
==
None
:
if
cur_u
==
None
:
cur_q
=
torch
.
relu
(
last_edge
+
last_subtree
)
cur_q
=
torch
.
relu
(
last_edge
+
last_subtree
)
else
:
else
:
cur_q
=
torch
.
relu
(
last_edge
+
last_subtree
)
# ERROR! where is u?
tmp
=
self
.
W_5
(
cur_u
)
cur_q
=
torch
.
relu
(
last_edge
+
last_subtree
+
tmp
)
return
cur_q
return
cur_q
class
EPTM
(
nn
.
Module
):
class
EPTM
(
nn
.
Module
):
...
@@ -246,13 +248,11 @@ class Decoder(nn.Module):
...
@@ -246,13 +248,11 @@ class Decoder(nn.Module):
start_node_probs
,
_
=
self
.
ptm_0
(
e
,
q
)
start_node_probs
,
_
=
self
.
ptm_0
(
e
,
q
)
return
start_node_probs
return
start_node_probs
def
forward
(
self
,
e
,
mask_visited
=
None
,
mask_unvisited
=
None
):
def
get_u_probs
(
self
,
e
,
mask_visited
=
None
,
mask_unvisited
=
None
):
"""
"""
@param e: input embeddings for all nodes, [#num_batch, #num_nodes, D]
@param e: input embeddings for all nodes, [#num_batch, #num_nodes, D]
@param last_u/w/v/h: embeddings for last u/w/v/h
@param last_subtree: embeddings for last subtree
@note define subtree(t=0) = 0
@note define subtree(t=0) = 0
@return probability of u, w
,
s
@return probability of u, ws
u, w: [#num_batch, #num_nodes]
u, w: [#num_batch, #num_nodes]
s: [#num_batch, #num_nodes, 2]
s: [#num_batch, #num_nodes, 2]
"""
"""
...
@@ -260,9 +260,14 @@ class Decoder(nn.Module):
...
@@ -260,9 +260,14 @@ class Decoder(nn.Module):
self
.
_last_subtree
=
self
.
subtree_gen
(
self
.
_last_subtree
,
self
.
_last_edge
)
self
.
_last_subtree
=
self
.
subtree_gen
(
self
.
_last_subtree
,
self
.
_last_edge
)
cur_q4u
=
self
.
q_gen
(
self
.
_last_edge
,
self
.
_last_subtree
)
cur_q4u
=
self
.
q_gen
(
self
.
_last_edge
,
self
.
_last_subtree
)
u
,
_
=
self
.
ptm
(
e
,
cur_q4u
,
mask
=
mask_visited
)
u_probs
,
_
=
self
.
ptm
(
e
,
cur_q4u
,
mask
=
mask_visited
)
return
u_probs
cur_q4w
=
self
.
q_gen
(
self
.
_last_edge
,
self
.
_last_subtree
,
u
)
def
get_ws_probs
(
self
,
e
,
E_u
,
mask_visited
=
None
,
mask_unvisited
=
None
):
ws
=
self
.
eptm
(
e
,
cur_q4w
,
mask
=
mask_unvisited
)
"""
@param u: is the node index choiced
"""
cur_q4w
=
self
.
q_gen
(
self
.
_last_edge
,
self
.
_last_subtree
,
E_u
)
ws_probs
=
self
.
eptm
(
e
,
cur_q4w
,
mask
=
mask_unvisited
)
return
u
,
w
s
return
ws_prob
s
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