[Relay][PRNG] Support generating data of any shape in threefry_generate by zhuzilin · Pull Request #8085 · apache/tvm

zhuzilin · 2021-05-20T03:53:13Z

This PR adds support for generating data of any shape in threefry_generate.

Thank you for your time on reviewing this pr.

tkonolige

Thanks for the PR! I've left a couple of comments. Also, could you add a test that makes sure the last 3 random number of a size 4*x+3 shape change between calls with different keys?

tkonolige · 2021-05-20T15:45:09Z

+ with irb.if_scope(out_len % 4 != 0):
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len % 4)
+ with irb.else_scope():
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) # increment counter


This is incorrect. It should just be out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) because we used out_len values from the counter.

@tkonolige I changed the increment to out_len % 4 here because I already update the tmp[7] above with:
tmp[7] =tmp[7] +tir.Cast(gen.dtype, out_len//4*4)
The reason for the separate update is that I think we need to update the key before the second threefry.
However, I update the second update from tir.Cast(gen.dtype, out_len % 4) to tir.Cast(gen.dtype, 4), because 4 random numbers are actually generated (though partially discarded).

Oh yeah, you are correct. Could you leave a comment that it was updated earlier.

tkonolige · 2021-05-20T15:47:35Z


 # Compute random values
 _threefry(irb, tmp, 0, tmp, 4, out_array, 0, out_len // 4)
+ with irb.if_scope(out_len % 4 != 0):


This should be if out_len.value % 4 != 0:

zhuzilin · 2021-05-21T02:00:28Z

@tkonolige Thank you for your review~ I've updated the code based on them. Could you take a second look? As for the incorrect part of the update, I have some different opinion, see the comment above.

zhuzilin · 2021-05-24T02:59:12Z

@tkonolige I've added the comment and rebased the code to main branch to fix the shape limit in uniform. Could you take another look? Thank you~

tkonolige

Looks good. Thank you!

zhuzilin · 2021-05-25T01:53:57Z

@tqchen Could you give a help to this PR? Thank you~ 😄

…te (apache#8085)

zhuzilin · 2021-05-20T03:53:13Z

This PR adds support for generating data of any shape in threefry_generate.

Thank you for your time on reviewing this pr.

cc @tkonolige

tkonolige

Thanks for the PR! I've left a couple of comments. Also, could you add a test that makes sure the last 3 random number of a size 4*x+3 shape change between calls with different keys?

tkonolige · 2021-05-20T15:45:09Z

+ with irb.if_scope(out_len % 4 != 0):
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len % 4)
+ with irb.else_scope():
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) # increment counter


This is incorrect. It should just be out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) because we used out_len values from the counter.

@tkonolige I changed the increment to out_len % 4 here because I already update the tmp[7] above with:
tmp[7] =tmp[7] +tir.Cast(gen.dtype, out_len//4*4)
The reason for the separate update is that I think we need to update the key before the second threefry.
However, I update the second update from tir.Cast(gen.dtype, out_len % 4) to tir.Cast(gen.dtype, 4), because 4 random numbers are actually generated (though partially discarded).

Oh yeah, you are correct. Could you leave a comment that it was updated earlier.

tkonolige · 2021-05-20T15:47:35Z


 # Compute random values
 _threefry(irb, tmp, 0, tmp, 4, out_array, 0, out_len // 4)
+ with irb.if_scope(out_len % 4 != 0):


This should be if out_len.value % 4 != 0:

zhuzilin · 2021-05-21T02:00:28Z

@tkonolige Thank you for your review~ I've updated the code based on them. Could you take a second look? As for the incorrect part of the update, I have some different opinion, see the comment above.

zhuzilin · 2021-05-24T02:59:12Z

@tkonolige I've added the comment and rebased the code to main branch to fix the shape limit in uniform. Could you take another look? Thank you~

tkonolige

Looks good. Thank you!

zhuzilin · 2021-05-25T01:53:57Z

@tqchen Could you give a help to this PR? Thank you~ 😄

…te (apache#8085)

zhuzilin · 2021-05-20T03:53:13Z

This PR adds support for generating data of any shape in threefry_generate.

Thank you for your time on reviewing this pr.

cc @tkonolige

tkonolige

Thanks for the PR! I've left a couple of comments. Also, could you add a test that makes sure the last 3 random number of a size 4*x+3 shape change between calls with different keys?

tkonolige · 2021-05-20T15:45:09Z

+ with irb.if_scope(out_len % 4 != 0):
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len % 4)
+ with irb.else_scope():
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) # increment counter


This is incorrect. It should just be out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) because we used out_len values from the counter.

@tkonolige I changed the increment to out_len % 4 here because I already update the tmp[7] above with:
tmp[7] =tmp[7] +tir.Cast(gen.dtype, out_len//4*4)
The reason for the separate update is that I think we need to update the key before the second threefry.
However, I update the second update from tir.Cast(gen.dtype, out_len % 4) to tir.Cast(gen.dtype, 4), because 4 random numbers are actually generated (though partially discarded).

Oh yeah, you are correct. Could you leave a comment that it was updated earlier.

tkonolige · 2021-05-20T15:47:35Z


 # Compute random values
 _threefry(irb, tmp, 0, tmp, 4, out_array, 0, out_len // 4)
+ with irb.if_scope(out_len % 4 != 0):


This should be if out_len.value % 4 != 0:

zhuzilin · 2021-05-21T02:00:28Z

@tkonolige Thank you for your review~ I've updated the code based on them. Could you take a second look? As for the incorrect part of the update, I have some different opinion, see the comment above.

zhuzilin · 2021-05-24T02:59:12Z

@tkonolige I've added the comment and rebased the code to main branch to fix the shape limit in uniform. Could you take another look? Thank you~

tkonolige

Looks good. Thank you!

zhuzilin · 2021-05-25T01:53:57Z

@tqchen Could you give a help to this PR? Thank you~ 😄

…te (apache#8085)

zhuzilin · 2021-05-20T03:53:13Z

This PR adds support for generating data of any shape in threefry_generate.

Thank you for your time on reviewing this pr.

cc @tkonolige

tkonolige

Thanks for the PR! I've left a couple of comments. Also, could you add a test that makes sure the last 3 random number of a size 4*x+3 shape change between calls with different keys?

tkonolige · 2021-05-20T15:45:09Z

+ with irb.if_scope(out_len % 4 != 0):
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len % 4)
+ with irb.else_scope():
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) # increment counter


This is incorrect. It should just be out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) because we used out_len values from the counter.

@tkonolige I changed the increment to out_len % 4 here because I already update the tmp[7] above with:
tmp[7] =tmp[7] +tir.Cast(gen.dtype, out_len//4*4)
The reason for the separate update is that I think we need to update the key before the second threefry.
However, I update the second update from tir.Cast(gen.dtype, out_len % 4) to tir.Cast(gen.dtype, 4), because 4 random numbers are actually generated (though partially discarded).

Oh yeah, you are correct. Could you leave a comment that it was updated earlier.

tkonolige · 2021-05-20T15:47:35Z


 # Compute random values
 _threefry(irb, tmp, 0, tmp, 4, out_array, 0, out_len // 4)
+ with irb.if_scope(out_len % 4 != 0):


This should be if out_len.value % 4 != 0:

zhuzilin · 2021-05-21T02:00:28Z

@tkonolige Thank you for your review~ I've updated the code based on them. Could you take a second look? As for the incorrect part of the update, I have some different opinion, see the comment above.

zhuzilin · 2021-05-24T02:59:12Z

@tkonolige I've added the comment and rebased the code to main branch to fix the shape limit in uniform. Could you take another look? Thank you~

tkonolige

Looks good. Thank you!

zhuzilin · 2021-05-25T01:53:57Z

@tqchen Could you give a help to this PR? Thank you~ 😄

…te (apache#8085)

zhuzilin · 2021-05-20T03:53:13Z

This PR adds support for generating data of any shape in threefry_generate.

Thank you for your time on reviewing this pr.

cc @tkonolige

tkonolige

Thanks for the PR! I've left a couple of comments. Also, could you add a test that makes sure the last 3 random number of a size 4*x+3 shape change between calls with different keys?

tkonolige · 2021-05-20T15:45:09Z

+ with irb.if_scope(out_len % 4 != 0):
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len % 4)
+ with irb.else_scope():
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) # increment counter


This is incorrect. It should just be out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) because we used out_len values from the counter.

@tkonolige I changed the increment to out_len % 4 here because I already update the tmp[7] above with:
tmp[7] =tmp[7] +tir.Cast(gen.dtype, out_len//4*4)
The reason for the separate update is that I think we need to update the key before the second threefry.
However, I update the second update from tir.Cast(gen.dtype, out_len % 4) to tir.Cast(gen.dtype, 4), because 4 random numbers are actually generated (though partially discarded).

Oh yeah, you are correct. Could you leave a comment that it was updated earlier.

tkonolige · 2021-05-20T15:47:35Z


 # Compute random values
 _threefry(irb, tmp, 0, tmp, 4, out_array, 0, out_len // 4)
+ with irb.if_scope(out_len % 4 != 0):


This should be if out_len.value % 4 != 0:

zhuzilin · 2021-05-21T02:00:28Z

@tkonolige Thank you for your review~ I've updated the code based on them. Could you take a second look? As for the incorrect part of the update, I have some different opinion, see the comment above.

zhuzilin · 2021-05-24T02:59:12Z

@tkonolige I've added the comment and rebased the code to main branch to fix the shape limit in uniform. Could you take another look? Thank you~

tkonolige

Looks good. Thank you!

zhuzilin · 2021-05-25T01:53:57Z

@tqchen Could you give a help to this PR? Thank you~ 😄

…te (apache#8085)

zhuzilin · 2021-05-20T03:53:13Z

This PR adds support for generating data of any shape in threefry_generate.

Thank you for your time on reviewing this pr.

cc @tkonolige

tkonolige

Thanks for the PR! I've left a couple of comments. Also, could you add a test that makes sure the last 3 random number of a size 4*x+3 shape change between calls with different keys?

tkonolige · 2021-05-20T15:45:09Z

+ with irb.if_scope(out_len % 4 != 0):
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len % 4)
+ with irb.else_scope():
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) # increment counter


This is incorrect. It should just be out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) because we used out_len values from the counter.

@tkonolige I changed the increment to out_len % 4 here because I already update the tmp[7] above with:
tmp[7] =tmp[7] +tir.Cast(gen.dtype, out_len//4*4)
The reason for the separate update is that I think we need to update the key before the second threefry.
However, I update the second update from tir.Cast(gen.dtype, out_len % 4) to tir.Cast(gen.dtype, 4), because 4 random numbers are actually generated (though partially discarded).

Oh yeah, you are correct. Could you leave a comment that it was updated earlier.

tkonolige · 2021-05-20T15:47:35Z


 # Compute random values
 _threefry(irb, tmp, 0, tmp, 4, out_array, 0, out_len // 4)
+ with irb.if_scope(out_len % 4 != 0):


This should be if out_len.value % 4 != 0:

zhuzilin · 2021-05-21T02:00:28Z

@tkonolige Thank you for your review~ I've updated the code based on them. Could you take a second look? As for the incorrect part of the update, I have some different opinion, see the comment above.

zhuzilin · 2021-05-24T02:59:12Z

@tkonolige I've added the comment and rebased the code to main branch to fix the shape limit in uniform. Could you take another look? Thank you~

tkonolige

Looks good. Thank you!

zhuzilin · 2021-05-25T01:53:57Z

@tqchen Could you give a help to this PR? Thank you~ 😄

…te (apache#8085)

zhuzilin · 2021-05-20T03:53:13Z

This PR adds support for generating data of any shape in threefry_generate.

Thank you for your time on reviewing this pr.

cc @tkonolige

tkonolige

Thanks for the PR! I've left a couple of comments. Also, could you add a test that makes sure the last 3 random number of a size 4*x+3 shape change between calls with different keys?

tkonolige · 2021-05-20T15:45:09Z

+ with irb.if_scope(out_len % 4 != 0):
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len % 4)
+ with irb.else_scope():
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) # increment counter


This is incorrect. It should just be out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) because we used out_len values from the counter.

@tkonolige I changed the increment to out_len % 4 here because I already update the tmp[7] above with:
tmp[7] =tmp[7] +tir.Cast(gen.dtype, out_len//4*4)
The reason for the separate update is that I think we need to update the key before the second threefry.
However, I update the second update from tir.Cast(gen.dtype, out_len % 4) to tir.Cast(gen.dtype, 4), because 4 random numbers are actually generated (though partially discarded).

Oh yeah, you are correct. Could you leave a comment that it was updated earlier.

tkonolige · 2021-05-20T15:47:35Z


 # Compute random values
 _threefry(irb, tmp, 0, tmp, 4, out_array, 0, out_len // 4)
+ with irb.if_scope(out_len % 4 != 0):


This should be if out_len.value % 4 != 0:

zhuzilin · 2021-05-21T02:00:28Z

@tkonolige Thank you for your review~ I've updated the code based on them. Could you take a second look? As for the incorrect part of the update, I have some different opinion, see the comment above.

zhuzilin · 2021-05-24T02:59:12Z

@tkonolige I've added the comment and rebased the code to main branch to fix the shape limit in uniform. Could you take another look? Thank you~

tkonolige

Looks good. Thank you!

zhuzilin · 2021-05-25T01:53:57Z

@tqchen Could you give a help to this PR? Thank you~ 😄

…te (apache#8085)

zhuzilin · 2021-05-20T03:53:13Z

This PR adds support for generating data of any shape in threefry_generate.

Thank you for your time on reviewing this pr.

cc @tkonolige

tkonolige

Thanks for the PR! I've left a couple of comments. Also, could you add a test that makes sure the last 3 random number of a size 4*x+3 shape change between calls with different keys?

tkonolige · 2021-05-20T15:45:09Z

+ with irb.if_scope(out_len % 4 != 0):
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len % 4)
+ with irb.else_scope():
+ out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) # increment counter


This is incorrect. It should just be out_gen[7] = tmp[7] + tir.Cast(gen.dtype, out_len) because we used out_len values from the counter.

@tkonolige I changed the increment to out_len % 4 here because I already update the tmp[7] above with:
tmp[7] =tmp[7] +tir.Cast(gen.dtype, out_len//4*4)
The reason for the separate update is that I think we need to update the key before the second threefry.
However, I update the second update from tir.Cast(gen.dtype, out_len % 4) to tir.Cast(gen.dtype, 4), because 4 random numbers are actually generated (though partially discarded).

Oh yeah, you are correct. Could you leave a comment that it was updated earlier.

tkonolige · 2021-05-20T15:47:35Z


 # Compute random values
 _threefry(irb, tmp, 0, tmp, 4, out_array, 0, out_len // 4)
+ with irb.if_scope(out_len % 4 != 0):


This should be if out_len.value % 4 != 0:

zhuzilin · 2021-05-21T02:00:28Z

@tkonolige Thank you for your review~ I've updated the code based on them. Could you take a second look? As for the incorrect part of the update, I have some different opinion, see the comment above.

zhuzilin · 2021-05-24T02:59:12Z

@tkonolige I've added the comment and rebased the code to main branch to fix the shape limit in uniform. Could you take another look? Thank you~

tkonolige

Looks good. Thank you!

zhuzilin · 2021-05-25T01:53:57Z

@tqchen Could you give a help to this PR? Thank you~ 😄

…te (apache#8085)

tkonolige requested changes May 20, 2021
View reviewed changes

zhuzilin added 3 commits May 24, 2021 10:32

support generating data of any shape in threefry_generate
2e4e457

update upon reviews
4f8548e

update upon review
c0dc062

zhuzilin force-pushed the prng_any_shape branch from 2b094af to c0dc062Compare May 24, 2021 02:54

tkonolige approved these changes May 24, 2021
View reviewed changes

tqchen approved these changes May 25, 2021
View reviewed changes

tqchen merged commit 6f82e98 into apache:mainMay 25, 2021

trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1aacec3
…te (apache#8085)

trevor-m pushed a commit to neo-ai/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1e449de
…te (apache#8085)

tkonolige requested changes May 20, 2021
View reviewed changes

zhuzilin added 3 commits May 24, 2021 10:32

support generating data of any shape in threefry_generate
2e4e457

update upon reviews
4f8548e

update upon review
c0dc062

zhuzilin force-pushed the prng_any_shape branch from 2b094af to c0dc062Compare May 24, 2021 02:54

tkonolige approved these changes May 24, 2021
View reviewed changes

tqchen approved these changes May 25, 2021
View reviewed changes

tqchen merged commit 6f82e98 into apache:mainMay 25, 2021

trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1aacec3
…te (apache#8085)

trevor-m pushed a commit to neo-ai/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1e449de
…te (apache#8085)

tkonolige requested changes May 20, 2021
View reviewed changes

zhuzilin added 3 commits May 24, 2021 10:32

support generating data of any shape in threefry_generate
2e4e457

update upon reviews
4f8548e

update upon review
c0dc062

zhuzilin force-pushed the prng_any_shape branch from 2b094af to c0dc062Compare May 24, 2021 02:54

tkonolige approved these changes May 24, 2021
View reviewed changes

tqchen approved these changes May 25, 2021
View reviewed changes

tqchen merged commit 6f82e98 into apache:mainMay 25, 2021

trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1aacec3
…te (apache#8085)

trevor-m pushed a commit to neo-ai/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1e449de
…te (apache#8085)

tkonolige requested changes May 20, 2021
View reviewed changes

zhuzilin added 3 commits May 24, 2021 10:32

support generating data of any shape in threefry_generate
2e4e457

update upon reviews
4f8548e

update upon review
c0dc062

zhuzilin force-pushed the prng_any_shape branch from 2b094af to c0dc062Compare May 24, 2021 02:54

tkonolige approved these changes May 24, 2021
View reviewed changes

tqchen approved these changes May 25, 2021
View reviewed changes

tqchen merged commit 6f82e98 into apache:mainMay 25, 2021

trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1aacec3
…te (apache#8085)

trevor-m pushed a commit to neo-ai/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1e449de
…te (apache#8085)

tkonolige requested changes May 20, 2021
View reviewed changes

zhuzilin added 3 commits May 24, 2021 10:32

support generating data of any shape in threefry_generate
2e4e457

update upon reviews
4f8548e

update upon review
c0dc062

zhuzilin force-pushed the prng_any_shape branch from 2b094af to c0dc062Compare May 24, 2021 02:54

tkonolige approved these changes May 24, 2021
View reviewed changes

tqchen approved these changes May 25, 2021
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tqchen merged commit 6f82e98 into apache:mainMay 25, 2021

trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1aacec3
…te (apache#8085)

trevor-m pushed a commit to neo-ai/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1e449de
…te (apache#8085)

tkonolige requested changes May 20, 2021
View reviewed changes

zhuzilin added 3 commits May 24, 2021 10:32

support generating data of any shape in threefry_generate
2e4e457

update upon reviews
4f8548e

update upon review
c0dc062

zhuzilin force-pushed the prng_any_shape branch from 2b094af to c0dc062Compare May 24, 2021 02:54

tkonolige approved these changes May 24, 2021
View reviewed changes

tqchen approved these changes May 25, 2021
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tqchen merged commit 6f82e98 into apache:mainMay 25, 2021

trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1aacec3
…te (apache#8085)

trevor-m pushed a commit to neo-ai/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1e449de
…te (apache#8085)

tkonolige requested changes May 20, 2021
View reviewed changes

zhuzilin added 3 commits May 24, 2021 10:32

support generating data of any shape in threefry_generate
2e4e457

update upon reviews
4f8548e

update upon review
c0dc062

zhuzilin force-pushed the prng_any_shape branch from 2b094af to c0dc062Compare May 24, 2021 02:54

tkonolige approved these changes May 24, 2021
View reviewed changes

tqchen approved these changes May 25, 2021
View reviewed changes

tqchen merged commit 6f82e98 into apache:mainMay 25, 2021

trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1aacec3
…te (apache#8085)

trevor-m pushed a commit to neo-ai/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1e449de
…te (apache#8085)

tkonolige requested changes May 20, 2021
View reviewed changes

zhuzilin added 3 commits May 24, 2021 10:32

support generating data of any shape in threefry_generate
2e4e457

update upon reviews
4f8548e

update upon review
c0dc062

zhuzilin force-pushed the prng_any_shape branch from 2b094af to c0dc062Compare May 24, 2021 02:54

tkonolige approved these changes May 24, 2021
View reviewed changes

tqchen approved these changes May 25, 2021
View reviewed changes

tqchen merged commit 6f82e98 into apache:mainMay 25, 2021

trevor-m pushed a commit to trevor-m/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1aacec3
…te (apache#8085)

trevor-m pushed a commit to neo-ai/tvm that referenced this pull request Jun 17, 2021
[Relay][PRNG] Support generating data of any shape in threefry_genera…
1e449de
…te (apache#8085)

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zhuzilin commented May 20, 2021

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zhuzilin commented May 21, 2021

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zhuzilin commented May 24, 2021• edited Loading Uh oh! There was an error while loading. Please reload this page.

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zhuzilin commented May 25, 2021

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zhuzilin commented May 20, 2021

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zhuzilin commented May 24, 2021•
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zhuzilin commented May 24, 2021•
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zhuzilin commented May 24, 2021•
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