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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2020/07/14 06:00:54 UTC
[GitHub] [incubator-mxnet] wkcn opened a new pull request #18707: Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
wkcn opened a new pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707
## Description ##
Fix #18695
Hi there, this PR supports the intput whose dimension is greater than 6 for Transpose and Rollaxis.
## Checklist ##
### Essentials ###
Please feel free to remove inapplicable items for your PR.
- [ ] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) created (except PRs with tiny changes)
- [ ] Changes are complete (i.e. I finished coding on this PR)
- [ ] All changes have test coverage:
- Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
- Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore)
- Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL)
- [ ] Code is well-documented:
- For user-facing API changes, API doc string has been updated.
- For new C++ functions in header files, their functionalities and arguments are documented.
- For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable
- Check the API doc at https://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
- [ ] To the best of my knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change
### Changes ###
- [x] Add a new function named `TransposeExImpl` to support inputs with 6+ dimenstions for transpose and rollaxis.
- [x] Add the attribute `FResourceRequest` for the extra workspace to store the argument `axes`
- [x] Update the unittest for transpose(in mx.nd and mx.np) and rollaxis in mx.np.
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[GitHub] [incubator-mxnet] wkcn edited a comment on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
wkcn edited a comment on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659304799
Performance Benchmark:
transpose operator on CPU, **axes is generated randomly**
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.0786
2|12582.9121|1.0851
3|12582.9121|0.6763
4|12582.9121|1.2172
5|12582.9121|6.4305
6|12582.9121|11.7841
7|12583.3604|65.7184
8|12583.4238|65.2171
9|12583.4883|82.4930
The increase of memory footprint is slight, but the time is intolerable when `axes.ndim() > 6`.
If **axes is monotonically increasing** (namely [0, 1, 2, 3, ..., ndim - 1]) (comment the line 21st `random.shuffle(axes)`),
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.1492
2|12582.9121|1.1732
3|12582.9121|1.3264
4|12582.9121|1.3896
5|12582.9121|0.9107
6|12582.9121|0.8965
7|12583.3604|0.9028
8|12583.4238|0.9105
9|12583.4883|0.8981
Test Code:
```python
import mxnet as mx
from mxnet import profiler
print(mx)
import numpy as np
from numpy.testing import assert_allclose
import time
import random
seed = 42
np.random.seed(seed)
mx.random.seed(seed)
#configure the profiler
profiler.set_config(profile_all=True, aggregate_stats=True, filename='trace_profile.json')
#start the profiler collecting data
def test_transpose(ndim):
for t in range(20):
dims = [4 for _ in range(ndim)]
dims[-1] *= 4 ** (10 - ndim)
axes = list(range(ndim))
random.shuffle(axes)
axes = tuple(axes)
x = mx.nd.array(np.random.normal(size=dims))
y = mx.nd.transpose(x, axes=axes)
assert_allclose(np.transpose(x.asnumpy(), axes=axes), y.asnumpy())
for ndim in range(1, 10):
profiler.set_state('run')
tic = time.time()
test_transpose(ndim)
print(ndim, "====", time.time() - tic)
#stop the profiler
profiler.set_state('stop')
#dump the profiling data as a string
print(profiler.dumps(reset=True))
print("Over")
```
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[GitHub] [incubator-mxnet] wkcn commented on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
wkcn commented on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659304799
Performance Benchmark:
transpose operator on CPU, axes is generated randomly
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.0786
2|12582.9121|1.0851
3|12582.9121|0.6763
4|12582.9121|1.2172
5|12582.9121|6.4305
6|12582.9121|11.7841
7|12583.3604|65.7184
8|12583.4238|65.2171
9|12583.4883|82.4930
The increase of memory footprint is slight, but the time is intolerable when `axes.ndim() > 6`. I will try to optimize it.
Test Code:
```python
import mxnet as mx
from mxnet import profiler
print(mx)
import numpy as np
from numpy.testing import assert_allclose
import time
import random
seed = 42
np.random.seed(seed)
mx.random.seed(seed)
#configure the profiler
profiler.set_config(profile_all=True, aggregate_stats=True, filename='trace_profile.json')
#start the profiler collecting data
def test_transpose(ndim):
for t in range(20):
dims = [4 for _ in range(ndim)]
dims[-1] *= 4 ** (10 - ndim)
axes = list(range(ndim))
random.shuffle(axes)
axes = tuple(axes)
x = mx.nd.array(np.random.normal(size=dims))
y = mx.nd.transpose(x, axes=axes)
assert_allclose(np.transpose(x.asnumpy(), axes=axes), y.asnumpy())
for ndim in range(1, 10):
profiler.set_state('run')
tic = time.time()
test_transpose(ndim)
print(ndim, "====", time.time() - tic)
#stop the profiler
profiler.set_state('stop')
#dump the profiling data as a string
print(profiler.dumps(reset=True))
print("Over")
```
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[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18707: Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
mxnet-bot commented on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-657985408
Hey @wkcn , Thanks for submitting the PR
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[GitHub] [incubator-mxnet] wkcn edited a comment on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
wkcn edited a comment on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659304799
Performance Benchmark:
transpose operator on CPU, axes is generated randomly
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.0786
2|12582.9121|1.0851
3|12582.9121|0.6763
4|12582.9121|1.2172
5|12582.9121|6.4305
6|12582.9121|11.7841
7|12583.3604|65.7184
8|12583.4238|65.2171
9|12583.4883|82.4930
The increase of memory footprint is slight, but the time is intolerable when `axes.ndim() > 6`. I will try to optimize it.
If axes is monotonically increasing (namely [0, 1, 2, 3, ..., ndim - 1]) (comment the line 21st `random.shuffle(axes)`),
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.1492
2|12582.9121|1.1732
3|12582.9121|1.3264
4|12582.9121|1.3896
5|12582.9121|0.9107
6|12582.9121|0.8965
7|12583.3604|0.9028
8|12583.4238|0.9105
9|12583.4883|0.8981
Test Code:
```python
import mxnet as mx
from mxnet import profiler
print(mx)
import numpy as np
from numpy.testing import assert_allclose
import time
import random
seed = 42
np.random.seed(seed)
mx.random.seed(seed)
#configure the profiler
profiler.set_config(profile_all=True, aggregate_stats=True, filename='trace_profile.json')
#start the profiler collecting data
def test_transpose(ndim):
for t in range(20):
dims = [4 for _ in range(ndim)]
dims[-1] *= 4 ** (10 - ndim)
axes = list(range(ndim))
random.shuffle(axes)
axes = tuple(axes)
x = mx.nd.array(np.random.normal(size=dims))
y = mx.nd.transpose(x, axes=axes)
assert_allclose(np.transpose(x.asnumpy(), axes=axes), y.asnumpy())
for ndim in range(1, 10):
profiler.set_state('run')
tic = time.time()
test_transpose(ndim)
print(ndim, "====", time.time() - tic)
#stop the profiler
profiler.set_state('stop')
#dump the profiling data as a string
print(profiler.dumps(reset=True))
print("Over")
```
----------------------------------------------------------------
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[GitHub] [incubator-mxnet] wkcn edited a comment on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
wkcn edited a comment on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659304799
Performance Benchmark:
transpose operator on CPU, axes is generated randomly
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.0786
2|12582.9121|1.0851
3|12582.9121|0.6763
4|12582.9121|1.2172
5|12582.9121|6.4305
6|12582.9121|11.7841
7|12583.3604|65.7184
8|12583.4238|65.2171
9|12583.4883|82.4930
The increase of memory footprint is slight, but the time is intolerable when `axes.ndim() > 6`. I will try to optimize it.
If axes is monotonically increasing (namely [0, 1, 2, 3, ..., ndim - 1]),
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.1492
2|12582.9121|1.1732
3|12582.9121|1.3264
4|12582.9121|1.3896
5|12582.9121|0.9107
6|12582.9121|0.8965
7|12583.3604|0.9028
8|12583.4238|0.9105
9|12583.4883|0.8981
Test Code:
```python
import mxnet as mx
from mxnet import profiler
print(mx)
import numpy as np
from numpy.testing import assert_allclose
import time
import random
seed = 42
np.random.seed(seed)
mx.random.seed(seed)
#configure the profiler
profiler.set_config(profile_all=True, aggregate_stats=True, filename='trace_profile.json')
#start the profiler collecting data
def test_transpose(ndim):
for t in range(20):
dims = [4 for _ in range(ndim)]
dims[-1] *= 4 ** (10 - ndim)
axes = list(range(ndim))
random.shuffle(axes)
axes = tuple(axes)
x = mx.nd.array(np.random.normal(size=dims))
y = mx.nd.transpose(x, axes=axes)
assert_allclose(np.transpose(x.asnumpy(), axes=axes), y.asnumpy())
for ndim in range(1, 10):
profiler.set_state('run')
tic = time.time()
test_transpose(ndim)
print(ndim, "====", time.time() - tic)
#stop the profiler
profiler.set_state('stop')
#dump the profiling data as a string
print(profiler.dumps(reset=True))
print("Over")
```
----------------------------------------------------------------
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[GitHub] [incubator-mxnet] wkcn edited a comment on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
wkcn edited a comment on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659304799
Performance Benchmark:
transpose operator on CPU, **axes is generated randomly**
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.0786
2|12582.9121|1.0851
3|12582.9121|0.6763
4|12582.9121|1.2172
5|12582.9121|6.4305
6|12582.9121|11.7841
7|12583.3604|65.7184
8|12583.4238|65.2171
9|12583.4883|82.4930
The increase of memory footprint is slight, but the time is intolerable when `axes.ndim() > 6`.
If **axes is monotonically increasing** (namely [0, 1, 2, 3, ..., ndim - 1]) (comment the line 21st `random.shuffle(axes)`),
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.1492
2|12582.9121|1.1732
3|12582.9121|1.3264
4|12582.9121|1.3896
5|12582.9121|0.9107
6|12582.9121|0.8965
7|12583.3604|0.9028
8|12583.4238|0.9105
9|12583.4883|0.8981
If **axes is monotonically decreasing** (namely [ndim - 1, ndim -2, ..., 2, 1, 0])
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.1290
2|12582.9121|1.1204
3|12582.9121|1.1874
4|12582.9121|1.4240
5|12582.9121|7.7080
6|12582.9121|24.0448
7|12583.3604|115.1126
8|12583.4238|105.9091
9|12583.4883|106.3913
Compare with NumPy Transpose:
ndim | numpy time (s) | mxnet time (s)
--|--|--
1 | 0.1621077060699463 | 0.31803297996520996
2 | 0.2637207508087158 | 0.33347415924072266
3 | 0.4311816692352295 | 0.47667574882507324
4 | 0.5303101539611816 | 0.49021244049072266
5 | 0.5940566062927246 | 1.48443603515625
6 | 0.8220541477203369 | 2.03752064704895
7 | 0.8727006912231445 | 9.488046169281006
8 | 1.0004301071166992 | 9.947605848312378
9 | 1.2341070175170898 | 12.262272119522095
Test Code:
```python
import mxnet as mx
from mxnet import profiler
print(mx)
import numpy as np
from numpy.testing import assert_allclose
import time
import random
seed = 42
np.random.seed(seed)
mx.random.seed(seed)
#configure the profiler
profiler.set_config(profile_all=True, aggregate_stats=True, filename='trace_profile.json')
#start the profiler collecting data
def test_transpose(ndim):
for t in range(20):
dims = [4 for _ in range(ndim)]
dims[-1] *= 4 ** (10 - ndim)
axes = list(range(ndim))
random.shuffle(axes)
axes = tuple(axes)
x = mx.nd.array(np.random.normal(size=dims))
y = mx.nd.transpose(x, axes=axes)
assert_allclose(np.transpose(x.asnumpy(), axes=axes), y.asnumpy())
for ndim in range(1, 10):
profiler.set_state('run')
tic = time.time()
test_transpose(ndim)
print(ndim, "====", time.time() - tic)
#stop the profiler
profiler.set_state('stop')
#dump the profiling data as a string
print(profiler.dumps(reset=True))
print("Over")
```
Test Code, compare with NumPy
```python
import mxnet as mx
from mxnet import profiler
print(mx)
import numpy as np
from numpy.testing import assert_allclose
import time
import random
seed = 42
np.random.seed(seed)
mx.random.seed(seed)
def test_transpose(ndim):
np_time = 0
mx_time = 0
for t in range(20):
dims = [5 for _ in range(ndim)]
dims[-1] *= 5 ** (10 - ndim)
axes = list(range(ndim))
random.shuffle(axes)
axes = tuple(axes)
x_np = np.array(np.random.normal(size=dims), dtype=np.float32)
x_mx = mx.nd.array(x_np, dtype=np.float32)
for _ in range(2):
y_np = np.transpose(x_np, axes=axes).copy()
y_mx = mx.nd.transpose(x_mx, axes=axes)
y_mx.asnumpy()
tic_np = time.time()
for _ in range(1):
y_np = np.transpose(x_np, axes=axes).copy()
np_time += time.time() - tic_np
tic_mx = time.time()
for _ in range(1):
y_mx = mx.nd.transpose(x_mx, axes=axes)
y_mx.asnumpy()
mx_time += time.time() - tic_mx
print(f"{ndim} | {np_time} | {mx_time}")
for ndim in range(1, 10):
test_transpose(ndim)
print("Over")
```
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[GitHub] [incubator-mxnet] szha commented on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
szha commented on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659556617
the comparison with numpy is unfair in that numpy just sets strides and doesn't have to be c contiguous.
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[GitHub] [incubator-mxnet] szha merged pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
szha merged pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707
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[GitHub] [incubator-mxnet] wkcn commented on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
wkcn commented on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659732747
@szha
In numpy, the output of np.transpose is not contiguous, but the copied ndarray is contiguous.
We compute each position of tranpose's output individually, but numpy computes them in blocks.
There is still an improvement space.
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[GitHub] [incubator-mxnet] wkcn edited a comment on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
wkcn edited a comment on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659304799
Performance Benchmark:
transpose operator on CPU, **axes is generated randomly**
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.0786
2|12582.9121|1.0851
3|12582.9121|0.6763
4|12582.9121|1.2172
5|12582.9121|6.4305
6|12582.9121|11.7841
7|12583.3604|65.7184
8|12583.4238|65.2171
9|12583.4883|82.4930
The increase of memory footprint is slight, but the time is intolerable when `axes.ndim() > 6`.
If **axes is monotonically increasing** (namely [0, 1, 2, 3, ..., ndim - 1]) (comment the line 21st `random.shuffle(axes)`),
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.1492
2|12582.9121|1.1732
3|12582.9121|1.3264
4|12582.9121|1.3896
5|12582.9121|0.9107
6|12582.9121|0.8965
7|12583.3604|0.9028
8|12583.4238|0.9105
9|12583.4883|0.8981
If **axes is monotonically decreasing** (namely [ndim - 1, ndim -2, ..., 2, 1, 0])
ndim | max use (kb) | avg time (ms)
---|---|--
1|12582.9121|1.1290
2|12582.9121|1.1204
3|12582.9121|1.1874
4|12582.9121|1.4240
5|12582.9121|7.7080
6|12582.9121|24.0448
7|12583.3604|115.1126
8|12583.4238|105.9091
9|12583.4883|106.3913
Test Code:
```python
import mxnet as mx
from mxnet import profiler
print(mx)
import numpy as np
from numpy.testing import assert_allclose
import time
import random
seed = 42
np.random.seed(seed)
mx.random.seed(seed)
#configure the profiler
profiler.set_config(profile_all=True, aggregate_stats=True, filename='trace_profile.json')
#start the profiler collecting data
def test_transpose(ndim):
for t in range(20):
dims = [4 for _ in range(ndim)]
dims[-1] *= 4 ** (10 - ndim)
axes = list(range(ndim))
random.shuffle(axes)
axes = tuple(axes)
x = mx.nd.array(np.random.normal(size=dims))
y = mx.nd.transpose(x, axes=axes)
assert_allclose(np.transpose(x.asnumpy(), axes=axes), y.asnumpy())
for ndim in range(1, 10):
profiler.set_state('run')
tic = time.time()
test_transpose(ndim)
print(ndim, "====", time.time() - tic)
#stop the profiler
profiler.set_state('stop')
#dump the profiling data as a string
print(profiler.dumps(reset=True))
print("Over")
```
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[GitHub] [incubator-mxnet] szha commented on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
szha commented on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659144361
how's the speed and memory consumption before and after the change? you can try [this](https://github.com/apache/incubator-mxnet/blob/master/benchmark/opperf/README.md#usecase-3---run-benchmarks-for-specific-operator) for speed benchmark and the [memory profiler](https://mxnet.apache.org/api/dev-guide/profiling) for memory consumption.
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[GitHub] [incubator-mxnet] wkcn commented on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis
Posted by GitBox <gi...@apache.org>.
wkcn commented on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659286009
@szha Thank you for the suggestion!
When axes.ndim() <= 6, it will call the original function `TransposeImpl`. `TransposeImpl` does not allocate any workspace, and its speed is consistent with the original `transpose`.
I will use the profiler on `transpose` and `rollaxis` to test `axes.ndim() <= 6 and axes.ndim() > 6`.
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