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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2020/12/17 20:58:18 UTC
[GitHub] [incubator-mxnet] waytrue17 opened a new pull request #19691: [WIP] ONNX fix softmax
waytrue17 opened a new pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691
## Description ##
Fix onnx softmax to support `use_length`.
Add test case.
## Checklist ##
### Essentials ###
- [ ] PR's title starts with a category (e.g. [BUGFIX], [MODEL], [TUTORIAL], [FEATURE], [DOC], etc)
- [ ] Changes are complete (i.e. I finished coding on this PR)
- [ ] All changes have test coverage
- [ ] Code is well-documented
### Changes ###
- [ ] Feature1, tests, (and when applicable, API doc)
- [ ] Feature2, tests, (and when applicable, API doc)
## Comments ##
- If this change is a backward incompatible change, why must this change be made.
- Interesting edge cases to note here
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[GitHub] [incubator-mxnet] waytrue17 commented on a change in pull request #19691: [WIP] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
waytrue17 commented on a change in pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#discussion_r545408064
##########
File path: tests/python-pytest/onnx/test_operators.py
##########
@@ -205,3 +206,15 @@ def test_onnx_export_fully_connected(tmp_path, dtype, num_hidden, no_bias, flatt
if not no_bias:
args.append(mx.nd.random.uniform(0,1,(num_hidden,)))
op_export_test('FullyConnected', M, args, tmp_path)
+
+@pytest.mark.parametrize('dtype', ['float32', 'float64'])
+def test_onnx_export_softmax(tmp_path, dtype):
+ x = mx.nd.random.uniform(0, 1, (2, 3, 4), dtype=dtype)
+ M1 = def_model('softmax')
+ op_export_test('softmax_1', M1, [x], tmp_path)
+ M2 = def_model('softmax', use_length=True, axis=0)
+ l2 = mx.nd.array([[2,0,3,1],[1,3,2,0], [0,0,0,1]], dtype=int)
Review comment:
`l2` and `l3` are intentionally generated to test certain cases e.g. [0,0,0,1] and [0,0,0]. I think it should be fine as `x` is randomly generated.
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[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #19691: [WIP] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
mxnet-bot commented on pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#issuecomment-747697904
Hey @waytrue17 , Thanks for submitting the PR
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[GitHub] [incubator-mxnet] Zha0q1 merged pull request #19691: [v1.x] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
Zha0q1 merged pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691
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[GitHub] [incubator-mxnet] waytrue17 commented on pull request #19691: [v1.x] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
waytrue17 commented on pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#issuecomment-748526235
@mxnet-bot run ci [unix-gpu, unix-gpu-cu110]
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[GitHub] [incubator-mxnet] waytrue17 commented on a change in pull request #19691: [v1.x] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
waytrue17 commented on a change in pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#discussion_r545532939
##########
File path: tests/python-pytest/onnx/test_operators.py
##########
@@ -253,3 +254,16 @@ def test_onnx_export_dropout(tmp_path, dtype, p):
M = def_model('Dropout', p=p)
x = mx.nd.array([[3,0.5,-0.5,2,7],[2,-0.4,7,3,0.2]], dtype=dtype)
op_export_test('Dropout', M, [x], tmp_path)
+
+@pytest.mark.parametrize('dtype', ['float16', 'float32'])
+def test_onnx_export_softmax(tmp_path, dtype):
+ x = mx.nd.random.uniform(0, 1, (2, 3, 4), dtype=dtype)
Review comment:
added more tests for temperature and axis
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[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #19691: [v1.x] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
Zha0q1 commented on a change in pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#discussion_r545525290
##########
File path: tests/python-pytest/onnx/test_operators.py
##########
@@ -253,3 +254,16 @@ def test_onnx_export_dropout(tmp_path, dtype, p):
M = def_model('Dropout', p=p)
x = mx.nd.array([[3,0.5,-0.5,2,7],[2,-0.4,7,3,0.2]], dtype=dtype)
op_export_test('Dropout', M, [x], tmp_path)
+
+@pytest.mark.parametrize('dtype', ['float16', 'float32'])
+def test_onnx_export_softmax(tmp_path, dtype):
+ x = mx.nd.random.uniform(0, 1, (2, 3, 4), dtype=dtype)
Review comment:
sorry about nitpicking: shall we also test high dimensional + axis = middle dim cases?
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[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #19691: [WIP] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
Zha0q1 commented on a change in pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#discussion_r545430693
##########
File path: tests/python-pytest/onnx/test_operators.py
##########
@@ -205,3 +206,15 @@ def test_onnx_export_fully_connected(tmp_path, dtype, num_hidden, no_bias, flatt
if not no_bias:
args.append(mx.nd.random.uniform(0,1,(num_hidden,)))
op_export_test('FullyConnected', M, args, tmp_path)
+
+@pytest.mark.parametrize('dtype', ['float32', 'float64'])
+def test_onnx_export_softmax(tmp_path, dtype):
+ x = mx.nd.random.uniform(0, 1, (2, 3, 4), dtype=dtype)
+ M1 = def_model('softmax')
+ op_export_test('softmax_1', M1, [x], tmp_path)
+ M2 = def_model('softmax', use_length=True, axis=0)
+ l2 = mx.nd.array([[2,0,3,1],[1,3,2,0], [0,0,0,1]], dtype=int)
Review comment:
gotcha
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[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #19691: [v1.x] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
Zha0q1 commented on a change in pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#discussion_r545525529
##########
File path: tests/python-pytest/onnx/test_operators.py
##########
@@ -253,3 +254,16 @@ def test_onnx_export_dropout(tmp_path, dtype, p):
M = def_model('Dropout', p=p)
x = mx.nd.array([[3,0.5,-0.5,2,7],[2,-0.4,7,3,0.2]], dtype=dtype)
op_export_test('Dropout', M, [x], tmp_path)
+
+@pytest.mark.parametrize('dtype', ['float16', 'float32'])
+def test_onnx_export_softmax(tmp_path, dtype):
+ x = mx.nd.random.uniform(0, 1, (2, 3, 4), dtype=dtype)
Review comment:
We might also parametrize temperature?
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[GitHub] [incubator-mxnet] Zha0q1 commented on pull request #19691: [v1.x] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
Zha0q1 commented on pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#issuecomment-748558599
Thanks!
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[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #19691: [WIP] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
Zha0q1 commented on a change in pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#discussion_r545405721
##########
File path: tests/python-pytest/onnx/test_operators.py
##########
@@ -205,3 +206,15 @@ def test_onnx_export_fully_connected(tmp_path, dtype, num_hidden, no_bias, flatt
if not no_bias:
args.append(mx.nd.random.uniform(0,1,(num_hidden,)))
op_export_test('FullyConnected', M, args, tmp_path)
+
+@pytest.mark.parametrize('dtype', ['float32', 'float64'])
+def test_onnx_export_softmax(tmp_path, dtype):
+ x = mx.nd.random.uniform(0, 1, (2, 3, 4), dtype=dtype)
+ M1 = def_model('softmax')
+ op_export_test('softmax_1', M1, [x], tmp_path)
+ M2 = def_model('softmax', use_length=True, axis=0)
+ l2 = mx.nd.array([[2,0,3,1],[1,3,2,0], [0,0,0,1]], dtype=int)
Review comment:
Shall we also use randomized inputs here?
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[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #19691: [v1.x] ONNX fix softmax
Posted by GitBox <gi...@apache.org>.
mxnet-bot commented on pull request #19691:
URL: https://github.com/apache/incubator-mxnet/pull/19691#issuecomment-748526247
Jenkins CI successfully triggered : [unix-gpu]
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