[draft] Xiaowu/fix bug(embedding bag) #1099
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Codecov ReportAttention:
Additional details and impacted files@@ Coverage Diff @@
## main #1099 +/- ##
===========================================
- Coverage 78.55% 56.93% -21.63%
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Files 118 106 -12
Lines 15154 12752 -2402
Branches 1620 1331 -289
===========================================
- Hits 11904 7260 -4644
- Misses 2872 5189 +2317
+ Partials 378 303 -75 ☔ View full report in Codecov by Sentry. |
Test Results 18 files ± 0 18 suites ±0 26m 13s ⏱️ - 37m 32s For more details on these errors, see this check. Results for commit 95a24dd. ± Comparison against base commit 10f9a1f. This pull request removes 3639 and adds 2403 tests. Note that renamed tests count towards both.This pull request removes 1409 skipped tests and adds 459 skipped tests. Note that renamed tests count towards both.♻️ This comment has been updated with latest results. |
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| print(max_indices) | ||
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| def test_embedding_bag_aten(): | ||
| import torch as t |
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PYLINT/C0415 Note
| print(max_indices) | ||
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| def test_embedding_bag_nn_function(): | ||
| import torch as t |
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PYLINT/C0415 Note
| [-4.2188, -4.2266, -2.7246, -6.8555, -7.6719]], dtype=t.float16) | ||
| indices = t.tensor([4, 9, 3, 0, 3], dtype=t.int64) | ||
| offsets = t.tensor([0, 3], dtype=t.int64) | ||
| mode = 0 # sum |
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PYLINT/W0612 Warning
| [-4.2188, -4.2266, -2.7246, -6.8555, -7.6719]], dtype=t.float16) | ||
| indices = t.tensor([4, 9, 3, 0, 3], dtype=t.int64) | ||
| offsets = t.tensor([0, 3], dtype=t.int64) | ||
| mode = 0 # sum |
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Code scanning / lintrunner
RUFF/F841 Warning
| [-4.2188, -4.2266, -2.7246, -6.8555, -7.6719]], dtype=t.float16) | ||
| indices = t.tensor([4, 9, 3, 0, 3], dtype=t.int64) | ||
| offsets = t.tensor([0, 3], dtype=t.int64) | ||
| mode = 0 # sum |
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Code scanning / CodeQL
Unused local variable
| @@ -3046,6 +3046,104 @@ | |||
| return result, offset2bag, bag_size, max_indices | |||
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| def test_embedding_bag_onnx(): | |||
| import numpy as np | |||
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PYLINT/C0415 Note
| # include_last_offset = True | ||
| per_sample_weights = np.array([2.4134, -0.1783, 7.1360, -0.7987, 2.3815], dtype=np.float16) | ||
| #per_sample_weights = np.array([-2.2930, 6.2148, 3.1562, 0.0791, 6.3555], dtype=np.float16) | ||
| result1, offset2bag, bag_size, max_indices = aten_embedding_bag(weight, indices, offsets, mode=mode, per_sample_weights=per_sample_weights) |
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PYLINT/W0612 Warning
| # include_last_offset = True | ||
| per_sample_weights = np.array([2.4134, -0.1783, 7.1360, -0.7987, 2.3815], dtype=np.float16) | ||
| #per_sample_weights = np.array([-2.2930, 6.2148, 3.1562, 0.0791, 6.3555], dtype=np.float16) | ||
| result1, offset2bag, bag_size, max_indices = aten_embedding_bag(weight, indices, offsets, mode=mode, per_sample_weights=per_sample_weights) |
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Code scanning / lintrunner
PYLINT/W0612 Warning
| # include_last_offset = True | ||
| per_sample_weights = np.array([2.4134, -0.1783, 7.1360, -0.7987, 2.3815], dtype=np.float16) | ||
| #per_sample_weights = np.array([-2.2930, 6.2148, 3.1562, 0.0791, 6.3555], dtype=np.float16) | ||
| result1, offset2bag, bag_size, max_indices = aten_embedding_bag(weight, indices, offsets, mode=mode, per_sample_weights=per_sample_weights) |
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Code scanning / lintrunner
PYLINT/W0612 Warning
| #test_embedding_bag_aten() | ||
| #test_embedding_bag_nn_function() | ||
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| exit(0) |
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PYLINT/R1722 Note
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from #1056 this, copy sample=7 data
we can got same result from test_embedding_bag_onnx() and test_embedding_bag_aten().
result from onnx-script:
result from aten: