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fix CI onnxruntime_test_python_sparse_matmul.py (#14039)
### Description
Numpy1.24.0 removed the np.float.
```
/opt/hostedtoolcache/Python/3.8.15/x64/bin/python onnxruntime_test_python_sparse_matmul.py
EE.
======================================================================
ERROR: testRunContribSparseMatMul (__main__.TestSparseToDenseMatmul)
Mutliple sparse COO tensor to dense
----------------------------------------------------------------------
Traceback (most recent call last):
File "onnxruntime_test_python_sparse_matmul.py", line 407, in testRunContribSparseMatMul
np.float,
File "/opt/hostedtoolcache/Python/3.8.15/x64/lib/python3.8/site-packages/numpy/__init__.py", line 284, in __getattr__
raise AttributeError("module {!r} has no attribute "
AttributeError: module 'numpy' has no attribute 'float'
======================================================================
ERROR: testRunSparseOutputOnly (__main__.TestSparseToDenseMatmul)
Try running models using the new run_with_ort_values
----------------------------------------------------------------------
Traceback (most recent call last):
File "onnxruntime_test_python_sparse_matmul.py", line 39, in testRunSparseOutputOnly
values = np.array([1.764052391052246, 0.40015721321105957, 0.978738009929657], np.float)
File "/opt/hostedtoolcache/Python/3.8.15/x64/lib/python3.8/site-packages/numpy/__init__.py", line 284, in __getattr__
raise AttributeError("module {!r} has no attribute "
AttributeError: module 'numpy' has no attribute 'float'
```
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
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1 changed files with 2 additions and 2 deletions
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@ -36,7 +36,7 @@ class TestSparseToDenseMatmul(unittest.TestCase):
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"""
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# The below values are a part of the model
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dense_shape = [3, 3]
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values = np.array([1.764052391052246, 0.40015721321105957, 0.978738009929657], np.float)
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values = np.array([1.764052391052246, 0.40015721321105957, 0.978738009929657], np.float32)
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indices = np.array([2, 3, 5], np.int64)
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sess = onnxrt.InferenceSession(
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get_name("sparse_initializer_as_output.onnx"),
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@ -404,7 +404,7 @@ class TestSparseToDenseMatmul(unittest.TestCase):
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5862,
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6165,
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],
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np.float,
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np.float32,
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).reshape(common_shape)
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sess = onnxrt.InferenceSession(
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