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Rename use_mkldnn to use_onednn in test cases - part4 #73904

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Jul 9, 2025
Merged

Rename use_mkldnn to use_onednn in test cases - part4 #73904

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44a352a
Fix
co63oc Jul 8, 2025
b193166
ci
co63oc Jul 9, 2025
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38 changes: 19 additions & 19 deletions test/mkldnn/test_reduce_bf16_mkldnn_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,12 +32,12 @@
class TestReduceSumDefaultBF16OneDNNOp(OpTest):
def setUp(self):
self.op_type = "reduce_sum"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.random((5, 6, 10)).astype("float32")
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.outputs = {'Out': self.x_fp32.sum(axis=0)}
self.attrs = {'use_mkldnn': self.use_mkldnn}
self.attrs = {'use_mkldnn': self.use_onednn}

def test_check_output(self):
self.check_output(
Expand Down Expand Up @@ -96,11 +96,11 @@ class TestReduceSum4DReduceAllDimAttributeBF16OneDNNOp(
):
def setUp(self):
self.op_type = "reduce_sum"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.normal(size=(2, 3, 5, 6)).astype('float32')
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.attrs = {'use_mkldnn': self.use_mkldnn, 'dim': [0, 1, 2, 3]}
self.attrs = {'use_mkldnn': self.use_onednn, 'dim': [0, 1, 2, 3]}
self.outputs = {'Out': self.x_fp32.sum(axis=tuple(self.attrs['dim']))}


Expand All @@ -109,11 +109,11 @@ class TestReduceSum4DReduceAllWithoutReduceAllAttributeNegativeDimsBF16OneDNNOp(
):
def setUp(self):
self.op_type = "reduce_sum"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.normal(size=(4, 7, 6, 6)).astype('float32')
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.attrs = {'use_mkldnn': self.use_mkldnn, 'dim': [-1, -2, -3, -4]}
self.attrs = {'use_mkldnn': self.use_onednn, 'dim': [-1, -2, -3, -4]}
self.outputs = {'Out': self.x_fp32.sum(axis=tuple(self.attrs['dim']))}


Expand All @@ -122,7 +122,7 @@ class TestReduceSum5DReduceAllKeepDimsBF16OneDNNOp(
):
def setUp(self):
self.op_type = "reduce_sum"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.normal(size=(2, 5, 3, 2, 5)).astype('float32')
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
Expand All @@ -135,11 +135,11 @@ class TestReduceSum4DReduceAllBF16OneDNNOp(
):
def setUp(self):
self.op_type = "reduce_sum"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.normal(size=(4, 5, 4, 5)).astype('float32')
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.attrs = {'reduce_all': True, 'use_mkldnn': self.use_mkldnn}
self.attrs = {'reduce_all': True, 'use_mkldnn': self.use_onednn}
self.outputs = {'Out': self.x_fp32.sum()}


Expand All @@ -152,11 +152,11 @@ class TestReduceMax3DBF16OneDNNOp(TestReduceSumDefaultBF16OneDNNOp):

def setUp(self):
self.op_type = "reduce_max"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.random((5, 6, 10)).astype("float32")
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.attrs = {'dim': [-1], 'use_mkldnn': self.use_mkldnn}
self.attrs = {'dim': [-1], 'use_mkldnn': self.use_onednn}
self.outputs = {'Out': self.x_fp32.max(axis=tuple(self.attrs['dim']))}


Expand All @@ -171,11 +171,11 @@ class TestReduceMax4DNegativeAndPositiveDimsBF16OneDNNOp(

def setUp(self):
self.op_type = "reduce_max"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.random((5, 6, 10, 9)).astype("float32")
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.attrs = {'dim': [-1, 0, 1], 'use_mkldnn': self.use_mkldnn}
self.attrs = {'dim': [-1, 0, 1], 'use_mkldnn': self.use_onednn}
self.outputs = {'Out': self.x_fp32.max(axis=tuple(self.attrs['dim']))}


Expand All @@ -188,33 +188,33 @@ class TestReduceMin3DBF16OneDNNOp(TestReduceSumDefaultBF16OneDNNOp):

def setUp(self):
self.op_type = "reduce_min"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.random((5, 6, 10)).astype("float32")
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.attrs = {'dim': [2], 'use_mkldnn': self.use_mkldnn}
self.attrs = {'dim': [2], 'use_mkldnn': self.use_onednn}
self.outputs = {'Out': self.x_fp32.min(axis=tuple(self.attrs['dim']))}


class TestReduceMean3DBF16OneDNNOp(TestReduceDefaultWithGradBF16OneDNNOp):
def setUp(self):
self.op_type = "reduce_mean"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.random((5, 6, 10)).astype("float32")
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.attrs = {'use_mkldnn': self.use_mkldnn}
self.attrs = {'use_mkldnn': self.use_onednn}
self.outputs = {'Out': self.x_fp32.sum(axis=0) / self.x_fp32.shape[0]}


class TestReduceMean4DBF16OneDNNOp(TestReduceDefaultWithGradBF16OneDNNOp):
def setUp(self):
self.op_type = "reduce_mean"
self.use_mkldnn = True
self.use_onednn = True
self.x_fp32 = np.random.random((5, 6, 3, 5)).astype("float32")
self.x_bf16 = convert_float_to_uint16(self.x_fp32)
self.inputs = {'X': self.x_bf16}
self.attrs = {'use_mkldnn': self.use_mkldnn, 'dim': [0, 1]}
self.attrs = {'use_mkldnn': self.use_onednn, 'dim': [0, 1]}
self.outputs = {
'Out': self.x_fp32.sum(axis=tuple(self.attrs['dim']))
/ (self.x_fp32.shape[0] * self.x_fp32.shape[1])
Expand Down
8 changes: 4 additions & 4 deletions test/mkldnn/test_reshape_bf16_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,16 +27,16 @@
class TestReshapeBf16Op(OpTest):
def setUp(self):
self.op_type = "reshape2"
self.use_mkldnn = False
self.mkldnn_data_type = "bfloat16"
self.use_onednn = False
self.onednn_data_type = "bfloat16"
self.init_data()
self.init_input_data()

self.inputs = {'X': self.input_data}
self.attrs = {
'shape': self.new_shape,
'use_mkldnn': self.use_mkldnn,
'mkldnn_data_type': self.mkldnn_data_type,
'use_mkldnn': self.use_onednn,
'mkldnn_data_type': self.onednn_data_type,
}
self.outputs = {
"Out": self.inputs["X"].reshape(self.inferred_shape),
Expand Down
4 changes: 2 additions & 2 deletions test/mkldnn/test_scale_bf16_mkldnn_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ def setUp(self):
self.scale = -2.3
self.inputs = {'X': self.x_bf16}
self.attrs = {'scale': self.scale, 'use_mkldnn': True, 'bias': 0.4}
self.use_mkldnn = True
self.use_onednn = True
self.outputs = {
'Out': (self.x_fp32 * self.attrs['scale']) + self.attrs['bias']
}
Expand Down Expand Up @@ -82,7 +82,7 @@ def setUp(self):
'bias': 0.0,
'bias_after_scale': False,
}
self.use_mkldnn = True
self.use_onednn = True
self.outputs = {
'Out': (self.x_fp32 + self.attrs['bias']) * self.attrs['scale']
}
Expand Down
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