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Merge pull request #224 from durswd/impl_triangles
implemented triangle functions
2 parents 7eebbf2 + 9cebb92 commit 8de1ef3

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‎README.md

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@@ -134,15 +134,21 @@ Currently 82 Chainer Functions are supported to export in ONNX format.
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- Absolute
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- Add
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- AddConstant
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- ArcCos
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- ArcSin
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- ArcTan
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- ArgMax
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- ArgMin
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- BroadcastTo
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- Cos
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- Cosh
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- Clip
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- Div
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- DivFromConstant
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- Exp
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- Identity
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- LinearInterpolate
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- Log
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- LogSumExp
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- MatMul
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- Max
@@ -156,11 +162,14 @@ Currently 82 Chainer Functions are supported to export in ONNX format.
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- PowVarConst
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- Prod
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- RsqrtGPU
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- Sin
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- Sinh
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- Sqrt
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- Square
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- Sub
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- SubFromConstant
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- Sum
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- Tan
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### Noise
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‎onnx_chainer/functions/__init__.py

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@@ -48,15 +48,21 @@
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from onnx_chainer.functions.math import convert_Absolute # NOQA
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from onnx_chainer.functions.math import convert_Add # NOQA
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from onnx_chainer.functions.math import convert_AddConstant # NOQA
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from onnx_chainer.functions.math import convert_Arccos # NOQA
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from onnx_chainer.functions.math import convert_Arcsin # NOQA
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from onnx_chainer.functions.math import convert_Arctan # NOQA
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from onnx_chainer.functions.math import convert_ArgMax # NOQA
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from onnx_chainer.functions.math import convert_ArgMin # NOQA
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from onnx_chainer.functions.math import convert_BroadcastTo # NOQA
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from onnx_chainer.functions.math import convert_Clip # NOQA
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from onnx_chainer.functions.math import convert_Cos # NOQA
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from onnx_chainer.functions.math import convert_Cosh # NOQA
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from onnx_chainer.functions.math import convert_Div # NOQA
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from onnx_chainer.functions.math import convert_DivFromConstant # NOQA
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from onnx_chainer.functions.math import convert_Exp # NOQA
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from onnx_chainer.functions.math import convert_Identity # NOQA
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from onnx_chainer.functions.math import convert_LinearInterpolate # NOQA
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from onnx_chainer.functions.math import convert_Log # NOQA
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from onnx_chainer.functions.math import convert_LogSumExp # NOQA
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from onnx_chainer.functions.math import convert_MatMul # NOQA
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from onnx_chainer.functions.math import convert_Max # NOQA
@@ -70,11 +76,14 @@
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from onnx_chainer.functions.math import convert_PowVarConst # NOQA
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from onnx_chainer.functions.math import convert_Prod # NOQA
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from onnx_chainer.functions.math import convert_RsqrtGPU # NOQA
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from onnx_chainer.functions.math import convert_Sin # NOQA
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from onnx_chainer.functions.math import convert_Sinh # NOQA
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from onnx_chainer.functions.math import convert_Sqrt # NOQA
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from onnx_chainer.functions.math import convert_Square # NOQA
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from onnx_chainer.functions.math import convert_Sub # NOQA
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from onnx_chainer.functions.math import convert_SubFromConstant # NOQA
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from onnx_chainer.functions.math import convert_Sum # NOQA
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from onnx_chainer.functions.math import convert_Tan # NOQA
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from onnx_chainer.functions.noise import convert_Dropout # NOQA
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‎onnx_chainer/functions/math.py

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@@ -115,6 +115,21 @@ def convert_Absolute(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Abs', input_names, output_names),
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@support((7,))
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def convert_Arccos(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Acos', input_names, output_names),
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@support((7,))
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def convert_Arcsin(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Asin', input_names, output_names),
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@support((7,))
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def convert_Arctan(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Atan', input_names, output_names),
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@support((1, 7))
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def convert_PowVarConst(
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func, opset_version, input_names, output_names, context):
@@ -143,6 +158,16 @@ def convert_Clip(func, opset_version, input_names, output_names, context):
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),
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@support((7,))
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def convert_Cos(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Cos', input_names, output_names),
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@support((9,))
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def convert_Cosh(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Cosh', input_names, output_names),
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@support((1, 6))
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def convert_Exp(func, opset_version, input_names, output_names, context):
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if opset_version == 1:
@@ -191,6 +216,16 @@ def convert_Minimum(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Min', input_names, output_names),
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@support((7,))
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def convert_Sin(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Sin', input_names, output_names),
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@support((9,))
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def convert_Sinh(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Sinh', input_names, output_names),
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@support((1, 6))
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def convert_Sqrt(func, opset_version, input_names, output_names, context):
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if opset_version == 1:
@@ -207,6 +242,11 @@ def convert_RsqrtGPU(func, opset_version, input_names, output_names, context):
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return gb.nodes(output_names)
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@support((6,))
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def convert_Log(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Log', input_names, output_names),
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def convert_LogSumExp(func, opset_version, input_names, output_names, context):
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# Use keepdims=False by default
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# since the chainer does not support keepdims option
@@ -259,6 +299,11 @@ def convert_Sum(func, opset_version, input_names, output_names, context):
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'ReduceSum', input_names, output_names, **kwargs),
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@support((7,))
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def convert_Tan(func, opset_version, input_names, output_names, context):
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return onnx_helper.make_node('Tan', input_names, output_names),
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@support((1, 6, 7))
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def convert_LinearInterpolate(
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func, opset_version, input_names, output_names, context):

‎onnx_chainer/mapping.py

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@@ -58,15 +58,21 @@
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'Absolute',
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'Add',
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'AddConstant',
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'Arccos',
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'Arcsin',
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'Arctan',
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'ArgMax',
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'ArgMin',
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'BroadcastTo',
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'Clip',
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'Cos',
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'Cosh',
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'Div',
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'DivFromConstant',
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'Exp',
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'Identity',
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'LinearInterpolate',
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'Log',
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'LogSumExp',
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'MatMul',
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'Max',
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'PowVarConst',
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'Prod',
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'RsqrtGPU',
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'Sin',
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'Sinh',
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'Sqrt',
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'Square',
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'Sub',
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'SubFromConstant',
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'Sum',
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'Tan',
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# Noise
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'Dropout',

‎tests/functions_tests/test_maths.py

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@testing.parameterize(
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{'op_name': 'Neg', 'ops': '-a'},
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{'op_name': 'Absolute', 'ops': 'abs(a)'},
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{'op_name': 'Arccos', 'ops': 'chainer.functions.arccos(a)'},
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{'op_name': 'Arcsin', 'ops': 'chainer.functions.arcsin(a)'},
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{'op_name': 'Arctan', 'ops': 'chainer.functions.arctan(a)'},
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{'op_name': 'Cos', 'ops': 'chainer.functions.cos(a)'},
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{'op_name': 'Cosh', 'ops': 'chainer.functions.cosh(a)'},
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{'op_name': 'Clip', 'ops': 'chainer.functions.clip(a, 0.1, 0.2)'},
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{'op_name': 'Exp', 'ops': 'chainer.functions.exp(a)'},
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{'op_name': 'Sqrt', 'ops': 'chainer.functions.sqrt(a)'},
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'condition': 'axis0'},
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{'op_name': 'Prod', 'ops': 'chainer.functions.prod(a, keepdims=True)',
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'condition': 'keepdims'},
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{'op_name': 'Log', 'ops': 'chainer.functions.log(a)'},
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{'op_name': 'LogSumExp', 'ops': 'chainer.functions.logsumexp(a)'},
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{'op_name': 'LogSumExp', 'ops': 'chainer.functions.logsumexp(a, axis=0)',
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'condition': 'axis0'},
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{'op_name': 'Sin', 'ops': 'chainer.functions.sin(a)'},
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{'op_name': 'Sinh', 'ops': 'chainer.functions.sinh(a)'},
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{'op_name': 'Square', 'ops': 'chainer.functions.square(a)'},
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{'op_name': 'Tan', 'ops': 'chainer.functions.tan(a)'},
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{'op_name': 'BroadcastTo',
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'ops': 'chainer.functions.broadcast_to(a, (2,2,3))'},
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)
@@ -78,8 +87,13 @@ def __call__(self, a):
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self.name = name
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skip_opset_version = []
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if self.op_name == 'Cosh' or self.op_name == 'Sinh':
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skip_opset_version.append(7)
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skip_opset_version.append(8)
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if self.op_name == 'BroadcastTo':
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skip_opset_version.append(7)
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self.skip_opset_version = skip_opset_version
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def test_output(self):

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