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Fix default values for the light API #63

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Merged
merged 1 commit into from
Jan 9, 2024
Merged

Fix default values for the light API #63

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163 changes: 81 additions & 82 deletions 163 onnx_array_api/light_api/_op_vars.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,10 @@ def BitShift(self, direction: str = "") -> "Var":
return self.make_node("BitShift", *self.vars_, direction=direction)

def CenterCropPad(self, axes: Optional[List[int]] = None) -> "Var":
axes = axes or []
return self.make_node("CenterCropPad", *self.vars_, axes=axes)
kwargs = {}
if axes is not None:
kwargs["axes"] = axes
return self.make_node("CenterCropPad", *self.vars_, **kwargs)

def Clip(
self,
Expand All @@ -27,12 +29,14 @@ def Col2Im(
pads: Optional[List[int]] = None,
strides: Optional[List[int]] = None,
) -> "Var":
dilations = dilations or []
pads = pads or []
strides = strides or []
return self.make_node(
"Col2Im", *self.vars_, dilations=dilations, pads=pads, strides=strides
)
kwargs = {}
if dilations is not None:
kwargs["dilations"] = dilations
if pads is not None:
kwargs["pads"] = pads
if strides is not None:
kwargs["strides"] = strides
return self.make_node("Col2Im", *self.vars_, **kwargs)

def Compress(self, axis: int = 0) -> "Var":
return self.make_node("Compress", *self.vars_, axis=axis)
Expand Down Expand Up @@ -71,19 +75,17 @@ def ConvInteger(
pads: Optional[List[int]] = None,
strides: Optional[List[int]] = None,
) -> "Var":
dilations = dilations or []
kernel_shape = kernel_shape or []
pads = pads or []
strides = strides or []
kwargs = {}
if dilations is not None:
kwargs["dilations"] = dilations
if kernel_shape is not None:
kwargs["kernel_shape"] = kernel_shape
if pads is not None:
kwargs["pads"] = pads
if strides is not None:
kwargs["strides"] = strides
return self.make_node(
"ConvInteger",
*self.vars_,
auto_pad=auto_pad,
dilations=dilations,
group=group,
kernel_shape=kernel_shape,
pads=pads,
strides=strides,
"ConvInteger", *self.vars_, auto_pad=auto_pad, group=group, **kwargs
)

def ConvTranspose(
Expand All @@ -97,23 +99,21 @@ def ConvTranspose(
pads: Optional[List[int]] = None,
strides: Optional[List[int]] = None,
) -> "Var":
dilations = dilations or []
kernel_shape = kernel_shape or []
output_padding = output_padding or []
output_shape = output_shape or []
pads = pads or []
strides = strides or []
return self.make_node(
"ConvTranspose",
*self.vars_,
auto_pad=auto_pad,
dilations=dilations,
group=group,
kernel_shape=kernel_shape,
output_padding=output_padding,
output_shape=output_shape,
pads=pads,
strides=strides,
kwargs = {}
if dilations is not None:
kwargs["dilations"] = dilations
if kernel_shape is not None:
kwargs["kernel_shape"] = kernel_shape
if pads is not None:
kwargs["pads"] = pads
if strides is not None:
kwargs["strides"] = strides
if output_padding is not None:
kwargs["output_padding"] = output_padding
if output_shape is not None:
kwargs["output_shape"] = output_shape
return self.make_node(
"ConvTranspose", *self.vars_, auto_pad=auto_pad, group=group, **kwargs
)

def CumSum(self, exclusive: int = 0, reverse: int = 0) -> "Var":
Expand All @@ -135,19 +135,17 @@ def DeformConv(
pads: Optional[List[int]] = None,
strides: Optional[List[int]] = None,
) -> "Var":
dilations = dilations or []
kernel_shape = kernel_shape or []
pads = pads or []
strides = strides or []
kwargs = {}
if dilations is not None:
kwargs["dilations"] = dilations
if kernel_shape is not None:
kwargs["kernel_shape"] = kernel_shape
if pads is not None:
kwargs["pads"] = pads
if strides is not None:
kwargs["strides"] = strides
return self.make_node(
"DeformConv",
*self.vars_,
dilations=dilations,
group=group,
kernel_shape=kernel_shape,
offset_group=offset_group,
pads=pads,
strides=strides,
"DeformConv", *self.vars_, group=group, offset_group=offset_group, **kwargs
)

def DequantizeLinear(self, axis: int = 1) -> "Var":
Expand Down Expand Up @@ -204,12 +202,11 @@ def MatMulInteger(
def MaxRoiPool(
self, pooled_shape: Optional[List[int]] = None, spatial_scale: float = 1.0
) -> "Var":
pooled_shape = pooled_shape or []
kwargs = {}
if pooled_shape is not None:
kwargs["pooled_shape"] = pooled_shape
return self.make_node(
"MaxRoiPool",
*self.vars_,
pooled_shape=pooled_shape,
spatial_scale=spatial_scale,
"MaxRoiPool", *self.vars_, spatial_scale=spatial_scale, **kwargs
)

def MaxUnpool(
Expand All @@ -218,16 +215,14 @@ def MaxUnpool(
pads: Optional[List[int]] = None,
strides: Optional[List[int]] = None,
) -> "Var":
kernel_shape = kernel_shape or []
pads = pads or []
strides = strides or []
return self.make_node(
"MaxUnpool",
*self.vars_,
kernel_shape=kernel_shape,
pads=pads,
strides=strides,
)
kwargs = {}
if kernel_shape is not None:
kwargs["kernel_shape"] = kernel_shape
if pads is not None:
kwargs["pads"] = pads
if strides is not None:
kwargs["strides"] = strides
return self.make_node("MaxUnpool", *self.vars_, **kwargs)

def MelWeightMatrix(self, output_datatype: int = 1) -> "Var":
return self.make_node(
Expand Down Expand Up @@ -267,19 +262,17 @@ def QLinearConv(
pads: Optional[List[int]] = None,
strides: Optional[List[int]] = None,
) -> "Var":
dilations = dilations or []
kernel_shape = kernel_shape or []
pads = pads or []
strides = strides or []
kwargs = {}
if kernel_shape is not None:
kwargs["kernel_shape"] = kernel_shape
if pads is not None:
kwargs["pads"] = pads
if strides is not None:
kwargs["strides"] = strides
if dilations is not None:
kwargs["dilations"] = dilations
return self.make_node(
"QLinearConv",
*self.vars_,
auto_pad=auto_pad,
dilations=dilations,
group=group,
kernel_shape=kernel_shape,
pads=pads,
strides=strides,
"QLinearConv", *self.vars_, auto_pad=auto_pad, group=group, **kwargs
)

def QLinearMatMul(
Expand All @@ -303,15 +296,17 @@ def RandomNormal(
seed: float = 0.0,
shape: Optional[List[int]] = None,
) -> "Var":
shape = shape or []
kwargs = {}
if shape is not None:
kwargs["shape"] = shape
return self.make_node(
"RandomNormal",
*self.vars_,
dtype=dtype,
mean=mean,
scale=scale,
seed=seed,
shape=shape,
**kwargs,
)

def RandomUniform(
Expand All @@ -322,15 +317,17 @@ def RandomUniform(
seed: float = 0.0,
shape: Optional[List[int]] = None,
) -> "Var":
shape = shape or []
kwargs = {}
if shape is not None:
kwargs["shape"] = shape
return self.make_node(
"RandomUniform",
*self.vars_,
dtype=dtype,
high=high,
low=low,
seed=seed,
shape=shape,
**kwargs,
)

def Range(
Expand Down Expand Up @@ -437,19 +434,21 @@ def Resize(
mode: str = "nearest",
nearest_mode: str = "round_prefer_floor",
) -> "Var":
axes = axes or []
kwargs = {}
if axes is not None:
kwargs["axes"] = axes
return self.make_node(
"Resize",
*self.vars_,
antialias=antialias,
axes=axes,
coordinate_transformation_mode=coordinate_transformation_mode,
cubic_coeff_a=cubic_coeff_a,
exclude_outside=exclude_outside,
extrapolation_value=extrapolation_value,
keep_aspect_ratio_policy=keep_aspect_ratio_policy,
mode=mode,
nearest_mode=nearest_mode,
**kwargs,
)

def RoiAlign(
Expand Down
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