def default_inputs(self):
return DefaultInputs(
axes=range(self.x.rank),
gamma=None,
beta=None,
epsilon=1e-5,
)
def default_inputs(self):
return DefaultInputs(
target_height=1,
target_width=1,
normalized_coordinates=False,
spatial_scale=1.,
box_coordinate_mode="CONRNERS_HEIGHT_FIRST",
sampling_mode="DEFAULT",
)
def default_inputs(self):
num_spatial_dims = self.x.rank - 2
return DefaultInputs(
bias=None,
strides=[1] * num_spatial_dims,
pad_type="valid",
pad=[0] * num_spatial_dims * 2,
dilations=[1] * num_spatial_dims,
groups=1,
)
def default_inputs(self):
return super().default_inputs() + \
DefaultInputs(
nbits=8,
)
def default_inputs(self):
return DefaultInputs(
target_size_height=1,
target_size_width=1,
sampling_mode="DEFAULT",
)
def default_inputs(self):
return DefaultInputs(
scale_factor_height=1,
scale_factor_width=1,
align_corners=True,
)
def default_inputs(self):
return DefaultInputs(
scale_factor_height=1,
scale_factor_width=1,
)
def default_inputs(self):
return DefaultInputs(
gamma=None,
beta=None,
epsilon=1e-5,
)
def default_inputs(self):
return DefaultInputs(
alpha=1e-4,
beta=0.75,
k=1.,
)
def default_inputs(self):
return DefaultInputs(epsilon=1e-6, )
def default_inputs(self):
Dout = self.weight.shape[0]
return DefaultInputs(bias=[0.] * Dout, )
def default_inputs(self):
return DefaultInputs(
transpose_x=False,
transpose_y=False,
)
