def elementwise_add(op: Tanh) -> List[Kernel]:
x0 = op.inputs["x0"]
y = op.outputs["y"]
shapes, strides = optimize_loop_structure([x0, y], y)
name_injector = KernelNameInjector(op)
uniform_injector = UniformInjector()
uniform_injector.register({
"X0": x0,
"s_y": texture_stride(y),
"d_Y": shapes[y],
"s_Y": strides[y],
"d_x0": texture_shape(x0),
"s_x0": texture_stride(x0),
"d_X0": shapes[x0],
"s_X0": strides[x0],
})
source = template_R if ChannelMode.get(
y) == ChannelModeEnum.R else template_RGBA
source = uniform_injector.inject(source)
source = name_injector.inject(source)
kernel = Kernel(source, name_injector.name, uniform_injector.samplers,
uniform_injector.uniforms, y)
return [kernel]
def elementwise_add(op: ClippedRelu) -> List[Kernel]:
x0 = op.inputs["x0"]
y = op.outputs["y"]
shapes, strides = optimize_loop_structure([x0, y], y)
name_injector = KernelNameInjector(op)
uniform_injector = UniformInjector()
uniform_injector.register({
"X0": x0,
"s_y": texture_stride(y),
"d_Y": shapes[y],
"s_Y": strides[y],
"d_x0": texture_shape(x0),
"s_x0": texture_stride(x0),
"d_X0": shapes[x0],
"s_X0": strides[x0],
"cap": op.parameters["cap"]
})
source = template
source = uniform_injector.inject(source)
source = name_injector.inject(source)
kernel = Kernel(source, name_injector.name, uniform_injector.samplers,
uniform_injector.uniforms, y)
return [kernel]
