from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.elementwise_add import ElementwiseAdd register_elementwise_kernel(ElementwiseAdd, "y = x0 + x1;")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel
from webdnn.graph.operators.softplus import Softplus
register_elementwise_kernel(Softplus,
"y = Math.log(1 + Math.exp(beta * x0)) / beta;",
{"beta": lambda op: op.parameters["beta"]})
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel
from webdnn.graph.operators.scalar_mul import ScalarMul
register_elementwise_kernel(ScalarMul, "y = x0 * value;",
{"value": lambda op: op.parameters["value"]})
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel
from webdnn.graph.operators.threshold_relu import ThresholdRelu
register_elementwise_kernel(ThresholdRelu,
"y = x0 > threshold ? x0 : 0;",
{"threshold": lambda op: op.parameters["threshold"]})
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.broadcast import Broadcast register_elementwise_kernel(Broadcast, "y = x0;")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.relu import Relu register_elementwise_kernel(Relu, "y = x0 > 0 ? x0 : 0;")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.log import Log register_elementwise_kernel(Log, "y = Math.log(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.elementwise_div import ElementwiseDiv register_elementwise_kernel(ElementwiseDiv, "y = x0 / x1;")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel
from webdnn.graph.operators.scalar_affine import ScalarAffine
register_elementwise_kernel(ScalarAffine,
"y = x0 * scale + bias;",
{"scale": lambda op: op.parameters["scale"],
"bias": lambda op: op.parameters["bias"], })
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.softsign import Softsign register_elementwise_kernel(Softsign, "y = x0 / (Math.abs(x0) + 1.0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.tanh import Tanh register_elementwise_kernel(Tanh, "y = Math.tanh(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.select import Select register_elementwise_kernel(Select, "y = (x0 == 1.0 ? x1 : x2);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel
from webdnn.graph.operators.leaky_relu import LeakyRelu
register_elementwise_kernel(LeakyRelu, "y = x0 > 0 ? x0 : (x0 * slope);",
{"slope": lambda op: op.parameters["slope"]})
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel
from webdnn.graph.operators.scalar_pow import ScalarPow
register_elementwise_kernel(ScalarPow,
"y = Math.pow(x0, value);",
{"value": lambda op: op.parameters["value"]})
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.asinh import Asinh register_elementwise_kernel(Asinh, "y = Math.asinh(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.elu import Elu register_elementwise_kernel(Elu, "y = x0 < 0.0 ? (Math.exp(x0) - 1.0) : x0;")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.atan import Atan register_elementwise_kernel(Atan, "y = Math.atan(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.elementwise_pow import ElementwisePow register_elementwise_kernel(ElementwisePow, "y = Math.pow(x0, x1);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.rsqrt import Rsqrt register_elementwise_kernel(Rsqrt, "y = 1.0 / Math.sqrt(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.axiswise_bias import AxiswiseBias from webdnn.graph.operators.elementwise_add import ElementwiseAdd register_elementwise_kernel(ElementwiseAdd, "y = x0 + x1;") register_elementwise_kernel(AxiswiseBias, "y = x0 + x1;")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.cos import Cos register_elementwise_kernel(Cos, "y = Math.cos(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.sigmoid import Sigmoid register_elementwise_kernel(Sigmoid, "y = 1.0 / (1.0 + Math.exp(-x0));")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.abs import Abs register_elementwise_kernel(Abs, "y = Math.abs(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.axiswise_scale import AxiswiseScale from webdnn.graph.operators.elementwise_mul import ElementwiseMul register_elementwise_kernel(ElementwiseMul, "y = x0 * x1;") register_elementwise_kernel(AxiswiseScale, "y = x0 * x1;")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.acosh import Acosh register_elementwise_kernel(Acosh, "y = Math.acosh(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.greater_equal import GreaterEqual register_elementwise_kernel(GreaterEqual, "y = x0 >= x1 ? 1.0 : 0.0;")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.exp import Exp register_elementwise_kernel(Exp, "y = Math.exp(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel
from webdnn.graph.operators.clipped_relu import ClippedRelu
register_elementwise_kernel(ClippedRelu,
"y = x0 < 0 ? 0 : x0 > cap ? cap : x0;",
{"cap": lambda op: op.parameters["cap"]})
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.sin import Sin register_elementwise_kernel(Sin, "y = Math.sin(x0);")
from webdnn.backend.fallback.kernels.elementwise import register_elementwise_kernel from webdnn.graph.operators.elementwise_mul import ElementwiseMul register_elementwise_kernel(ElementwiseMul, "y = x0 * x1;")
