def otest_abs_greater(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy_bool]: "onnx numpy greater" return nxnp.abs(x) > x
def otest_abs_add2(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy addition" return nxnp.abs(x) + numpy.float32(2)
def otest_abs_mod(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.int64]: "onnx numpy modulo" return nxnp.abs(x).astype(numpy.int64) % numpy.int64(2)
def otest_abs_set1d(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy set" temp = nxnp.abs(x).copy() temp[:4:2] = numpy.array([-1.5, -1.6], dtype=numpy.float32) return temp
def otest_abs_set1g(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy set" temp = nxnp.abs(x).copy() temp[3:] = numpy.array([-1.5] * 4, dtype=numpy.float32) return temp
def otest_abs_log_multi(x): "onnx numpy log multiple type" return nxnp.log(nxnp.abs(x))
def otest_abs_flatten2(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy flatten" return nxnp.abs(x).flatten(axis=1)
def otest_abs_sum2(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy sum" return nxnp.sum(nxnp.abs(x), axis=1, keepdims=1)
def otest_abs_transpose_t(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy transpose T" return nxnp.abs(x).T
def otest_abs_and(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy_bool]: "onnx numpy and" return (nxnp.abs(x) < x) and (nxnp.abs(x) < numpy.float32(0))
def otest_abs_or(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy_bool]: "onnx numpy or" return (nxnp.abs(x) < x) or (nxnp.abs(x) < numpy.float32(0))
def otest_abs_less_or_equal(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy_bool]: "onnx numpy less or equal" return nxnp.abs(x) <= x
def otest_abs_less(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy_bool]: "onnx numpy less" return nxnp.abs(x) < x
def otest_abs_greater_or_equal(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy_bool]: "onnx numpy greater or equal" return nxnp.abs(x) >= x
def otest_abs_not(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.bool_]: "onnx numpy not" temp = nxnp.abs(x) > numpy.float32(0) return temp.not_()
def otest_abs_cast(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.int64]: "onnx numpy cast" return nxnp.abs(x).astype(numpy.int64)
def otest_abs_filter(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy filter" return nxnp.abs(x)[x[:, 0] > numpy.float32(15)]
def otest_abs_reshape_11(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy reshape with opset 11" return nxnp.abs(x).reshape((-1, 1))
def otest_abs_size(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.int64]: "onnx numpy size" return nxnp.abs(x).size
def otest_abs_slice2(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy slice 2" return nxnp.abs(x)[:1, 1]
def otest_abs_abs(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy abs abs" return nxnp.abs(nxnp.abs(x))
def otest_abs_slice23(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy slice 23" return nxnp.abs(x)[::2, ::3]
def otest_abs_set1f(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy set" temp = nxnp.abs(x).copy() temp[3:5] = numpy.float32(-1.5) return temp
def otest_abs_slice_end(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy slice end" return nxnp.abs(x)[1:, :3]
def otest_abs_addm(x1: NDArray[Any, numpy.float32], x2: NDArray[Any, numpy.float32] ) -> NDArray[Any, numpy.float32]: "onnx numpy addition" return nxnp.abs(x1) + x2
def otest_abs_gather2(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy gather" return nxnp.abs(x)[:, 1]
def otest_abs_pow(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy power" return nxnp.abs(x) ** numpy.float32(2)
def otest_abs_neg(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy neg" return - nxnp.abs(x)
def otest_abs_matmul(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy.float32]: "onnx numpy addition" return nxnp.abs(x) @ x
def otest_abs_not_equal(x: NDArray[Any, numpy.float32], ) -> NDArray[Any, numpy_bool]: "onnx numpy inequality" return nxnp.abs(x) != x