CMPL (BX), DX                           // 3913
	CMPL (BX), R11                          // 44391b
	CMPL (R11), DX                          // 413913
	CMPL (R11), R11                         // 45391b
	CMPL DX, DX                             // 39d2 or 3bd2
	CMPL DX, R11                            // 4439da or 413bd3
	CMPL R11, DX                            // 4139d3 or 443bda

		return true
	}
	// match: (CMPL x y)
	// cond: canonLessThan(x,y)
	// result: (InvertFlags (CMPL y x))
	for {
		x := v_0
		y := v_1
		if !(canonLessThan(x, y)) {
			break
		}
		v.reset(OpAMD64InvertFlags)
		v0 := b.NewValue0(v.Pos, OpAMD64CMPL, types.TypeFlags)
		v0.AddArg2(y, x)
		v.AddArg(v0)
		return true
	}
	// match: (CMPL l:(MOVLload {sym} [off] ptr mem) x)

Class <org.gradle.api.internal.file.archive.impl.AbstractZipEntry$1> is not annotated (directly or via its package) with @org.gradle.api.NonNullApi in (AbstractZipEntry.java:0)
Class <org.gradle.api.internal.file.archive.impl.AbstractZipEntry> is not annotated (directly or via its package) with @org.gradle.api.NonNullApi in (AbstractZipEntry.java:0)

    *   `pfor/vectorized_map`: Added support for vectorizing 56 more ops.
        Vectorizing `tf.cond` is also supported now.
    *   Set as much partial shape as we can infer statically within the gradient
        impl of the gather op.
    *   Gradient of `tf.while_loop` emits `StatelessWhile` op if `cond` and body
        functions are stateless. This allows multiple gradients while ops to run
        in parallel under distribution strategy.